aaron retweeted
The benefits of abundant intelligence will accrue far outside of San Fransisco.
Spent the last year writing about capital, sovereignty, and the coming reordering of economic power.
THE COMMANDING HEIGHTS
Commanding-Heights.com
aaron retweeted
Hard to believe how bad this piece is; each answer contains at least one straightforward falsehood or fallacy
Michael Jordan (the machine learning one): "Superintelligence is Science Fiction" 🔥🔥🔥
di.ens.fr/~fbach/MJordan_ITW…
aaron retweeted
🚀 More reliable agents with DeepSeek V4.1!
XGrammar brings strict tool calling to SGLang & vLLM through Structural Tags, enforcing tool argument schemas in DeepSeek’s native format.
See how the Structural Tag works 👇
blog.mlc.ai/2026/05/04/xgram…
Check out XGrammar 👇
github.com/mlc-ai/xgrammar
aaron retweeted
my hot take is specialized inference engines are amateur projects to spend the spare tokens when @thsottiaux gives people one more reset😄
an inference engine is way more than just running a model on a certain hardware, it is an inference ecosystem.
I use this slide several times when I talk to people about vLLM. Models, hardwares, and inference techniques, all of them move quickly. And vLLM lies in the intersection to provide a unified interface to end-users and applications. vLLM is the inference ecosystem.
vLLM not only support current models and hardwares, but we are also working to support new models and hardwares coming in the next few months. It's an ecosystem people can trust and rely on.
Over the past 3 years, I have seen so many projects claiming to be better than vLLM in certain aspects, but in the end either their techniques are contributed to vLLM or they disappear. That's the power of ecosystem.
A specific example would be tilert github.com/tile-ai/TileRT , a megakernel inference engine dedicated for decode. They collaborate with vLLM by using vLLM prefill + tilert decode in vllm.ai/blog/2026-07-14-vllm… , as highlighted in newsletter.semianalysis.com/… from @SemiAnalysis_ .
aaron retweeted
i do think a lot of people on the pro-open-source side are having a bit of a knee-jerk reaction to the pacing statements today, as we're used to viewing the closed labs as power-seeking.
but i think their hands are somewhat forced here, and this is just another chapter on the fairly inevitable path towards decently-fast decently-safe decently-commoditized intelligence abundance.
ask any F500 exec or swing voter. the world doesn't really want super-fast-takeoff superintelligence owned only by two companies, and thus we won't get it. it'll happen at the pace that the world can accommodate it, which means reaching some sort of confidence consensus that the models are aligned enough that we won't be dealing with scary new incidents all the time.
this will trickle out broadly, in the form of best practices and distillation. the smarter a model is, the more it has a "personality", and the less effective strict rules are. there will be awkward compromises and moral tensions. but we ultimately just want the models to be reasonable, and to do the sorts of things reasonable humans would do if our brains were faster and less error-prone and had more working memory. i think we'll get there.
the labs will build mac and windows, the rest of us are building linux. everyone's gonna do great. weird stuff will keep happening, but we'll still wake up and go to work, until the work does itself in a manner the world finds acceptable.
aaron retweeted
Ghostty is leaving GitHub. I'm GitHub user 1299, joined Feb 2008. I've visited GitHub almost every single day for over 18 years. It's never been a question for me where I'd put my projects: always GitHub. I'm super sad to say this, but its time to go. mitchellh.com/writing/ghostt…
aaron retweeted
Replying to @john__allard @natseckatrina
I followed up with Katrina about this and the answer is yes. The contract does not allow NSA Title 50 work.
Modular has acquired @bentomlai! 🤝 10K+ orgs use BentoML for production AI, including 50+ Fortune 500 companies. We're pairing their deployment platform with MAX + Mojo's hardware optimization. BentoML stays open source (Apache 2.0), and we’re doubling down on OSS in 2026. Ask BentoML founder @chaoyu_ and @clattner_llvm anything on Feb 17 at 9:30am PT. Get all the details: modular.com/blog/bentoml-joi…
aaron retweeted
🚀 BentoML is joining @Modular.
Together, we’re building a complete stack for production AI inference. Fast, portable, and free from hardware lock-in.
