Karan Brar

ceo/co-founder of autoresearch, inc. | prev ml enjoyer @reductoai @dynamo_ai, math enjoyer @uoft

[Karan Brar @deepmatmul]

About as much as every other field is cooked. I’m not a fan of these takes because it implies that math is somehow over. If anything, we’re entering the golden age of the industrialization of mathematics.

[Franklyn Wang @frank_liquid]

Is math cooked?

[Edgar Shaghoulian @eshaghoulian]

lol what a gross post

[Karan Brar @deepmatmul]

@_TarunKathuria I def think wsp replacing backprop is certain delusion

[Karan Brar @deepmatmul]

We’ll certainly have a lot more exotic optimization algorithms that combine classical techniques + LLM driven optimization. WSP is only the beginning.

[Tarun Kathuria @_TarunKathuria]

I’ll take the other side of this bet. If one understands any reinforcement learning, it should be clear why weight space editing is a last mile touch up and not a backprop or heck even ZO opt replacement

[Anicet @AniC_dev]

pro tip: don't punch down on a 1000x smaller competitor for not updating their comparison page, it's not the flex you think it is

[Tarun Kathuria @_TarunKathuria]

I found all the people saying negative things about Sutton and quoting bitter lesson to be quite surprising. It's as if they completely forgot how basically everyone was talking (including Dwarkesh Patel with Sutton on his podcast) when pretraining only was the dominant paradigm (pre o1 etc) and everyone thought just keep scaling and you'll get PhD level math models with just pretraining and then reasoning models came and completely shattered that ceiling becoming a great step up in capabilities.

Sutton is 100% right (as he usually is) here btw and if you don't see it you have major skill issue and don't even understand bitter lesson properly

[∞-modal Noah @NoahChrein]

The vibe type theory explosion is bound to occur. Axiom and others will realize their systems can make new type theories that are more expressive than the hand crafted ones we use.

[Axiom @axiommathai]

Post-train a formal theorem proving model to reach frontier performance to push the frontier of math 🔥🔥🔥

[Karan Brar @deepmatmul]

should we do it

[Thomas Boser @thomasboser]

bad business idea: abliterated ai model inference provider but you report your customers to the FBI

[Karan Brar @deepmatmul]

@lxe We are!

[Kunal Jha @kjha02]

What if a swarm of AI agents could learn to work together on its own? 🐝

No leader. No roles. No turn order. Just one shared reward.

Our new paper s³: multi-agent RL lets LLM swarms self-organize, beat best-of-N, and scale past their training size!

https://t.co/c4SyIKhX7O 🧵

[Karan Brar @deepmatmul]

Still curious if formalization of mathematics will yield any gains in terms of our ability for discovery, or it’s mostly just to accomplish the autistic dream of a formally verified encyclopedia of mathematics.

Most mathematicians I’ve spoken to see this as a vanity project with no real applications, but the rest is to be seen.

[Jonathan Laurent @jonath_laurent]

Using the Stacks formalization we built at Axiom, we formalized the Weil conjectures in a single day. With the foundations in place, formalizing research-level algebraic geometry is now within reach for anyone working in the field.

[Jonathan Laurent @jonath_laurent]

Using the Stacks formalization we built at Axiom, we formalized the Weil conjectures in a single day. With the foundations in place, formalizing research-level algebraic geometry is now within reach for anyone working in the field.

[Geoffrey Miller @gmiller]

The mask has slipped.

The heart of the pro-AI movement is contempt for humanity. Not progress. Not 'Abundance'.

Just frustration that ordinary Americans simply refuse to vote the way that AI devs and economics professors think they should.

[Francois Chaubard @FrancoisChauba1]

re: weight-space programming (WSP) craziness… just tried something that blew my mind..

i asked the question: is Astra + WSP a better optimizer than BP on simple extrapolation learning on any turing computable function.. (let alone interpolation)..

so far my answer is yes..

just tried a bunch of functions like:
x^2
sin(x)
x^x
tanh(x)
add
sub
rolling_sum
sort
fib

WSP gets to beyond machine precision in many cases for interp and extrap.. (exactly matched every tested 64-bit reference output) (DISCLAIMER: very prelim results so far mind you..)

and BP does not.

WSP beats BP on every task I gave it..

iso-architecture/iso-param/iso-initialization/iso-inputs..

I have been stuck on the following problem for 12 years... if UAT is true, why cant we find a decent root in the loss landscape..

its bc BP sucks.. WSP is the first optimizer that actually can in a lot of cases. this is a whole new area of optimization burgeoning..

[Tom Bibby @tombibbys]

"I am prepared to risk murdering innocent children for a chance of immortality"

[Karan Brar @deepmatmul]

stfu already man you’ve been shitting yourself the past 48 hours we get it you hate the dems and love Elon you don’t need to continue virtue signalling

[Beff (e/acc) @beffjezos]

This is the nightmare scenario they want.

Total AI Dystopian 1984.

We must fight this tooth and nail.

The resistance begins now.

[Deven Pietrzak @DevenPzak]

20 days ago we built a system that writes GPU code. Today its kernels outperform the state of the art. We just open-sourced 9 megakernels, which outperform NVIDIA’s stack on DeepSeek and run self-driving, robotics, protein folding and world models 2–3× faster than the current best systems. Every model runs in a single launch instead of thousands, and most of our kernels were generated in under an hour.🧵