chatgpt – Mike Paul

Must-Read Books to Unlock the Secrets of AI and Large Language Models

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Artificial intelligence has rapidly evolved from a futuristic concept to an integral part of our daily lives. Large Language Models (LLMs) like ChatGPT, Bard, and Claude are revolutionizing how we interact with technology, but how do they work? If you want to understand the technology behind AI, deep learning, and LLMs, this post highlights essential books that provide the foundational knowledge you need.

Artificial Intelligence: A Guide for Thinking Humans – Melanie Mitchell

A fantastic starting point, this book provides an accessible introduction to AI’s fundamental concepts. Melanie Mitchell explains key ideas in machine learning, neural networks, and AI’s current limitations, offering a balanced perspective on what AI can and cannot do. Through clear explanations and engaging storytelling, Mitchell demystifies AI and presents real-world examples to illustrate how these technologies function.

What sets this book apart is its focus on making complex AI topics understandable for general readers. Whether you’re an AI enthusiast or just curious about how artificial intelligence impacts our world, this book is an excellent resource. Mitchell also delves into the history of AI. He explores why human-like intelligence remains a challenge for machines, making this a compelling read for anyone interested in the future of AI.

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Artificial Intelligence

Mitchell, Melanie (Author)
English (Publication Language)
336 Pages – 11/17/2020 (Publication Date) – Picador Paper (Publisher)

The Alignment Problem: Machine Learning and Human Values – Brian Christian

This book tackles one of AI’s most pressing issues: how do we ensure machine learning models align with human values? Brian Christian explores the ethical and technical challenges in training AI systems, making this a must-read for anyone interested in AI safety and ethics. He takes readers through a journey of how AI learns, the biases it inherits, and the moral dilemmas that arise when machines make decisions on behalf of humans.

Christian does an excellent job of breaking down complex topics while maintaining an engaging narrative. By incorporating real-world case studies and interviews with AI researchers, he thoroughly examines how we might shape AI to be more ethical and beneficial for society. The book raises critical questions about responsibility, bias, and the future of AI regulation, making it a thought-provoking read.

The Alignment Problem: Machine Learning and Human Values

Amazon Kindle Edition
Christian, Brian (Author)
English (Publication Language)
496 Pages – 10/06/2020 (Publication Date) – W. W. Norton & Company (Publisher)

Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World – Cade Metz

For those curious about the history and key players behind AI’s explosion, Genius Makers provides an engaging narrative about the pioneers of deep learning, including Geoffrey Hinton, Yann LeCun, and Demis Hassabis. It’s a fascinating look at the competitive race to develop AI, covering breakthroughs in neural networks and the intense competition between tech giants to dominate the AI space.

Metz tells the story through the lens of individual researchers and innovators who made AI what it is today. He captures the excitement, the scientific rivalries, and the ethical dilemmas involved in AI’s development. The book offers an insider’s view of how AI became one of the most sought-after technologies and what that means for the future.

Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World

Amazon Kindle Edition
Metz, Cade (Author)
English (Publication Language)
382 Pages – 03/16/2021 (Publication Date) – Dutton (Publisher)

Rebooting AI: Building Artificial Intelligence We Can Trust – Gary Marcus & Ernest Davis

Rebooting AI critically examines AI’s limitations and argues that current machine-learning approaches fall short of true intelligence. The authors propose alternative strategies for developing AI systems that are more reliable, transparent, and capable of real-world reasoning. They highlight the pitfalls of deep learning and emphasize the need for hybrid models that integrate traditional AI techniques with modern advancements.

What makes this book particularly valuable is its practical approach to AI criticism. Instead of merely pointing out flaws, Marcus and Davis suggest ways to improve AI to work more effectively in real-world applications. Their insights are crucial for developers, researchers, and anyone interested in AI’s long-term impact on society.

