Latent Space

The Future of AI Infra: from Kubernetes to Agent Sandboxes — Akshat Bubna, Modal CTO

🔬 "The Most Innovative Diffusion Research Is Happening in Drug Discovery, Not Image Generation"

Cooking with OpenAI’s Research Chief: AGI, o1, Evals, and Scaling Laws — Mark Chen

AI research at the frontier relies on a combination of rigorous scaling laws and creative problem-solving, where research taste is cultivated by replicating foundational papers and identifying novel cross-disciplinary breakthroughs. OpenAI maintains a stable high-level roadmap—focusing on pre-training, reasoning, and a...

The Agent Cloud: Databricks’ Bet on the Future of AI — Matei Zaharia and Reynold Xin

AI Security After Codex and Claude Code — Zico Kolter & Matt Fredrikson, Gray Swan

AI systems introduce unique security vulnerabilities that differ fundamentally from traditional software, necessitating specialized defense strategies. Zico Kolter and Matt Fredrikson, founders of Gray Swan, explain that as AI agents gain autonomy and access to sensitive tools, they become susceptible to indirect promp...

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

Continual learning represents the next major evolution in AI, shifting from static, pre-trained models to systems that dynamically improve through real-world user interactions. Ronak Malde, co-founder of Trajectory and former researcher at DeepMind and Windsurf, argues that capturing expert traces and user corrections ...

Why AI Labs With Unlimited GPUs Still Fail — Anjney Midha, AMP

🔬 The Limits of AI in Science - Why We Need Self-Driving Labs — Joseph Krause, Radical AI

The Blueprint for Autonomous Work Agents | Gavriel Cohen, NanoClaw

⚡️Making DeepSeek v4 outperform Opus 4.7 with Taste — @AhmadAwais , CommandCode.ai

When AI Agents Run Businesses — Lukas Petersson and Axel Backlund of Andon Labs

Scaling Past Informal AI - Carina Hong, Axiom Math

Satya Nadella on AI: @NoPriorsPodcast x Latent Space Crossover Special at Microsoft Build 2026

Microsoft’s AI strategy centers on enabling enterprises to build their own "frontier intelligence" rather than relying solely on generalist models. By combining private evaluations, specialized harnesses, and proprietary data, companies can create durable, long-running agents that automate complex workflows. This shift...

GitHub’s Agent Era: 14x Commits, 200M Developers, Copilot’s Next Act — Kyle Daigle

Inside xAI: Building Grok Imagine in 3 Months, Videogen vs World Models, and Video Agents— Ethan He

Devin’s 80% Moment: Background Agents, 7x PRs, & End of Hand-Held Coding — Walden Yan & Cole Murray

Autonomous background agents are fundamentally transforming software engineering by enabling end-to-end workflows from specification to pull request. These systems move beyond simple "computer use" to complex problem-solving, requiring sophisticated orchestration of frontier models and secure, cloud-based sandbox envir...

🔬 The Bitter Lesson is Coming for Proteins - Alex Rives, BioHub

⚡️ Why you should build Science Fiction — Sunil Pai, Cloudflare

AI Agents Need Computers: 74% MoM Growth, 850K/Day Runs, & New Agent Cloud — Ivan Burazin, Daytona

The Agent-Native Cloud: 3M Users, 100K Signups/Wk, Data Centers, & Death PRs — Jake Cooper, Railway