Ryan Vilim

386 posts

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Ryan Vilim

Ryan Vilim

@ryanvilim

New York, USA Bergabung Kasım 2012
245 Mengikuti111 Pengikut
Ryan Vilim
Ryan Vilim@ryanvilim·
@dylanmatt I just did this after seeing this tweet and it trivially found me a thousand dollars. My cpa didn’t claim treasury or ny/nyc bond income on my New York tax return.
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dylan matthews 🔸
dylan matthews 🔸@dylanmatt·
Claude found $455 in savings on my federal tax return and $424 on my DC return, so that's my boy paying for almost four years' worth of himself
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Hao Zhang
Hao Zhang@haozhangml·
Big congrats on @inferact! Since we initiated vLLM’s earliest research push back in 2023, it has been incredible to watch @vllm_project become the OSS inference engine for so many teams. Building a project like this takes persistence across everything: research breakthroughs, ruthless engineering, performance + stability work, ecosystem integration, and the unglamorous grind of docs/CI/issues/releases. Huge gratitude to the maintainers & contributors—can’t wait to keep upstreaming new inference ideas in 2026 with the greater community and @inferact 🚀
Woosuk Kwon@woosuk_k

Today, we're proud to announce @inferact, a startup founded by creators and core maintainers of @vllm_project, the most popular open-source LLM inference engine. Our mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. The Challenge Inference is not solved. It's getting harder. Models grow larger. New architectures proliferate: mixture-of-experts, multimodal, agentic. Every breakthrough demands new infrastructure. Meanwhile, hardware fragments: more accelerators, more programming models, and more combinations to optimize. The capability gap between models and the systems that serve them is widening. Left this way, the most capable models remain bottlenecked and with full scope of their capabilities accessible only to those who can build custom infrastructure. Close the gap, and we unlock new possibilities. And the problem is growing. Inference is shifting from a fraction of compute to the majority: test-time compute, RL training loops, synthetic data. We see a future where serving AI becomes effortless. Today, deploying a frontier model at scale requires a dedicated infrastructure team. Tomorrow, it should be as simple as spinning up a serverless database. The complexity doesn't disappear; it gets absorbed into the infrastructure we're building. Why Us vLLM sits at the intersection of models and hardware: a position that took years to build. When model vendors ship new architectures, they work with us to ensure day-zero support. When hardware vendors develop new silicon, they integrate with vLLM. When teams deploy at scale, they run vLLM, from frontier labs to hyperscalers to startups serving millions of users. Today, vLLM supports 500+ model architectures, runs on 200+ accelerator types, and powers inference at global scale. This ecosystem, built with 2,000+ contributors, is our foundation. We've been stewards of this engine since its first commit. We know it inside out. We deployed it at frontier scale—in research and in production. Open Source vLLM was built in the open. That's not changing. Inferact exists to supercharge vLLM adoption. The optimizations we develop flow back to the community. We plan to push vLLM's performance further, deepen support for emerging model architectures, and expand coverage across frontier hardware. The AI industry needs inference infrastructure that isn't locked behind proprietary walls. Join Us Through the open source community, we are fortunate to work with some of the best people we know. For @inferact, we're hiring engineers and researchers to work at the frontier of inference, where models meet hardware at scale. Come build with us. We're fortunate to be supported by investors who share our vision, including @a16z and @lightspeedvp who led our $150M seed, as well as @sequoia, @AltimeterCap, @Redpoint, @ZhenFund, The House Fund, @strikervp, @LaudeVentures, and @databricks. - @woosuk_k, @simon_mo_, @KaichaoYou, @rogerw0108, @istoica05 and the rest of the founding team