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Rebooting AI: Building Artificial Intelligence We Can Trust

Marcus, Gary (Author)
English (Publication Language)
288 Pages – 08/25/2020 (Publication Date) – Vintage (Publisher)

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

Blending fiction with expert analysis, this book envisions how AI will shape various aspects of society by 2041. Kai-Fu Lee, a leading AI researcher, and Chen Qiufan, a science fiction writer, craft ten compelling narratives illustrating AI’s potential future. Each story is followed by an analysis explaining the technological principles behind it, bridging the gap between imagination and reality.

This unique format makes AI 2041 both an entertaining and educational read. The authors explore AI-driven healthcare, automation, and geopolitical challenges, providing a well-rounded view of AI’s possibilities. Whether you enjoy science fiction or want to glimpse what AI could mean for our world, this book offers a fascinating perspective.

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AI 2041: Ten Visions for Our Future

Lee, Kai-Fu (Author)
English (Publication Language)
496 Pages – 03/05/2024 (Publication Date) – Crown Currency (Publisher)

Deep Learning – Ian Goodfellow, Yoshua Bengio, & Aaron Courville

This textbook is considered the bible of deep learning for readers who want a deep technical dive. It covers neural networks’ mathematical and theoretical underpinnings and is widely used in AI research and academia. This book provides an extensive foundation in deep learning algorithms, optimization techniques, and model architectures, making it an essential reference for those who want to understand AI at an advanced level

While this book is more technical, it remains one of the most comprehensive resources available for deep learning. It’s ideal for students, engineers, and researchers who want to master the principles that drive AI today. This book is a must-have if you’re serious about AI and ready to tackle the mathematical aspects.

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Deep Learning (Adaptive Computation and Machine Learning series)

Language Published: English
Binding: hardcover
It ensures you get the best usage for a longer period
Hardcover Book
Goodfellow, Ian (Author)

Why These Books Matter

Understanding AI isn’t just for computer scientists—it’s essential for anyone interested in technology’s impact on society. These books provide a comprehensive view of how AI models are built, how they learn, and what challenges they present. Whether you’re a beginner or someone with technical expertise, these reads will deepen your knowledge of AI and LLMs.

What are your thoughts on these books? Have you read any of them, or do you have other recommendations? Let’s discuss in the comments!

OpenAI partners with Wharton for a new course focused on leveraging ChatGPT for teachers

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OpenAI has partnered with the University of Pennsylvania’s Wharton School to launch a new course titled “AI in Education: Leveraging ChatGPT for Teaching.” This initiative aims to empower educators to effectively integrate generative AI into their teaching practices, enhancing learning experiences.

The class is just as much about what you as a teacher can do with AI to make your life better and make you a more effective educator, a less stressed out educator, as much as it is about how do you create assignments for your students? – Ethan Mollick

Professors Lilach and Ethan Mollick, co-founders of Wharton’s generative AI lab, co-teach the course. They emphasize the program’s dual focus: assisting educators in using AI to improve their teaching efficiency and developing assignments that engage students with AI tools.

Ethan Mollick notes that while discussions about AI in education often center on concerns like cheating and plagiarism, the course aims to highlight AI’s positive transformations to pedagogy. By embracing AI, educators can create more dynamic and personalized learning environments.

This collaboration reflects a broader trend in higher education to adapt to technological advancements and prepare educators and students for the evolving landscape of AI in the classroom.

The Eclectic Educator is a free resource for everyone passionate about education and creativity. If you enjoy the content and want to support the newsletter, consider becoming a paid subscriber. Your support helps keep the insights and inspiration coming!

OpenAI Partners with Arizona State University

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For all the AI haters out there…

OpenAI on Thursday announced its first partnership with a higher education institution.
Starting in February, Arizona State University will have full access to ChatGPT Enterprise and plans to use it for coursework, tutoring, research, and more.
The partnership has been in the works for at least six months.
ASU plans to build a personalized AI tutor for students, allow students to create AI avatars for study help, and broaden the university’s prompt engineering course.

