TikTok’s parent company, ByteDance, has been secretly using OpenAI’s technology to develop its own competing large language model (LLM). “This practice is generally considered a faux pas in the AI world,” writes The Verge’s Alex Heath. “It’s also in direct violation of OpenAI’s terms of service, which state that its model output can’t be used ‘to develop any artificial intelligence models that compete with our products and services.’”
Training one AI with the output of another AI will just make an even crappier AI.
Ever since that paper about “model decay” this has been a common talking point and it’s greatly misunderstood. Yes, if you just repeatedly cycle content through AI training over and over through successive generations, you get AIs that lose “fidelity.” But that’s not what any actual real world training regimen using synthetic data does. The helper AI is usually used to process input data. For example, if you’re training an AI to respond in a chat-like format, you could take raw non-conversational text (like a book) and have the helper AI create a conversation about that content for the new AI to learn from. Or to take a real-world example, Dalle3 was trained by having a helper AI look at pictures and create detailed text descriptions of them to use as the caption to associate with the image when training.
OpenAI has put these restrictions in its TOS as a way of trying to “pull up the ladder behind them”, preventing rivals from trying to build AIs as good as the ones they have already. Fortunately it’s not going to work. There are already open LLMs that can be used as “helpers” without needing OpenAI at all. ByteDance was likely just being lazy here.
There is actually a whole subsection of AI focused on training one model with the output of another called knowledge distillation.
Works kinda neat with stable Diffusion tho
Depends how it’s done. GAN (Generative Adversarial Network) training works with exactly that, having networks train against each other, each improving the other over time.
I’ve watched Multiplicity enough times to know you get a slightly less functional copy.
She touched my peppy Steve.
That wasn’t a documentary, and it wasn’t about machine learning.
Like photocopying a picture of a terd
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Not necessarily: there have been recent works that indicate that filtering effects of fine tuned LLMs greatly improves the data efficiency (e.g phi-1). Further, if you have e.g. human selection on top of LLM generated content you can get great results as the LLM generation can be used as a soft curriculum, with the human selection biasing towards higher quality.
Sounds like what you’d get if you ordered a ChatGPT off of Wish dot com. Cheap knock-offs that blatantly steal ideas/designs and somewhat work are kinda their thing.
I hope this harms OpenAI in their lawsuits somehow. Their argument of “we can train on the output of others, but nobody can train on our output” has no moral foundation. Pick a lane.
Should change its name to closed ai.
A lot of open source models are trained using data from gpt outputs actually. It’s a cheap way to generate huge training data. The difference is those models are made by independent researchers not backed by a huge company for commercial purpose so OpenAI probably left them alone.
Probably an honest mistake. Who hasn’t bent down to tie their shoe, lost their balance and accidentally coded up a LLM to steal from an existing product? I’d still trust them to plant listening devices, cameras and keyloggers in my pocket since they’ve displayed such a commitment to honesty, integrity and transparency.
Yes, honestly you have also been a subject of a lot of propaganda. The US and the US media are villifying a lot of Chinese companies while American companies are not much better if not worse.
Who hasnt been subject to a lot of propaganda?
This is the mis-information age.
I wonder if that clause is legal. It could be argued that it legitimately protects the capital investment needed to make the model. I’m not sure if that’s true, though.
I can’t speak for every jurisdiction, but I’d be hard pressed to see why it wouldn’t be legal in the US, especially in these circumstances. ByteDance is a massive legally sophisticated corporation, so they should’ve been expected to fully read and understand the terms and conditions before accepting them. They probably won’t bring a legal challenge, because they know they don’t have a particularly strong legal argument or a sympathetic angle to use.
The issue is that what they are doing there is blatantly anticompetitive.
Sorry for the late reply, but this doesn’t really seem like it’d come close to invoking any of the US’s neutered antitrust enforcement. Open AI doesn’t have a monopoly position to abuse, since there are other large firms offering LLMs that see reasonable amounts of usage. This clause amounts more to an effort to stop reverse engineering than stifle anyone trying to build an LLM.
I doubt if it is clear-cut enough to bring down enforcement in any case. However, that does not mean that the clause is enforceable.
It is easy to circumvent such a ban. Eventually, the only option that MS has is suing. Then what?
Why would the clause be unenforceable? It doesn’t violate any of the general principles of contract law. If you intentionally contract around these terms that don’t violate any existing body of law and don’t run counter to public interest, a court would have no problem enforcing the terms of a contract. They probably wouldn’t sue you or me in our individual capacity if we circumvented. There’s a much greater chance of recovery if they go after a company which is pretty clearly using their service in a bad faith. If ByteDance wanted to use their LLM to train their own, they could’ve negotiated such a license.
