Sep 04, 2025

The Day AI Solves My Puzzles Is The Day I Worry (Prof. Cristopher Moore)

Professor Cristopher Moore of the Santa Fe Institute discusses the surprising effectiveness of AI, arguing it stems from the rich, non-random structure of the real world. He explores the limits of current models, the nature of intelligence as creative problem-solving and abstraction, the importance of grounding and shared reality, and the profound implications of computational irreducibility and the need for algorithmic transparency in high-stakes applications.

Aug 22, 2025

The Moonshot Podcast Deep Dive: Jeff Dean on Google Brain’s Early Days

Google DeepMind’s Chief Scientist Jeff Dean discusses the origins of his work on scaling neural networks, the founding of the Google Brain team, the technical breakthroughs that enabled training massive models, the development of TensorFlow and TPUs, and his perspective on the evolution and future of artificial intelligence.

Aug 08, 2025

The Moonshot Podcast Deep Dive: Andrew Ng on Deep Learning and Google Brain

Andrew Ng, founder of Google Brain and DeepLearning.AI, discusses the history of neural networks and the foundational ideas that led to modern AI breakthroughs. He covers the controversial early bets on scale and general-purpose algorithms, the technical innovations behind Transformers, and the future democratizing effect of artificial intelligence.

Aug 01, 2025

Flipping the Inference Stack — Robert Wachen, Etched

The current AI inference stack, reliant on general-purpose GPUs, is economically and technically unsustainable for real-time AI at scale. AI hardware expert Robert Wachen argues that the future is specialized hardware, like Transformer-specific ASICs, which can unlock currently bottlenecked applications such as real-time video, code generation, and large-scale enterprise deployments by solving critical latency and cost-per-user challenges.