The problem today is we had 10 years of “learn to code” and a a lot of people did. Similar to 2001. 2009 wasn’t really bad for tech since we had a huge shortage of workers in the space. Companies would hire straight out of mid-tier universities. CS departments were desperate for students.
It’s like all these things though - it’s not a real production worthy product. It’s a super-demo. It looks amazing until you realize there’s many months of work to make it something of quality and value.
I think people are starting to catch on to where we really are right now. Future models will be better but we are entering a trough of dissolution and this attitude will be widespread in a few months.
For years the advantage big tech had was that capital expenditure was minimal and now with every big tech company trying to become an AI company they’re blowing gobs of money on data centers and everything that goes inside of them.
AI is a huge bubble right now and although it is useful and future models will be more so, the truth is that it’s a lot of pie in the sky too.
Probably aren’t seeing the promised productivity improvements of AI in terms of shipping production code and not just “super demos” that aren’t robust. So they want to see if the withers are really putting in the time or if the models struggle past a level of complexity that stalls or reverses early gains.
The funny thing about AI is counterintuitive. It will put an even higher value on quality as quantity is now essentially worthless. I don’t believe AI can generate high quality on its own. It needs to be used and manipulated to generate higher quality outputs than a human or AI alone can.
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