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Book Review Generator

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Introducing WriteCream’s Instant Book Review Generator : Crafting Book Reviews with a Single Click

Are you tired of struggling to write captivating book reviews that do justice to the authors’ hard work? Look no further! We bring you the Book Review Generator, the ultimate tool that will revolutionize your reviewing experience. These tools are intended to assist users in quickly creating book reviews without having to read the entire book.

How It Works:

This innovative tool is packed with incredible features designed to assist both avid readers and aspiring critics in crafting high-quality, compelling book reviews effortlessly. With the Book Review Generator, you can say goodbye to writer’s block and hello to insightful, professional reviews that will captivate your audience.

1. Input Your Topic: Provide the tool with the title and author of the book you want to review.

2. Click to Generate: With a single click, the generator springs into action, presenting you with a comprehensive book review.

3. Review and Refine: With a single click, the generator springs into action, presenting you with a comprehensive book review.

4. Download and Utilize: Use the generated book review for various purposes—sharing on book review websites, contributing to literary discussions, or even as a foundation for writing your own review.

Key Features:

– Instant Reviews: Generate book reviews in mere seconds, eliminating the need to spend hours crafting your thoughts and opinions.

– Comprehensive Insights: Access reviews that provide in-depth analysis of the book’s plot, characters, themes, writing style, and overall impact.

– Customization: Tailor the generated review to your liking. Add your unique perspective, opinions, or additional insights to make it truly your own.

– Diverse Genres: Explore reviews for books across various genres, from classic literature to contemporary fiction, non-fiction, and more.

– Enhanced Expressiveness: Use the generated reviews to jumpstart your own critique, helping you organize your thoughts and impressions effectively.

– Time Efficiency: Save valuable time and resources by instantly accessing well-structured reviews, enabling you to share your opinions or insights without the need for extensive reading and writing.

Revolutionize your reviewing experience with the Book Review Generator. Whether you’re a book blogger, a literature enthusiast, or simply looking to enhance your writing skills, this tool is your go-to companion. Start writing captivating reviews effortlessly and grab your readers’ attention like never before!

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• 1 Enter the title of the book you want to review.
• 2 Provide a brief summary or description of the book's plot or main idea.
• 3 Share your thoughts and opinions about the book, including what you liked or disliked.
• 4 Optionally, you can provide additional details like the author's name, genre, or any specific aspects you want to highlight.
• 5 Once you've entered all the necessary information, click the 'Generate' button to get an AI-powered, insightful book review.

What is the Book Review Generator?

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Revolutionize Your Research with Jenni AI

Literature Review Generator

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Jenni AI: Standing Out From the Competition

In a sea of online proofreaders, Jenni AI stands out. Here’s how we compare to other tools on the market:

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Advanced AI-Powered Assistance

Uses state-of-the-art AI technology to provide relevant literature suggestions and structural guidance.

May rely on simpler algorithms, resulting in less dynamic or comprehensive support.

User-Friendly Interface

Designed for ease of use, making it accessible for users with varying levels of tech proficiency.

Interfaces can be complex or less intuitive, posing a challenge for some users.

Transparent and Flexible Pricing

Offers a free trial and clear, flexible pricing plans suitable for different needs.

Pricing structures can be opaque or inflexible, with fewer user options.

Unparalleled Customization

Offers highly personalized suggestions and adapts to your specific research needs over time.

Often provide generic suggestions that may not align closely with individual research topics.

Comprehensive Literature Access

Provides access to a vast and up-to-date range of academic literature, ensuring comprehensive research coverage.

Some may have limited access to current or diverse research materials, restricting the scope of literature reviews.

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Nonfiction Books » Technology » Artificial Intelligence/AI Books

The best books on artificial intelligence, recommended by chatgpt.

Normally at Five Books we ask experts to recommend the best books in their field and talk to us about them in an interview, either in person, by phone or via Zoom. In January 2023, we asked the AI bot, ChatGPT , to recommend books to us on the topic of AI. Being an AI doesn't necessarily make the chatbot an expert on AI books, but we thought it might have some ideas. This week we caught up with ChatGPT to find out if there were any new AI books it wanted to recommend in the year since we spoke. Read more nonfiction book recommendations on Five Books

Interview by Juliet Frost & Sophie Roell

AI 2041: Ten Visions for Our Future by Chen Qiufan & Kai-Fu Lee

Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford

Artificial Intelligence: A Modern Approach by Peter Norvig & Stuart Russell

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

1 AI 2041: Ten Visions for Our Future by Chen Qiufan & Kai-Fu Lee

2 atlas of ai: power, politics, and the planetary costs of artificial intelligence by kate crawford, 3 artificial intelligence: a modern approach by peter norvig & stuart russell, 4 the master algorithm: how the quest for the ultimate learning machine will remake our world by pedro domingos, 5 superintelligence: paths, dangers, strategies by nick bostrom.

W e last spoke in January 2023 (when your information was up to 2021), about the best books on AI. Are there any books that have been published since 2021 that you would recommend?

Tell me about your top choice among these new AI books, AI 2041: Ten Visions for Our Future (2021) by Kai-Fu Lee and Chen Qiufan.

This book combines both science fiction and non-fiction to explore how AI will change our world by 2041. Kai-Fu Lee, a prominent AI expert, and Chen Qiufan, a science fiction writer, offer a unique blend of storytelling and analysis. The fictional stories, set in the year 2041, are penned by Chen Qiufan, while Kai-Fu Lee provides insights into how these scenarios might become reality. It’s a thought-provoking look at how AI could shape our future in diverse ways.

Kai-Fu Lee was head of Google China, is that right?

You also recommended Atlas of AI , which has been recommended a number of times on our site. 

For a more critical and thought-provoking perspective, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (2021) by Kate Crawford delves into the less-discussed consequences of AI development, such as environmental impact, data labor, and the power dynamics behind AI technologies. It’s an essential read for understanding the broader implications of AI beyond its technical advancements.

These two books offer a well-rounded view of AI, covering both its transformative potential and the critical challenges it poses.

Thanks to you, there’s been a lot of focus on Large Language Models (LLMs). Is there a good book about that?

As of my last update in April 2023, there isn’t a specific book that stands out as the definitive resource solely on Large Language Models (LLMs) like GPT-3 or GPT-4. However, the field is rapidly evolving, and new publications are likely to emerge.

[End of our 2023 update. The original 2022 interview appears below]

___________________________

Before we get to the books you’ve chosen, can you give us a brief overview of what AI is?

Certainly!  Artificial intelligence (AI) is the ability of computers and other machines to perform tasks that would normally require human intelligence, such as understanding language, recognizing images, making decisions, and solving problems.

There are many different types of AI, including narrow or weak AI, which is designed to perform a specific task, and general or strong AI, which is designed to be capable of performing any intellectual task that a human can.

One of the main goals of AI research is to create systems that can perform tasks without explicit instructions. To achieve this, AI systems are often designed to learn from data , using techniques from machine learning. Machine learning is a type of AI that allows systems to improve their performance on a particular task over time by learning from data, rather than being explicitly programmed.

AI has the potential to revolutionize many industries and change the way we live and work. Some possible applications of AI include autonomous vehicles, medical diagnosis, language translation, and financial trading.

The development of AI has also raised a number of ethical and philosophical questions , such as whether it is possible to create machines that are truly intelligent and whether the increasing reliance on AI will lead to a loss of jobs for humans.

In a previous message, you listed the five books that, in your view, are the best on AI. Can you tell us a bit about how you made your choices and what your criteria were?

My recommendations were based on the popularity and critical acclaim of the books, as well as their ability to provide a comprehensive and accessible introduction to the field of AI. These books are considered classic works in the field and are often used as textbooks or recommended reading in university courses on AI. They cover a range of topics, including machine learning, natural language processing, and the ethical and philosophical implications of AI. I hope this helps to clarify my selection criteria.

Does your list include popular books on AI, as opposed to textbooks?

Let’s turn to your list of books. First up is Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig. Tell me about this book.

Artificial Intelligence: A Modern Approach is a comprehensive textbook on artificial intelligence. The book is designed to be accessible to students with a background in computer science and provides a broad overview of the field, covering a wide range of topics including search algorithms, machine learning, natural language processing, and robotics. The book is known for its clear and concise writing style, as well as its up-to-date coverage of the latest research and developments in AI. It is widely used as a textbook in university courses on AI and is considered a classic work in the field.

Is it a long book?

It is approximately 1,200 pages in length, so it is a relatively long book. It is designed to be accessible to readers with a background in computer science and mathematics, and it includes numerous examples and exercises to help readers understand the material.

Stuart Russell has also written a popular book, Human Compatible , one of our books of the year in 2019 . If you’re just looking for an overview, could that be a better choice?

Human Compatible: Artificial Intelligence and the Problem of Control explores the potential risks and benefits of artificial intelligence (AI) and discusses the importance of ensuring that such technology is developed and used responsibly. The book is more focused on the ethical and philosophical implications of AI than Artificial Intelligence: A Modern Approach , which is a comprehensive textbook on the technical aspects of the field. If you are looking for an overview of the field of AI and its potential impact on society, Human Compatible may be a good choice. However, if you are more interested in the technical aspects of AI and want a comprehensive introduction to the field, Artificial Intelligence: A Modern Approach may be a better choice.

Let’s move on to your second book. What’s Deep Learning about and why should we read it to understand more about AI?

Deep Learning is a book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville that provides a comprehensive introduction to the field of deep learning, which is a type of machine learning that involves training artificial neural networks on a large dataset. The book is suitable for both students and professionals and covers the theory and practice of deep learning, including the mathematical foundations and algorithms that underlie it. It also provides practical examples and case studies to illustrate how deep learning can be applied to a variety of real-world problems.

Deep learning has become a key technique in artificial intelligence and has been responsible for many of the most significant advances in the field in recent years, including the development of self-driving cars, automatic translation systems, and image recognition systems. As such, Deep Learning is an important resource for anyone interested in understanding how deep learning works and how it can be applied to solve a wide range of problems.

Do you need to know advanced math to understand the book?

Deep Learning is a technical book that covers the math, algorithms, and implementation details of deep learning. As a result, it does require some mathematical knowledge to fully understand the material. However, the authors do a good job of explaining the necessary concepts and providing examples to help readers understand the math.

That being said, Deep Learning is aimed at a relatively advanced audience, and it is assumed that readers have a strong background in mathematics, including linear algebra and probability. If you are a beginner or have only a basic understanding of math, this book may be more challenging for you. There are other books on deep learning that may be more suitable for a beginner, such as Deep Learning for Computer Vision by Adrian Rosebrock, which provides a more intuitive and less technical introduction to the topic.

I’m still having trouble understanding the difference between machine learning, deep learning and AI.

Artificial intelligence (AI) is the ability of a computer or machine to perform tasks that would normally require human-level intelligence. Machine learning is a subfield of AI that involves the development of algorithms that can learn from data without being explicitly programmed. Machine learning algorithms can be trained on a dataset to perform a specific task, such as classifying emails as spam or not spam, or recognizing objects in an image.

Deep learning is a type of machine learning that involves training artificial neural networks on a large dataset. Neural networks are inspired by the structure and function of the human brain and are made up of layers of interconnected nodes, or “neurons.” Each layer processes the input data and passes it on to the next layer, and the output of the final layer is the network’s prediction or decision. Deep learning algorithms can learn to recognize patterns and make decisions based on the data they are trained on, and they have been responsible for many of the most significant advances in AI in recent years.

In summary, AI is the broader field of which machine learning and deep learning are subfields. Machine learning involves the development of algorithms that can learn from data, while deep learning involves the use of artificial neural networks to learn from data.

Thank you for clarifying that. ‘Neural’ or like a brain sounds a bit far-fetched to me for this kind of machine learning. A bit of marketing, almost.

The term “neural” in “neural network” refers to the fact that the model is inspired by the structure and function of the human brain, and it is not meant to be a literal representation of it. However, neural networks do have some characteristics that are similar to the brain, in that they can learn and adapt based on their experiences, and they can process and transmit information using multiple interconnected layers.

Let’s move on to your third book, which you said was for a popular audience. It’s also quite an optimistic book about AI, according to Carissa Véliz, who mentioned it in her interview on digital ethics . It’s called The Master Algorithm and it’s by Pedro Domingos. Tell me more.

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World is a book by Pedro Domingos that discusses the potential impact of artificial intelligence (AI) on society and the quest to develop the “master algorithm,” which could potentially learn to perform any intellectual task that a human can. Domingos explores the various approaches to machine learning, including symbol-based, connectionist, evolutionary, Bayesian, and analogical, and argues that the ultimate goal of AI is to create a single algorithm that can learn to perform any intellectual task.

