Nearly all of those can run just fine on-device. I think the part of the bubble that’s ripe to burst is the gigantic gigawatt data centers; we don’t even have the power to run them if all the ones under construction were completed. The current trajectory is not sustainable, and the more contact it has with reality the harder that will be to ignore.
Comment on Is AI Facing a Trough of Disillusionment?
chrash0@lemmy.world 3 days agoi know it’s popular to be very dismissive, but a lot of “AI” has already been integrated into normal workflows. AI autocomplete in development text editors, software keyboards, and question asking bots isn’t going away. text-to-speech, “smart eraser”, subject classification, signal processing kernels like DLSS and frame generation, and so many more will be with us and improving for a long time. Transformers, machine learning optimized chips, and other ML fields are going to be with us for a long time. the comparison to NFTs is either angst or misunderstanding.
absentbird@lemmy.world 2 days ago
jacksilver@lemmy.world 3 days ago
That’s the issue, AI right now means LLMs not deep learning/ML.
The Deep Learning/ML stuff will keep chugging along.
chrash0@lemmy.world 3 days ago
but LLMs do represent a significant technological leap forward. i also share the skepticism that we haven’t “cracked AGI” and that a lot of these products are dumb. i think another comment made a better analogy to the dotcom bubble.
jacksilver@lemmy.world 3 days ago
We definitely haven’t cracked AGI, that’s without a doubt.
But yeah, LLMs are big (I’d say really Transformers were the breakthrough). My point though was that Deep Learning is the underlying technology driving all of this and we certainly haven’t run out of ideas in that space even if LLMs may be hitting a dead end.
CheeseNoodle@lemmy.world 2 days ago
I feel like LLMs didn’t hit a deadend so much as people started trying to use them in completely inappropriate applications.