🎙️ Podcasts

Jordan Peterson

Jordan Peterson argues that a meaningful life requires specifying clear goals and negotiating daily schedules with yourself rather than tyrannizing yourself. He demonstrates that maturity inevitably demands sacrifice—either chosen deliberately or suffered catastrophically later—and critiques Nietzsche's notion of self-created values by showing that human psychology consists of autonomous sub-personalities that enforce moral conscience regardless of conscious intent.

Stanford Online

Former federal prosecutor and tech security chief Joe Sullivan recounts his journey from prosecuting cybercrime to leading security at eBay, Facebook, Uber, and Cloudflare, sharing hard-won lessons on the critical importance of transparency in security incidents through the lens of his personal prosecution for the 2016 Uber data breach cover-up.

20VC with Harry Stebbings

The video analyzes Nvidia's record-breaking $81.6

80,000 Hours Podcast (Rob Wiblin)

Contrary to fears of immediate job elimination, AI automation will likely create a temporary '

Interesting Times with Ross Douthat

Chris Brose argues that the US military remains trapped in outdated assumptions of short, decisive wars with technological superiority, leaving it unprepared for the attritional, drone-dominated reality of modern combat against peer adversaries like Russia and Iran.

Huberman Lab

Andrew Huberman explains that grief requires neurologically 'remapping' the three dimensions of attachment—space, time, and closeness—while preserving the emotional bond itself, offering specific tools to navigate loss without becoming trapped in counterfactual guilt loops.

Impact Theory

Simon Dixon argues that three industrial complexes—financial, military, and technological—operate above national governments to extract real assets through a debt-based monetary Ponzi scheme, deliberately cycling through empires as fiat currencies collapse and reset.

Stripe

French tech leaders reflect on the ecosystem's transformation from early 2000s corporate culture to today's AI-driven renaissance, highlighting how reduced capital barriers and improved infrastructure are reshaping entrepreneurship.

Stanford Online

This lecture explains why RLHF hits overoptimization limits with learned reward models, and how RLVR (Reinforcement Learning from Verifiable Rewards) enables unlimited compute scaling on verifiable tasks like math and coding through simpler algorithms like GRPO.

Stanford Online

This lecture explains how post-training transforms raw pre-trained models like GPT-3 into instruction-following systems like ChatGPT through supervised fine-tuning and reinforcement learning, emphasizing that high-quality data curation matters more than algorithmic sophistication.

Stanford Online

This lecture details the pre-training data pipeline, covering the transformation of raw HTML and PDFs into linear text and classifier-based filtering strategies to curate domain-specific datasets, while emphasizing the strategic trade-off between data quality and training duration.

Stanford Online

Sachin Katti, OpenAI's head of industrial compute, details the infrastructure economics driving the AI supercycle, explaining how the company plans to scale to 30 gigawatts by 2030 while navigating the shift from training to inference-heavy agentic workloads and managing massive energy and supply chain constraints.