Baris Gultekin: recommendation

Transcript context

…I'm halfway through doing an AMA episode. One of the questions I got was, is fine-tuning really dead? What do you think? So it sounds like you're saying it's not quite dead, but it seems like it's specialized. It's on the decline in your analysis. I wouldn't say it's on the decline. I think it is really well-suited for certain types of things. And maybe the best example is actually what Cursor recently did. At their scale, it does make a lot of sense for them to have a custom model that is doing their autocomplete for instance. So being able to figure out in which situations you need a custom model versus not is something that is evolving. Starting with the large language models makes a lot of sense. And then over time, as you have more and more data and if you have specific needs, if you have either specific needs because of data or because of cost or throughput, that's when specialized models come into picture. You mentioned these partnerships that you have with the Frontier companies. Before getting to that, would you like to shout out or highlight any particular open source models that are your go-tos? We hear a lot about obviously the Chinese ecosystem is like continuing to open source a lot more than the American ecosystem at this point. I don't know if you guys feel Like, comfortable using Chinese models in your stack? I get very different answers on that when I ask that question. But what are the models that you guys go to today when you're like, okay, we're going to explore some new custom direction, either for all of our customers or even just for one customer. What are the handful of models that you go to as starting points to begin that journey?…

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