Thesis-driven early-stage venture capital firm.
Berlin
Joined May 2011
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How do you go from academic research to building a company?
We’re coming to Cambridge on 5 November and teaming up with Founders at the University of Cambridge and Cambridge Enterprise Ventures for a special Founder Braintrust. 👋🧠
We’ll kick off with a fireside chat between @louicop and @fhuszar, co-founder of Reasonable AI, about Ferenc’s journey from Cambridge Professor of Machine Learning to founder and what he wishes he’d known at the start.
The fireside chat will be followed by Braintrust discussions, bringing together up to 50 early-stage and aspiring founders to share work in progress, work through blockers and exchange candid feedback.
If you’re building an early-stage startup or testing a startup idea, particularly as a researcher, scientist or engineer considering the move from academia to founding, we’d love to see you there.
P.S. Louis will also host a small number of 1:1 office hours earlier in the day. The evening will include fireworks, food and more conversation.
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Real customers. Live orders. Production at scale.
We’re teaming up with @Teradyneinc and @Universal_Robot to run Cortex on UR cobots. Hundreds of robots shipped across Europe, and now heading to North America.
See it live at the @nvidia booth, Hall 3. #GTCBerlin
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LFG🚀
Very proud to say @attio is in the top 25 fastest-growing software companies in the world (and the No. 1 fastest growing CRM!). Truly surreal. What a journey!
brex.com/journal/brex-benchm…
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The robot messed up the fold. Then folded it correctly. No one taught it that. Check out the new research from Sereact.
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Robots that learn by copying people hit a ceiling.
Cortex 2.6 now learns from practice: after 50 attempts per task, its success on three returns-handling tasks rose from 60–70% to 85–100%.
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Tried a bunch of neoclouds / neocloud adjacent services (@FireworksAI_HQ , @togethercompute , @baseten , @nebiusai) the other day and me and my agent made the following observations.
I was running benchmarks and deploying a bunch of OSS models via Claude Code on these services, and doing some internal benchmarking.
Maybe I messed something up, but has anyone does some comparisons across these providers?
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Reinforcement learning on real robots
New research developed in the field by @TuscherMarc @SereactAI
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I've built this little website to view my @goodreads bookshelf in a much nicer way:
bookshelf-aea8f1.netlify.app
If you'd like to get a version for your books, LMK and I'll open-source the code on Github ... or I'll just give you the prompt ... or you just point Claude/Codex to the URL and tell it to copy/rebuild it. :)
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We are still living in interesting times. The world is changing very fast, and after 10 years of full-time investing, it is time for me to open a new chapter of my career.
I have therefore decided to step down from my role as a General Partner and transition to a new role.
My journey with Point Nine has been beyond anything I could have imagined. I joined as a fresh MIT graduate almost exactly 10 years ago after meeting Pawel and Christoph on Skype, became a General Partner alongside Ricardo 7 years ago, and have loved every single bit of my day-to-day ever since.
To my P9 partners, to all P9 team members (current and past), to all P9 LPs, and to all P9 entrepreneurs (P9 family members) I’ve worked with over the past 10 years, thank you. I am proud of the work we’ve done to build a venture firm that is different, more human, more approachable, and entirely dedicated to serving entrepreneurs building some of the most ambitious companies in Europe and beyond.
Over the past few months, I've spent most of my time speaking with AI researchers at various universities across Europe about how to bring their research to market. This led to our investment in a legal-focused AI lab called grubel and made it clear to me that I should get involved with companies as early as possible, including taking an increasingly operational role.
Starting now, I’ll continue to be part of Point Nine on a part-time basis as a Venture Partner, working with my portfolio companies, investing with the team in a few AI research projects at their inception, and figuring out what the next chapter of my career will be.
To more adventures like this one,
Louis
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Most teams running at scale want to move their agent off OpenAI or Anthropic onto a cheaper model. Few do, because it's kinda hard to guarantee quality stays the same and there are no regressions (harder then it looks).
We've been working on this problem the last few weeks. How to give a better guarantee of swapping to OSS looking at historical traces? In one example, we swapped the model for a fintech and a retail support agent across thousands of conversations and here are some findings:
1/ The usual check compares the cheap model’s next reply to the old one’s. It approved swaps that resolved 6–10 points fewer requests correctly. Replaying full conversations caught every one.
2/ A cheap model can look fine reply by reply and still fail the conversation: skip an identity check, offer a refund it shouldn’t, hand off too early.
3/ Serving matters as much as the model. FP8 cost ~10 points. One wrong config setting broke 95% of conversations.
4/ And recheck your judge. One tuned on GPT’s answers won’t automatically grade Qwen fairly.
We’re building Kitaru to capture, replay, and evaluate agent runs. If you run an agent on a closed model, send me a sample of your traces and I’ll tell you what’s safe to swap and what you’d save. Can sign an NDA if needed. DMs open.
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The real benchmark for physical AI is production.
300+ live systems across Europe and the US. One model learning from all of them.
Proud to be #5 in @Siftedeu’s AI 100. Thank you to everyone building this with us. 🦾
#SiftedAI100
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In the age of agents, systems of record have never mattered more. They’ve also never been less prepared for what’s coming.
Today, we’re announcing @attio's hybrid architecture, with the controls of application software at the scale of infrastructure.
To agents, Attio looks like a database, queryable in SQL - a language they're RL’d on. Unlike a database, the business logic, policies, and compliance sit behind the query.
This makes all of Attio’s data accessible by agents in the most powerful and flexible syntax. It gives GTM teams an order of magnitude more value from their time, with the full power of agents working across the entire customer lifecycle.
A new shape of software is here.
attio.ai/architecture
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🚀 Your customer data just got a lot more actionable!
We just shipped:
📋 Contact Lists with powerful filters
👤 Contact Profiles
✉️ Batch email & sequence enrollment
🤖 Automated outreach with workflows
All connected to your subscription and revenue data.
chartmogul.com/blog/contact-…
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Clio named to Fortune’s Future 120 - a list of companies with exceptional long term growth potential.
@goclio
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Another saying that I recently heard and completely agree with is that during a raise the founders should first solve for the people on the other side of the deal, then for the raise amount, and then the valuation.
There was an old saying in startup world: “Getting an investor on your cap table is like marriage. A divorce is very hard “
Maybe it became politically incorrect to use those terms.
But there was a lot of truth to that.
Choose your investors carefully. Some will suck. Some will be outright malicious. And some will have more money, power, and influence than you...and may decide to bully you.
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Odyssey is pushing the frontier of world models day in day out
