Hard numbers, no. Even high level concepts and theory you need to triangulate and prompt in different angles, across different models, and figure out what overlaps to build a mental mode that’s - even then - roughly 80% correct. It’s better than google, but the information isn’t free
Reversing to which direction? Because what I've always seen here is a pretty good mix of positive and negative sentiments. Usually we get a lot of AI related submissions, but with skeptics/opposers in the comments.
I’m not sure. I’ve been reading death-of-the-software engineer for years, but recently the -vibe- feels different. I don’t have anything anecdotal to back it up so take it with a grain of salt. I might be reading what I want to see
I'm assuming it's a turn to the negative and not more positivity you're seeing? Geohot's article and Hasimoto's tweet about AI psychosis kind of made me pay attention.
In my opinion, as AI was oversold for too long, it was was easy to dismiss it. Classical image processing was marketed as “AI”. Doomsday predictions about AI seemed laughable, just as SkyNet in the Terminator seemed unrealistic.
The early ChatGPT versions were also pretty silly and equally oversold.
At this point, the popular messaging of AI is still 90% fiction but the remaining real 10% is now a force to be reckoned with.
Companies laying off Indian call center employees to replace with AI is something I never would have dreamed of.
My experience of using AI as a search engine has surprised me. I never expected an overgrown pile of matrices to work that well.
> My experience of using AI as a search engine has surprised me. I never expected an overgrown pile of matrices to work that well.
The first version of Google was also surprising. Mind blowing use of linear algebra (also a pile of matrices, but this time sparse matrices mostly) to rank websites
So maybe the search business was always meant to use pile of matrices
I think the lack of progress is lack of understanding. If everything is generated and not viewed, does it exist? Like if a tree fell in the forest. Strip the observer and suddenly there is no universe. Strip the engineer and there is no codebase
You can triangulate. Ask it the same thing in different ways and with different LLMs. Operate in domains where the output is verifiable, like in the sciences but in terms of numerical computing. Study the output, graph it, learn it, reason with it, rinse, and repeat until your mental model makes practical sense.
I always wanted to wrangle ~10 of these together and practice distributed computing for the price of ~$200. That was a 2014 dream. I guess instead someone else ran with all of Jensen's polygon drawers and Hynix's backlog. Que sera
Zero 2s can still hit that price, can't they? With much better CPUs than the 2014 dream.
And if you're not worried about CPU you can get a pile of Pi Picos or ESP32s.
Actually, considering that the original zero had a better CPU than 2014 Pis, I'm surprised you didn't get a 10 pack of those when they were extra cheap.
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