Topic
Google DeepMind
4 episodes
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Overview: Predictive Modeling
We finally slow down and explain predictive modeling from the ground up — the core idea that powers most of what we talk about on this show, from fraud detection to weather forecasting to the brain-prediction research we've looked at.
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Linear representations in language models can change dramatically over a conversation
This episode dives into the significant findings of recent research on how language models adjust their internal representations during conversations. We explore the implications of these changes for developers and practitioners in AI, discuss potential applications, and highlight the challenges they present for interpretability and reliability in AI outputs.
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What Even Is a Parameter
This episode explores the significance of parameters in large language models (LLMs), discussing their role in AI functionality and the implications for real-world applications. Hosts engage in a dialogue about how these parameters affect model behavior and the energy demands of training them, illustrating concepts with relatable analogies and examples.
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In this episode, we dive into the latest developments from the r/singularity community, focusing on AI advancements and the implications of human enhancement technologies. We discuss Google's SIMA 2, an innovative agent that interacts and learns in 3D environments, and what this means for our future.