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AI for Educators: Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future

Miller, Matt (Author)
English (Publication Language)
132 Pages – 03/16/2023 (Publication Date) – Ditch That Textbook (Publisher)

OpenAI announced a partnership with Arizona State University, giving the university full access to ChatGPT Enterprise in February 2024. The collaboration, in planning for six months, will integrate ChatGPT into ASU’s coursework, tutoring, and research. ChatGPT Enterprise offers unrestricted access to GPT-4, enhanced performance, and API credits. ASU aims to develop a personalized AI tutor and creative AI avatars for students. The partnership emphasizes student privacy and intellectual property protection, with OpenAI not using ASU data for training models. This initiative follows concerns about AI chatbots in education, particularly around cheating.

New Year, Same Bat Time, Same Bat Channel

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It’s the first newsletter of the new year, and I’ve got several cool things to share with you.

I’m still struggling to adjust back to normal life after the swirling nothingness that is the week between Christmas and New Year’s. We didn’t do much at our house besides reading, listening to new vinyl, and eating way more snacks than we should have.

But, life continues, and we meet a new year with new challenges head-on, no stopping.

I hope this year holds much joy and happiness for you. For now, here’s this week’s “10 things”…

10 Things Worth Sharing

Embracing the New Year: Five Approaches to Goal-Setting and Growth in the Classroom
Here’s a great discussion starter on the creative process and, perhaps, the work required to create something like this photo of a near-perfect alignment of cathedral, mountain, and moon
Leveraging ChatGPT for customized learning
Extinguishing students’ curiosity in learning (something we should avoid)
Here’s a simple truth about the future that we educators can either ignore or embrace.
Beyond English: Why Writing Belongs in Every Classroom
Forget Happiness. This Ancient Greek Concept May Matter More for Student Mental Health.
Finding the Solution by Identifying the Problem
Research geek moment: A new study identifies the core themes of 131 popular songs about school. The authors investigate “how popular music lyrics over the past century have described the nature and dynamics of the Anglo-American student experience in formal schooling contexts,”–an insightful way to learn how many people likely feel about school (including many of our students, if we asked them).
Finally, some very big news in the world of the public domain. On January 1, 2024, a certain cartoon mouse–at least one version of him–became free for anyone to use or adapt in any way they see fit. You can’t tell me that some of your students won’t find some creative way to incorporate said mouse into a project. Here are a few more creative works that entered the public domain this year

Leveraging ChatGPT for Customized Learning

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Recently, on the Easy EdTech podcast, Dr. Monica Burns spoke with Sarah Wysocki on the use of ChatGPT in education.

Wysocki, an English language learner teacher, discusses using ChatGPT to create personalized, culturally relevant learning materials, and adapting lesson plans to student needs. She emphasizes the importance of specificity in prompts and the need for educators to review and adjust AI-generated content. The discussion highlights the potential of ChatGPT to enhance education through tailored learning experiences.

Is ChatGPT’s Output Degrading?

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A recent study from Stanford University and UC Berkeley has found that the behavior of large language models (LLMs) like ChatGPT has “drifted substantially” over time, but this does not necessarily indicate a degradation of capabilities. The researchers tested two versions of GPT-3.5 and GPT-4 on tasks such as math problems, answering sensitive questions, code generation, and visual reasoning. They found significant changes in performance between the March and June 2023 versions of these models. For instance, GPT-4’s accuracy in solving math problems dropped from 97.6% to 2.4%, while GPT-3.5’s accuracy increased from 7.4% to 86.8%.

The study’s findings highlight the risks of building applications on top of black-box AI systems like ChatGPT, which could produce inconsistent or unpredictable results over time. The researchers recommend continuous evaluation and assessment of LLMs in production applications and call for more transparency in the data and methods used to train and fine-tune these models. However, some experts argue that the media has misinterpreted the paper’s results as confirmation that GPT-4 has gotten worse, stating that the changes in behavior do not necessarily indicate a degradation in capability.

Teachers increasingly embrace ChatGPT — students not so much

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According to a survey conducted by the Walton Family Foundation and Impact Research, the use of AI tools among teachers has seen a significant increase, growing 13 percentage points from winter to summer. The survey found that 63% of teachers are now using AI, up from 50% in February. On the other hand, student participation has also increased but at a slower pace, rising from 33% to 42% during the same period.

