Ep. 206: Nigel Toon on How AI Thinks and How We Can Control It
Mar 8, 2024
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In this podcast, Nigel Toon discusses comparing CPU vs GPU vs IPU chips, big data and neural networks, memory availability in processors, and exploring the intersection of AI and human behavior. He also talks about the importance of diverse skills and perspectives in AI development.
IPUs perform multiple instructions on multiple data similar to the brain's parallel processing, essential for powerful AI processors.
Rigorous testing and regulatory standards are crucial to ensure AI aligns with human intentions and desired outcomes.
Balancing innovation in AI governance and regulation is imperative to address safety concerns and foster advancement in the evolving landscape.
Deep dives
The Evolution of Semiconductors and AI Processing Units
Semiconductor technology has rapidly advanced over decades, ushering in new types of chips like the Intelligence Processing Unit (IPU) designed for AI. CPUs operate on single instructions, GPUs on single instructions on multiple pieces of data, while IPUs perform multiple instructions on multiple data akin to the brain's parallel processing. Creating efficient and powerful AI processors involves addressing the challenge of inter-processor communication, crucial for complex data handling.
AI's Impact on Creativity and Decision-Making
AI serves as a complex problem-solving tool, expanding human creativity by generating novel ideas and inspirations. While concerns exist over AI's alignment with human intentions, rigorous testing and regulatory standards are vital. The iterative nature of software development contrasts with the need for comprehensive testing in AI to ensure alignment with desired outcomes and prevent unintended consequences.
Challenges and Innovations in AI Safety and Governance
The alignment problem in AI highlights the need for rigorous testing and verification to ensure AI systems operate as intended. Innovations like chain of thoughts and tree of thought methodologies aim to enhance AI reasoning and transparency. Balancing innovation in AI governance and regulation to address safety concerns while fostering advancement presents a delicate challenge in the evolving AI landscape.
Regulation and Innovation in Technology Industries
Regulation in technology industries can lead to both innovation and potential challenges like regulatory capture, where established firms hinder competition by influencing regulations. The importance of maintaining a balance between regulation and fostering innovation is highlighted by historical examples from banking. Concepts like David Hume's skepticism towards miracles and Bayes' theorem underscore the significance of probabilistic approaches and feedback mechanisms in improving systems, such as reinforcement learning, albeit with potential unintended consequences.
AI Applications in Health and Environmental Understanding
The utilization of AI in healthcare, particularly in areas like understanding protein folding to develop effective drugs for conditions like cancer, showcases significant advancements. AI's role in enhancing our comprehension of the human body and the environment, including biodiversity, presents promising prospects. The discussion extends to applications in deciphering whale communication, emphasizing AI's potential to enrich our understanding of the natural world and foster humility regarding human uniqueness.
Nigel Toon is the founder of Graphcore, which builds unique IPU chips designed for AI. He sits as a Non-Executive Director on the board of the UK Research and Innovation Council and has sat on the UK Prime Minister’s Business Council. He has been ranked #1 on Business Insider’s UK Tech 100 and named as one of the ‘Top 100 entrepreneurs in the UK’ by the Financial Times. He is the author of the best-selling book ‘How AI Thinks’. This podcast covers: comparing chips: CPU vs GPU vs IPU, data vs information, big data and neural networks, and much more.
