The Rise of the AI Engineer
I'm a natural skeptic, and I believe we're still on the rising edge of the "AI" hype cycle.  Five years ago, it was "blockchain", and everyone was trying to ram blockchain into everything, attracting lots of VC and media attention, etc.  It seems that blockchain is beyond the honeymoon phase: I haven't seen an NFT or even a Bitcoin headline in HN for a while.<p>So I'm trying to wrap my head around what an "AI Engineer" is. As I see it, it's all about calling a function that takes some text as an input, and getting some text as output.  That function, of course, is being run on some big hardware that in most cases, you don't own.  So is the "engineering" part of this finessing the input and massaging the output?  Do most "AI Engineers" actually understand what's going on in that function, beyond what they learned in the "LLM 101" videos and articles that have been flooding the web over the past year?<p>While an application developer doesn't need to know all of the ins-and-outs of the underlying operating systems they run on, those developers that <i>do</i> have a deep understanding of the OS are the ones who write more performant code, and can really get to the bottom of issues that arise do to how their code uses the OS. Can the same be said of "AI Engineers"?<p>All of a sudden, everyone's an AI Engineer.  Where where these experts hiding five years ago?<p><a href="https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=blockchain,GPT" rel="nofollow noreferrer">https://trends.google.com/trends/explore?date=today%205-y&ge...</a>