3 ms·
Given that you need monumental amounts of compute power to come close to something like GPT-4, I don't think the added costs of not treading on people's IP is t
by simiones 3y ago
Given that you need monumental amounts of compute power to come close to something like GPT-4, I don't think the added costs of not treading on people's IP is the major moat that it's being made out to be.
- tavavex 3y agoThe difference here is that compute is always getting cheaper. In 5 or 10 years, it may be feasible to train something GPT-4-sized for a small business. Not to mention that we're likely not at the highest efficiency yet, and there may be undiscovered methods of training better LLMs on lesser hardware. But licensing costs are not going to decrease. If dataset compilation is ruled to be something that needs to be paid for, it'd put a never-changing "must be worth $Xm or more" badge on any small AI company.
- simiones 3y agoI don't agree. Companies seeking to make money from their IP have good reasons to provide different prices for different licensees. Why would the NYT ask Mom&Pop-AI for 100M dollars for their IP just because it wants 100M dollars from OpenAI?