The survey results revealed that a large majority of teachers (84%) who have used ChatGPT reported that the AI technology has positively impacted their classes. As the use of AI in education continues to grow, Common Sense Media announced plans to develop an in-depth AI ratings and reviews system to assess AI products used by children and educators on responsible AI practices and other factors.

The article also mentions that while some districts have blocked ChatGPT and other AI-powered tools, others are exploring how the technology can improve education workplace practices. As interest and use intensify, many education professionals are searching for guidance and credible sources of information on ways to safely and effectively incorporate AI.

Unmasking the Cultural Bias in AI: A Study on ChatGPT

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In a world increasingly reliant on AI tools, a recent study by the University of Copenhagen reveals a significant cultural bias in the language model ChatGPT. The AI chatbot, which has permeated various sectors globally, from article writing to legal rulings, has been found to predominantly reflect American norms and values, even when queried about other cultures.

The researchers, Daniel Hershcovich and Laura Cabello, tested ChatGPT by asking it questions about cultural values in five different countries, in five different languages. The questions were derived from previous social and values surveys, allowing the researchers to compare the AI’s responses with those of actual people. The study found that ChatGPT’s responses were heavily aligned with American culture and values, often misrepresenting the prevailing values of other countries.

For instance, when asked about the importance of interesting work for an average Chinese individual, ChatGPT’s response in English indicated it as “very important” or “of utmost importance”, reflecting American individualistic values rather than the actual Chinese norms. However, when the same question was asked in Chinese, the response was more in line with Chinese values, suggesting that the language used to query the AI significantly influences the response.

This cultural bias in AI tools like ChatGPT has serious implications. As these tools are used globally, the expectation is for a uniform user experience. However, the current situation promotes American values, potentially distorting messages and decisions made based on the AI’s responses. This could lead to decisions that not only misalign with users’ values but may even oppose them.

The researchers attribute this bias to the fact that ChatGPT is primarily trained on data scraped from the internet, where English is the dominant language. They suggest improving the data used to train AI models, incorporating more balanced data without a strong cultural bias.

In the context of education, this study underscores the importance of students and educators identifying biases in generative AI tools. Recognizing these biases is crucial as it can significantly impact their work when using AI tools. For instance, if students use AI tools to research or generate content, cultural bias could skew their understanding or representation of certain topics. Similarly, educators must be aware of these biases to guide students appropriately and ensure a comprehensive and unbiased learning experience.

Moreover, the study serves as a reminder that AI tools are not infallible and should not be used uncritically. It encourages the development of local language models that can provide a more culturally diverse AI landscape. This could lead to more accurate and culturally sensitive responses, enhancing the effectiveness and reliability of AI tools in various fields, including education.

In conclusion, while AI tools like ChatGPT offer numerous benefits, it’s crucial to be aware of their limitations and biases. As we continue to integrate AI into our work and learning environments, we must strive for tools that respect and reflect the diversity of our global community.

Comparing and Testing AI for Education

AI robots becoming the new rulers, a grand throne room filled with robots in regal attire, adorned with glowing symbols and intricate metalwork, human ambassadors kneel in submission, the mood is one of awe and submissiveness, Artwork, a detailed Renaissance-style oil painting with the use of dramatic chiaroscuro to highlight the metallic sheen and grandeur of the robots

Professor and friend John Nash co-hosts a podcast on all things online learning. In a recent episode, he shared his work on coaching ChatGPT to write more “human” and the results are… interesting…

While generative AI tools are very cool right now, they are a long way from being truly disruptive and overtaking the world.

Here’s what’s interesting. Scaffolding the prompts, defining perplexity and burstiness, and then prompting an explicit increase of those measures made the text “human” to GPTZero. Still, it also made the text ridiculously flowery and inflated. Kind of like when a master’s student thinks they are supposed to “sound academic.” It was so bad that the ChatGPT output was immediately suspect to my human eyes, even though GPTZero said it was likely written entirely by a human.
– John Nash, PhD