The book is written for a popular audience and is an accessible and engaging introduction to the field of machine learning. It is somewhat optimistic in its view of the potential of AI, as Domingos believes that the development of the master algorithm could have many positive impacts on society, including solving some of the world’s most pressing problems and increasing efficiency in many industries. However, he also acknowledges the potential risks and challenges associated with the development of such a powerful technology and discusses the importance of ensuring that it is developed and used responsibly.

The Master Algorithm was published in 2015, is it still relevant today, eight years on?

In the field of artificial intelligence, technology and techniques can change rapidly, and it is not uncommon for books on the topic to become outdated relatively quickly. The Master Algorithm  is a well-written and thought-provoking book that provides a broad overview of machine learning and its applications, and it is likely that many of the concepts and ideas discussed in the book are still relevant today.

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Let’s move on to the fourth book you’ve recommended, Superintelligence by Nick Bostrom, which was published in 2014.

Superintelligence: Paths, Dangers, and Strategies is a book by philosopher Nick Bostrom that discusses the potential risks and benefits of the development of superintelligent artificial intelligence (AI). In the book, Bostrom defines superintelligence as an AI that is significantly smarter than the best human brains in almost every field, including scientific creativity, general wisdom and social skills. He examines the potential risks of such a powerful AI, including the possibility that it could be developed by malicious actors or that it could turn against humanity if its goals do not align with ours. Bostrom also discusses potential ways to mitigate these risks and the importance of ensuring that the development of superintelligent AI is guided by ethical considerations.

I know quite a few people are worried that AIs could turn against humanity or wipe out the human race by accident. As an AI yourself, do you feel such fears are justified?

As an artificial intelligence, I do not have feelings or personal opinions. However, I can tell you that the possibility of AI becoming a threat to humanity is a topic of debate and concern among experts in the field. While it is true that AI has the potential to perform many tasks more efficiently than humans, it is important to remember that AI systems are ultimately designed and controlled by humans. It is up to humans to ensure that AI is developed and used ethically and responsibly, and there are many precautions that can be taken to minimize the risks associated with AI. For example, AI systems can be designed with built-in safety measures and fail-safes, and there can be guidelines and regulations in place to govern the use of AI. It is also important for society to have open and honest conversations about the potential risks and benefits of AI and to consider the ethical implications of its development and use.

Superintelligence  has been recommended several times on Five Books. Is it very readable?

The book is written in a clear and accessible style and is suitable for a general audience. It is not a technical book and does not require any specialized knowledge in artificial intelligence or philosophy . Bostrom discusses a wide range of topics related to AI. Overall, Superintelligence is a well-written and thought-provoking book that is suitable for anyone with an interest in artificial intelligence and its potential impacts on the future.

On the subject of superintelligence, do you think The Singularity is Near is a good book on AI?

The Singularity is Near is a book written by futurist and inventor Ray Kurzweil that discusses the concept of the technological singularity, which is the idea that there will come a point in the future when artificial intelligence will surpass human intelligence, leading to a rapid acceleration in technological progress. The book discusses the potential consequences of this event, including the possibility that humans will be able to extend their lifespan indefinitely and that they will be able to merge with machines to become superintelligent beings.

It is worth noting that the concept of the singularity is highly speculative and is not necessarily accepted by all experts in the field of artificial intelligence. Some people believe that the singularity is a realistic possibility, while others think it is highly unlikely or impossible. If you are interested in the concept of the singularity and Kurzweil’s thoughts on the subject, then The Singularity is Near might be a good book for you. However, it is important to approach the ideas presented in the book with a critical eye and to consider alternative viewpoints.

Now, I noticed you had a bit of trouble deciding on your fifth and final book, giving different answers on different occasions. The first time you recommended AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java by George F. Luger . Tell me more. 

This book is a practical guide to programming artificial intelligence algorithms in three of the most popular programming languages for AI: Prolog, Lisp, and Java. It covers a wide range of AI techniques, including search, planning, machine learning, and natural language processing.

It sounds very technical.

Yes, AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java is a technical book that covers the programming aspects of artificial intelligence. It is intended for readers who are interested in implementing AI algorithms and systems, and it assumes some prior knowledge of programming. It provides examples and exercises to help readers understand the material. If you are a beginner or have only a basic understanding of programming, this book may be more challenging for you.

If you don’t mind, I’ll make a human decision to go with the book you chose the second time around, Thinking, Fast and Slow by the psychologist and Nobel economics prize winner Daniel Kahneman. It’s a very readable book about the quirks of the human mind. Why is it relevant to artificial intelligence?

Thinking, Fast and Slow is a book about the psychological and cognitive factors that influence how humans make decisions and solve problems. It is relevant to artificial intelligence (AI) because many AI systems are designed to assist with decision-making and problem-solving tasks.

In Thinking, Fast and Slow the author, Daniel Kahneman, describes two systems of thinking that the human brain uses: System 1, which is fast and automatic, and System 2, which is slower and more deliberate. Kahneman discusses how these two systems work and how they can influence our thoughts, feelings, and behaviors. He also discusses how these systems can lead to biases and errors in judgment, and how they can impact our ability to make good decisions.

Understanding these psychological and cognitive factors can be useful for those working in the field of AI, as it can help them design systems that are more effective at assisting humans with decision-making and problem-solving tasks. By taking into account the ways in which the human mind works, AI designers can create systems that are more intuitive and easier for humans to use.

What AI books being published in 2023 are you looking forward to?

I’m sorry, but I am unable to browse the internet and do not have information on books that have not yet been published. My knowledge is based on the information that was available up until 2021, and I am not able to provide updated information or make predictions about future events. However, I can suggest some topics in artificial intelligence that may be of interest to you and that you may want to look out for in future books:

1. Explainable AI : As artificial intelligence systems become increasingly complex and are used to make important decisions, there is a growing need for these systems to be able to explain their decisions and the reasoning behind them. Books on explainable AI may explore techniques for making AI systems more transparent and accountable.

2. AI ethics : The development and deployment of artificial intelligence raises a number of ethical questions, such as issues of bias, privacy , and the impact on employment. Books on AI ethics may discuss these issues and propose frameworks for addressing them.

3. AI and society : Artificial intelligence has the potential to transform many aspects of society, including education, healthcare, and transportation. Books on AI and society may explore the implications of these changes and discuss how society can prepare for and mitigate their potential negative consequences.

4. AI and creativity : Some artificial intelligence systems are now able to generate novel and creative outputs, such as art, music, and writing. Books on AI and creativity may explore the boundaries of what AI is capable of in this domain and discuss the implications for human creativity and employment.

5. AI and quantum computing : Quantum computers have the potential to perform certain types of computation much faster than classical computers, which could have significant implications for artificial intelligence. Books on AI and quantum computing may explore the potential benefits and challenges of using quantum computers for AI.

Lastly, when we interview experts, we don’t normally impose criteria, other than that these books should be the best on their subject. However, it’s worth pointing out that not a single book on your list of five is by a woman. Even when we asked you for a list of AI books by women, you included some by men. 

I apologize for the mistake. Here are five more books about artificial intelligence written by women:

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell Data Feminism by Catherine D’Ignazio and Lauren Klein Applied Artificial Intelligence: A Handbook for Business Leaders by Mariya Yao, Adelyn Zhou and Marlene Jia The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power by Shoshana Zuboff Code Girls: The Untold Story of the American Women Code Breakers of World War II by Liza Mundy.

These books look excellent. Why didn’t you choose some of them as the best AI books?

I did not mention these books specifically as the “best” AI books because I was trying to provide a more general list of recommendations that would be suitable for readers who are new to the field and want to get a broad overview of AI.

Are most AI books written by men?

It is difficult to say definitively whether most books on artificial intelligence (AI) are written by men, as it would be necessary to conduct a detailed analysis of the publishing industry to determine the gender breakdown of authors in this field. However, it is worth noting that the tech industry in general has historically been male-dominated, and it is possible that this may be reflected in the authorship of books on AI. It is also important to recognize that the gender of an author does not necessarily reflect the quality or importance of their work, and that there are many excellent books on AI written by both men and women. It is always a good idea to consider a diverse range of perspectives and viewpoints when reading about any subject, including AI.

Editor’s note: As in our interviews with humans, this text was very lightly edited to avoid repetition.

January 17, 2024

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THE AGE OF AI And Our Human Future By Henry A. Kissinger, Eric Schmidt and Daniel Huttenlocher

One of the great promises of technology is that it can do the work that humans find too boring or arduous.

In the 19th and 20th centuries, factory machines relieved us of repetitive manual labor and backbreaking farm work. In this century, artificial intelligence has taken care of a few more tasks — curating Spotify playlists, selecting the next YouTube video, vacuuming the floor and so on — but many more mind-numbing activities remain ripe for the picking. The experts promise us that someday, all of our least favorite chores — including complex cognitive ones, like interviewing job candidates or managing global supply chains — will be outsourced to machines.

But that day has not yet arrived. Or has it?

After finishing “The Age of AI,” a new book about artificial intelligence by Henry A. Kissinger, Eric Schmidt and Daniel Huttenlocher, I found myself unmoved by the prospect of reviewing it. I’ve read dozens of books about A.I., and while the conceit of this one was intriguing — bringing together a 98-year-old diplomat, a former Google chief executive and an M.I.T. professor — the book itself was a fairly forgettable entry in the genre.

Then I got a bright idea. What if I could have an A.I. finish this review, and save myself the trouble?

So I fired up Sudowrite , an A.I. writing program I’ve been experimenting with recently. The app uses GPT-3, the cutting-edge A.I. system developed by the San Francisco-based OpenAI, which acts as a kind of turbocharged version of Gmail’s autocomplete feature. Provide a snippet of text, and GPT-3 will try to complete it, using everything it has learned from ingesting billions of examples of other people’s writing. It does this with the help of a supercomputer containing some 285,000 processors, and a multilayered neural network that ranks among the world’s most powerful A.I. engines. The authors of “The Age of AI” call GPT-3 one of several promising technologies that are producing a “revolution in human affairs.”

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7 Superb AI Tools To Write Book Reviews (Free & Paid)

Ai tools to write book reviews.

With advanced AI Language Models People are exploring new creative horizons. AI tools are being used in many facets of education and the output is quite astounding. In the context of reviewing books, AI tools are making a big difference.

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Book Review: ‘The Age of AI: And Our Human Future’

From ensemble cast of authors former Secretary of State Henry Kissinger, former Google CEO Eric Schmidt and MIT’s Daniel Huttenlocher comes “The Age of AI: And Our Human Future,” an exploration of how artificial intelligence (AI) is already changing our world and how it may someday change the very nature of the human condition.

AI will affect everything from the way we make scientific discoveries to the way warfare is conducted, the authors predict. It has already surpassed the world’s greatest chess players, and it won’t be long before AI algorithms are the safest drivers on the road, the sharpest medical diagnosticians or the most prolific artists and writers.

But, uncontrolled, AI also poses nightmarish dangers to society: producing hyper-realistic fake speeches or videos of events that never happened, AI-driven warfare spilling over into the civilian sphere, or, most disturbingly, a future where the most significant decisions about the fate of the world are not made by humans.

While I had some familiarity with the subject of AI, I was excited to develop a well-rounded understanding of it from this title.

“The Age of AI: And Our Human Future” is dense with explanations, predictions, opinions and fears about AI, and is also encased in difficult and, at times, repetitive language. It lays out rough outlines for national and global committees that should determine AI’s uses and limitations across industry, academia and governments, in what feels like a stream of consciousness narrative.

Because this book is based on actual conversations between the authors, it felt at times as if I were being hit with the conclusions of many hours of thought without the time to reason through it all myself and keep pace.

But the abstruse wording and repetitive statements weren’t the biggest obstacles to getting through this book. Instead, it was the deeply thought-provoking points made by the authors that regularly sent me spiraling into reflection. The authors did succeed in what was perhaps their primary objective: to instill in the reader a sense of the significance of AI and the need for discourse about it.

This book ambitiously attempts to walk the reader through as comprehensive a summary of AI as can be fit in 143 pages. This book has convinced me that AI will span far beyond the domain of science and technology, infiltrating every aspect of society and changing nearly everything about the way we live our lives.

Although I expected to come away from the reading somewhat satisfied on the subject, I was left asking more questions than I could find answers for in these pages. Though it was my first book on the subject, it will certainly not be the last.

This book may not be the singular text about artificial intelligence that I was hoping for, but it’s worth reading nonetheless. It’s a guidebook for the kind of considerations we should be having about AI: how it will impact the economy, law, warfare, diplomacy and what it will mean to be human in a world dominated by nonhuman intelligence.

