[codexon]

Even for coding, it seems to still make A LOT of mistakes.

https://youtu.be/8brENzmq1pE?t=1544

I feel like everyone is counting chickens before they hatch here with all the doomsday predictions and extrapolating LLM capability into infinity.

People that seem to overhype this seem to either be non-technical or are just making landing pages.

[netdevphoenix]

Waiting until the moment they get good enough is not a smart thing to do either. If you are a farmer and know it is going to snow, at some point in the next 5 months, you make plans NOW, you don't wait until the temperatures drop and you see the snow falling. Right now, people are waiting for the snowfall before moving their proverbial chickens indoors

[codexon]

Top AI researchers like Yann LeCunn have said that LLMs are a dead end.

It seems to me that LLM performance is plateuing and not improving exponentially anymore. This recent hubbub about rewriting a worse GCC for $20,000 is another example of overhype and regurgitating training data.

You don't know for sure if it is going to "snow" (AI reaches general intelligence) Snow happens frequently, AI reaching general intelligence has never happened. If it ever happens, 99% of jobs are gone and there is really nothing you can do to prepare for this other than maybe buy guns and ammo, and even that might not do anything to robotic soldiers.

People were worried about AI taking their jobs 60 years ago when perceptrons came out, and anyone who avoided a tech career because of that back then would have lost out majorly.