Sep 23, 2026

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

Eric Nguyen, CEO of Radical Numerics, details the journey from early genome language models to Omni, a system that excels in DNA reading, writing, and reasoning. Omni outperforms specialized models in disease-variant prediction, particularly in previously challenging non-coding regions. The discussion also covers the critical need for AI-native biosecurity defenses, addressing how models can design biological sequences that evade current detection systems, and the broader vision for General Biological Intelligence.

Sep 23, 2026

Skill issue: stop deploying vision language models, use them with Skills — Merve Noyan, Hugging Face

Merve Noyan discusses the pitfalls of directly using large Vision Language Models (VLMs) at runtime due to performance limitations and restrictive licensing. She introduces "Web Vision," a toolkit that enables efficient training of smaller, task-specific computer vision models using a novel "vibe training" methodology. This approach leverages VLMs for initial labeling and judgment, followed by training efficient models like RF-DETR, all while adhering to Apache 2.0 licenses and costing only a few dollars.

Sep 23, 2026

Are AI labs ignoring cybersecurity experts?

This podcast explores the friction between frontier AI labs and cybersecurity experts, who disagree on AI safety priorities (alignment vs. traditional controls). It discusses the dual risks of open-weight AI models enabling sophisticated hacks like the TikTok camera exploit, and the challenges of CISA's call for transparent breach disclosures amidst corporate self-interest and the complexities of global AI regulation.

Sep 23, 2026

Thinking in Platforms • Kasper von Grünberg & Luca Galante • GOTO 2026

Kaspar von Grünberg and Luca Galante discuss their book "Thinking in Platforms," tracing platform engineering's origins from addressing key person dependencies to its critical role as an "operating model" for AI-first organizations. They highlight how AI agents necessitate standardized, productized internal platforms for effective deployment, emphasizing that platform efforts often fail due to social rather than technical challenges.

Sep 22, 2026

100x More Reliable Voice Agents

SLNG.ai introduces Unmute, an open declarative standard for voice agents, addressing platform lock-in and the limitations of current agent architectures. It proposes a shift from LLM-centric, sequential pipelines to declared execution with structural guarantees, enabling portable, cost-effective, and robust voice agents by breaking down complex interactions into modular, context-aware steps. This approach minimizes token usage, enhances determinism, and improves agent reliability compared to traditional single-prompt designs.

Sep 22, 2026

Debating RSI, the US-China Gap, and Jaggedness of Frontier AI

Jean-Stanislas Denain of Epoch AI and Nathan Lambert debate the nuanced trajectory of AI. They discuss the current state of RSI, the US-China AI capabilities gap (estimated 6-8 months), and the role of distillation and compute in closing it. The conversation also covers the challenges and differing paces of AI in robotics, insights from Chinese AI job postings, and the complex trade-offs between open and closed models regarding safety and misuse. They touch on Epoch AI's research philosophy and speculate on the intricate, evolving post-training recipes at frontier AI labs.