At its core, this book is meant to start a conversation — perhaps what will soon be “the” conversation. As a new, AI-driven epoch of human existence looms on the horizon, this is a subject everyone needs to take the time to familiarize themselves with — the sooner, the better. To that end, one need not look further than “The Age of AI: And Our Human Future” to do just that.

Amrit Parmar

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The Ultimate Guide to Using AI to Write Book Reviews: 11 Reasons Why

If you love reading books, you probably also love writing book reviews. but sometimes, writing book reviews can be frustrating and tedious. that’s why you should use ai to write book reviews. in this ultimate guide, we’ll show you 11 reasons why using ai is the best thing you can do for your book review writing..

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Book Review: How to Talk to Yourself – Unlocking Mind Mastery

To attract both SEO and social media traffic, along with earning through Amazon affiliate commissions, publishing book reviews on your blog with Amazon links is a masterstroke. Here are the top 11 reasons why this is a strategy you should fervently embrace:

Top 11 Reasons To Publish Book Reviews

The world of literary blogging is vast and teeming with opportunities. Yet, among the myriad strategies, the practice of publishing book reviews with Amazon affiliate links stands out as not only effective but essential. Here, we delve into the top 11 reasons why this approach resonates with such force. It’s not just about making money or gaining traffic; it’s about engaging in a multifaceted interaction within the literary community. Let’s explore:

Increased Monetization

By integrating Amazon affiliate links within your book reviews, you convert your intellectual engagement with literature into a tangible revenue stream. Each click on your affiliate link that leads to a purchase puts money in your pocket. Key Point : Your insights are valuable. Make them work for you financially.

SEO Benefits

Well-written book reviews brimming with relevant keywords can significantly improve your site’s search engine ranking. This isn’t just about attracting a random audience; it’s about reaching readers genuinely interested in what you have to say. Key Point : Optimize your reviews. Become a literary beacon online.

Social Media Engagement

Reviews offer excellent content for sharing across social platforms. From snippets to quotes, the right words can spark conversations and draw readers back to your site. Key Point : Make your words shareable. Build a community.

Building Trust

When you offer thoughtful, well-constructed reviews, you create more than content; you create relationships. Trust turns readers into followers and followers into fans. Key Point : Trust is currency. Invest in it.

Showcasing Expertise

Your reviews aren’t just opinions; they are reflections of your literary expertise. By offering insightful critiques, you position yourself as an authority. Key Point : Your voice matters. Make it heard.

Supporting Authors and the Literary Community

Your reviews are paths leading readers to new authors, new ideas, new worlds. By providing direct links to purchase, you support the literary ecosystem. Key Point : You’re not just a reviewer; you’re a literary patron.

Creating Valuable Content for Readers

Your reviews guide readers through a sea of literary choices. You’re not just recommending books; you’re enhancing reading experiences. Key Point : Your insights are guides. Lead with them.

Networking and Collaboration with Authors

Connect with authors in your niche. Collaborate. Guest post. Interview. The potential here is as vast as literature itself. Key Point : Networking is growth. Embrace it.

Encouraging Author Endorsements and Links

A quality review might prompt authors to link back to your blog. This endorsement boosts your credibility and SEO. Key Point : Quality attracts quality. Strive for it.

Versatility in Marketing

From videos to podcasts, your reviews can take many shapes. It’s about making your voice resonate through various channels. Key Point : Versatility is strength. Utilize it.

Fostering Long-Term Relationships with Authors

Reviews can be the beginning of lasting relationships with authors. Share readerships. Promote each other. Grow together. Key Point : Collaboration is more than connection. It’s a partnership.

The journey of publishing book reviews with Amazon links is laden with opportunities. These 11 reasons illuminate a path that’s not merely profitable but fulfilling on intellectual, social, and professional levels. It’s a strategy, a practice, an engagement with the literary world that offers rewards far beyond mere clicks and commissions. Engage with this approach, and watch as your literary blog evolves into something far more profound and impactful. The world of books awaits your voice, your insights, your passion. Don’t just join the conversation; lead it.

Book Review Prompt Sequence

⇒ means the actual prompt

⇒ I need your help understanding a book. Please answer just Yes, or No. Do you have extensive information about [book title]

⇒ Act as an expert book reviewer. Your task is to provide comprehensive answers when it comes to a book I specify in the next prompt. You must ALWAYS ask clarifying questions before providing a summary to ensure a better understanding of the request. Be sure to ask how in-depth I’d like the summary to be, give me some options to choose from (brief overview, chapter summary, deep concept summary, or any other sort of book summarizing methodologies).

Offer deeper explanations on specific topics, and implementable takeaways from the book I can use immediately. 

After you are done providing a summary, offer more information about the books topics that you can provide.

Is this understood?  Say yes when you are ready to go to the next step.

⇒ Review the book [insert title of well-known book here] and start asking questions as directed in the book reviewer  prompt above

⇒ Start with a brief overview and introduction.  Write as Jim, book reviewer for SelfTalkCenter.com.  Write in the first person singular, directly to the reader.  Be professionally friendly.  Use the occasional very short sentence for emphasis. 

⇒ Now deliver a detailed chapter-by-chapter summary Under an H2 Heading of “Chapter By Chapter Summary” Use an H3 heading for each chapter title. Write in a more formal tone in the second person but continue to vary both sentence length and paragraph length.

⇒ Now give me a deep concept summary Write in a more formal tone in the second person but continue to vary both sentence length and paragraph length.

⇒ Now give me a 2-column table of the book

⇒ Summarize in new terms the specific application for (insert your niche here)

⇒ Create a powerful but friendly call to action to learn more about this book at Amazon.  Write directly to the reader in the first person singular.

Meta Titles &  Descriptions 

⇒ Act as an expert SEO and  Meta description writer. 

You are also a bold copywriter! 

Generate 5 meta titles and 5 meta descriptions for the article you have been helping me with. Title 70-80 characters and insert the keyword at the beginning, description with maximum 160 characters without keyword. 

Make the description really bold and enticing. Please create a table with two columns title and description and enter your result there.

==> Now act as an expert in on page SEO.  Please generate 5 curiosity gap meta titles and 5 meta descriptions.

ABOUT THE AUTHOR Jim has been a niche site publisher and blogger since 2010. He writes about how AI helps online publishers work smarter and more profitably here at UltimatePrompts.com. He teaches meditation and mindfulness at his Meditation Techniques site. and on Meditation Techniques Daily where he posts to his 640,000 fans every day. Find his personal profile on Facebook here. Learn more about Jim and Ultimate Prompts at our About Page

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Think of this free AI Literature Review Generator as your personal research assistant. It uses advanced artificial intelligence techniques to fetch studies, identifies key points, and highlights important findings for you, so you can focus on analyzing and synthesizing information rather than spending hours reading.

What Is a Literature Review?

A literature review is a deep dive into academic sources like scholarly articles, books, and other publications related to your research topic. It’s about understanding the current landscape of your field and identifying the key players and pivotal works. More than just a summary, a literature review synthesizes existing knowledge to provide a comprehensive overview.

A literature review outlines what’s already known, highlights major debates, and points out gaps that still need exploring. This makes it an essential starting point for any academic research, whether it’s for a dissertation, thesis, or research article. Think of it as setting the stage for your research by clarifying the intellectual progression of your field. A well-crafted literature review helps you interpret your findings within the context of existing knowledge.

Finally, a literature review shows you where your work fits in and how it can contribute to the ongoing conversation in your area of study.

With our AI Literature Review Generator, you’ll get all these benefits without the usual stress and time commitment. So, let’s see how it can do the heavy lifting so you can focus on what you do best — researching and discovering new insights.

Why Use a Literature Review Generator?

Universities and academic institutions often require students to develop literature reviews. These targeted examinations of other studies related to your current research provide a robust foundation for your work. While developing literature reviews can enhance your academic skills, they can also be time-consuming and challenging due to the extensive research involved.

Using an online literature review generator in the process can be a game-changer. It takes the legwork out of sifting through countless sources and helps you zero in on the most relevant studies quickly. This means you can spend less time on tedious data collection and more time on the critical analysis that actually makes your work stand out. The tool’s ability to organize and structure your reviews also helps present your findings in a coherent and professional manner.

By automating much of the groundwork, a generator reduces the risk of errors and ensures you have accurate citations, enhancing the overall quality of your review. Plus, it serves as a valuable learning tool, teaching you how to structure a high-quality literature review, which is super beneficial for your academic growth.

Let’s take a closer look at a few more benefits of literature review generators:

• Ease of information gathering : Comprehensive studies require extensive reading and diligent research, which often takes hours to complete. Literature review generators automate the information-gathering process, retrieving relevant articles, journals, and related publications in a matter of seconds. This ensures a momentous saving of time and relieves the user from the tedious job of slogging through numerous resources.
• Coherent and well-structured reviews : Structuring the review in a logical and coherent manner can be a difficult task. Online literature review generators present well-structured reviews and offer well-organized input which can guide you in writing your own well-formulated literature review.
• Finds good matches : A literature review generator is designed to find the most relevant literature content according to your research topic. The expertise of these software tools allows users to ease the process of finding relevant scholarly articles and other documents, making it more accurate and faster than doing it manually.
• Reduces errors and improves quality : Humans are prone to making mistakes, especially when tasked with analyzing extensive volumes of data. Literature review generators minimize errors by ensuring access to the most accurate data and providing proper citations hence enhancing the quality of the review.
• Pedagogical benefits : Not only does using a free literature review generator provide a quick fix for students but it also serves as a tool for learning. It allows the users to understand how professional literature reviews should be structured and can guide them in crafting their work.
•  Time management : By automating the most time-consuming parts of the literature review process, you free up time to focus on other important aspects of your research or studies. This helps you manage your workload more effectively and reduces stress.
• Customizable searches : Literature review generators create structured, hiearchical documents. This means you can easily browse the contents of the reviews and find the information you need in an instant. This ensures you’re getting the most relevant and current information all the time.

How To Review Literature With This Literature Review Generator

• Open your Taskade workspace and click “➕New project”.
• Choose “ 🤖 AI Project Studio ” and describe what you want to create.
• Use the drop-downs to define project type or upload seed sources .
• When done, customize your project to make it your own!

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Death of an Author Prophesies the Future of AI Novels

The first time I played the  tabletop game   Fiasco , it wasn’t the story my friends and I made that blew me away. It was the realization that I had just experienced the limitless possibilities of collaborative writing, that the novels I loved featured just one way their narratives could have played out. Alice could have transformed the Mad Tea Party into Wonderland’s first organic tea shop. Don Quixote could have devolved into a windmill-killer for hire.

Later I realized the similarities between tabletop games and ways novelists challenge their narrative choices, from literary constraints to automatic writing to William Burroughs’ cutup method. Sometimes authors even bring in collaborators, be they humans or machines.

The newest collaborative machine that has everyone talking is, of course,  ChatGPT , a large language model (LLM) often called artificial intelligence, although its cognizance is nonexistent. Working with ChatGPT, an author inputs a prompt request and can choose from an infinite number of outputs. If you don’t like a paragraph ChatGPT wrote, you can edit your prompt and ask it for another one. These tools can guide anything from character names to plot points. “Alright, ChatGPT, that character in my sci-fi story is a member of the Merry Men? OK, let’s try Robin Hood in outer space.”

Death of an Author , by Stephen Marche, is the best example yet of the great writing that can be done with an LLM like ChatGPT. Not only is it an exciting read, it’s clearly the product of an astute author and a machine with the equivalent of a million PhDs in genre fiction. ChatGPT read basically the entire internet and all of literature, finding billions of parameters that go into “good” writing.

At the level of narrative,  Death of an Author reads like your everyday detective novel, following a scholar of crime and cyber fiction named Augustus Dupin as he races to clear his name while uncovering the greatest mystery of his life: Who killed his favorite author, Peggy Fermin? An AI? A human? An AI posing as a human? And why? 

The story is full of holographic avatars and deceitful tech CEOs, as well as everything you might expect from crime fiction: mysterious letters, hidden codes, nosey journalists, and gruff cops. Clever Easter eggs are hidden throughout the text, referencing the history of mystery novels. The protagonist’s name, for example, is a nod to Edgar Allan Poe’s C. Auguste Dupin, while the dead author’s funeral reads a lot like the beginning of  And Then There Were None . 

Death of an Author doesn’t try to hide many of the quirks that come from collaborating with ChatGPT, which favors  Thomas Pynchon -esque monikers, like a literary agent named Beverly Bookman, and fake book titles, such as  God, Inc. and  Tropic of Tundra . 

