Searchable transcript of Which AI model should you use?🤖 — IBM Technology (01:07). Search for a phrase, then click its timestamp to jump straight to that moment in the video.
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00:00 And one of the things that's always interesting about cost optimization with models on this is there's kind of two schools of thought where you use the cheaper model and then you go to the bigger one if you need to, or you try a one shot at with the more expensive model. So you save the person's time. And I think both are interesting approaches and I'm not quite sure where we've landed yet.
00:21 Yeah, I mean the first piece is always choice is good. Right. So more model is it's always good, right. It gives folks, uh, choices in terms of which models to pick. And the more the merrier, right. That overall, yes it is. You know, you can view it as a little bit of that commoditization which also drives down the costs initially for the the ecosystem for the industry as a whole.
00:43 Right. So the cost pressures, yes, there are going to be some constraints from the compute like we've talked about before. Right. There are going to be some physical limitations that are— that in the short term will impact certain, you know, ceiling prices. But overall I think, you know, we'll we'll see the the costs go down as the choices become wider.
Use a cheaper model first and escalate when needed for cost efficiency, or use a more expensive model immediately when saving time matters. Broader model choice should reduce costs overall, subject to short-term compute constraints.
The more the merrier.