Shawn Wang: preference

Transcript context

…Well, it's quite interesting for me because I was listening to your podcast explaining the different dimensions of what an AI engineer does, and maybe we haven't called them AI engineers just yet, but we are seeing very healthy interest amongst people in companies that take an enthusiastic approach to try and see how AI can be helpful to their business. They seem to me to fit the bill. They seem to me already, whether they recognize it or not, to be the kind of AI engineers that you have in mind, meaning that they may not have done a PhD, they may not have gotten their degrees in computer science, they may not have themselves used NLP. They may not be steep in this area, but they are acquiring the skills very quickly. They are pivoting. They have the domain knowledge. Correct. It's not even about the pivoting. They might just train from the start, but the point is that they can take a foundation model that is capable of anything and actually fashion it into a useful product at the end of it. Yes. Right? Which is what we all want. Everybody downstairs wants that. Everybody here wants that. They want useful products, not just general capable models. I see the job title. There are some people walking around with their lanyards today, which is kind of cool. I think you have a lot of terms, which are AI creators, AI practitioners. I want to call out that there was this interesting goal to increase the triple the number of AI practitioners, which is part of the national AI strategy from 5,000 to 15,000. But people don't walk around with the title AI practitioners. Absolutely not.…

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