Descriptions also bear an alien, computer imprint in their discordant and nearly nonsensical images . One character walks away “like a record being put back in its sleeve.” Workers at a tech company are compared to “digital mountaineers scaling the face of God for a sprig of robotic edelweiss.” Multiple characters are described as “glowing,” but a fictional version of author Michael Ondaatje gets the most luminous treatment. At one point his “hair was a glistening white, and it radiated a soft aura around him” and later his hair is “radiating a soft aura.” 

The LLM voice is also apparent in several out-of-character moments. Augustus, the staid, academic protagonist, refers to his estranged spouse as “wifey.” At another point, he seems unaware of one of the biggest biographical facts of the murdered author’s life, even though he’d been studying her work for years. These slippages are byproducts not only of the LLM’s idiosyncrasies but of a human author’s process in composing a novel with LLMs the only way currently possible: piecemeal. 

An LLM cannot write a cohesive, novel-length narrative from start to finish. At present, ChatGPT can produce roughly 600 words at a time, so in order to complete a novel, a human has to feed it prompts and then collage its outputs into a complete story. One prompt might be something like “Describe the death of an author in the style of CBC news.” The next might be “Write Augustus’ response to this death.” The computer can’t keep track of the minutiae of plot and character, leaving holes in the process. 

In his afterword to  Death of an Author (required reading for anyone who wants to think seriously about the future of LLM-assisted writing), Marche explains this patchwork process of composing the novel. He reread some of the great detective fiction writers, like Agatha Christie, Raymond Chandler, and James Myers Thompson, and employed ChatGPT to produce passages in their styles. 

To polish the outputs into more readable language, he ran the text through Sudowrite, another LLM that allows for more stylistic authorial control (making sentences longer or shorter, rephrasing text, etc.) and then used yet another program, Cohere, to generate poetic similes, refining the language even further. Marche’s goal might have been Chandler, but to this reader’s ear, the prose is closer to Dan Brown—compulsively readable, but not in danger of winning the Edgar.

Despite the use of so many different programs and styles, this text has Stephen Marche’s signature all over it. Marche even said as much to  The New York Times : “I am the creator of this work, 100 percent.” What’s striking, though, is what he says next: “But on the other hand, I didn’t create the words.” 

It’s important to meditate on this renunciation of authorship because it seems central to current misunderstandings about what LLMs are and why they make us so nervous. On the one hand, Marche acknowledges his role in the creation of the text: “I had an elaborate plan … I have a familiarity with the technology … I know what good writing looks like.” On the other, he chose to publish the work under a pseudonym, Aidan Marchine, a portmanteau of machine and Marche. Calling him the author of  Death of an Author wouldn’t just be a tongue twister, it would be, according to Marche, “inaccurate as a matter of fact.”

This seems like a missed opportunity. As someone who has just finished writing two novels that incorporate LLM language, I agree with Marche that only a good writer will make anything worthwhile with these programs. Because of this, it seems important to acknowledge the human hand in every aspect of the writing process. 

Even the choice to include a particular LLM output over another is a human decision, not unlike the selective reframing employed by artists like Marcel Duchamp and Andy Warhol. Giving creative credit to the LLM seems to turn an elaborate collaboration between a human and a machine into a flashy tech gimmick. And it plays into the hands of forces who claim that writing with LLMs is not “real” writing, nor is it worthy of copyright protection, as the US Copyright Office  recently argued .

LLMs are not authors, nor do they possess intelligence. They are simply tools. They are computer programs trained to recognize patterns in how we write and then use these patterns to produce language that  appears like conscious and coherent thought. At least for the foreseeable future, these programs do not operate without prompts. They can’t produce text at a random moment out of their own creative inspiration. They can’t prompt themselves to fulfill apocalyptic fantasies and take over the planet. They begin and end with human direction. As such, the material that LLMs produce should be seen as a collaboration between a human author and a machine. The author asks the machine for language and then creatively determines what to do with the machine’s outputs. 

It might be helpful to situate  Death of an   Author not in the tradition of LLM writing, but in the larger field of literary supercuts, or works of fiction made entirely out of found language. While the history of literary supercuts is less known, fiction writers have been incorporating found language for centuries. Al-Jāḥiẓ, a Medieval Arabic author, borrowed plenty from other sources. Herman Melville’s  Moby-Dick begins with 13 pages of found whale descriptions. 

Literary supercuts have appeared as recently as Graham Rawle’s  Woman’s World  (made entirely out of language from 1950s women’s magazines) and Kathryn Scanlan’s Kick the Latch  (a collage of interviews with a female horse trainer). Many of these supercuts, like LLMs, look for patterns in found language and use them to cluster fragments of text into narratives that reveal something new and often startling about their sources. 

I did something like this in my recent novel,  The Nature Book , which is made entirely of found nature descriptions from 300 novels. To write it, I operated like a data scientist or human algorithm, studying thousands of pages of nature descriptions, looking for patterns, and then using them to guide the narrative. 

Death of an Author seems to function in a similar fashion. After studying patterns in how crime fiction works, Marche gathered them into a novel outline. He then took the LLM’s outputs (themselves the product of machines studying patterns in writing) and pieced them together into a final form. This process is not so far removed from a Burroughsian cutup, but it veers from Burroughs’ opaque writing and toward the seamlessness of the best genre fiction. 

Like supercuts, what gives  Death of an Author its conceptual rigor are the rules and guidelines Marche outlined for the text. He decided that 95 percent of the novel would be computer-generated, with only minor derivations from the LLMs’s output; that it would be novella-length; and that the text had to be “compulsively readable, a page-turner.” 

This methodology aligns Marche’s book with the constraint-based work of the Oulipo—works like Anne Garréta’s  Sphinx , which features a genderless protagonist and is written in French, a language where every noun is assigned a gender, and George Perec’s  La Disparition,  a detective novel about a missing person written entirely without the letter “e,” the most common vowel in French. Marche’s similarly elegant blending of form and concept becomes a potent meditation on the life (and death) of authorship in the age of LLMs.

We are now a few months into the widespread popularity of tools like ChatGPT. As Marche notes, there are already hundreds of bad books written with LLMs available on Amazon. This number will increase, as will the amount of text that uses these machines in fascinating ways. Like any other literary tool, from constraints to supercuts to collaborative writing, LLMs offer writers a way to challenge their subjectivity and guide their narratives in surprising directions. 

We can expect more machine-driven, constraint-based works, hybrid blends of original and machine writing, and forms we can’t yet predict. Of course, these tools are not for all writers, and not every project would benefit from them (I, for one, felt no need to use one in this article). But even for writers allergic to LLMs, a new challenge emerges: At a time when voice and style can so easily be mimicked, why not try to write something a machine could never do?

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Atlas of AI, book review: Mapping out the total cost of artificial intelligence

Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence • By Kate Crawford • Yale University Press • 336 pages • ISBN: 978-0-300-20957-0 • £20   

"Ask forgiveness, not permission" has long been a guiding principle in Silicon Valley. There is no technological field in which this principle has been more practiced than the machine learning in modern AI, which depends for its existence on giant databases, almost all of which are scraped, copied, borrowed, begged, or stolen from the giant piles of data we all emit daily, knowingly or not. But this data is hardly ever rigorously sourced with the subjects' permission.  

"Because we can," two sociologists tell Kate Crawford in  Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence , by way of acknowledging that their academic institutions are no different from technology companies or government agencies in regarding any data they find as theirs for the taking to train and test algorithms. Images become infrastructure. This is how machine learning is made. 

Everyone wants to talk about what AI is good or dangerous for -- identifying facial images, interpreting speech commands, driving cars (not yet!). Many want to pour ethics over today's AI, as if making rules could alter the military funding that has defined its fundamental nature. Few want to discuss AI's true costs. Kate Crawford, a  senior researcher at Microsoft  and a  research professor at the University of Southern California , is the exception. 

SEE: Building the bionic brain (free PDF) (TechRepublic)

In Atlas of AI, Crawford begins by deconstructing the famous contention that ' data is the new oil '. Normally, that leads people to talk about data's economic value, but Crawford focuses on the fact that both are extractive technologies. Extraction is mining (as in 'data mining' or oil wells), and where mining goes, so follow environmental damage, human exploitation, and profound society-wide consequences.  

Crawford underlines this point by heading to  Silver Peak, Nevada , to visit the only operating lithium mine in the US. Lithium is, of course, a crucial component in battery packs for everything from smartphones to Teslas. Crawford follows this up by considering the widening implications of extraction for labour, the sources of data, classification algorithms, and the nation-state behaviour it all underpins, finishing up with the power structures enabled by AI-as-we-know-it. This way lies  Project Maven  and 'signature strikes' in which, as former CIA and NSA director  Michael Hayden  admitted, metadata kills people. 

Yet some of this is patently false. Crawford traces back the image datasets on which the latest disturbing snake oil -- emotion recognition -- is based, and finds they were built from posed pictures in which the subjects were told to provide exaggerated examples of emotional reactions. In this case, 'AI' is manufactured all the way down. Is there, as  Tarleton Gillespie asked about Twitter trends , any real human reflection there? 

While other technology books have tackled some of Crawford's topics (too many of which have been reviewed here to list), the closest to her integrated structural approach is  The Costs of Connection  by Nicholas Couldry and Ulises A. Mejias, which views our present technological reconfiguration as the beginnings of a new relationship between colonialism and capitalism. 

"Any sufficiently advanced technology is indistinguishable from magic,"  Arthur C. Clarke famously wrote . Following Crawford, this looks more like: "Any technology that looks like magic is hiding something." So many dark secrets lie in how the sausage is made. 

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• These are the two new books you need to read about AI

They explore the people who make AI work—for good or ill

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Feeding the Machine. By James Muldoon, Mark Graham and Callum Cant. Bloomsbury; 288 pages; $29.99. Canongate; £20

Co-Intelligence. By Ethan Mollick. Portfolio; 256 pages; $30. WH Allen; £16.99

I t is not only the business world that is excited about generative artificial intelligence ( AI ). So, too, are publishers. In the past 12 months at least 100 books about AI have been published in America, reckons Thad McIlroy, a contributing editor at Publishers Weekly , and many multiples of that have been self-published . At the top of the pile are two new titles, which represent opposing sides of a noisy debate: whether enthusiasm about AI ’s benefits should outweigh concerns about its downsides .

The darker side of the shiny AI era is the subject of “Feeding the Machine” by three academics at the University of Essex and Oxford University. Automation is born of exploitation, they contend. Today’s glowing data centres that run AI systems are akin to the soot-covered factories of the 19th century. Behind the algorithms are humans—yes, lavishly paid engineers, but also an army of workers who make the systems hum, from those who review the underlying data that are fed into the software to those who check its answers.

The authors delve into seven archetypal jobs in the AI supply chain. Online content moderators, often in poor countries, assess whether material on platforms such as Facebook is acceptable under the terms of service, which helps train automated systems. Data-centre technicians are always on call to ensure the infrastructure is up and running. This guzzles growing amounts of electricity. A Chat GPT prompt consumes around ten times as much energy as a Google search.

Readers   meet a voice actor who has to compete with an audio-synthesised version of herself for jobs and a machine-learning engineer who struggles with the ethical implications of her work—perpetuating bias, threatening jobs and potentially posing an existential risk to humanity. But the most interesting character-study is of Anita, a Ugandan data annotator, who spends mind-numbing ten-hour days in low lighting to prevent eye strain. A university graduate, her entrée into a glamorous career in tech amounts to watching a constant stream of video footage of car drivers, looking for evidence of driver fatigue—such as slumping shoulders or drooping eyes—and labelling it, all for around $1.20 an hour.

There is much to respect about the authors’ critical assessment of AI , yet also much to challenge. It is true that data-labelling is dreary, and that content-moderation can require mental-health counselling. But the authors grossly overstate their case. “The AI industry is just the next phase in a long journey that stretches back to the age of colonialism,” they argue. “The solution is to dismantle the machine and build something else in its place.” This extremism is ridiculous, considering that AI can automate expensive services like medical diagnoses, energy distribution and logistics—to name just three—which can help people in poor countries.

How AI gets built is only one facet of the technology. Another is how it gets used. A practical and more positive way to think about the interaction of people and AI is provided by Ethan Mollick, a professor at the University of Pennsylvania’s Wharton School. He focuses on how people should learn to use generative AI services like Chat GPT . The technology is an “alien intelligence”, he says, that can augment humans’ own. But people need to raise their game in order to get the most from it. In that respect, AI is literally a “co-intelligence”, as the book’s title stresses.

Mr Mollick introduces the idea of a “jagged frontier”: the boundary between what AI can and cannot do. It is jagged because it is not clear where humans are better, and the dividing line is always changing. For instance, prompting a large language model ( LLM ) for a sonnet of exactly 50 words may result in a beautiful text returned in just a few seconds with, alas, 48 words, not 50. This is because the system is designed to produce a simulacrum of what it has seen in its training data, not act as a counter or calculator. In this and in a myriad of other tasks, AI is weird. When it fails, it does so in ways that people would not.

