AI one-percenters seizing power forever is the real doomsday scenario, warns AI godfather::The real risk of AI isn’t that it’ll kill you. It’s that a small group of billionaires will control the tech forever.
Business Insider warning about late stage capitalism feels more than a little ironic.
As does being warned of technological oligarchs monopolizing AI by someone who works for fucking Meta.
Not to mention the reason we can all fuck around with llama models despite the fact. Props to yann and other meta AI researchers. Also eager to see future jepa stuff.
If only openAI was so open.
They should rename themselves to Business Balls Deep Insider.
Business Insider is run by college students making minimum wage.
That’s how they got inside.
This is why we need large-scale open-source AI efforts, even if it scares the everliving shit out of me.
Might be one of the key democratizing forces us plebs will have…I do suggest people try out some of the open solutions out there already just to have that skill in their back pockets (e.g. GPT4All).
One Percenters already control most of the planet in every way
Calling anyone the “godfather” or “father” of AI is the stupidest shit.
Longtime expert, prodigy, and one of the greatest minds in the field just isn’t good enough
Unless they say Al instead of AI.
Truer words were never spoken!
At first the fear mongering was about how AI is so good that you’ll be able to replace your entire workforce with it for a fraction of the cost, which would be sooo horrible. Pwease investors pwease oh pwease stop investing in my company uwu
Now they’re straight up saying that the people who invest the most in AI will dominate the world. If tech companies were really all that scared of AI they would be calling for more regulations yet none of these people ever seem to be interested in that at all.
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
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.
Probabilistic computing based on statistical models has value and will be useful. Pretending it is a world changing AI tech was a gift from day 1.
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.
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.
A claim that we have a computing model that shares a design with the operation of a biological brain is philosophical and conjecture
Mathematical actually. See the 1943 McCulloch and Pitts paper for why Neural networks are called such.
We use logic and math to approximate neurons
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!
Hgttg?
42
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.
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
it’s in an over hype phase poised for a drop
AI isn’t a stock.
a final pump before the dump.
This is not how investment capital works.
I understood what you were saying.
You’re conflating polarized opinions of very different people and groups.
That being said your antagonism towards investors and wealthy companies is very sound as a foundation.
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.
I’ve heard some of them are calling for regulation, that favours them.
God I can’t stand these people who are only basically only worried about AI’s affect on the stock market. No normal person would even notice. we have more realistic issues with AI.
Sure AI is going to kill us all, but what about the Dow?!
Raytheon is going to make a killing selling terminators!!! BUY!BUY!BUY!
This is the best summary I could come up with:
He named OpenAI’s Sam Altman, Google DeepMind’s Demis Hassabis, and Anthropic’s Dario Amodei in a lengthy weekend post on X.
“Altman, Hassabis, and Amodei are the ones doing massive corporate lobbying at the moment,” LeCun wrote, referring to these founders’ role in shaping regulatory conversations about AI safety.
That’s significant since, as almost everyone who matters in tech agrees, AI is the biggest development in technology since the microchip or the internet.Altman, Hassabis, and Amodei did not immediately respond to Insider’s request for comment.
Thanks to @RishiSunak & @vonderleyen for realizing that AI xrisk arguments from Turing, Hinton, Bengio, Russell, Altman, Hassabis & Amodei can’t be refuted with snark and corporate lobbying alone.
In March, more than 1,000 tech leaders, including Elon Musk, Altman, Hassabis, and Amodei, signed a letter calling for a minimum six-month pause on AI development.
Those risks include worker exploitation and data theft that generates profit for “a handful of entities,” according to the Distributed AI Research Institute (DAIR).
The original article contains 768 words, the summary contains 163 words. Saved 79%. I’m a bot and I’m open source!
Me running various models that outperform gpt or bard just fine on a 4080: 👌👍
That’s great. Now try training that model on a 4080 and you’ll see it’ll take significantly longer. Try amassing the data needed for training on your home PC and see how much longer beyond that which you’ll need. There’s a reason the current race is down to just a few companies, it costs pennies to run queries on an existing model, millions to build and train that model in the first place.
