But how many that give you a Git repo where you actually *own* the entire intelligence stack? Runtime, model choice, skills, tools, connectivity, sandbox…
it's really much easier if you can understand how to center a div as they say if you can vertically center a div in HTML then you can probably learn assembly language I would say
I remember anytime I would work with a big site on their performance problems, uh you could easily spend half a day, um you know, just looking at traces before you've even written any fixes at all. And now that we have LLMs, it's very quick to like reason through massive stack traces and actually be able to get down to fixes you can make.
However, looking ahead, I still do not believe that future AI (say, in 15 years) will be based on the LLM stack. I believe it will necessarily have to move closer to its optimal, final form -- symbolic learning. Obviously this is a risky and contrarian belief -- the safe bet would be LRMs. But let's see.
In a world of AI with agents operating across multiple systems, wanting source of truth data, the importance of having preferred paved paths that get the most of the benefits and produce some guardrails so we can make sure we're doing good work, common infrastructure, common paved paths, solving problems once with a core set of capabilities becomes more important.
And eventually, you have to really move into a full stack. So, not just a silicon, you need to have a software, and some of the customer asked me, "Give me the whole rack." So, there's a system that you have to build.
Trustworthiness is the most underrated asset in all of business. And the things that create trustworthiness by definition stack rank to the bottom if we do it by ROI because doing the right thing has intangible rewards but tangible costs.
the work that we do with building our our computing platform. If we don't if we don't do it, I genuinely believe it doesn't get done. If we didn't take the risk that we take, if we didn't build MVLink the way we built, if we didn't build the whole stack, if we didn't create the ecosystem the way we did it, if we didn't dedicate ourselves to 20 years of CUDA while losing money most of that time, if we didn't do it, nobody else would have done it.
And so our expertise um helps our our our um uh our AI labs partners get another 2x out of their stack easily. Often times it's not unusual that we you know by the time that we're done optimizing their stack or optimizing a particular kernel their model sped up by 3x 2x 50%.
Nvidia's computing stack is the best performance per TCO in the world, bar none. Nobody can demonstrate to me that any single platform in the world today has better performance TCO ratio. Not one company.
Um, and then you stack on 70 this year, 80 next year, growing to 100 by 2030. You're at like 700 EV tools by the end of the decade. Um, 700 EV tools, three and a half tools per gigawatt. um assuming it's all allocated to AI which it's not but three and a half tools per gigawatt gets you to 200 gigawatts worth of AI chips for the data centers to deploy
Many AI researchers are overly focused on risks from model misalignment, and will be in for a rough surprise when havoc arises from other layers of the stack.
Local-first is not going to win, but that's okay We'll explore the complexities of traditional stack (db-server-frontend), develop a theory of software evolution: which systems succeed and why.
many of the breakthroughs that we've had that have enabled us to to deliver such quality and cost savings and more have come through novel agent architectures and and really going down a click or two in in the stack to innovate at at lower levels of the technology stack.
the meta problem here is if we don't move our industrial stack off fossil fuels in 10 or 20 years, first of all, we'll get poor the same way you UK did, right? Because they ran out of coal basically. And the second thing is we'll get poor because we'll flood our coastal cities in Florida underneath climate change.
They do have flame graphs in Nsight Graphics for GPU workloads, although their flame graphs are currently shallow as it is GPU code only, and onerous to use as I believe it requires an interposer; on the plus side they have click-to-source.
As I set out last time, the usual story — that this was caused by deforestation, making firewood so scarce that people resorted to burning an inferior but cheaper fuel — simply does not stack up.
I use Sendy for newsletters. It's a self-hosted service which uses Amazon Simple Email Service. It's written using PHP and thus it needs the LAMP stack to be hosted. I use a DigitalOcean droplet with the LAMP stack installed to host it.
My hot take is that JS has the lowest bar of entry to building and being productive (a good thing) but one of the highest bars of any language and stack to building high quality, stable, and reliable software. Very few devs have the expertise to pull off the latter
And for a long time, I thought that's what had worked. That this was why Ruby on Rails took off, became one of the most popular full-stack web frameworks of all time, inspired countless clones, and created hundreds of billions in enterprise value for companies built on it. But I was wrong. It wasn't the crusade that did it.
It’s always harder to write software for more specialized hardware. A GPU is pretty generic. If you can’t write an in Nvidia stack, there’s no way you can write a stack for your chip. My approach with Tinygrad is first write a performant NVIDIA stack.
There’s two stacks of life in the world. There’s the biological stack and the silicon stack. The biological stack starts with reproduction. Reproduction is at the absolute core. The first proto-RNA organisms were capable of reproducing. The silicon stack, despite, as far as it’s come, is nowhere near being able to reproduce.
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