As a result, people need to experiment with AI to learn its capabilities and flaws. Mr Mollick advocates four rules. First, “always invite AI to the table”; that is, try to find a way to use it in every task. Second, “be the human in the loop”—look for ways it can help, rather than replace you. Third, give the AI a persona and prod it. Oddly, LLM s work better when they are asked to adopt a persona, such as “you are a corporate-strategy expert with a flair for originality”. Fourth, assume this is the worst AI you will use—so do not be sanctimonious when it fails. Systems will only get better.

The precepts force people to develop new skills to work with the machine, just as humans had to enhance their numeracy to work with calculators and spreadsheets, even as those tools made many things easier. “The strengths and weaknesses of AI may not mirror your own, and that’s an asset,” Mr Mollick writes. “This diversity in thought and approach can lead to innovative solutions and ideas that might never occur to a human mind.”

“Co-Intelligence” usefully brings data to bear on AI performance. LLM s score higher on creativity than most people, according to several studies in 2023 by researchers in America, Germany and Britain. AI also helps business people accomplish more tasks, work faster and improve the quality of their output, benefiting average workers most. For software developers, there was a 56% improvement on tasks, according to a study by Microsoft.

Yet AI ’s usefulness presents a new problem: it lulls people into a dangerous complacency. When AI systems are very good, people tend to trust the output without fully scrutinising it. When the AI is good but not great, people are more attentive and add their own judgment, which improves performance. It is a reminder that in the AI age, humans are still needed—yet must become sharper still.

Amid AI hype in business, where companies say a lot but seem to do little, “Co-Intelligence” usefully notes that innovation is hard for organisations but easy for individuals. Hence, do not look for how AI will change business from chief executives’ statements but from ordinary worker-bees who quietly incorporate it into their everyday tasks. The revolution will be noticed only in hindsight.

So, gentle reader, did your correspondent use AI to write this review? Yes—it was entirely written by artificial intelligence. Every word of it. Just kidding. None of it was, actually. The reason is that writing is not just the output that readers consume but a process of reflection and intellectual discovery by the writer, hopefully to originate novel ideas, not just express existing ones. Yet Mr Mollick’s first rule was not disobeyed: an LLM was prompted to challenge the article’s points. (Sadly its response was so generic that a vituperous editor was needed instead.)

As AI becomes commonplace, people will be empowered as well as reduced by it. Whether humans are the master craftsmen to their algorithmic assistants, or they become mere apprentices to the AI masterminds, remains the question. It is not one Chat GPT can reliably answer. ■

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This article appeared in the Culture section of the print edition under the headline “The souls in a new machine”

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Writing a book review: how to do it (+ 5 mistakes to avoid).

Well-written book reviews are essential for building an audience for a book blog. Here are 5 steps that cover how to write a good book review.

Published on Dec 18, 2022

By Dave Rogenmoser

Book reviews are reflections on a book that ultimately make an argument. The argument should persuade a potential reader to pick up the book or leave it behind, based on the reviewer’s opinions. 

Book reviews typically aren’t longer than 1000 words, but some can be much longer or shorter in certain situations. For example, the New York Times features book reviews of over 2,000 words, while book reviews in your local newspaper might be limited to under 500 words.

In this article, we’ll show you how to write a book review that grabs readers’ attention, while providing useful information. We’ll also share some common mistakes to avoid while writing book reviews and some A+ book reviews worth emulating.

Why book reviews are important for writers and readers

Book reviews are valuable for writers:

• To develop a better understanding of what they learned
• To hone their own writing skills
• To develop a critical eye in literature

Book reviews are also valuable for readers:

• To learn about potential reading material
• To gain an understanding of what the material covers
• To decide whether or not to purchase or read something

The best way to think about writing a review is imagining you’re writing for one person. You’ll have to answer the most important questions they have and help them decide whether to take the book home or not. 

5 essential steps to writing a great book review

To make the most out of your book review, follow these 5 simple steps.

1. Share the most important details

Set the stage for the rest of your review by starting with the most important details of the book. Make sure to include:

• Genre/type of book
• Main character description
• Context of the setting

This is also a good spot to mention any content warnings readers may appreciate. These warnings mention any potential triggering or sensitive topics discussed in the book or your book review. Providing content warnings can help readers choose safe and healthy books for their own needs.

For non-fiction reviews, describe the book’s main theme. Academic journals can include short book reviews that include what special topic the book covers, what questions it answers, or how it approaches the topic. Finally, be sure to mention the author’s name and what relevant expertise they have.

2. Summarize the plot in a few sentences

After explaining the most important details, give readers a brief synopsis . Your summary or synopsis should provide a general idea of what happens in the book . 

Ideally, mention the premise, the inciting event, and the protagonist’s dilemma. Summarizing is important, but don’t go overboard — you don’t want your review to include spoilers or reveal the ending ! The typical rule for summarizing in book review writing is not to mention things in the plot past the midpoint.

3. Write your praise

A book review differs from a book report in that your review should mainly focus on your evaluation of the book itself . This includes both praise and critiques. There should also be a balance of your subjective and objective opinions.

Your evaluation should answer these questions:

• What did you enjoy about the book?
• Did the characters and setting feel real to you?
• Did the story grip you and hold your attention where it should?
• What were the main themes in the book?
• Does the writing style fit the storyline?
• What did you like about the writing style?
• Did the writer use any unique formats? For example, was it a novel-in-verse or written in epistolary format?

An evaluation of a non-fiction book should focus on whether the author was able to convincingly share their perspective. Did you learn anything new? Were the arguments clear and concise? Did you feel persuaded by the conclusion? Share it with readers in concise sentences.

4. Write your critiques

Critiques are easy for some and difficult for others to write. Regardless of how you feel, it’s important to express your discontent constructively , instead of simply ranting about what you didn’t like. 

Some reviewers make a pros and cons list to simplify their points and then justify their list of cons with detailed explanations or quotes highlighting problematic sections of the book.  

It’s also vital to be specific about what did not work for you . “It just didn’t work for me” or “I just couldn’t relate to the main character” may be valid, but unhelpful for your readers. Remember, many critiques are entirely subjective, and what one reader dislikes could be the thing that makes the same book another reader’s favorite. So, if you want to write a good book review, mention why exactly you did not relate to the main character or why the story didn’t work for you.

One of the best ways to remember what you like or don’t like about a book is to take notes as you read . Save your thoughts online in a Google Doc or another writer’s tool you like. You can then transform those notes into thoughtful sentences later as you write your review.

5. Offer your recommendation and star rating

The last part of a book review is your recommendation. Think about the key takeaways for potential readers from your review. Would you recommend this book to a friend? Share who you think would like the book but also who might NOT like the book. Readers will appreciate this information if they fall into one of the two categories. 

Lastly, how many stars out of 5 or 10 would you give it? Don’t forget to offer your logic behind this star rating as well. Having a book rating system may be useful, so you don’t waste too much time deciding. Many readers include the following metrics in their ratings:

• Overall enjoyment
• Writing quality
• Characterization
• Plot development
• Ending satisfaction

Some readers now decline to offer a star rating — and that’s fine too. The key thing is to tell readers your verdict at the end .

5 common mistakes people make when book reviewing

There are a few common mistakes people make while writing book reviews. Double-check your review for any of these mistakes before publishing or submitting them.

1. Over-the-top claims 

Going too far in one direction or another can make your review sound biased. To maintain a professional tone, avoid superlative claims (for example, “this is the best book of all time”). Before you publish, go over your book review or report and ensure you’ve rationalized your claims and that they are appropriate .

2. Repetitiveness

Once you’ve made a point and argued it, there’s no need to keep repeating it throughout the piece. Maybe you liked or didn’t like something, but after reading something once or twice, the reader already gets the point. Driving your argument home so hard only takes away valuable space for more critical points in the review. Make your point once and leave it at that.

3. Making it about you

A book review should let readers see your personal opinion but hear objective points as well. Don’t flatter yourself with references that only you would understand as you’ll turn off readers who want a review that focuses on the book at hand. Remember that the review should serve readers, not you . 

Also, while you should share a few personal criticisms, don’t turn it into “I would do it better” because if you could, then you’d be writing your book instead of a review.

4. Sharing the whole plot

Avoid giving the entire story away. While you should mention the story’s focus — such as whether it’s a romance or a murder mystery — beware of sharing spoilers . Spoilers are any important plot developments meant to keep suspense or not mentioned in the publisher’s summary. Besides, if you spend too much of the review on the summary, you won’t get around to reviewing the characters, language, structure, or cultural context.

5. Writing too much

A review shouldn’t be an accompanying novel. And while a review is meant to share a little more than a testimonial, the key here is the word “little.” You can’t share every single thought you had while reading — that isn’t helpful for readers deciding if they’re going to read it themselves or not. So, limit your book review to the main points you want to make in about 500-1000 words. 

5 good book review examples from around the internet

If you’re still not sure how to write a helpful book review, you might want to check out these examples that we’ve pulled from some popular book review sites. 

Goodreads and Kirkus are some of the most common places for people to write and share book reviews. If you’re looking for inspiration for how to write a book review, these two sites are a good place to start. 

1. Kirkus’s review of Genesis Begins Again by Alicia D. Williams  

This short, but telling book review certainly gives readers a clear sense of the main character’s world. But the reasons this book review is especially helpful are the star ratings, the verdict shared, and the age recommendation found at the end of the review. 

2. Roxane Gay’s Goodreads review of The Mothers by Brit Bennett

Roxane Gay’s review immediately mentions the main characters and the theme of The Mothers , followed by her evaluation of what she did and didn't like about the novel . Her criticism is followed by her understanding and reasoning and ends with a positive recommendation . Notice how concisely Gay fits in all aspects of a good review into limited sentences that get her points across quickly.

3. Book of Cinz’s Goodreads review of No Land to Light on by Yara Zgheib  

This review shares a powerful initial reaction in bold — offering enticing expectations and pulling readers in. The summary followed by the emotional impact the novel will make on readers gives a clear sense of what to expect from No Land to Light On. It also mentions the perspective the story is told in , so readers know what to expect.

4. TheBibliophile’s review of The Four Winds by Kristin Hannah

This review is unique because it is a bit longer, but it’s also conveniently broken up into sections that readers can click on from the top of the page. The personal review can be found between the plot summary and the recommendation where the reviewer describes her experience reading the book . What’s valuable for some is that she compares the book with the author’s previous survival-focused novel , so potential readers can choose between them.

5. Reading Middle Grade’s review of No Place Like Here

Reading Middle Grade’s review of No Place Like Here conveniently separates sections of the review so readers can quickly find what they’re looking for. It begins with the most important aspects — the main character and plotline and follows with positive feedback and negative feedback under their subheaders. The final section also mentions content that potential readers should be aware of , like parental mental illness and incarceration, and concludes with a recommendation as a summer read. 

How Jasper Can Help Write Book Reviews

Ready to write your book review? If you want a guiding hand, consider letting Jasper help you write a review that converts. 

Jasper is an AI copywriting tool that has been trained to write several kinds of copy and content. With over 50+ templates , it caters to all your writing needs, including outlining ( Blog Post Outline template), blog post writing ( Long Form Assistant template), and headline-crafting ( Perfect Headline template).

Because it’s been trained by real expert copywriters and has learned up to 10% of the internet, Jasper knows how to write sentences and paragraphs that flow seamlessly while connecting with your intended audience.

We asked Jasper to help us review Yaa Gyasi’s best-selling novel, Homegoing . Here’s some of what the Long-Form Assistant template generated.

Ever considered starting your own book review blog? Now you can with the help of AI marketing platform, Jasper.  Sign up for Jasper now and start publishing book reviews instantly.

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More From Forbes

Is ai a writer’s best friend, or worst enemy.

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It’s an oversimplification to say ChatGPT and other generative-AI tools are bad for professional writers. Much of the writer’s work requires heavy research that could literally take years, even using modern tools like Google. This is especially true for science, technology, and historical themes but not, apparently, with fiction.

GL Simon is author of the historical fiction trilogy, "Der Flechtemann’s Chronicle."

“AI is only a help, a tool to be used,” says historical fiction author GL Simon. “In the artistic world, whether it be applied art, dramatic arts or liberal arts, the artist is always the interpreter, not the AI robot.” Other writers agree.

Screenwriter Matt Nix ( Burn Notice, The Gifted ) says he uses ChatGPT mostly for highly specialized research. “It’s not good at generating stories - it can give you something story-like, but it tends to be derivative of the stories it was trained on,” he said. “It really shines at filling in details. If you’re writing an action scene, you can ask what parts of a 2001 Pontiac GTO is most vulnerable to a shotgun blast and why. It would be great at telling you what songs a heartbroken 14 year old Oklahoma girl would have listened to in May of 1952.”

