This part of the industry is struggling more and more (or more likely silently taking more risks to hide the struggle). It has no path to sustainability and it starts to show.
More in depth look at the launch white paper and the issues covered in the PR. Not much survives scrutiny... there's nothing special with this model.
Indeed, and it's going to get even crazier at some point. I guess somewhat soon but who knows...
One of the dark sides of our industry, and this is is accelerating at a worrying pace. Maybe it's time to look at and fix the whole hardware life cycle?
Stop looking at the shiny toy, remember the ethics behind them...
Almost Half of US Data Centers That Were Supposed to Open This Year Slated to Be Canceled or Delayed
It's getting clearer that the industrial LLM complex will have a hard time meeting its targets.
Excellent piece, it show quite well the problem of skipping the "grunt work". Without it you can't really learn your trade (be it astrophysics or anything else). It also shows how the incentives on scientific careers are wrong. It's not new, but when LLM agents become available, things are definitely changing for the worst.
It feels like it's supercharging an old bias... We tend to confuse confidence for competence.
Real innovations come from constraints. The frugal AI movement is clearly where we will see interesting things emerging. Interestingly, those approaches are closer to what AI is about as a research field than the industrial complex which got unleashed with all its extractive power.
The price hike on RAM due to the LLM as a service bubble is really killing interesting fields. Can't we have nice things? Will the arm race end soon?
Not peer reviewed as far as I can tell. That said if confirmed by other studies this feels like an important paper. The language flattening might be real and this will have lasting cultural impacts.
I personally think this is where it'll head after the bubble pops. We should be able to recover enough material to have something viable to run locally. The question will be "where the updated models come from?", it might be the public sector helping there and hopefully those will be truly FOSS and ethical (like Apertus).
This is concerning, hopefully the amount of issues which get through will be limited.
Very good essay on why the developer profession is not going away. On the contrary we need to double down on essential skills and put in the work. This is long overdue anyway.
One more example that it should be used for NLP tasks, not knowledge related tasks. The model makers are consuming so much data indiscriminately that they can't easily fine comb everything to remove the poisoned information.
The OpenClaw instances running around are really a security hazard...
This planned giant data center by Meta shows how the big players are grabbing land to satisfy their hubris. So much waste all around.
Still a bit mysterious but could be interesting if they really deliver.
I was so waiting for someone motivated enough to publish a review of that paper. I indeed threw it away as weak after reading it. Thanks for taking the time to write this up! This is good scientific inquiry... and it shows there were interesting findings in the paper that the authors decided to just ignore.
Are we on the verge to a push toward a mainframe based future? I really hope not, but for sure the hardware prices surging won't make things easy.