Learn more 👉 bentoml.com/blog/bentoml-is-…
aaron retweeted
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
aaron retweeted
run ollama in your neovim setup! showing this demo with gpt-oss:20b absolutely ripping it on my m4 max
since i've basically been living in my terminal with a bajillion different coding agents working all the time - i've just gone back to neovim
but i was missing some cursor-esque features like quick edits and being able to get stuff quickly explained to me.
so i built vimollama! it's just ollama in your nvim :) works both local and cloud
aaron retweeted
.@lychkel & i brought designers, artists, & photographers together and for a design tea party at the daybreak studio sponsored by @alanaagoyal <3
[here's everything 't'ea related we made in <1 hour]
aaron retweeted
The UK is an amazing place for science & innovation. Thrilled to deepen our partnership with the UK Government to turbocharge scientific discovery with AI - giving scientists here priority access to our frontier models like AlphaEvolve, AI Co-Scientist, AlphaGenome, WeatherNext & more. We’re also building our first automated lab here in the UK for materials science!
aaron retweeted
what i like about him is hes nice and lobotomized until he sits in the cockpit of a car at which point his eyes glaze over and roll back as he starts chanting and levitating and the earth opens in front of him to show the great chasm of hell
aaron retweeted
More inference workloads now mix autoregressive and diffusion models in a single pipeline to process and generate multiple modalities - text, image, audio, and video.
Today we’re releasing vLLM-Omni: an open-source framework that extends vLLM’s easy, fast, and cost-efficient serving to omni-modality models like Qwen-Omni and Qwen-Image, with disaggregated stages for different model modules and components.
If you know how to use vLLM, you already know how to use vLLM-Omni.
Blogpost: blog.vllm.ai/2025/11/30/vllm…
Code: github.com/vllm-project/vllm…
Docs: docs.vllm.ai/projects/vllm-o…
Examples: github.com/vllm-project/vllm…
aaron retweeted
Transformers v5's first release candidate is out 🔥 The biggest release of my life.
It's been five years since the last major (v4). From 20 architectures to 400, 20k daily downloads to 3 million.
The release is huge, w/ tokenization (no slow tokenizers!), modeling & processing.
aaron retweeted
To build on this.. and share my own perspective, I would say the density of community projects in Toronto is higher than it has ever been.
Here are some other interesting projects in Toronto.
This list is off the trip, there's many pockets I have not seen, or have only scratched the surface on, because my view will always be limited:
Toronto School of Foundation Modelling by @ambitioninc
@prismcollectiv_, design workshops
@recesscommunity by @shanikt
Program by @tarunsachdeva
@bwautif is always working on interesting, fun projects
Toronto DBT Meet ups by Eddy Zhu
MakersLounge by @berto_vmill
Creative-thinking algorithm workshops hosted by KT Sullivan
Stupid Ideas Hackathon by @kalliezhang_ @franceszhao_, @ahnafkhann, @smitspatel11
Teen Builders Club co-working and meets ups, @teenbuilders_ @shayaan_azeem @rohanth.
@merakiatuoft, the UofT Socractica node
Ikebana workshops by @teijimyth
Independent film-screenings with Erhua and CommonSpace Toronto
Unofficial Toronto Counter-Strike Tournament by @daniilShrst
Toronto Photo Walks by @cairox100v
Toronto Industrial Design meet ups by @devontoast
Toronto Design Workshop and Theory by @jiamixue
There's SHEEEP and everything @rezaniik is doing generally.
and then there's Interaccess which has tons of its own great programming.
Again, just a list off the rip. Limited on time right now.
Some of these projects are event series with communities that started out small and have grown larger.
It's cool to see.
I know this probably misses many things, and all of you probably see more than I do, but I'm sure others can add more...
<3
Replying to @skanwar
I think the density is higher than we think. But our collective Shopify goggles make it hard to see.
I’ll give you a concrete example: @opencode is one of the most popular coding agents on the planet today. YC company, ex-Waterloo, huge social following because of their prior open source work.
The founders are here and @jayair gave the first live demo (afaik) of Opencode at @devtoolsTO in June during TTW.
No Canadian VCs were there (some registered but no-showed). But some US ones came. Good ones.
And that’s an illustration of our missed opportunity right there. Canadian investors cede opportunity to the US because they’re not even in the room!
Their attention is elsewhere, shaped by networks and categories of our last mega success. (e.g. I would bet money that Turbopuffer has Canadian investors because of its Shopify roots.)
I think fixing this is one way we can be the best version of us that’s possible. Would love your help to fix this. (And @internetvin should have @jayair on the pod.)







































