Nice. I guess this must have existed in some form for GPUs before this, and that this is just better with the latest software stack?
This could be generally useful for a lot of algorithms like kmeans(ish) like Cut algorithm that projects points into eigen space — as opposed to the kernel space in Kmeans — need the affinity matrix(distance for K points).
And Incidentally prefill would also be how caching,say, a system prompt saves you some $ for API usage with LLM providers. They only compute the kv cache for the new tokens after the system prompt.
If you like better content look for kagi's small web or better yet find a better algorithm that optimizes for your preferences rather than engagement.
I have my instagram, x on a locked down browser in a container with a fake profile that an LLM drives and finds the posts for specific users and compiles a gist of all the important things in my locality(or what u care about) every evening, without me ever going near that FOMO driven dumpster fire of tiktok/insta/x.
I would never install an extension with a 1000 foot pole, because of its seriously flawed security model. I think in 2026 if you really badly need an extension as an end user, write your own or pay someone to do it. I would also accept open source ones, since I can review the code.
Your extension can and will likely read all your data and likely has broad permissions to just fax all your Gmail to remote cloud server.
Thanks for all the amazing work! I have Noob question. Wouldn't this get the funding back? Or would that not be preferable way to continue(as opposed to just volunteer driven)?
Like this is a big deal to get a project to a state where volunteers are spun up and actively breaking tasks and getting work done, no? It's a python JIT something I know next to nothing about — as do most application developers — which tells one how difficult this must have been.
The funding was Microsoft employing most of the team. They were laid off (or at least, moved onto different projects), apparently because they weren't working on AI.
With Python being the main language for AI, isn't like more important to be more performant?
I kinda don't get Microsoft reasoning, maybe they're just tight in money
Python is pretty big as glue in the AI ecosystem as far as I can tell. It also seems to be most agent's 'preferred' language to write code in, when you don't specify anything.
(The latter is probably more to do with the preferences they give it in the re-inforcement learning phase than anything technical, though.)
So, ultimately, to the question, what exactly is Sarvam AI?
Is it a company that builds LLMs cheaply and open-sources them? Is it India’s Deepseek?
Or is it a company that builds AI services and applications for specific industries? Like, say, Scale AI?
Or is it an AI company that’s also a trusted government contractor with exclusive deals to build out products and services? Like India’s Palantir? Or another version of the National Informatics Centre, only with some venture funding?
I would call it code-plumber. It's like a plumber who are today socio-economocally very distinct from architects, civil and structural engineers.
They will have very narrow to zero understanding — don't need it to fix — of shear forces, navier stokes.
They will command high rates if labor is limited(a plumber in Indonesia will commande lower ppp adjusted hourly rates than America). CS education become a subset of applied math since graduate hiring of code-plumber will require a narrower certificate to fix an AI system — which works very much like how plumber working to fix a building leak is different from a person fixing a water pipe burst under a road.
A few AI systems will become dominant, That should be a mix of Anthropics and your Googles. They will hire code plumbers to plumb together all the things they provide.
You don't have to use much brain at all as a code-plumber. You become a remote journeyman logging in and plumbing with given tools, making sure there is low back pressure(a term where load on future plumbers interacting/fixing with ai decreases) and the like.
I can't tell if yourr comparison to plumbers who don't understand theory (Navier-Stokes) is supposed to apply to "ape coders" who write code by hand or to "vibe coders" who outsource their understanding.
We should just have phones connected to AI bots of our own that talk to them.
I've used CC with chrome to access social feeds autonomously and give me a notification at set times of the day, summarizing everything that I feel is worth knowing about— local events, local municipal announcements, some misc comics and some harmless fun with dogs/OnlyInNYC. It really takes out all the FOMO driven brain fuckery of feed and ads.
What does 'a legal approach' mean where there is no rule of law? USA just bombed another country without having a domestic legal basis for that. Can't imagined they're holding back on AI use that is illegal -- even textbook-clear warcrimes (like blowing up shipwrecked people) does not give Hegseth and Trump pause.
That goes for domestic actions too, happy to arm a paramilitary and set them loose against citizens who are not politically aligned with Trump... the Republican Senate barely even blinks. Hard to imagine they'd care about AI use in mass surveillance, nor AI use in automated anti-personnel weapons. The Senate will be, 'Oh no they unlawfully killed USA citizens, again... Welp, let me check my insider trading gains... yh, seems fine'.
Economics of producing goods(software code) would dictate that the world would settle to a new price per net new "unit" of code and the production pipeline(some wierd unrecognizable LLM/Human combination) to go with it. The price can go to near zero since software pipeline could be just AI and engineers would be bought in as needed(right now AI is introduced as needed and humans still build a bulk of the system). This would actually mean software engineering does not exist as u know it today, it would become a lot more like a vocation with a narrower defied training/skill needed than now. It would be more like how a plumber operates: he comes and fixes things once in a while a needed. He actually does not understand fluid dynamics and structural engineering. the building runs on auto 99% of the time.
Put it another way: Do you think people will demand masses of _new_ code just because it becomes cheap? I don't think so. It's just not clear what this would mean even 1-3 years from now for software engineering.
This round of LLM driven optimizations is really and purely about building a monopoly on _labor replacement_ (anthropic and openai's code and cowork tools) until there is clear evidence to the contrary: A Jevon's paradoxian massive demand explosion. I don't see that happening for software. If it were true — maybe it will still take a few quarters longer — SaaS companies stocks would go through the roof(i mean they are already tooling up as we speak, SAP is not gonna jus sit on its ass and wait for a garage shop to eat their lunch).
This could be generally useful for a lot of algorithms like kmeans(ish) like Cut algorithm that projects points into eigen space — as opposed to the kernel space in Kmeans — need the affinity matrix(distance for K points).
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