California, USA
Joined June 2009
In 2006, I was in my mid-20s, had wound down my company and was doing a postdoctoral scholarship to pay my bills. I had been told that I should raise venture capital for my next startup. I googled “nanotechnology” and “venture capital,” and the first Google search result was Lux, based in NYC, founded by a couple guys my age, who had funded companies building next-gen lithography, batteries, displays, and longevity. I was FLOORED. This is at a time when SoLoMo, ad-tech, and “cloud” were all the rage. I didn’t know VCs existed in NYC, or below the age of 40. I reached out to Pete and Josh offering to help source and diligence asking for nothing but friendship/mentorship in return, as I didn’t even have an idea at the time, and they replied the same day inviting me to spend time with them. No other VC had given such a warm reply to my blind outreach. Being flat broke, I submitted papers to land speaking slots at conferences in NYC to be able to go out to see them, and the rest is history. 20 years in, I’ve had the fortune of working with talent and being part of the inception and success of amazing companies in fields investors were shunning or simply not paying attention to. I’ve learned so much from working closely with incredible people who have brought different perspectives to the firm. In 2006, deep tech felt lonely; today the talent is everywhere, but conviction still matters. It’s a privilege to be part of this next chapter with our fresh $1.5B fund to continue working with founders as they are ideating to pulling together to launching to growing to establishing generational companies accelerating our future with feats of science and engineering.
We started Lux in 2000 with a simple conviction: the biggest opportunities lie at the frontier of science and technology that others find too hard, too early, or too confusing. Twenty-five years later, that conviction hasn't changed. What has changed is that the world has caught on. Now compute, automation, and biology have matured into scalable engineering disciplines, and what was once fringe "deep tech" has become essential infrastructure. New talent, new tools, and new industrial capacity now exist to turn the most cutting-edge technology across the physical, computational, and life sciences into enduring businesses. For these businesses and founders to become category-defining winners, they need meaningful capital and conviction. That is why we are especially excited to announce our largest fund to date, Lux Ventures IX, a $1.5B commitment to investing in the people turning sci-fi into sci-fact. Today entire sectors of aerospace, biotech, defense, industrials, transportation and beyond are being reinvented by a new generation of brilliantly ambitious, often irreverent, scientists and engineers. And while markets have changed and capital reshapes around fewer companies and larger checks, our focus on the craft remains constant. That focus matters because science doesn’t scale itself. The path from a result in the lab, only known to a few, to something durable the entire world will use requires a different kind of partnership. One that deploys the first $100K and the last $100M, that stays through the full arc of company-building, that mobilizes a powerful network of kinetic like-minded founders, and that treats capital as a tool rather than the product. Forty-four people at Lux now manage $7B, still operating with the same discipline and purpose we had on day one. We find and fund founders others have overlooked, back conviction over consensus, and build alongside these rebels of science and tech at every stage. We’re grateful to our valued LPs who've partnered with us through multiple cycles, and to the founders who trust us with their life's work. The mission continues, with even greater intensity and momentum. luxcapital.com/news/announci…
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Physical AI is only useful when its deployed @goformic was one of the first, and now boasts 750K hours of live production across 100+ factories and warehouses Proud that @samanfarid chose us as his early partner, and excited for their fresh capital infusion:
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Coding models that run on your MacBook Pro have never been this powerful. Big props to @Recursive_SI on Flint, pushing the Pareto frontier with a model largely built by their own Eureka Machine. Go @RichardSocher
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
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Proud to be partnered with this incredible team bending the physics of compute, and Bernoulli!
We’ve spent the past year developing new primitives for GPUs. We believe this enables new algorithms to change how machines learn, open new markets, and dramatically reshape AI’s cost structure. We have raised a $1 billion Series A, co-led by Index and Lux.
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Shahin Farshchi retweeted
Robot intelligence is becoming cheap and abundant!!
We built a robotics data engine with Astra-level performance at 125x lower cost. And we are open-sourcing the weights today! Introducing Flora, a suite of open models to parse the physical world and turn raw footage into rich training signals. Flora already powers our in-house data engine, labeling 200K hours of videos a day on 500 GPUs. We created it to scale the frontier for robot learning. Now you own the weights too. Flora gives you: - High-quality, timestamped captions to curate and filter human egocentric and robot data; - Dense progress rewards for quality control and RL post-training; - Rubrics scoring for real-world benchmarking Try it today, links in thread:
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Fantastic sunset panel at #LATW with the great @WillBruey and @IanCinnamon, hosted by @moislamvc We tackled the big questions: 🚀 Is space overhyped? No. 🛰️ Datacenters in space? Likely. 🏭 Vertically integrate? Sometimes.
