Long-form interviews and conversations with tech, AI, and finance leaders (30min+)
Paige Bailey demonstrates Google DeepMind's rapid release of the Gemini 3.1 model series and AI Studio tools, showcasing how developers can leverage multimodal capabilities, sandboxed code execution, and real-time screen sharing to build production AI applications with exceptional cost efficiency.
Maxime Labonne explains that small language models (350M–24B parameters) for edge deployment face unique architectural and training challenges distinct from simply scaling down large models, requiring specialized solutions like short convolutions, massive over-training, and targeted reinforcement learning to overcome memory constraints and 'doom looping' while excelling at agentic tool use.
Wirecutter gift expert Samantha Shea joins hosts Kyra Blackwell and Rosie Garen to share curated Mother's Day gift ideas organized by life stage, emphasizing that the best presents acknowledge maternal labor, provide genuine breaks, and avoid adding to a mother's mental load.
Jamie Dimon explains that JPMorgan's 200-year success stems from a culture built through daily discipline, relentless anti-bureaucracy tactics like small empowered teams and rigorous follow-up, and zero tolerance for self-serving employees who prioritize process over client outcomes.
Economist Clem Chambers predicts 7-9% inflation for 5-10 years as governments print money to fund massive industrial buildouts and AI infrastructure, warning that bond crises are inevitable but manageable through debt monetization.
Renee DiResta traces her decade-long investigation into information warfare from early vaccine misinformation to Russian election interference, explaining how analysts now use the 'Actors, Behaviors, Content' framework to identify coordinated inauthentic networks rather than adjudicating specific speech, while detailing the shift from adversarial to collaborative relationships between researchers and tech platforms.
This lecture details how to scale language model training across massive clusters using 4D parallelism, contrasting TPU and GPU networking architectures while addressing the critical memory bottlenecks—particularly optimizer states—that dominate training costs at scale.
This lecture introduces distributed training for large language models, explaining how to scale beyond single-GPU memory limits using collective communication primitives (all-reduce, all-gather, reduce-scatter) across hardware topologies ranging from NVLink-connected single nodes to InfiniBand-linked multi-node clusters.
This lecture bridges the gap between GPU programming abstractions and hardware realities, explaining how thread hierarchies, memory systems, and hardware constraints like warps and bank conflicts determine kernel performance for deep learning workloads.
This lecture explains why high-dimensional pixel space (approximately 1 million dimensions for standard images) is computationally intractable for diffusion models, and how Variational Autoencoders (VAEs) solve this by compressing images into structured latent spaces that follow standard normal distributions, enabling efficient and meaningful generation.
At the 2025 Investment Conference hosted by Norges Bank Investment Management, CEO Nikolai Tangen and guests David Rubenstein and Kenneth Griffin argued that corporate culture—not strategy or technology—is the only true competitive advantage, determining whether companies survive generational transitions or collapse under pressure.
Eric Zakariasson from Cursor details the roadmap to building autonomous "software factories," outlining six levels of AI coding autonomy and the practical infrastructure—modular codebases, dynamic guardrails, and verifiable systems—required to evolve from writing code to managing AI agents.