I'll be in Rio for #ICLR2026. Let's meet at the Liquid booth if you're around! We're also hiring for many positions across applied post-training, inference, pre-training, infrastructure, multi-modal, and many more!
@maximelabonne
-
Gen AI’s Impact on Job Market: Roles and Technical Skills
By
–
What's inside: → Gen AI's impact on the job market and the core concepts you actually need to know → A breakdown of AI roles, leveling matrices, and how to build a roadmap that fits your background → The full Gen AI stack: RAG, vector databases, function calling,
-
Building AI Career: New Book from Tech Industry Leaders
By
–
So when @PacktPublishing reached out about writing a book on building a career in AI, it was an immediate yes. I co-authored it with @AliArsanjani
, Sadid Hasan, @andreas_horn1
, and Leonid Ganeline Kuligin, bringing perspectives from Google, Microsoft, IBM, and Liquid AI -
Educational Content Helps Readers Land AI Industry Jobs
By
–
Some of the most rewarding messages I get are from readers of my articles, books, and courses telling me how they helped them land a job in this industry. It's a great feeling!
-
New AI Career Building Book Released
By
–
Big announcement: I'm releasing a new book! Over the years, I've talked to a lot of professionals and students about how to build a career in AI. It's a topic I'm genuinely passionate about. It's a bit cheesy to say, but it does have a real impact on people's lives
-
FrankenMoEs and Mergekit Experiments in AI Model Fusion
By
–
That's so nice, it reminds me of frankenMoEs like Phixtral and Beyonder experiments with mergekit! (cc @chargoddard
) -
Kimi K2.6 Routes Tasks Across Multiple Specialized Agents
By
–
Claw Groups adds another layer to the agentic madness: Kimi K2.6 routes different tasks to different agents with different capabilities Built on top of Agent Swarm. I don't know if it's really useful, but it sounds so cool
-
Tokenizer Switching: Computational Efficiency in LLM Operations
By
–
It's possible but switching to a new tokenizer is actually very cheap and easy, so it'd be a big waste of compute
-
Mythos High Score Graphwalks BFS: Training Methods Analysis
By
–
iirc this theory is based on Mythos's high score on Graphwalks BFS. There are many easier ways to explain this score (data, RL, distillation), so I don't think it's a strong argument to explain it
