I think it's a bit more subtle than that. The code of this tool runs in your browser and makes it download the model from huggingface. So it does not host the model or provide it to you, it just does the download on your behalf directly from where the owner of the model put it. The author of this tool is not providing the model to you, just automating the download for you.
Not saying it's not a copyright violation, and IANAL, but it's not a obvious one.
> Besides, can we even attract experienced developers to a non-glamorous industry like logistics?
I wouldn't worry about this. For some devs the industry might matter, but for many code is code, independently if it's for finance, healthcare or logistics. Just make sure salaries are in line with the market.
Internalizing devs will likely produce cost savings long term unless off the shelf tools are good enough for you, but it's an investment that needs long term commitment. Initially you'll still have to pay for your existing product plus the devs, so it'll feel like you just added a cost. Make sure you are committed enough to pass that phase. Your first hires should be able to work independently, talking directly with employees about requirements, without requiring extensive documentation or dedicated PMs before starting. Too much structure initially would be detrimental, you'll probably want to keep the team small anyway.
They are quite well differentiating generative AI models, that are not trained on customer data because they could leak customer data, and other types of AI models (e.g. recommendation systems) that do not work by reproducing content.
The examples in the linked page are quite informative of the use cases that do use customer data.
You and many others here are conflating AI and LLMs. They are not the same thing. LLMs are a type of AI model that produce content, and if trained on customer data would gladly replicate them. However, the TOS explictly say that Generative AI models (=LLMs) are taken off the shelf and not retrained on customer data.
Before LLMs exploded a year and a half ago lots of other AI models had been in place for several years in a lot of systems, handling categorization, search results ranking, etc. As they do not generate text or other content, they cannot leak data. The linked FAQ provides several examples of features based on such models, which are not LLMs: for example, they use customer data to determine a good emoji to suggest for reacting to a message based on the sentiment of the message. An emoji suggestion clearly has no potential of leaking customer data.
well, you need to have something to run that business logic (which includes phoning home to the manufacturer), don't you? Java is as good as any other runtime.
> Periodical reminder that copyright and GPL do not talk about linking.
> At all.
GPLv2 does not, but both LGPL and GPLv3 explicitly mention linking in the license text, so this part of your comment is factually false.
However, it's mostly used as an example; I agree any work with strict dependencies to a GPLed work might be considered a derivative even if the dependency is not expressed by linking.
> We ignore their "we noticed you may benefit from Enterprise, call us today!" spam
Of course if you ignore their offers to talk with the sales team, you won't talk to them. Bigger companies than yours will be interested in their enterprise package and/or will want to negotiate volume discounts.
However, in the case of Meta, if you are a Facebook user they are likely using your likes, friends, any personal information you give them, the content of your posts/comments/private messages to better target your ads. So you, in fact, agree with this ban.
