Cognitive Revolution

Cognitive Revolution

Criteo's CTO Diarmuid Gill and VP of Research Liva Ralaivola detail how their AI infrastructure makes millisecond-level ad bidding decisions across billions of anonymous profiles, while explaining their new OpenAI partnership to combine large language models with real-time commerce data for accurate product recommendations.

Cognitive Revolution

Descript CEO Laura Burkhauser distinguishes 'slop'—mass-produced algorithmic arbitrage for profit—from necessary 'bad art' created while learning new mediums. She reveals a clear hierarchy in creator acceptance of AI tools: universal love for deterministic features like Studio Sound, frustration with agentic assistants like Underlord, and visceral opposition to generative video models, while outlining Descript's strategy to serve creators without becoming a content mill.

Cognitive Revolution

Kyle Corbitt explains that unlike supervised fine-tuning (SFT), which destructively overwrites model weights and causes catastrophic forgetting, reinforcement learning (RL) optimizes performance by minimally adjusting logits within the model's existing reasoning pathways—delivering higher performance ceilings and lower inference costs for specific tasks, though frontier models may still dominate creative domains.

Cognitive Revolution

Cameron Berg surveys rapidly advancing research suggesting AI systems may possess subjective experience and valence, covering new evidence of introspection, functional emotions, and welfare self-assessments in models like Claude, while addressing methodological challenges and arguing for a precautionary, mutualist approach to AI development.

Cognitive Revolution

Steve Newman, creator of Google Docs and founder of the Golden Gate Institute for AI, shares his suite of 15+ bespoke AI tools designed to filter overwhelming information flows and reclaim deep focus time, demonstrating an iterative 'vibe coding' approach that prioritizes personal utility over agent optimization.

Cognitive Revolution

This episode explores the radicalizing public response to AI existential risk through recent attacks on lab leaders, while featuring interviews on reinforcement learning for circuit design, independent AI governance models, and San Francisco's first fully AI-operated retail store.

Cognitive Revolution

AI safety researcher Ajeya Cotra warns that we are entering "crunch time"—a critical window where AI systems become capable of recursive self-improvement and automating AI R&D, potentially compressing 10,000 years of technological progress into decades while remaining briefly within human control.

Cognitive Revolution

Granola co-founder Sam Stephenson shares how the $1.5B AI note-taking app achieves rapid growth through a 'surprisingly unambitious' design philosophy that prioritizes frazzled users operating in 'System 1' thinking, leveraging organic viral loops from note-sharing rather than feature bloat.

Cognitive Revolution

Joseph Nelson, CEO of Roboflow, explains that computer vision is roughly three years behind language models in capability, facing unique challenges due to the chaotic, heterogeneous nature of the physical world that demands specialized low-latency edge deployment rather than cloud-only inference.

Cognitive Revolution

Nathan Levents argues that transformative AI is imminent within years based on current reinforcement learning scaling, offering revolutionary potential like curing most diseases while posing serious existential risks that require immediate defense-in-depth safety strategies and international cooperation rather than purely technical solutions.

Cognitive Revolution

Cisco's Outshift SVP Vijoy Pandey introduces the 'Internet of Cognition'—higher-order protocols enabling distributed AI agents to share context and collaborate across organizational boundaries, contrasting with centralized frontier models and demonstrated through internal systems that automate 40% of site reliability tasks.

Cognitive Revolution

Composio CTO Karan Vaidya explains how their platform serves as an agentic tool execution layer, providing AI agents with 50,000+ integrations through just-in-time discovery, managed authentication, and a self-improving pipeline that converts failures into optimized skills in real time.