Remix.run Logo
SwellJoe 3 hours ago

The moat looks deep today but it's going to become more shallow every year.

Training a new model from scratch takes serious resources. Post-training/fine-tuning an existing model, dramatically less. The knowledge for the process was esoteric two years ago, now you can ask a current model (one of several) to walk you through it, while building the tools to do it as you go. Several of my recent weekend projects have been exactly that sort of thing, just so I understand it better. "Let's make a LoRA", "let's generate a corpus of training data for fine-tuning a model for X task", "how can I put my face in a text-to-image model?" stuff like that. All of this is do-able on kinda modest local hardware (a couple of old GPUs or a Strix Halo or DGX Spark or big Mac Studio), or for a few bucks or a few hundred bucks or a few thousand bucks of cloud compute, depending on scale.

Scale that up to corporate or startup scale, with the money that's been flowing into AI for the past couple/few years, and it's obviously there's going to be a lot of competition just as the top model makers need to start ringing the cash register. That's a lot of opportunities for people to look at their ballooning Claude usage costs and find other ways to do the same thing for drastically less money. $100/month or $200/month is a no-brainer for Claude Code with probably the best model for coding, but they're pushing more users to usage-based billing which becomes cost-prohibitive real fast.

So, they desperately need to continue to be among the only ways to solve the hardest problems, and they need the alternatives to cost a similar amount. They can count on OpenAI and Google to ratchet up prices, too. They probably can't count on everybody, especially the vendors in China with different economics, to do it. And, they can't count on companies to look at their own usage and not ask, "Can we train a smaller specialist model that does this one thing we're using the Anthropic API most heavily for?"

I'm hoping they just mean stuff like using Claude for distillation by e.g. Chinese model makers, and not "how do I fine-tune Gemma 4 to write more like me?" or whatever.

Ferret7446 5 minutes ago | parent | next [-]

The moat is not the model, it's the harness. I wager that's one of the main reasons why Google made Antigravity closed source.

hedora 3 hours ago | parent | prev | next [-]

What moat? There are multiple companies providing pareto-optimal frontier models, and it takes O(10) people to build one of these things.

The rest is capital intensive, and the price will approach the cost of production over time.

Thinking this is a profitable endeavor is equivalent to claiming coal plants have good margins because boilers are expensive.

SwellJoe 3 hours ago | parent | next [-]

I think we agree?

What moat? You answered yourself: "capital intensive"

But, history says the supercomputer of today will fit in your pocket in a few years.

They've bought up all the RAM and GPUs, which pushes the capital requirements upward for everyone else. But, they can't corner the market forever, there are too many competing interests. AMD and Intel keep making new GPUs and APUs. The memory makers can't just sell to only AI companies forever, if they do Chinese manufacturers will move in and eventually eat them from below (as has happened many times before).

They have a moat today, and it's just that it's really expensive to train and host frontier models, especially at commercial scale. It used to be there was also some secret sauce to making it fast and efficient. But, secret sauce is being published daily by all sorts of researchers, folks are figuring out how to do more with less and it often finds its way into llama.cpp or vLLM or SGLang within days or weeks.

theLiminator 2 hours ago | parent | next [-]

> But, history says the supercomputer of today will fit in your pocket in a few years.

I don't think this will be true in the same time span anymore. Each miniaturization is costing more and more money.

Perhaps they'll come up with exotic fundamental improvements, but I don't think the rate of improvement of compute/watt will match the previous decades.

pixl97 2 hours ago | parent | next [-]

Really the biggest concerns are not computers getting spectacularly faster, but 'intelligence' algorithms getting orders of magnitude better.

Drop the power requirements 1000 fold, and yea you will be able to make your own SOTA model on the cheap. The problem is the person that has a few exaflops of power will still leave you in the dust in the intelligence explosion that would happen after an event like this.

SwellJoe 2 hours ago | parent | prev | next [-]

Yeah, that's probably true, but we're also seeing that there's still tons of inefficiencies in how LLMs are being run. Seems like every couple months there's some new technique to squeeze more performance out of less hardware. KV caching improvements, fast attention, speculative decoding, dynamic quantization, quantization aware training, etc.

That said, I recently replaced my five year old self-built PC (with a top-of-the-line desktop CPU, chipset, memory, and GPU of the time) with a new everything-the-best build, and while it's clear we're not keeping up with Moore's Law anymore, it's still 4-5 times faster for compute-intensive stuff, especially parallelizable tasks. We're still getting faster/cheaper. So, the time scale is maybe ten years rather than five.

altcognito 32 minutes ago | parent | prev [-]

Single clock speed hasn't had much of an upgrade, but the architecture for doing exactly what they are doing? That will improve for at least 5-10 years. There are both huge power gains from Processing in Memory (PIM) chips (70-80% discount in energy), and improvements to engineering to make memory cheaper and cheaper.

altcognito 33 minutes ago | parent | prev [-]

The other half of the moat is the data they stole from everyone else, some of it illegally. So, be sure they will do everything in their power to stop others from getting that data freely.

redox99 5 minutes ago | parent | prev [-]

O(10) people?

iplaymyowngames 24 minutes ago | parent | prev [-]

> The moat looks deep today

Does it? What can this model do that I both want and cannot already do?

Anthropic made a nice little post saying how dangerous it is, because it is good enough to eat their own business. But I don't want to eat their business. They also said it was good at playing Slay the Spire, but I can't think of anything more insulting than have a machine do that in my place. That's MY comfort game, not something for a stupid Clanker to take away.

They did not provide any other use case.