Podcasts

Stanford Online

This seminar outlines a roadmap for autonomous surgical robotics to address critical healthcare labor shortages, proposing a physics-based approach built on four pillars—perception, modeling, planning, and control—that achieves sub-2mm precision through real-time digital twinning rather than relying on data-scarce foundation models.

Stanford Online

Inference now dominates AI economics, with OpenAI generating 8.6 trillion tokens daily—exceeding frontier model training compute in under four days. Unlike training, autoregressive inference cannot parallelize across sequences, making it fundamentally memory-bandwidth bound rather than compute bound, with batch sizes under 295 on H100s failing to saturate GPU capacity.

Stanford Online

This lecture transitions from theoretical foundations to practical architecture design for diffusion models, explaining how U-Net structures leverage convolutional inductive biases, hierarchical downsampling for global context, and skip connections to preserve local details while maintaining strict dimensional requirements for iterative denoising.

Stanford Online

Shrimai Prabhumoye presents advanced LLM pre-training strategies from her work at Nvidia, demonstrating that curriculum learning (two-phase training) and front-loading reasoning data during pre-training create stronger foundations and durable performance gains that cannot be matched by increased compute in later stages.

Stanford Online

Nuaman Tazzy from HuggingFace explains how to scale transformer training to thousands of GPUs using data parallelism strategies, from basic Distributed Data Parallel (DDP) to Fully Sharded Data Parallel (FSDP/ZeRO), emphasizing memory optimization techniques and the critical importance of overlapping communication with computation to keep GPUs fully utilized.

Adam Taggart | Thoughtful Money

Bill Fleckenstein warns that algorithmic passive investing flows and QE have created a 'giant mindless robot' driving stocks to all-time highs regardless of war risks or fundamentals, but predicts catastrophic consequences when the bond market finally revolts against unsustainable US debt levels.

Stanford Online

Ben Horowitz explains how Andreessen Horowitz rearchitected venture capital by treating entrepreneurs as customers, centralizing control to enable scaling, and bootstrapping network effects through asymmetric early investments.

The David Lin Report

Crypto analyst Michael Terpin is actively shorting Bitcoin at $83K, predicting a final capitulation to the $48K-$57K range by October 2025 before resuming the march toward his $1 million by 2033 target.

Jordan Peterson

Jordan Peterson traces the evolution of psychological thought from behaviorism through constructivism to depth psychology, arguing that human complexity—ranging from perception to psychopathology—cannot be reduced to simple models, ultimately warning that ignoring immutable cognitive diversity in pursuit of forced equity leads to totalitarian outcomes.

AI Engineer

Fryderyk Wiatrowski presents Victor, an AI employee that lives natively in Slack to automate complex cross-functional tasks by leveraging shared company context and 3,000+ tool integrations, evolving from early browser-based agents to solve the unique memory and permission challenges of multi-user enterprise environments.

a16z Podcast

Marc Andreessen argues that AI is ushering in a golden age of productivity while warning that institutional corruption—exemplified by AI safety advocates inadvertently training models on doomer literature and advocacy groups allegedly funding the hate groups they claim to oppose—reveals how fear and false empathy often manufacture the very crises they purport to solve.

Impact Theory

Recent graduates booed an AI commencement speaker amid fears of workforce disruption reminiscent of the brutal industrial revolution transitions, while geopolitical analysis suggests Trump's rejection of Iran's peace proposal risks a prolonged stalemate that weakens US credibility and emboldens China regarding Taiwan.