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Ryan Vilim me-retweet
Ying Xiao
Ying Xiao@YingXiao·
Everyone knows that @NoamShazeer is a genius, but one thing that most people don't know is how kind and honest he is. His treatment of *all* employees in the events today was exceptionally fair and generous. 10/10 would work for him again.
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Ryan Vilim me-retweet
Character.AI
Character.AI@character_ai·
Thrilled to share that we're open sourcing our innovative approach to prompt design! Discover how Prompt Poet is revolutionizing the way we build AI interactions in our latest blog post: research.character.ai/prompt-design-…
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dr. jack morris
dr. jack morris@jxmnop·
what are some easy ways for a normal person like me to speed up training a transformer on a single GPU? i'm using huggingface T5 implementation + defaults. i know about FlashAttention and BetterTransformer and torch compile? will these all work together? is there anything else?
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Ryan Vilim
Ryan Vilim@ryanvilim·
@Eulerson314 @gabrielpeyre Eg the models expand both the velocity and magnetic fields in terms of spherical harmonics, then do the numerical solves on that representation (for the linear terms).
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Ryan Vilim
Ryan Vilim@ryanvilim·
@Eulerson314 @gabrielpeyre In the study of planetary magnetic fields they are used all over the place. First, in representing the fields themselves and second, all the numerical models that simulate magnetic field generation use them as their basis function.
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Gabriel Peyré
Gabriel Peyré@gabrielpeyre·
Spherical harmonics is an orthogonal basis of eigenvectors of the Laplacian on the sphere. Eigenspaces of fixed frequency are rotation invariant. The basic tool to perform linear and invariant signal processing on the sphere. en.wikipedia.org/wiki/Spherical…
Gabriel Peyré tweet media
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Ryan Vilim
Ryan Vilim@ryanvilim·
@itunpredictable I grew up in a semi-rural part of Canada. Somehow Seinfeld was seemingly always on one of the two channels we got and my dad loved it so I watched _a lot_ of Seinfeld. Not sure it's helped my career, I think most people conclude I'm a very young looking boomer.
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sisyphus bar and grill
sisyphus bar and grill@itunpredictable·
The single best career move I ever made was gathering an encyclopedic knowledge of Seinfeld. This has done more for me and my career than any number of the impressive, impactful projects I've been responsible for at the fastest growing startups in the world.
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Ryan Vilim
Ryan Vilim@ryanvilim·
@bernhardsson A old colleague of mine had a phrase that I love (and may not be his originally), which is we should design systems to cause people to fall into the pit of success, rather than then put of failure. E.g. make the easiest thing also the “correct” thing.
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Erik Bernhardsson
Erik Bernhardsson@bernhardsson·
Random thought: the usability of a tool shouldn't be judged by how easy it is to succeed, but by how hard it is to fail. The best tools actively nudge you towards the right path.
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Douwe Osinga
Douwe Osinga@dosinga·
Here's a @NeptyneHQ spreadsheet with the life-expectancy by occupation for people that have a wikipedia page. It's best to become a billionaire and all these people wanting to be a podcast host - lookout! neptyne.com/neptyne/9iofhm…
Douwe Osinga tweet media
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Ryan Vilim
Ryan Vilim@ryanvilim·
@academic_exit I’m my first job: yes, by a factor of 8, after 7 years by a factor of 16. All of this with a better work-life balance, while still working on interesting problems. I don’t regret my time in academia, but I’m very glad I left.
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Academic Exit
Academic Exit@academic_exit·
PhDs working outside of academia: do you make more money in your post-academic role than you did in academia? Inquiring minds (of PhDs still in academe) want to know.
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Ryan Vilim
Ryan Vilim@ryanvilim·
@erikapullum I don’t understand why snowflake doesn’t have a comprehensive list for functionality that is different on Redshift (maybe they do now). I asked our Snowflake rep and he pointed us to a 4 paragraph blog article that I already knew about.
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Ryan Vilim
Ryan Vilim@ryanvilim·
@erikapullum The answer for the SQL question is “it depends what db”. I lead a migration from Redshift to Snowflake for a very large dbt project, and one of the funnest differences was LEAST(4,null) is 4 on one, and null on the other.
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@erikapullum@data-folks.masto.host
@[email protected]@erikapullum·
Data folk -- what's the worst, best, or funniest null-related bug you've introduced? What should people learning SQL know about null?
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Ryan Vilim
Ryan Vilim@ryanvilim·
@markmahoney Who doesn't love trading a series of known issues for fun, new, unknown issues, annihilating any existing knowledge of how a system works, and incurring opportunity costs while we do it?
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Ryan Vilim
Ryan Vilim@ryanvilim·
@levelsio Lol “Even the Canadians don’t use it” and we all know that ANYTHING goes in the great white north.
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@levelsio
@levelsio@levelsio·
Email of the year
@levelsio tweet media
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Ryan Vilim
Ryan Vilim@ryanvilim·
@holman The other thing is, why would you want someone who has mentally already moved on? By the time I’m giving notice I’m already thinking of all the cool stuff I’m gonna do/learn at the next place. I don’t know why anyone would want me to stay if my hearts not in it.
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Zach Holman
Zach Holman@holman·
So weird to see companies work so hard to convince an employee to stay after they’ve already put in their notice. There were probably dozens of times you could have stepped in before it got to that point; a meager raise isn’t going to help now.
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Ryan Vilim
Ryan Vilim@ryanvilim·
@bernhardsson I write lots of code in non-Python e.g. I've written a ton of C++ in my life. But my prior is that my EV out of a project is highest if I use Python, because in all likelihood I won't end up nailing it on the first try, and Python will let me find that out the fastest.
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Ryan Vilim
Ryan Vilim@ryanvilim·
@bernhardsson I feel all my gripes with Python are around the things that slow my development down, not make it more Correct (in a SWE purity sense)
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Erik Bernhardsson
Erik Bernhardsson@bernhardsson·
My new rule is you can only dunk on Python after acknowledging that (a) people pick the language that makes them the most productive (b) Python is the most widely used language in the world
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