You’re conflating polarized opinions of very different people and groups.
That being said your antagonism towards investors and wealthy companies is very sound from a foundational standard.
Hinton only gave his excessive worry after he left his job. There is no reason to suspect his motives.
Lecun is the opposite side and believes the danger is in companies hoarding the technology. He is why the open community has gained so much traction.
OpenAI are simultaneously being criticized for putting AI out for public use, as well a for not being open enough about the architecture, or allowing the public to actually have control of the state of AI developments. That being said they are leaning towards more authoritarian control from united governments and groups.
I’m mostly geared towards yann lecun and being more open despite the risks, because there is more risk and harm from hindering development of or privatizing the growth of AI technology.
The reality is that every single direction they try is heavily criticized because the general public has jumped onto a weird AI hate train.
See artists still complaining about adobe AI regardless of the training data, and hating on the open model community despite giving power to the people who don’t want to join the adobe rent system.
Sharklaser@sh.itjust.works 11 months ago
I think you’ve spotted the grift here. AI investment has faltered quickly, so a final pump before the dump. Get the suckers thinking it’s a no-brainer and dump the shitty stock. Business insider caring for humanity lol
Pohl@lemmy.world 11 months ago
Either ML is going to scale in an unpredictable way, or it is a complete dead end when it comes to artificial intelligence. The “godfathers” of ai know it’s a dead end.
Probabilistic computing based on statistical models has value and will be useful. Pretending it is a world changing AI tech was a grift from day 1. The fact that art, that cannot be evaluated objectively, was the first place it appeared commercially should have been the clue.
frezik@midwest.social 11 months ago
ML isn’t a dead end. I mean, if your target is strong AI at human-like intelligence, then maybe, maybe not. If your goal is useful tools for getting shit done, then ML is already a success.
Pohl@lemmy.world 11 months ago
That’s pretty much what I meant. ML has a lot of value, promising that it will deliver artificial intelligence is probably hogwash.
Useful tools? yes. AI? No. But never let the truth get in the way of an investor bonanza.
ricdeh@lemmy.world 11 months ago
That is literally modelling how your and all our brains work, so no, neuromorphic computing / approximate computing is still the way to go. It’s just that neuromorphic computing does not necessarily equal LLMs. Paired with powerful mixed analogue and digital signal chips based on photonics, we will hopefully at some point be able to make neural networks that can scale the simulation of neurons and synapses to a level that is on par or even superior to thr human brain.
Pohl@lemmy.world 11 months ago
A claim that we have a computing model that shares a design with the operation of a biological brain is philosophical and conjecture.
If we had a theory of mind that was complete, it would simply be a matter of counting up the number of transistors required to approximate varying degrees of intelligence. We do not. We have no idea how the computational meat we all possess enables us to translate sensory input into a contiguous sense of self.
It is totally valid to believe that ML computing is a match to the biological model and that it will cross a barrier at some point. But it is a belief that does not support itself with empirical evidence. At least not yet.
Sharklaser@sh.itjust.works 11 months ago
Neural networks have been phenomenal in the results they have achieved, out doing support vector machines, random trees, Markov models etc… But I do wonder if there is a bias towards it being able to mimick what the brain does like the other post said, and where are the limits.
For example in medicine, we want to spot unknown correlations to improve things like drug discovery, stratified medince, strange patterns in disease within a population that suggests unknown factors at play… There might be a mathematical model better that convolutional neural networks that doesn’t mimick the brain, but we maybe need an ai to develop that, maybe like deep thought in hgttg!
SCB@lemmy.world 11 months ago
I love hearing these takes.
“TVs are just a fad. All the good content is on radio!”
“The Internet is just a sandbox for nerds. No normal person will use it.”
“AI is just a grift. It won’t ever be useful.”
Lmao sure Jan.
Sharklaser@sh.itjust.works 11 months ago
AI has been, is and will be very useful, but it’s in an over hype phase poised for a drop. I don’t think you understood what I was saying
SCB@lemmy.world 11 months ago
AI isn’t a stock.