It could be the beginning of Neutrino astronomy [1]. So far, we only used the electromagnetic spectrum, from radio waves to gamma rays, to observe the universe. If we could equally leverage neutrinos or gravitational waves, we could observe much more of the universe. For example, the cosmic microwave background radiation enables us to deduce the conditions at 300ky after the Big Bang. The cosmic neutrino background [2] could give us insight in the conditions 1s after the Big Bang.
Similar to the Millennium prize by the Clay institute, the amount of luck and effort you need to receive the prize don't make it worthwhile. Plus, it's generally expected to use that money for further research. It would be advisable to focus on other endeavors, if money is your motivator.
Photons work better for driving a car too but being able to hear is still quite useful.
In other words: we already have lots of things that measure photons. You see things on two totally different media it's a lot more compelling than just one.
That may be the case, but it doesn't explain why neutrinos would be essential for intergalactic communication. Maybe the person I was responding to didn't realize neutrinos travel very close to the speed of light, not infinitely fast?
Kind of contrived, but if you're sending a signal from some other planet to our planet, depending on the geometry, there will be times of the year that our local star is in the way of photons.
Also, if you're sending out photons from a planet, chances are there's a local star nearby. Stars tend to be a broad-spectrum photon source, which is going to make it tough for receivers to decode the intentional signal.
Neutrinos are not an analog to sound in the point you are trying to make. They are many orders of magnitude more weakly interacting and much, much difficult to measure.
No, they can just solve tasks verifiably. Reinforcement learning from verifiable rewards. Pure next-token supervision is only in the pre-training phase for modern LLM agents. They can also define new RL environments and pose new challenges to themselves and train themselves to solve them faster. Yes, at some point some human steering and judgment comes in as to what sorts of tasks to train towards. But there is no obvious taper-off at human level.
In the age of AI, human super-intelligence, is extremely valuable. But yeah, just being intelligent? Not so much.
Just to illustrate, many have complained that big AI labs "buy" startups only because they want to acqui-hire the Stanford/CalTech/MIT PhDs who started it. Then they pretty much $#!t-can the rest of the people who were, to be fair, mostly just run of the mill UTexas/Umichigan/UofwhateverState TF/PyTorch monkeys. But the point is that in the old days, the second tier guys would have made out like bandits as well.
I think that was, kind of, the start of human intelligence becoming a winner take all game. The AI's only need to learn the latest and greatest from one person before they can leverage that value everywhere. And business is not likely to care too much about who that person is. They will care even less about the people who are not that person.
> AIDE demonstrates that recursive self-improvement at the harness layer can produce transferable gains in an AI research agent’s research efficiency. During the recursive self-improvement run, the loop accepted seven rewrites, each under a fixed evaluation budget (section 3.2). Under this fixed evaluation budget, gains in optimization capability on AI R&D tasks translate to gains in research efficiency."
