Plus first-mover advantage has consistently shown to not be a legitimate strategy as there are a ton of cases where the first winner gets taken over by a new entrant once the market matures (Friendster being the classic example). Often the later companies learn from the mistakes of the first play.

R&D heavy markets might have some different characteristics but it's still way too early to say with AI.

I can already run gpt4xalpaca on my PC, a model that is not-bad-at-all and is completely uncensored (i.e. does things that chatGPT can't do). I think it's true that LLMs are racing to the bottom and will be even more once they can fit as a peripheral to every computer. whoever is investing in this to monopolize has not thought it through

This is a repeat of the early GPU era.

It's not the software or hardware that will "win" the race, it's who delivers the packaged end user capability (or centralizes and grabs most of the value along the chain).

And end user capability is comprised of hardware + software + connectivity + standardized APIs for building software on top + integration into existing systems.

If I were Nvidia, I'd be smiling. They've been here before.

Nvidia: just as the sun starts setting on crypto mining, the foundation model boom begins. And in the background of it all, gaming grows without end.

If you've got a choice, sail your ship on a rising tide! And if you can spread the risk over multiple rising tides, so much the better!

My dad told me a quip once: "It's amazing how much luckier well prepared people are."

Imagine you're a tech company that pays software engineers $200K/year. There is a free open-source coding model that can double their productivity, but a commercial solution yields a 2.1x productivity improvement for $5000 annually per developer. Which do you pick?

The existence of the models is making programmers cheaper rather than the reverse.

But i think it is underestimated how important it is for the model to be uncensored. ChatGPT is currently not very useful beyond making fluffy posts. As a public model, they won't be able to sell it for e.g. medical applications because it will have to be perfect to pass regulators. It cannot give finance advice. Censorship for once is proving to be a liability for a tech company.

In-house models OTOH can already do that, and they can be retrained with additional corpus or whatever. And it's not even like they require very expensive hardware.

I find your argument persuasive, companies should spend extra for the significant productivity gain. But then again from experience most companies don’t give you the best tools the market hast to offer..

Not sure if parent had a certain answer in mind, but my answer is OSS because (1) I can try it out whenever I want, and (2) I don't have the vexing experience of convincing the employer to purchase it.

That’s the endless «build vs buy” argument. And countless businesses are buying.

I don't this it's the same thing, at least for me.

In the GP's scenario, I wouldn't be building either piece of software.

It’s astonishing to me that people seem to believe the llama models are “just as good” as the large models these companies are building, and most people are only using the 7B model, because that’s all their hardware can support.

…I mean, “not-bad-at-all” depends on your context. For doing mean real work (ie. not porn or spam) these tiny models suck.

Yup, even the refined ones with the “good training data”. They’re toys. Llama is a toy. The 7B model, specifically.

…and even if it weren’t, these companies can just take any open source model and host it on their APIs. You’ll notice that isn’t happening. That’s because most of the open models are orders of magnitude less useful than the closed source ones.

So, what do want, as an investor?

To be part of some gimp-like open source AI? Or spend millions and bet you can sell it B2B for crazy license fees?

…because, I’m telling you right now; these open source models, do not cut it for B2B use cases, even if you ignore the license issues.

You know what I believe is also a toy model? chatGPT Turbo, you can tell by the speed of generation. And it works quite well, so small size is not an impediment. I expect there will be an open model on the level of chatGPT by the end of the year because suddenly there are lots of interested parties and investors.

Eventually there will be a good enough model for most personal uses, our personal AI OS. When that happens there is a big chance advertising is going to be in a rough spot - personal agents can filter out anything from ads to spam and malware. Google better find another revenue source soon.

But OpenAI and other high-end LLM providers have a problem - the better these open source models become, the more market they cut underneath them. Everything open source models can do becomes "free". The best example is Dall-E vs Stable Diffusion. By the next year they will only be able to sell GPT4 and 5. AI will become a commodity soon, OpenAI won't be able to gate-keep for too long. Prices will hit rock bottom.

> I expect there will be an open model on the level of chatGPT by the end of the year because suddenly there are lots of interested parties and investors.

I really don't think you understand just how absurdly high the cost is to train models of this size (which we still don't know for sure anyways). I struggle to see what entity could afford to do this and release it as no cost. That doesn't even touch on the fact that even with unlimited money, OpenAI is still quite far ahead.

Still cheaper than a plane, a ship or a power plant, and there are thousands of those.

And how many are given away for free?

I think you're conflating speed of inference/generation with optimization. gpt-3.5-turbo does not fit on a single GPU unlike the "toy" models.

gpt4xalpaca is 13B

7? 13? Who cares? It’s an order of magnitude smaller than the GPT models. It’s a toy.

I think that Alpaca 30 billion is pretty competitive with ChatGPT except on coding tasks. What benchmarks are you using to make your determination about suitability for B2B?

> I can already run gpt4xalpaca on my PC

You can also run your stack on a single VPS instead of cloud, gimp instead of photoshop, open street maps instead of Google maps, etc.

There will always be companies who can benefit from a technology, but want it as a service. In addition, there will be a lot fine-tuning of LLMs for the the specific use case. It looks like OpenAI is focusing a lot on incorporating feedback into their product. That’s something you won’t get with open-source models.

Yeah but with very simple tasks with the 2k tokens limit. Let alone the fact that it can't access the internet, or have more powerful extensions (say Wolfram).

Alpaca is the Napster or LLMs

That’s an argument, but I don’t buy it. Models are a commodity. You don’t get VC valuations and returns from raising $5B for a grain startup.

The application of AI to business problems will be lucrative, but the models are just a tool and the money will come from the domain-specific data (i.e. user and business data), which Microsoft, Google, and even Meta are positioned for. Having a slightly better model but no customer data or domain expertise doesn’t seem like a great recipe.

Then again it’s AI, so there’s more uncertainty than the commodity market. Maybe Anthropic will surprise and I’ll be as wrong about this as I was about OS/2 being the future. But I’m very skeptical.

I don't think the grain market is growing as fast as the AI market

Don’t confuse the ai market with the foundational llm model market.

Think of LLMs as the understanding component in the brain, once you can understand instructions and what actions need to happen from those instruction you’re done.

The rest is integrations, the arms legs and eyes of langchain. Then memory and knowledge from semantic search, vector databases and input token limits.

This is the real answer.

The LLM is but the core of the entire ecosystem. Just like how MLOps is 99% of the work, choosing an LLM is 1% of the effort in the final product.

What do they have besides an admittedly very cool name?

Anthropic is currently the only company that can compete with OpenAI (because they have comparable expertise). The rest (Google, Meta, Microsoft, etc) are still pretty far behind.

This approach didn’t work for Docker.

> can probably yield enough profit from spillover hype for investors to make their investments back.

The correct term for this is “pyramid scheme”.

Nope

No, this is more "everyone is selling X, let's get in the business of X". On the other hand, yes, some will miss the boat and lose money.

I interpreted “spillover hype” as meaning “more investors coming in in future rounds” (ie pyramid scheme), but it’s possible that’s not what the commenter intended.

But if early investors only profit due to late investors pouring money in, that’s by definition a pyramid scheme.