No Free LL-unch
This video covers some of the emerging tools and platforms for tuning and comparative testing of Large Language Models, including Vellum.ai, Gradio, Lambda Labs and Paperspace. “No Free Lunch” is […]
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A review of six months’ worth of developer posts on the OpenAI Developer Community page shows a range of markups from a low(!!) of 100% to a high of 100x cost.
After exploring how those markups get determined, this video moves on to an even harder problem. As one developer wrote:
“Not trying to limit users tokens, but not trying to be on the hook for tokens used, but not trying to confuse the end user, but trying to explain the relationship between queries, tokens and costs… Man, that’s hard!”
Yes, it is!
This video explores two competing schools of thought about how to handle this: (1) What we’ll call the “cell phone company” approach vs. (2) the “pay-as-you-go” approach. In doing that, we’ll unpack four different trade-offs between those choices.
It turns out that the best way to balance risk and reward between these options might depend, to a very large extent, on the target market itself. In this video, we’ll see why.
But . . . Why is there dance music at the end of the video??
Stay tuned to the end to find out!
This video covers some of the emerging tools and platforms for tuning and comparative testing of Large Language Models, including Vellum.ai, Gradio, Lambda Labs and Paperspace. “No Free Lunch” is […]
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