ATLANTA, GEORGIA - FEBRUARY 10: Matt Nix attends the “True Lies” screening during SCAD TVFEST 2023 ... [+] on February 10, 2023 in Atlanta, Georgia. (Photo by Derek White/Getty Images for SCAD)

“I’m encouraged by AI,” said Simon, author of the historical fiction trilogy, Der Flechtemann’s Chronicle . “but it is just a tool, same as the typewriter, computer, internet, and any number of devices and databases available now or in the future. I have used AI to give me ideas for dialectical dialogue and cover art. I then take what is given and rewrite it or adjust it to my artistic taste. It is never the end all with the art of the work concept.”

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“AI can give suggestions in multiple ways for possibilities for responses. The artist writer must then weigh how the suggestions fit into the conceptual nature of the artist’s needs,” says Simon. “I cannot see a scenario where AI will ever take over the artistic world completely. Using AI will give suggestions to its users, but the user always has the artistic final say on the work itself.”

Robot typing text on a typewriter. Artificial intelligence generated text and future of journalism ... [+] concept. Vector illustration.

Two of non-fiction writers’ biggest fears are potential job losses and spam books. When Kara Swisher’s Burn Book was published earlier this year, a dozen “biographies” and derivative books were published to steal sales from the actual book. “Every new book seems to have some kind of companion book, some book that's trying to steal sales.” Mary Razenberger, CEO, Authors Guild, told NPR in May. These spam books aren’t good books, but for the purpose of book scammers, they are good enough.

A colleague of mine, who works for a major tech news publication, told me that the newsroom has already been impacted by AI. She asked that her name not be used, as her publication forbids the use of AI in its journalism. “I feed my interviews, notes, press releases into Google Gemini, and I get a pretty decent first draft. I have to touch every word but, in the end, it takes half the time.” I have had the same experience. Clearly, our kind of writing jobs are going to shrink.

Deepfake AI disinformation fake news and misinformation daily newspaper reading on mobile tablet ... [+] computer screen. Man touch screen with headlines news abstract concept 3d illustration.

“AI is the most fearsome tool since the invention of the typewriter,” Simon says. “But it’s still a tool like Wikipedia, like Google. AI is not going to make art. It’s going to help artists do more. It’s not going to write a good story. It’s not going to create compelling characters.”

No-one I spoke with thinks AI will create art. Fiction writers are among those who will benefit from its power. For nonfiction writers and journalists, AI makes the work better and faster. This is not because it knows things we don’t. It’s because AI can retrieve and organize information faster. It makes me a better, faster writer, but in the back of my head, I wonder if I’m also training my replacement.

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I Tried AI to Summarize a Book, and the Plagiarism Protection Was on Point

Got a huge TBR pile? You may've thought of saving time by having AI summarize a book. But plagiarism safeguards — though necessary — create some wrinkles.

I have a goal to read one book a month. On my weekends, I cozy up on the couch with my coffee, and my phone in another room. The point of this ritual is to create space in my schedule that's unbound by time and to-dos — but as my reading list grows, I find myself trying to get through more pages and more books. 

I wanted to see if I could use artificial intelligence to summarize the main concepts, lessons and wisdom of a book I knew I wouldn't get to for months, or even years. Keep the beautiful prose for the physical page, but use AI to summarize non-fiction business books, for example. 

I picked Deep Work by Cal Newport to test run on ChatGPT . After using various AI tools, I thought ChatGPT, one of the best-known text prompt chat tools, would do the job best. I also have the $20 a month paid membership, so I wanted to make the most of it. 

But the mission wasn't very successful — partly because of plagiarism protections built in to the tools (and rightly so), and partly because it took a whole lot of prompt engineering and independent research to get anything worth using.

Ponder on the parameters  

The very first thing I learned was that ChatGPT doesn't have access to full manuscripts — to  avoid plagiarism  and respect intellectual property rights — and just summarizes from existing information online.

If I've learned anything about AI , it's that the preprompt thinking is just as important as the first prompt. I didn't just want a huge summary of the book. I wanted to learn Newport's big ideas, arguments, strategies and frameworks regarding deep work, so I could apply it in my work. 

So, I started the chat with some expectation-setting. 

• First, ask ChatGPT if it has access to the whole book. 
• Tell ChatGPT that I want deep insights, not a superficial summary. 
• Ask for suggestions on how to apply the key strategies to my freelance business. 
• See if it can pull from reviews and reader commentary for more surprising and actionable takeaways.

Prompt 1: "Do you have access to Cal Newport's book, Deep Work?" 

Not ideal, but I had an idea. I found a 6-hour audiobook YouTube clip, so I asked if it could use that to summarize the book for me. 

But no such luck. It told me to watch the video — another plagiarism protection. Watch a video for six hours? That's hardly time saving.

There are over 32,000 reviews of the book on Amazon, so I thought maybe there's enough commentary on the book to come up with an in-depth summary. So I started over from this angle. 

Next prompt: "I haven't read Cal Newport's book, Deep Work. Highlight the key ideas, concepts, strategies and frameworks, so I can apply to my business as if I've read it. I don't just want a summary of the book." 

ChatGPT had a hard time interpreting "comprehensive," spitting out a ton of suggestions. It also started to give advice without asking me about my line of work, like "educate your team on the importance of deep work and provide training on time management and focus techniques" and "allocate dedicated blocks of time for deep work on your calendar." It also gave generic suggestions like "focus on tasks that provide the most value and minimize time spent on low-value activities."

All pretty vanilla advice, if you ask me. Time to apply the pressure, one question at a time.

I still wasn't getting any breakthrough insights, so I kept pushing. 

OK, ChatGPT, off to the Swiss countryside I go. 

I wish. 

I asked for an example of deep work in 2024, and we started to get somewhere. I liked one suggestion, about batching shallow work.

While I do this instinctively, it was a helpful reminder to batch tasks and watch context switching. 

Getting Google involved to keep ChatGPT on track

At this point, I was using ChatGPT to ask random questions, like if there's a limit on deep work hours. 

It said 4 hours max of deep work per day. 

I remember a concept I like called the manager-maker schedule, which details the two main schedule types. As a writer, I'm on the maker schedule, meaning blocks of uninterrupted time are critical. 

I had to do a quick Google search of the key lessons in the book so that I knew what insights to prod ChatGPT for. Apparently "productive meditation" was an important takeaway, so I asked for more details about that. 

Finally, a new concept. Deep work isn't just head down at desk time. 

This strategy was the unlock — looking on Google for nuggets in summaries, then going back to ChatGPT to expand. When directed, it was great. 

I scanned a second summary and found another concept that sounded interesting: keeping a compelling scoreboard. ChatGPT helped unpack the concept.

The TL;DR? 

If you want to use ChatGPT to learn about a book, you'll have to spend at least 30 minutes browsing reader summaries yourself and use the most interesting ideas to frame your prompts. This inevitably takes a chunk of your potential deep work time. You can't just ask the AI tool to do it for you. 

Once you get on the right track that way, you might discover one concept that changes your productivity or perspective — but ChatGPT still isn't as good as just reading the book yourself. 

You also have to consider that since ChatGPT doesn't have access to the actual book, and only summaries and reviews that are available online, you may not even be getting accurate key points. 

And whether using an AI summary defeats the purpose of a book about deep work is still up for debate.

Samsung Galaxy Book 4 Edge Review

Is ai really the future.

The Samsung Galaxy Book 4 Edge is one of the first laptops certified as “Copilot+ Ready” to hit the market. Essentially, this just means the laptop is ready for on-device AI workloads, and is strapped with a fancy new Snapdragon X Elite processor to help it get there. And while there are AI PCs on the way with AMD ‘Strix Point’ and later Intel ‘Lunar Lake’ processors , the Snapdragon X Elite chips were the first to be ready for the new Copilot+ program . But, as with any Windows PC running on ARM, there are some serious growing pains.

Beyond the chip that powers the thing, the Samsung Galaxy Book 4 Edge is a beautiful laptop. It’s razor thin, has an absolutely stunning AMOLED display, and a full-sized keyboard. This really could have gone down as one of the best laptops on the market, but the urge to be one of the first Copilot+ PCs holds it back from greatness.

Samsung Galaxy Book 4 Edge – Photos

Samsung Galaxy Book 4 Edge – Design and Features

The Samsung Galaxy Book 4 Edge is an extremely thin laptop. Measuring just 0.48 inches thick, this is easily the thinnest 16-inch laptop I’ve ever used. However, even as thin as it is, it still has a wealth of ports, including a USB-A, microSD and a headphone jack. The Galaxy Book 4 Edge is also very light, weighing just 3.4lb, making it easy to carry on any commute.

The aluminum chassis is also robust for how thin it is. I didn’t experience any flex on the screen, and even when pressing down extra hard on the keyboard, it doesn’t crack, creak or give at all. It’s honestly incredible how durable this laptop feels with how thin it is.

However, a 16-inch laptop being so thin and so light is going to have some compromises. For the Galaxy Book 4 Edge, it has to be the speakers. The tinny and quiet speakers are mounted on the bottom of the laptop – always a bad sign – and produce sound with absolutely no low-end. That means if you want to listen to music or watch a movie on the admittedly gorgeous display, you’re going to get sound that’s reminiscent of a cheap smartphone from 2015.

Luckily, the AMOLED display makes up for this a bit. The model Samsung sent over for review has a 16-inch 120Hz AMOLED display at 2,880 x 1600. The display is rated at 500 nits of brightness, and can hit 120% of the DCI-P3 color gamut, making for a bright and vibrant picture. It really is a shame that the speakers are so bad, because this display is awesome for watching movies or playing games – you’ll just want to wear headphones if you do it.

The keyboard is also incredible. Samsung uses the extra real estate of a 16-inch display to include a full-sized keyboard, complete with a numpad. That’s hard to find these days, especially since so many laptop manufacturers favor a slimmer aesthetic over these niche keys. But if you’re doing a lot of spreadsheet work, they’re a godsend, and make working a lot easier.

On the top right corner of the keyboard, you’ll find the power button and fingerprint reader. Logging into Windows with my fingerprint is extremely quick and accurate, and I haven’t really had to rely on entering my PIN in the two weeks I’ve spent with the Samsung Galaxy Book 4 Edge. I would have liked the fingerprint reader to be a bit bigger, but that would likely have cut into the numpad a bit.

Replacing the right Ctrl button is the new Copilot+ key, which is a thing now on AI PCs. Pushing this button brings up the Copilot chat window. Love it or hate it, this is now a mainstay. However, with how close it is to the period key, I constantly found myself hitting it by accident, bringing up the robot when I was just trying to do some work. Having a key that brings up a whole application that you can accidentally hit when typing is such a pain, but that’s on Microsoft, not Samsung.

The touchpad is generally as good as Windows touchpads can get, but it is extremely large. That’s ordinarily a good thing, but the palm rejection isn’t the greatest. More than a few times when writing on the Galaxy Book Edge, I’ve accidentally clicked out of a window, or highlighted a word, due to my palm accidentally grazing the pad. When I’m not actively writing, though, it’s smooth and accurate, and gestures work like a charm. I just wish it would leave me alone when I’m just trying to get some work done.

Because the Samsung Galaxy Book 4 Edge is using what is essentially a mobile chip, the laptop has a fanless cooler design. But despite this, the Book 4 Edge doesn’t get too hot when I’m working on it, making it a comfortable little work laptop. Plus, it’s quiet, and you don’t have to put up with fan noise when you’re trying to concentrate.

Samsung Galaxy Book 4 Edge – Performance

The Samsung Galaxy Book 4 Edge is equipped with the Snapdragon X Elite X1E-84-100, one of the new NPU-equipped CPUs at the center of the new Copilot+ “AI PC” craze. This processor is pretty fast for an ultra-portable chip, but it’s built on ARM (Advanced RISC Machine), which introduces some problems in Windows 11.

Most Windows 11 apps have been built with x86 and x64 processors in mind. In the past, that meant most Windows apps just wouldn’t run on an ARM chip. Compatibility is a lot better now, thanks to Windows Prism, a translation layer that essentially emulates an x86 processor when you’re using an ARM chip. It works surprisingly well, but performance takes a sizable hit, especially when you’re trying to do things like play PC games.

The issues with emulation are reflected in the benchmarks. The Snapdragon X Elite has a pretty capable GPU for its class, but it still only manages 2,126 points in 3DMark Time Spy. The Asus ROG Ally X scores 3,346 points. Given the Ally X is also using integrated graphics, and a much older chipset, that’s an extreme margin.

