…“Eventually, we need some form of universal basic income for everybody while they work and once they retire,” Roubini added. “We’re already on the way.”…
“We’ll have either ex-post distribution—that is universal basic income—or we’ll have it ex-ante. Ex-ante means some form of socialism,” Roubini explained. “Essentially, the government is going to take over some fraction of the big tech firms.”
He said AI companies are already willing to hand over stakes to the government, alluding to a Financial Times report that said OpenAI has discussed giving 5% as a way for the public to share in the upside of AI.
Altman’s proposal would entail other AI companies providing similar stakes, although it’s not clear if his U.S. rivals would be willing to do so.
As a result, Roubini believes universal basic income or socialism is inevitable, saying “We’re going already in that direction, effectively.”…
…he called it optimistic, given that it assumes 10% growth and “machines doing all the work.”…
Ai doest infer or understand anything
It is just probability formulas.
It can only copy what a human has already done. Only apply it how a human tells it to.
You’re mistaken. It’s a neural network, not so dissimilar from a physical brain - just with simulated, digital synapses instead of biological, physical ones. It is much more than probability formulas. You’re thinking of a Markov Chain, which is completely different from the neural network of modern LLMs. Neural networks are capable of novel generation, outside of what was learned during training. There is no copying involved, at all.
I’m a cognitive neuroscientist and I’m knowledgeable about these “neural networks”. They are in fact , not like the brain.
They are probability models.
The human brain does not use mathematical probability. Nor does it use information the way probability models use it.
The only way that they are like the brain is that both can be visualized like a network of nodes that connect with lines.
“Visualized” . Meaning an artistic representation.
That’s where the similarities end.
They are not capable of novel generation except that can remash existing procedures with other procedures that humans programmed them to do, into infinite combinations.
This is not creation. It’s not innovation.
It’s systematic trial-and-error based on human solutions.
And sometimes after a million iterations, a handful work.
A human wouldn’t have needed to approach the problem like that. We rarely problem solve systematically because it’s inefficient and we are way better at finding solutions through our own methods.
We only use systematic methods in research and then we still use novel problem solving to implement focused systematic methods. We have limited time and funding usually so we have to be smart about it and not do every combination. Also doing big systematic methods increases a type 1 error.
Which AI does a lot of.
I value your time and response, but it doesn’t match my experience. I am a computer scientist, and have created neutral networks. Just because they aren’t structured the same, and have different methodologies, doesn’t mean the similarities end at visual representation. The layered digital neurons allow obfuscation of actual processing, there is no hard coded logic as you seem to imply.
And I don’t know what models you’ve been using, but I get a valid, relevant and insightful response 99% of the time, not once every million attempts. Your assertions do not align with my experiences at all.
Generating something that did not exist before IS creation, and it can be innovative. I don’t know how you can assert otherwise, unless you’ve been using very poor excuses for LLMs. I don’t see trial and error in responses to my prompts,I see thoughtful, intuitive and insightful responses that demonstrate a level of context inference that couldn’t just be random chance.
Perhaps you’re familiar with the structural, mathematical and organizational concepts, and you can differentiate their respective methods of operation, but it seems to me like you have faulty information regarding capabilities and the resulting potential usage of LLM models.
Would you be willing to give me examples of things you’ve attempted that didn’t work until after millions of tries, and which model(s) you were using? You seem confident, so I’m wondering where the mismatch is in our mutually shared, individually observed reality.
Dude. Ai is statistical formulas.
Just because it “feels” insightful does not make it anything more than probabilities.
If you create it yourself, you surely understand this.
Ai is a system designed to mimic.
Don’t be fooled by a mimic.
You give it “life”. You interpret ai as being more than it actually is.
I’m starting to think AI psychosis really is a thing. Way too many people seem to think it’s actually alive. Or has consciousness.
It understands nothing. It only regurgitates.
And when I was talking about trial and error I’m referring to the so-called problem solving AI systems being applied to many things.
I never claimed it was alive. I do think you oversimplify it’s function, though.
Let me provide an example, and you tell me where the misunderstanding exists?
I take a photo of a wall, and tell a model I’d like a recommendation on color to match the existing palette. It responds with a recommendation that won’t clash, but further adds that based on the furniture in the room it suspects the room is used for studying and contemplation. Based on this unprompted observation, it recommends a different specific color, and further adds that the distance to the ceiling is less than standard, so it further recommends incorporating vertical lines into the design to provide the illusion of greater space than is actually available.
I call the additional information insightful, and surmising the purpose of the room based on furnishings, when it was unrelated to the original question, is an example of advanced inference of information. Is it not?
No it’s not an example of advance anything.
It pulls information based on what you, a human asked it to do and it used information commonly found on guides. That a human made.
It’s a glorified search engine.
I didn’t ask it to analyze the purpose of the room, or make a modified recommendation on the determination. It took the initiative to incorporate that information, inferred a conclusion I didn’t provide, and further volunteered helpful information wholly unrelated to the prompt.
Of course humans made the original information. It’s the culmination of all human knowledge! Are you suggesting that to be doing anything at all impressive, it would need to spontaneously learn what dolphins think and know?
A search engine… You’re not even serious. Nevermind. Go back to earning your PhD in psychology and leave us plebians alone.
But it used popular guides online. That a human made.
It didn’t think “oh I should really go above and beyond to make sure this person gets the perfect color”.
It doesn’t have such motivations since it’s a probability formula it instead searches reddit comments and popular websites and uses that information.
These are popular in the first place because they provided good information. Ai doesn’t pull from a reddit post with 10 downvotes. Or a website with little information and even less traffic.
And This is how dead internet works.
The websites ai stole that information from only invested in making such guides to pull traffic to their site which likely sells something.
When these guides no longer pull in traffic to their store because Google just stole their tutorials or guides (without crediting the humans that made them) , stores will stop creating guides, tutorials and the like.
Why would they invest in creating knowledge when AI is just going to steal it?
They won’t.
In a matter of years there will be no new innovation or guidelines made and vetted by humans. Just AI that stole it from AI that stole it from AI …that stole it from a human who wrote it 10 years ago to the point where the guide isn’t even relevant anymore. And AI has added a bunch of made up sounding things at every iteration so it’s now all just nonsense.