📈 Obsess over market size? You're creating the market!
🎤 Which VCs to work with? Those who aim to EARN your partnership vs. BUY it
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Packaging went from commodity, to barrier, to secret weapon:
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Building what can't be built on Earth Orbital factories, satellite buses at scale, and a glimpse into the future they are accelerating Join us at this out-of-this-world event tomorrow where I have the pleasure of sharing the stage with greats @moislamvc @IanCinnamon and @WillBruey
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Shahin Farshchi retweeted
Lux family co @goformic + @physical_int
Replying to @physical_int
Love seeing @goformic in the demo 👏
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AI workloads aren't just prefill and decode anymore Users expect hundreds of thousands of cached context tokens that persist for hours Today's memory-constrained GPUs have to choose between paging that context out (slow time-to-first-token) or sitting idle @majestic_labs memory-first architecture keeps 10–100x more live, giant sessions in memory, and the shift to agentic AI is only widening the gap
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Shahin Farshchi retweeted
The future of manufacturing isn’t one robot that does everything. It’s general purpose and special purpose robots working side by side to build the things America needs. That’s what we’re deploying on factory floors today. @physical_int
Working with @physical_int, we are bringing general purpose robotics models into the places that need them most —- the factories that make things we all need and use. 150 factories using Formic robots and counting!
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Shahin Farshchi retweeted
Check out our new paper on Inference Auctions! We also design inference auction autobidders, which allow a user to specify an inference budget and dynamically adjusts its bids over time to maximize user utility subject to the budget constraint.
When LLM demand exceeds capacity, which requests should go first? Model providers already offer a few priority tiers. But even within a tier, requests compete for compute, and users value latency differently. Your coding agent might be blocked due to a request that belongs to an unattended background job. Why not let the market decide? In our new paper, Inference Auctions, users bid for request priority, and our auction allocates that priority to those who value it most. Unfortunately, naively selling to the highest bidders destroys prefix-cache locality, increasing SGLang's average latency by up to 12x in our experiments. Our fix is to run an auction over depth-first search traversals of the request prefix tree, ordering subtrees by average bid. This maximizes social welfare while retaining cache optimality, with VCG payments incentivizing truthful bidding, and the resulting request order preserves key performance metrics (cache hits and mean TTFT) of the underlying scheduler. w/ @keegan_w_harris @sidpra5ad @nhaghtal and Michael Jordan Paper: arxiv.org/abs/2609.40070 Project page: inferenceauctions.com
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AMEN
The biggest limit on AI today isn't chips. It's power, and the years it takes to build a data center around it. Our answer is the Armada AI factory. We build them on a production line, then deploy them wherever the energy already is. Watch @danwrightSF tell the story:
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Amca is America's engineering company Amca won a @USArmy contract built around quickly engineering, qualifying, and producing critical parts. Huge congrats to the team for this great achievement Amca is restoring our nation’s ability to engineer anything its critical systems depend on
Amca has been awarded a contract by the @USArmy, establishing an enterprise-wide partnership with Army Materiel Command for rapid engineering, qualification, and component production. This is the first partnership of its kind, designed to increase readiness for a priority missile system by re-engineering and improving manufacturability of critical components and subsystems. We're grateful for the Army’s trust, urgency, and leadership, and look forward to re-engineering American industry together.
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48 hours in Osaka meeting great founders, corporates, and government reps My message to each: Founders: trade believability for audacity, certainty for upside, and short-term results for long-term impact Corporates: partner with startups early, adapt before you're adapted to, and suspend disbelief. Governments: buy from startups instead of handing out grants, and push everyone else to do the same. Japan has all the ingredients for many more great startups!
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Great startups are being built everywhere, and capital is hunting for the best teams regardless of geography Had the privilege of joining a breakfast panel for Japan's top VCs From chips to ships, Japan has the industrial base to breed world-class startups The missing piece: domestic growth capital
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First sunset in Osaka at the Global Startup EXPO. Already met a remarkable lineup of Japanese founders and corporates working to automate everything from chip design to chip fab. Speaking tomorrow on the next era of deep tech venture. The US and Japan have a lot to build together!
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Shahin Farshchi retweeted
Sovereign AI shouldn't take years to stand up. Resilience shouldn’t be conditional. Proud day as @PalantirTech names Armada its Inaugural Modular Data Center Partner. The Sovereign AI revolution is here. businesswire.com/news/home/2…
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