Posts

Open Models at Google DeepMind — Cassidy Hardin, Google DeepMind

Open Models at Google DeepMind — Cassidy Hardin, Google DeepMind

Cassidy Hardin from Google DeepMind introduces Gemma 4, a new family of open-weight models with significant architectural and performance improvements. This summary covers the four new models (31B Dense, 26B MoE, and two "Effective" on-device models), deep dives into architectural changes like mixed global/local attention and Per-Layer Embeddings (PLE), and details the new native multimodal capabilities for vision and audio.

The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition

The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition

Qasar Younis and Peter Ludwig, founders of Applied Intuition, discuss the shift from autonomy tooling to a comprehensive physical AI platform. They explain why physical AI is more than just LLMs on wheels, highlighting the critical bottleneck of deploying models onto constrained hardware. The conversation covers their three-pillar tech stack—simulation, operating systems, and AI models—and makes the case for an 'Android for every moving machine' to solve the fragmentation in safety-critical systems like cars, trucks, and robots.

It's 2026, and We're Still Talking Evals

It's 2026, and We're Still Talking Evals

Maggie Konstanty, AI Product Manager at Prosus, provides a candid look into the realities of LLM evaluation in production. She argues that standard metrics like accuracy are misleading and advocates for a culture of continuous, goal-oriented evaluation focused on deep failure analysis and understanding real user behavior, asserting that mature teams inevitably build custom tooling to meet their specific needs.

Why Agents are Driving Software Development to the Cloud

Why Agents are Driving Software Development to the Cloud

Zach Lloyd, CEO of Warp, explains why the future of software development is moving from local, interactive agents to cloud-native, collaborative systems. He discusses the flaws in the "dev box" sandbox model, the decline of traditional SaaS interfaces in favor of "just-in-time apps," and how platforms like Warp's Oz are providing the necessary orchestration, observability, and access control for teams to effectively deploy AI agents at scale.

What is OpenClaw? Inside AI Agents, LLMs and the Agentic Loop

What is OpenClaw? Inside AI Agents, LLMs and the Agentic Loop

AI agents represent a paradigm shift from conversational AI to autonomous systems that can perform actions. This is achieved through an 'agentic loop' combining Large Language Models (LLMs) with tools, as exemplified by the OpenClaw framework, which enables complex, automated workflows while also raising important security considerations.

Collaborative AI Engineering — Maggie Appleton, GitHub Next

Collaborative AI Engineering — Maggie Appleton, GitHub Next

Maggie Appleton from GitHub Next argues that current agentic tools are flawed by focusing on individual productivity, ignoring the collaborative nature of software development. She introduces ACE (Agent Collaboration Environment), a multiplayer platform designed to solve team alignment issues by integrating planning, development, and shared context in a real-time, sandboxed environment.