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> Congratulations, you just wrote a code completion AI!

> In fact, this is pretty much how we started out with Cody autocomplete back in March!

Am I wrong in thinking that there's only like 3(?) actual AI companies and everything else is just some frontend to ChatGPT/LLama/Claude?

Is this sustainable? I guess the car industry is full of rebadged models with the same engines and chassis. It's just wild that we keep hearing about the AI boom as though there's a vibrant competitive ecosystem and not just Nvidia, a couple of software partners and then a sea of whiteboxers.

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For those who might not be aware of this, there is also an open source project on GitHub called "Twinny" which is an offline Visual Studio Code plugin equivalent to Copilot: https://github.com/rjmacarthy/twinny

It can be used with a number of local model services. Currently for my setup on a NVIDIA 4090, I'm running both the base and instruct model for deepseek-coder 6.7b using 5_K_M Quantization GGUF files (for performance) through llama.cpp "server" where the base model is for completions and the instruct model for chat interactions.

llama.cpp: https://github.com/ggerganov/llama.cpp/

deepseek-coder 6.7b base GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-base-GGU...

deepseek-coder 6.7b instruct GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-instruct...

you've got to differentiate between training, inference and hardware. they all benefit from the "AI boom" but at different levels and have varying levels of substitutability (Google tells me that's a real word)

it make sense, in order to come up with a base model, you will need a lot of quality training data, tons of compute.

the role of an AI startup is to come up with ideas, thus useful products. Most of existing products pre-AI, are also front ends to existing operations systems and exiting databases, because creating the whole stack does not make sense. At least we have state of the art open models that we can use freely

Now think about the amount of products built and scaled worldwide by this audience on top of the few cloud compute providers out there.

Your question can be reformulated as "will the application layer's lunch be eaten by better foundation models?"

Alternatively: Will my drop-shipping business be killed by AliExpress?

I mean... the article goes on to explain all their value add... which of course can be replicated, but it's not as if you can just grab an API key and do the same.

But OpenAI could make this themselves in a few weeks, right? If they happen to decide to, then this company is done.

That's what I don't get about all these AI startups. The core value of their business is an API call they don't own. It's like people who were selling ______ apps on iPhone when Apple added their own built-in _____ features to iOS, except the entire industry is like that.

Well, the same happened in the early days of the PC. There were all these companies that sold basic utilities like disk scanners, defragmenters, partitioners, antiviruses, etc. When operating systems started to get bigger and include these utilities by default, that industry dried up overnight. I don't think there's anything wrong in building an inherently ephemeral business that just seeks to fill a niche that exists just because someone else hasn't filled it yet.

Don't forget text editors! And even though it didn't last, many people made very good money on these.

Well sure, a company with ample funding could in theory do anything. It seems sort of like asking why Google didn't beat GitHub on code hosting. They did try, but their focus was elsewhere, so they gave it up. [1] And OpenAI doesn't seem to be doing developer tools at all?

GitHub and Microsoft are more likely candidates. GitHub Copilot is a competing product that could be improved if they chose to do so.

[1] https://code.google.com/archive/

I'm not really saying that small companies should never compete with big companies.

I'm saying that a small company whose biggest competitor is also their key supplier is, if not doomed, at least operating on borrowed time. If my value proposition is reselling AWS hosting with an easy-to-use dashboard, I better pray to god Amazon never makes AWS simpler.

I feel like that can be said about any SaaS app. The reality is, mega-corps move very slowly and often can't deliver the same user experience as a start up. If everyone had the approach of "well I shouldn't make this app because if Google wanted to, they could do it in a few weeks" we wouldn't have 90% of the startups we see today.

Aren't we all operating on borrowed time though? Even if some company exists for 3 years and is able to founders a small acquihire exit, what's wrong with borrowing some time from AWS/OpenAI? We can't all come up with PageRank and patent it and form a company around it.

From the article, it sounds like they are using Claude? Maybe there's more than one possible supplier. There probably will be more.

Edit: looks like the autocomplete provider is configurable in the VS Code plugin settings. Not sure what the default is.

Currently for chat we support Claude 2, Claude 3 Haiku, Sonnet, and Opus, GPT-4 Turbo, and Mixtral 8x7b.

For autocomplete we're using Starcoder 16b.

We also support local inference with any LLM via Ollama (this is experimental and only for Cody Free/Pro users). Enterprise customers can choose which LLMs they want.

The “core value” of many companies is a database service they don’t own, but their businesses seem to do just fine. There’s a few who get obviated over time (usually they are also slow to react), but they’re a minority.

I would also question the idea that OpenAI could build a code editing companion this robust in a fee weeks. It’s been a long time since the models have been the limiting factor in these tools.

I think I’d argue that the models are still a limiting factor for these kinds of tools - but there’s still also plenty of competitive space outside of models. The context you gather, the way you gather it and your prompting matters.

> The context you gather, the way you gather it and your prompting matters.

But your API provider gets to see most of that because you send it to them along with your prompts. I don't know what the ToS for these AI providers are like, but it seems like they could trivially copy your prompts.

Uhhh, no they don't? They see the results of RAG but there's very little to distinguish what is context you gathered vs. what isn't. On top of that, there's nothing in the prompt that indicates what decision was made before inserting something into a prompt. Let's say my retrieval pipeline used a mix of semantic search and keyword-based search, and I used some mechanism to decide which results from which search to include for this specific request. Nothing in the prompt will say that, and so the differentiating behavior is still kept "secret" if you will.

But I think this line of thinking is a bit ridiculous. Yes, if you send your data to a database service, that provider has your data and theoretically use it to run you out of business. Except they kinda can't, both as a matter of practicality and legality. OpenAI, Anthropic, and others have SOC II compliance. The easiest way to ensure you run yourself out of the market is to start violating that stuff.

Most companies have valuable data that they do own stored in a commodity database they don't. I know if Amazon started charging 10x for RDS, it would be painful but we could migrate in a few weeks.

Which part do you think you couldn't do on your own with your own api key?

They’ve been thinking about the problem continuously for the past year, can run experiments across their user base and thus have a lot more context and insight than someone whipping up an implementation.

well they wrote a whole blog about how they do it... and im sure this isn't the only one on how to approach this. they also only have a 30% acceptance rate, which is only 10% over their initial attempt with just a prompt.

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