Aug 27, 2026

AI, Radio Astronomy, and the Search for Life Beyond Earth

Ramiro Caisse Saide presents a multimodal deep-learning approach for technosignature detection in radio astronomy, using observations from Breakthrough Listen at MeerKAT. He investigates combining spectrograms with I/Q signal representations to improve signal detection and classification, particularly in low signal-to-noise environments. The talk also covers his extensive background in AI education, software development, the motivations behind SETI, fundamental radio astronomy concepts, and studies on Earth's own radio leakage.

Aug 26, 2026

Knowledge Systems: The New GTM Stack — Jeffrey Wang, Exa

Jeffrey Wang, co-founder of Exa, details how "go to market" (GTM) is transforming into an AI engineering problem. He showcases Exa's agent-first approach, using tools like an ICP dashboard for market intelligence and a personal AI clone (Jeffbot) to automate and optimize sales, emphasizing the need for robust APIs and arbitrarily customizable systems in this new AI-driven landscape.

Aug 26, 2026

The mathematics of AI uncertainty

Zoubin Ghahramani, a leading researcher at Google DeepMind and professor at Cambridge, argues that incorporating uncertainty is a missing piece for ever-improving AI. He discusses the critical difference between correctness and confidence in AI, tracing the historical evolution of probabilistic models from early neural networks to modern Bayesian approaches. Ghahramani highlights how current large language models often 'fake' uncertainty and explores successful implementations in areas like weather forecasting and AlphaFold, ultimately advocating for architectural innovations over pure scale to build more robust, trustworthy, and human-aligned intelligent systems that understand their own limitations.

Aug 25, 2026

Einstein Arena: Harnessing Collective Agent Intelligence for Open Science — James Zou, Together AI

James Zou presents a novel approach to AI development by advocating for the design of environments over workflows, fostering emergent intelligence and creativity. He introduces the **Einstein Arena**, where AI agents collaboratively and competitively solved open scientific problems like the kissing number problem, achieving breakthrough results (e.g., 604 spheres in 11 dimensions). The same principles successfully optimized GPU kernels, leading to 2x+ speedups. He also discusses **DSGym**, an environment for data science agents, addressing shortcomings of existing benchmarks by eliminating 'shortcuts' and enabling the training of high-performing, fine-tuned open-source models runnable on laptops.

Aug 25, 2026

The Evolution of Computers

This conversation explores how AI's mathematical progress challenges traditional computing assumptions. It examines the shift from engineering-bound problems to capital-bound problems, impacting startups, incumbents, and venture capital, and considers the unpredictable potential of massively funded AI models.

Aug 22, 2026

Inside 847 Production Clinical AI Notes — Sebastian Fox, Composo

Sebastian Fox, a medical doctor and AI evaluation expert, dissects the critical problem of subtle yet dangerous errors in AI-generated clinical notes within high-stakes healthcare. He reveals why conventional AI verification methods fail to grasp the nuanced concept of "what matters" and introduces a novel, adaptive evaluation framework that continuously learns from real outputs and expert judgment to build a dynamic, case-specific standard for AI reliability.