Written in 1884, 'Flatland: A Romance of Many Dimensions' is a satirical novella by Edwin Abbott Abbott. The story is set in a two-dimensional world inhabited by geometric figures, where social status is determined by the number of sides of each figure. The narrator, A Square, guides readers through the practicalities and social hierarchy of Flatland, before being introduced to the concept of higher dimensions by a Sphere. The book is both an introduction to the idea of higher dimensions and a satire of Victorian society, critiquing its class system, gender roles, and social norms. Despite its satirical elements, the book also delves into mathematical concepts and the limitations of perception in different dimensions[1][3][5].
In 'ChatGPT and the Future of AI', Terrence Sejnowski offers a nuanced exploration of large language models (LLMs) like ChatGPT. The book delves into the debates surrounding LLMs’ comprehension of language, the notions of 'thinking' and 'intelligence', and the historical evolution of language models. It focuses on the role of transformers, the correlation between computing power and model size, and the intricate mathematics shaping LLMs. Sejnowski also discusses the potential future of AI, including next-generation LLMs inspired by nature and the importance of developing energy-efficient technologies. The book is structured into three parts: Living with Large Language Models, Transformers, and Back to the Future, making it accessible and valuable for both tech-savvy readers and newcomers to the field.
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Can AI tools like ChatGPT actually "think," or is it just really good at mimicking human conversation? How much of what AI spits out is a reflection of our own ideas and intentions? And where's all this tech headed in the future?
Today, I’m joined by Terry Sejnowski, a renowned computational neuroscientist and pioneer in AI and deep learning. Based at the Salk Institute for Biological Studies and the University of California, San Diego, he bridges neuroscience and AI to explore how biological brains and artificial systems learn and process information.
Terry is also the co-creator of the Boltzmann Machine, a game-changing algorithm that has shaped today’s​​ AI and is a foundation for modern neural networks. He has also written some incredible books, including The Deep Learning Revolution” and “ChatGPT and the Future of AI.
In our conversation, we discuss the current state of AI, what’s next, the ins and outs of prompt engineering, the mirror hypothesis (how AI reflects us), its impact on productivity, and the ethical challenges we must tackle.
Tune in to discover the truth about AI!
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Key Takeaways:
- 00:00 Intro
- 00:36 Judging a book by its cover
- 07:05 The impact of AI on human capabilities
- 12:32 Einstein's happiest thought and can AI think?
- 16:51 Can AI come up with something novel?
- 24:20 The role of learning and neural networks in AI
- 32:37 The future of AI and its potential impact
- 46:43 The mirroring effect
- 50:52 Practical applications of AI
- 54:00 Outro
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Additional resources:
➡️ Learn more about Terry Sejnowski:
đź“š ChatGPT and the Future of AI: https://a.co/d/cZnuZbs
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✖️ Twitter: https://twitter.com/DrBrianKeating
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✍️ Check out my blog: https://briankeating.com/cosmic-musings/
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Into the Impossible with Brian Keating is a podcast dedicated to all those who want to explore the universe within and beyond the known.
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Into the Impossible With Brian Keating 
