LLM inference, optimization & large-scale serving for RL training pipelines @hcompany_ai. Previously built on-device voice ML libraries @Sonos.
Paris, France
Joined June 2019
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2022 me was actually cooking
github.com/sonos/tract/pull/…
Repo if you want to try it: github.com/ai-dynamo/snapsho…
Really cool work from @DecagonAI, especially the on policy drafter automated finetuning !
Curious about the benchmark workload and how much training data was needed to get there 🤔
Counterintuitively, we used more inference GPUs (8 to 14.8 on average).
But the trainer kept 32 H100s allocated throughout. Cutting rollout wait from 51s to 14s/step saved more GPU-time than the additional inference workers consumed.
Training curves below 👇
Link to the slides: drive.google.com/file/d/1a6v…
Great time speaking at NVIDIA GTC Berlin about post-training open-source models with Prime-RL and Dynamo!
I shared some of the optimizations we' e made at @hcompany_ai to speed up training and improve inference efficiency.
Thanks to everyone who joined and for the great discussions afterward! 🚀
Heading to NVIDIA #GTCBerlin this Thursday!
Catch our talk on using RL + NVIDIA Dynamo to ship open models as production agents at H Company alongside NVIDIA & Prime Intellect.
Session details: nvidia.com/en-eu/gtc/session…
Let’s grab a coffee if you're in town! ☕️
Excited to chat with @NVIDIAAI this Thursday about how we are using Dynamo to scale VLM serving for computer-use agents at H !
Looking forward to the discussion and live Q&A! 🚀
Live with @NVIDIAAI this Thursday: how we serve vision-language models for computer-use agents.
Thu Oct 8 · 1PM CEST / 7AM ET
With @AvshalomM (inference team lead) and @EmrickSini (research engineer). Live Q&A.
Emrick retweeted
Call for London based runners 🏃
@hcompany_ai is organising a short run followed by breakfast on Oct 16 - bring your friends, colleagues, dogs and let's sweat a bit!
Today we're releasing the Holo4 model family.
Once again, we've pushed the Pareto frontier of capability vs. cost per task for computer-use agents.
A few of the things that made this possible:
• We scaled our environments and built an Agentic Task Factory that has generated ~10k verifiable tasks across web, desktop and MCP environments
• We further improved our SFT and asynchronous online RL infrastructure to train efficiently and reliably on long horizon agentic tasks
• We expanded beyond pure GUI interaction: Holo4 can click, code, call MCP tools and APIs, choosing the right interface for the task
More details below 👇
Emrick retweeted
New party alert - Sep 22, Paris 🪩
@hcompany_ai is teaming up with @bfl_ai and @modal to throw a casual get together ahead of the @aiDotEngineer conference organised by @MistralAI !
There will be drinks, food, smart folks, and all of this by the Seine!