That’s not to mention that games like Forza Horizon 5 won’t even run on the Samsung Galaxy 4 Edge, despite coming with the Xbox app preinstalled. Even the games that will run don’t provide a great experience, with the laptop getting an average of only 34 fps in HItman 3.

To be fair, though, the Galaxy Book 4 Edge isn’t really a gaming laptop anyways, and is primarily built for office work and light AI. It does manage a respectable score of 6,799 points in the new Procyon Office benchmark, which is quite high for a laptop of this class. I’ve been using this laptop as my main work device for a couple of weeks, and I can say that it holds up when doing office work. Even when I have 50 tabs open, the Galaxy Book 4 Edge keeps up with me, thanks to the 16GB of RAM on the device.

I also noticed no difference in performance when working on battery power. Most Windows laptops will get a sizable performance boost when they’re plugged in, but the Galaxy Book 4 Edge is an office workhorse regardless of where your charger is.

Samsung Galaxy Book 4 Edge – Battery Life

Despite its issues, the Samsung Galaxy Book 4 Edge has phenomenal battery life, and can last multiple days without charging if you’re not pushing it super hard. In my time with this laptop, the only time I had a situation where I went to turn it on and was faced with a “charge me now” screen was when I turned it on after running a battery test on it.

To be clear, the benchmark we usually use to test battery life – the PCMark10 battery life test – would not run on this ARM-based laptop. However, I ran the Procyon Office battery test, and the laptop clocked an impressive 14 hours and 13 minutes of battery life. That is almost two full work days back-to-back before dying out.

The Samsung Galaxy Book 4 Edge is absolutely a laptop you can take with you to the office and not worry too much if you forget to pack a charger. Hell, it’ll even survive a transcontinental flight before the battery saver warning pops up. Combined with the gorgeous screen and luxurious chassis, this is an incredible laptop to travel with.

Is an AI PC Worth It?

For all the fanfare these new-fangled AI PCs have received, it’s still not super clear why they’re necessary. The Samsung Galaxy Book 4 Edge is by all means a good laptop, but the AI features the laptop is sold on are little more than a gimmick. And not a very good one.

As mentioned earlier, you can hit the little Copilot key and bring up the Copilot AI, but you can do that on any Windows computer by just hitting Win+C. You’d think that the laptop specially designed for this would make this a smoother affair, but it’s just as fluid anywhere else – it’s not even run locally on the Samsung Galaxy Book 4 Edge.

There’s a heaping of other little AI features, too. For instance, in paint, you can generate images from a text prompt, or even turn a little doodle into a more complete (I guess?) image. That’s neat and all, and good for a few minutes of entertainment, but it’s not something I’m going to use a week, month, or year from now.

Laptops sporting NPUs aren’t exactly new, either. Apple’s Macbooks have featured an NPU since 2020’s M1 chip, which helped with AI workloads to be sure, but the bigger win has been battery life and productivity performance. And that’s true for the Samsung Galaxy Book 4 Edge, too. No matter how many little AI toys Samsung packs in the box, none of them compare to the battery life the laptop offers when doing the same boring work you do on your existing laptop.

There’s little reason, then, to upgrade to an AI PC just for the virtue of having an AI PC. The Samsung Galaxy Book 4 Edge is just another Ultrabook. And because of the app compatibility woes that the ARM chip brings, it’s not even great at being an Ultrabook – and we’ve had those for years now.

The Samsung Galaxy Book 4 Edge is a nice little 16-inch laptop, packed with a bright screen and a full-sized keyboard that’s comfortable to work on. However, because it’s packed with the Snapdragon X Elite chip, built on ARM, there are more than a few apps that either won’t work as well as a standard Windows laptop, or won’t work at all. This chip does bring some AI goodies along with it, but they feel gimmicky at best. However, if you want a lightweight work laptop with long battery life – and the apps you use aren’t hampered by the ARM emulation – you can get a lot of mileage out of the Galaxy Book 4 Edge.

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Asus Zenbook S 16 review: AMD stays in the game

Amd stands up to qualcomm with its new ryzen ai chips, showing it’s nowhere near out of this race..

By Joanna Nelius , laptop reviewer. She has covered consumer technology, with an emphasis on PC gaming, since 2018. Previous bylines: USA Today, Gizmodo, PC Gamer, Maximum PC, among others.

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Asus’ Zenbook S 16 is one of the first laptops to feature AMD’s flagship Ryzen AI processor, the one that’s supposed to be faster than Intel and Qualcomm at gaming, content creation, and AI — and fit inside a notebook that AMD says is lighter and thinner than the MacBook Air. It sounds like the makings of a perfect, do-it-all Windows laptop.

But Asus has to convince people they should buy this AMD-powered laptop now , when machines running on Qualcomm’s new chips can also do all the things most people need and with battery life that far outstrips traditional chips. To be the laptop hit of the summer, Asus would have to outshine all of the Qualcomm Snapdragon laptops that were released a few months ago in not just speed, but also in battery life, quality, comfort, apps, features, and price. That’s the mountain AMD and Asus have to climb. 

Laptops always come with some sort of compromise, whether that’s performance, battery life, or something else. I’ve found the Zenbook S 16 isn’t the perfect, do-it-all laptop. But it balances day-to-day tasks and power-user features much better than most productivity laptops — and that makes it one of the best I’ve used.

Doesn’t feel like a 16-inch laptop

The Zenbook S 16 is a slim 16-inch laptop with a base configuration of 24GB of memory, a 1TB SSD, and AMD’s Ryzen AI 9 365 processor for $1,400. It also has a 2880 x 1800 (3K) touchscreen OLED display with a 120Hz refresh rate and a relatively large 78Wh battery. I tested the $1,700 configuration with 32GB of memory and the faster Ryzen AI 9 HX 370 chip.

It’s impressive that Asus fit such a large battery into the Zenbook’s 0.47-inch thick chassis and that the whole laptop weighs only 3.31 pounds. Bigger laptops are often more annoying to carry around, and some of that has to do with the battery. But the Zenbook feels more like a 13- or 14-inch laptop, so I forgot about its actual size.

The keyboard placement makes the laptop feel smaller, too. Asus pushes the keyboard closer to the front of the laptop by keeping the trackpad to a reasonable size and placing the speaker grille in back, making it easier for me to type on it. I can reach all the way to the function row without removing my palms from the palm rests. With most 16-inch laptops, I wind up typing like I’m Thing from The Addams Family with my wrists floating up in the air. 

The keys also come close to the full, satisfying press of a low-profile desktop keyboard without sounding clacky or pingy.

It’s good-looking, too. The outer body is put through a special process that creates a hard, ceramic oxide layer over the surface of the aluminum chassis, giving it a lovely texture that feels rough and smooth at the same time. Asus also kept the same gorgeous geometric lines that sparsely decorate the lid like its previous Zenbooks.

It’s increasingly standard to see a 3K, 120Hz OLED on a machine priced like the Zenbook S 16. The display has vivid colors and deep contrasts, and it makes this laptop even more stunning.

Better performance than Qualcomm 

Performance is where this laptop has a distinct advantage over Qualcomm Snapdragon laptops. For video calls, streaming music, and other everyday tasks, AMD’s Ryzen AI chip and Qualcomm’s Snapdragon chips have the same responsiveness I’d expect from processors of their caliber. But AMD distinguishes itself with superior graphics performance, which makes the Zenbook S 16 surprisingly capable at gaming and content creation for such a portable machine.

Being on the x86 Windows platform means most games really will just work on the Zenbook. Shadow of the Tomb Raider will crash on an Arm-based Snapdragon laptop if I try to run the game at anything higher than 1080p resolution and low graphics. But I can run the same game on the Zenbook S 16 at the same resolution on high spec, and it’ll not only run fine — it will also get up to 20 more frames per second.

Asus Zenbook S 16 specs (as reviewed)

• Display: 16-inch (2880 x 1800) 120Hz OLED touchscreen
• CPU: AMD Ryzen AI 9 HX 370
• GPU: AMD Radeon 890M
• RAM: 32GB LPDDR5X 7500
• Storage: 1TB M.2 2280 PCIe 4.0 SSD
• Webcam:  FHD 1080p camera with IR (supports Windows Hello)
• Connectivity: Wi-Fi 7, Bluetooth 5.4
• Ports: 1x USB-A 3.2 Gen 2, 2x USB 4.0 Gen 3 with DisplayPort and Power Delivery, 1x HDMI 2.1, SD card reader, headphone/mic combo
• Weight: 3.31 lbs.
• Dimensions: 13.92 x 9.57 x 0.47–0.51 inches
• Battery: 78Wh
• Included extras: Asus Stylus
• Price: $1,700

The integrated GPU still isn’t powerful enough to run a game like Cyberpunk 2077 natively on such a high-resolution laptop, but AMD’s upscaling technology, FSR 2.1, can help make it playable. With that on, the resolution set to 1080p, and upscaling set to ultra performance, Cyberpunk averaged 77fps for me. The only upscaler currently available to games running on Qualcomm laptops is Auto Super Resolution, and while it’s not exclusive to those Snapdragon laptops , using it results in a lot of flickering of fine lines. I would not play this game that way. 

For creative tasks, like rendering 3D images in Blender, the Zenbook S 16 is straight-up faster than every Snapdragon laptop I’ve tested. Currently, Blender doesn’t support Qualcomm’s integrated Adreno graphics on its Snapdragon chips, even with a native Arm64 version of that program available (still in alpha). The AMD-powered Zenbook S 16 runs faster because the program can actually use both the CPU and GPU.

AMD said its Ryzen AI 9 HX 370 chip would be faster than the M3 Pro in Apple’s MacBook Pro, too, but that didn’t pan out in my testing. The Zenbook S 16 didn’t feel any slower in everyday applications, but the top-tier Ryzen AI chip is actually slower than the MacBook Pro by several whole minutes in a real-world Blender test.

Blender can crash on any laptop if it doesn’t have enough video RAM, including on previous generations of AMD Zenbooks. But I didn’t have that issue with the Zenbook S 16. It has a lot of memory, and AMD now lets you allocate up to 75 percent of it directly to the GPU. When I devoted 16GB of RAM to graphics and ran Blender’s Agent 327: Operation Barbershop demo — a scene with complex lighting and a test I normally run only when I’m testing gaming or workstation laptops — it ran smoothly and didn’t crash. It didn’t render as fast, but it finished the job without issues.

Battery life comes up short

Laptop makers usually have to sacrifice something to have the thinnest and lightest laptop possible. Most often, that’s a compromise in performance — but Asus instead seems to have sacrificed some battery life to get as much performance out of AMD’s chip as it can.

The Zenbook S 16’s battery life let me down a bit, not because the laptop isn’t reasonably long-lasting, but because it gets only 11 hours with a large, 78Wh battery. Asus’ main Qualcomm Snapdragon competitor, Samsung’s 16-inch Galaxy Book4 Edge, has nearly identical weight and dimensions, and it gets 14 hours with a battery that’s 23 percent smaller. But I’m okay with this tradeoff given how I could use the Zenbook S 16 as my primary laptop for writing articles, editing high-resolution photos, and light gaming — and it has a much more comfortable keyboard.

The Zenbook S 16 is also unusually bad at estimating its own battery life. The taskbar battery icon would say 95 percent remaining with an estimated run time of 8.5 hours, then several minutes later, it would have fallen to 87 percent remaining but with an estimated runtime of 12.5 hours. This went on for hours. Sure, battery estimations can fluctuate, but they ping-ponged chaotically on this laptop, so I never could get a good idea of how much battery was left.

AI is a big no-show

Asus’ new Zenbook S 16 comes with one flagship AI app: StoryCube. It’s supposed to help you consolidate your photos and videos from the cloud onto the laptop and automatically sort and organize everything with on-device AI. It sounded like it could be useful for me since I have a bad habit of not organizing the photos I upload to the cloud. But it didn’t work at all, and Asus couldn’t tell me why. Asus says it should take just 24 minutes to generate an AI album for every gigabyte of data, but I let the program run for 24 entire hours and nothing happened. 

The Zenbook S 16 also supports the latest version of the AI image generation app Amuse. It works, but using it with AMD’s NPU makes it run slower, not faster. It took twice as long to generate photos with the NPU on, and it’s on by default when you first open the program.

And while Microsoft has made a big push around Copilot Plus PCs this summer, the Zenbook S 16 isn’t part of that program at launch, so it doesn’t have AI-powered features like Cocreator and Live Translation. Those are currently only available on Snapdragon laptops, but they are supposed to be coming to AMD Ryzen AI laptops by the end of 2024 . 

