Sara Hooker - Why US AI Act Compute Thresholds Are Misguided
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
1w ago
Sara Hooker is VP of Research at Cohere and leader of Cohere for AI. We discuss her recent paper critiquing the use of compute thresholds, measured in FLOPs (floating point operations), as an AI governance strategy. We explore why this approach, recently adopted in both US and EU AI policies, may be problematic and oversimplified. Sara explains the limitations of using raw computational power as a measure of AI capability or risk, and discusses the complex relationship between compute, data, and model architecture. Equally important, we go into Sara's work on "The AI Language Gap." This rese ..read more
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Prof. Murray Shanahan - Machines Don't Think Like Us
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
1w ago
Murray Shanahan is a professor of Cognitive Robotics at Imperial College London and a senior research scientist at DeepMind. He challenges our assumptions about AI consciousness and urges us to rethink how we talk about machine intelligence. We explore the dangers of anthropomorphizing AI, the limitations of current language in describing AI capabilities, and the fascinating intersection of philosophy and artificial intelligence. Show notes and full references: https://docs.google.com/document/d/1ICtBI574W-xGi8Z2ZtUNeKWiOiGZ_DRsp9EnyYAISws/edit?usp=sharing Prof Murray Shanahan: https://www ..read more
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David Chalmers - Reality+
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
2w ago
In the coming decades, the technology that enables virtual and augmented reality will improve beyond recognition. Within a century, world-renowned philosopher David J. Chalmers predicts, we will have virtual worlds that are impossible to distinguish from non-virtual worlds. But is virtual reality just escapism? In a highly original work of 'technophilosophy', Chalmers argues categorically, no: virtual reality is genuine reality. Virtual worlds are not second-class worlds. We can live a meaningful life in virtual reality - and increasingly, we will. What is reality, anyway? How can we lead a ..read more
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Ryan Greenblatt - Solving ARC with GPT4o
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
2w ago
Ryan Greenblatt from Redwood Research recently published "Getting 50% on ARC-AGI with GPT-4.0," where he used GPT4o to reach a state-of-the-art accuracy on Francois Chollet's ARC Challenge by generating many Python programs. Sponsor: Sign up to Kalshi here https://kalshi.onelink.me/1r91/mlst -- the first 500 traders who deposit $100 will get a free $20 credit! Important disclaimer - In case it's not obvious - this is basically gambling and a *high risk* activity - only trade what you can afford to lose. We discuss: - Ryan's unique approach to solving the ARC Challenge and achieving impressi ..read more
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Aiden Gomez - CEO of Cohere (AI's 'Inner Monologue' – Crucial for Reasoning)
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
3w ago
Aidan Gomez, CEO of Cohere, reveals how they're tackling AI hallucinations and improving reasoning abilities. He also explains why Cohere doesn't use any output from GPT-4 for training their models. Aidan shares his personal insights into the world of AI and LLMs and Cohere's unique approach to solving real-world business problems, and how their models are set apart from the competition. Aidan reveals how they are making major strides in AI technology, discussing everything from last mile customer engineering to the robustness of prompts and future architectures. He also touches on the broad ..read more
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New 50% ARC result and current winners interviewed
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
1M ago
The ARC Challenge, created by Francois Chollet, tests how well AI systems can generalize from a few examples in a grid-based intelligence test. We interview the current winners of the ARC Challenge—Jack Cole, Mohammed Osman and their collaborator Michael Hodel. They discuss how they tackled the ARC (Abstraction and Reasoning Corpus) Challenge using language models and neural networks. We also discuss the new "50%" approach announced today from Redwood Research. Jack and Mohammed explain their approach, which involves fine-tuning a language model on a large, specially-generated dataset and the ..read more
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Cohere co-founder Nick Frosst on building LLM apps for business
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
1M ago
Nick Frosst, co-founder of Cohere, on the future of LLMs, and AGI. Learn how Cohere is solving real problems for business with their new AI models. This is the first podcast from our new Cohere partnership! Nick talks about his journey at Google Brain, working with AI legends like Geoff Hinton, and the amazing things his company, Cohere, is doing. From creating the must useful language models for businesses to making tools for developers, Nick shares a lot of interesting insights. He even talks about his band, Good Kid! Nick said that RAG is one of the best features of Cohere's new Command R ..read more
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What’s the Magic Word? A Control Theory of LLM Prompting.
Machine Learning Street Talk (MLST)
by Machine Learning Street Talk (MLST)
1M ago
These two scientists have mapped out the insides or “reachable space” of a language model using control theory, what they discovered was extremely surprising. Please support us on Patreon to get access to the private Discord server, bi-weekly calls, early access and ad-free listening. https://patreon.com/mlst YT version: https://youtu.be/Bpgloy1dDn0 Aman Bhargava from Caltech and Cameron Witkowski from the University of Toronto to discuss their groundbreaking paper, “What’s the Magic Word? A Control Theory of LLM Prompting.” (the main theorem on self-attention controllability was developed ..read more
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CAN MACHINES REPLACE US? (AI vs Humanity) - Maria Santacaterina
Machine Learning Street Talk
by Machine Learning Street Talk (MLST)
2M ago
Maria Santacaterina, with her background in the humanities, brings a critical perspective on the current state and future implications of AI technology, its impact on society, and the nature of human intelligence and creativity. She emphasizes that despite technological advancements, AI lacks fundamental human traits such as consciousness, empathy, intuition, and the ability to engage in genuine creative processes. Maria argues that AI, at its core, processes data but does not have the capability to understand or generate new, intrinsic meaning or ideas as humans do. Throughout the conversati ..read more
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Connor Leahy - e/acc, AGI and the future.
Machine Learning Street Talk
by Machine Learning Street Talk (MLST)
3M ago
Connor is the CEO of Conjecture and one of the most famous names in the AI alignment movement. This is the "behind the scenes footage" and bonus Patreon interviews from the day of the Beff Jezos debate, including an interview with Daniel Clothiaux. It's a great insight into Connor's philosophy. At the end there is an unreleased additional interview with Beff. Support MLST: Please support us on Patreon. We are entirely funded from Patreon donations right now. Patreon supports get private discord access, biweekly calls, very early-access + exclusive content and lots more. https://patreon.com/ml ..read more
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