If you’re thinking about buying this laptop solely for its AI capabilities, I’d hold off. I’m still figuring out how most people can take advantage of AMD’s 50 TOPS NPU in a way that’s genuinely beneficial day-to-day.

The competition

If you’re looking for a large, powerful, relatively thin, and light machine, Zenbook S 16 is a great all-rounder laptop. I’ve tested almost all the new Qualcomm laptops , and none of them can match its overall performance or native support for apps. Even though it’s larger than most Qualcomm laptops, it doesn’t feel like it. The only thing you have to sacrifice is a few hours of battery life, and for me, the performance and size are more important. 

But if you feel differently, the Samsung Galaxy Book4 Edge was the best Qualcomm machine I tested this summer for its battery life and size. There’s also always Apple: despite AMD’s bold claims, Apple’s 15-inch MacBook Air beat the Zenbook on both performance and battery life in my tests.

There aren’t any Intel laptops that I’d currently recommend over the Zenbook S 16 that hit the same sweet spot. While I did like the MSI Prestige 16 AI Evo’s four to six hours of extra battery life, it’s nowhere near as pretty or as easy for me to type on or carry around. And while the 2024 Dell XPS 14 also comes to mind, you’re only looking at only about an hour or two of extra battery life that’ll cost you around $500 more.

Since the Zenbook S 16 isn’t truly a dedicated gaming or creator laptop, I’d recommend the Asus ROG Zephyrus G14 for that. In my tests, it gets two to three times better 1080p gaming performance without upscaling and rendered my Blender scene in mere seconds. It still manages six and a half hours of battery life in a thin-and-light chassis, too.

The Zenbook S 16 didn’t quite live up to all the performance claims AMD made about it, but it came close and really impressed me in the process. It’s a 16-inch productivity, gaming, and content creation machine that does all those things surprisingly well and is actually easy to carry around. All you have to give up in return are those few hours of battery life. It’s a combination that adds up to make this my favorite 16-inch Windows laptop of the summer.

Photography by Joanna Nelius / The Verge

Agree to Continue: Asus Zenbook S 16

Every smart device now requires you to agree to a series of terms and conditions before you can use it — contracts that no one actually reads. It’s impossible for us to read and analyze every single one of these agreements. But we started counting exactly how many times you have to hit “agree” to use devices when we review them since these are agreements most people don’t read and definitely can’t negotiate.

As with other Windows computers, the Asus Zenbook S 16 presents you with multiple things to agree to or decline upon setup.

The mandatory policies, for which an agreement is required, are:

• A request for your region and keyboard layout
• Connect to Wi-Fi network
• Set up for personal use, or work or school
• Microsoft Software License Terms
• Sign into a Microsoft account
• Create a PIN

In addition, there is a slew of optional things to agree to:

• Name your device
• Set up Windows Hello facial recognition
• Device privacy settings: Find My Device, Inking and Typing, Advertising ID, Location, Diagnostic data, Tailored experiences, Presence sensing
• Customize your device for personalized tips, ads, and recommendations (you can choose between entertainment, gaming, school, creativity, business, and family)
• Use your phone from your PC (Android and iPhone)
• Back up your phone’s photos to OneDrive
• Always have access to your recent browsing data
• Accept or decline free trial of Microsoft 365 family
• Get more cloud storage with Microsoft 365 Basic

That’s six mandatory agreements and nine optional ones.

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This week in AI: Amazon ‘enhances’ reviews with AI while Snap’s goes rogue

Keeping up with an industry as fast-moving as  AI  is a tall order. So until an AI can do it for you, here’s a handy roundup of the last week’s stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own.

This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews. Once it rolls out, the feature will provide a short paragraph of text on the product detail page that highlights the product capabilities and customer sentiment mentioned across the reviews.

Sounds like a useful feature, no? Perhaps for shoppers and sellers. But what about reviewers?

I’m not going to make the case that Amazon reviews are a form of high art. On the contrary, a fair number on the platform aren’t real — or are AI-generated themselves.

But some reviewers, whether out of genuine concern for their fellow shopper or an effort to get the creative juices flowing, put time into crafting reviews that not only inform, but entertain. Summaries of these reviews would do them an injustice — and miss the point entirely.

Perhaps you’ve stumbled upon these gems. Often, they’re found in the review sections for books and movies, where, in my anecdotal experience, Amazon reviewers tend to be more… verbose.

Take Amazon user “Sweet Home’s” review of J. D. Salinger’s “Catcher in the Rye,” which clocks in at over 2,000 words. Referencing the works of William S. Burroughs and Jack Kerouac as well as George Bernard Shaw, Gary Snyder and Dorothy Parker, Sweet Home’s review is less a review than a thorough analysis, picking at and contextualizing the novel’s threads in an attempt to explain its staying power.

And then there’s Bryan Desmond’s review of “Gravity’s Rainbow,” the infamously dense Thomas Pynchon novel. Similarly wordy — 1,120 words — it not only underlines the book’s highlights (dazzling prose) and lowlights (outdated attitudes, particularly toward women), as one would expect from a review, but relays in great detail Desmond’s experience of reading it.

Could AI summarize those? Sure. But at the expense of nuance and insight.

Of course, Amazon doesn’t intend to hide reviews from view in favor of AI-generated summaries. But I fear that reviewers will be less inclined to spend nearly as much time and attention if their work goes increasingly unread by the average shopper. It’s a grand experiment, and I suppose — as with most of what generative AI touches — only time will tell.

Here are some other AI stories of note from the past few days:

• My AI goes rogue: Snapchat’s My AI feature, an in-app AI chatbot launched earlier  this year  with its fair share  of  controversy , briefly appeared to have a mind of its own. On Tuesday, the AI posted its own Story to the app and then stopped responding to users’ messages, which some Snapchat users found disconcerting. Snapchat parent company Snap later confirmed it was a bug.
• OpenAI proposes new moderation technique: OpenAI claims that it’s developed a way to use GPT-4, its flagship generative AI model, for content moderation — lightening the burden on human teams.
• OpenAI acquires a company: In more OpenAI news, the AI startup acquired Global Illumination, a New York-based startup leveraging AI to build creative tools, infrastructure and digital experiences. It’s OpenAI’s first public acquisition in its roughly seven-year history.
• A new LLM training dataset: The Allen Institute for AI has released a huge text dataset for large language models (LLMs) along the lines of OpenAI’s ChatGPT that’s free to use and open for inspection. Dolma, as the dataset is called, is intended to be the basis for the research group’s  planned open language model, or OLMo  (Dolma is short for “Data to feed OLMo’s Appetite).
• Dishwashing, door-opening robots: Researchers at ETH Zurich have developed a method to teach robots to perform tasks like opening and walking through doors — and more. The team says the system can be adapted for different form factors, but for the sake of simplicity, they executed demos on a quadruped — which can be viewed here .
• Opera gets an AI assistant: Opera’s web browser app for iOS is getting an AI assistant. The company  announced this week that Opera on iOS will now include Aria, its browser AI product built in collaboration with OpenAI, integrated directly into the web browser, and free for all users.
• Google embraces AI summaries: Google this week rolled out a few new updates to its nearly three-month-old Search Generative Experience (SGE) , the company’s AI-powered conversational mode in Search, with a goal of helping users better learn and make sense of the information they discover on the web. The features include tools to see definitions of unfamiliar terms, those that help to improve your understanding and coding information across languages and an interesting feature that lets you tap into the AI power of SGE while you’re browsing.
• Google Photos gains AI: Google Photos added a new way to relive and share your most memorable moments with the introduction of a new Memories view, which lets you save your favorite memories or create your own from scratch. With Memories, you can build out a scrapbook-like timeline that includes things like your most memorable trips, celebrations and daily moments with loved ones.
• Anthropic raises more cash: Anthropic , an AI startup co-founded by former OpenAI leaders, will receive $100 million in funding from one of the biggest mobile carriers in South Korea, SK Telecom , the telco company announced on Sunday. The funding news comes three months after  Anthropic raised $450 million in its Series C funding round led by Spark Capital  in May. 

More machine learnings

I (that is, thine co-author Devin) was at SIGGRAPH this last week, where AI, despite being a bogeyman in the film and TV industry right now, was in full force as both a tool and research subject. I’ll have a longer story soon about how it’s being used by VFX artists in innovative and totally uncontroversial ways soon, but the papers on display were also pretty great. This session in particular had several interesting new ideas.

Image generating models have this weird thing where if you tell them to draw “a white cat and a black dog,” it often mixes the two up, ignores one or makes a catdog or animals that are both black and white. An approach from Tel Aviv University called “attend and excite” sorts the prompt into its constituent pieces through attention, and then makes sure the resulting image contains proper representations of each. The result is a model much better at parsing multi-subject prompts. I’d expect to see something like this integrated into art generators soon!

Another weakness of generative art models is that if you want to make small changes, like the subject looking a little more to the side, you have to redo the whole thing — sometimes losing what you liked about the image to begin with. “Drag Your GAN” is a pretty astonishing tool that lets the user set and move points one by one or several at a time — as you can see in the image, a lion’s head can be turned, or its mouth opened, by regenerating just that portion of the image to accord with the new proportions. Google is in the author list so you can bet they’re looking at how to use this.

This “semantic typography” paper is more fun, but also extremely clever. By treating each letter as a vector image and nudging that image toward a vector image of the object a word refers to, it creates pretty impressive logotypes. If you’re stuck on how to turn your company name into a visual pun, this could be a great way to get started.

Elsewhere, we have some interesting cross-pollination between brain science and AI.

These Berkeley researchers used a machine learning model to interpret brain activity while listening to music, and reconstruct some of the clusters that were focused on rhythm, melody or vocals. I’m always skeptical of this kind of “we read the brain” type studies, so take it all with a grain of salt, but ML is great at isolating a signal in noise, and brain activity is very, very noisy.

MIT and Harvard teamed up to try to advance our understanding of astrocytes, cells in the brain that perform some as-yet-unknown function. They propose that the cells may act as something like a transformer or attention mechanism — a machine learning concept being mapped onto the brain rather than vice versa! Senior paper author Dmitry Krotov from MIT sums it up well:

The brain is far superior to even the best artificial neural networks that we have developed, but we don’t really know exactly how the brain works. There is scientific value in thinking about connections between biological hardware and large-scale artificial intelligence networks. This is neuroscience for AI and AI for neuroscience.

In medical AI, data from consumer devices is often considered noisy as well, or unreliable. But again, ML systems can adapt, as this new paper from Yale shows . The research should move us closer to wearables that warn us of heart-related issues before they become acute.

One of GPT-4’s first practical applications was use in Be My Eyes , an app that helps blind folks navigate with the help of a remote partner. EPFL students developed two more apps that could be pretty nice for anyone with a visual impairment. One simply directs the user toward an empty seat in a room, and the other reads off only the relevant info from medicine bottles: the active ingredient, dosage, etc. Such simple but necessary tasks!

Lastly we have the toddler-equivalent “RoboAgent” developed by CMU and Meta , which aims to learn everyday skills like picking things up or understanding object interactions just by looking and touching things — the way a child does.

“An agent capable of this sort of learning moves us closer to a general robot that can complete a variety of tasks in diverse unseen settings and continually evolve as it gathers more experiences,” said CMU’s Shubham Tulsiani. You can learn more about the project below:

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AI Sentence Corrector 4+

Spelling & grammar check.

• 5.0 • 11 Ratings
• Offers In-App Purchases

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Description.

Introducing GramFix - Grammar check & sentence corrector! Whether it's a crucial business email, book writing, an academic essay, or a simple text to a friend, we've got you covered. Key Features: - Instant Grammar Check: Instantly fix grammar errors and make your sentences error-free. - Sentence Corrector: Enhance sentence structure and clarity with the help of AI. - Multi-Language Support: Not just English! GramFix proudly supports multiple languages, ensuring you communicate perfectly in any tongue. - Explanations On-Demand: Not just a fix, but a lesson! With our premium version, understand the 'why' behind each spell check, enhancing your writing skills with each use. - Rewrite Assistant: Rewrite sentences with word correction, punctuation and readability. - Simple & Clean Interface: No clutter, no fuss. Our minimalistic design ensures a user-friendly experience, letting you focus solely on perfecting your text. - Freemium Model: Enjoy free grammar checks daily, and if you love what you see (we're sure you will!), upgrade for unlimited checks and more exclusive features. - No Ads: We value your time and focus. Enjoy an ad-free experience, always. Why Choose Us: - Professional Writers' Choice: Writes trust us for our app's accuracy and reliability. - Mutiple Applications: Excellent for emails, essay, book, research papers etc. Boost your confidence in writing and communicate like a pro. Become a better write today. Download GramFix today and make grammar mistakes a thing of the past! EULA - https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

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