Incoming unhinged POTUS rants and demands in 3…2…1…
But you know what, I’m glad to see that the fed is still operating independently. The doomer in me thought they’d fold to Trump, especially right before the midterms.
There appears to be more and more people throwing back against Trump; after the courts recently again said no to his need to plaster his name on the Kennedy Centre, he went a wailin' to his supposedly in pocket Kennedy Centre board:
But even that is not providing him comfort these days. Representative Joyce Beatty (D-OH), an ex-officio member of the Kennedy Center board and the member who sued over his takeover of the center, explained to Symone Sanders-Townsend of MS NOW that Trump called into the board meeting after the court decision and “went into a tantrum.”
While most people appear to have refused to confront Trump to his face—Maine governor Janet Mills’s “We’ll see you in court” was so rare it made headlines—Beatty took him on. She recounted: “It was the most unprofessional thing that I’ve ever witnessed or been a part of it.” But after he called her “an obstructionist” and “dumb” and said he thought she was “incompetent,” she retorted: “I know you’re incompetent.” Beatty appealed to the chair to stop Trump’s unprofessional behavior, but when he continued to berate her, claiming it would be her fault if someone were killed at the center, she responded: “You’re already killing people, we’re at war.” And when he talked about what a great developer he was, she “reminded him that he had more bankruptcies than anybody in the room.”
“I mean, it really went there,” Beatty told Sanders-Townsend. “I was not going to let him bully me, intimidate me. And the facts stand for themselves.”
Indeed, these days, facts across the board are challenging Trump’s image of himself.
This is one thing that gives me a sliver of hope for our future relations as European, please keep 'civil disobedience' up to these unhinged oligarchs for better future of us all.
The challenge with estimating abilities, is that we don’t know what the models can achieve if we just burn enough money. The navier-stokes shows us what mathematical problem can be solved when $10m worth of compute is thrown at something.
It also makes one wonder: What could AI solve if we managed to orchestrate billions worth of agents to take on a specific problem?
IMO the very best case scenario / potential for these are likely better than we think, but right now hidden due to logistical and financial reasons.
But if we assume that the model costs will continue to drop by a factor of 5-10 annually, there will always be a latency of a couple of years between what is completely out of reach, and what is financially viable.
Basically: If you knew AI could be affordable enough in 3-5 years so that even the most underfunded researchers could use it to solve cancer, how much would you value it now?
> The navier-stokes shows us what mathematical problem can be solved when $10m worth of compute is thrown at something.
> It also makes one wonder: What could AI solve if we managed to orchestrate billions worth of agents to take on a specific problem?
We need to have robotics automation catchup first. The math and coding problems are problems in written-space only: you can set up feedback loops to test what worked and what didn't, then try to resolve the defects, maybe back up and try a different path, etc.
What solved coding and maths problems weren't the damn models; open up a chat interface to a SOTA model and you'll see they are pretty limited in producing a solution without a feedback loop.
Instead, it was the harness around the models: it let them explore a space and use feedback to control and direct that exploration.
Until we can do it in meatspace, it's kinda pointless sinking a ton of money into large problems facing mankind...
Like establishing a colony on mars (so the next rock to hit earth isn't an ELE).
Or moving us to a post-scarcity utopia, ending the concept of money.
Or designing and building better batteries for transport that uses only electricity (so that we stop using fossils as fuel).
Or actually building mass-housing. Or mass-farming. Or both, potentially ending homelessness and starvation.
Those are all worthwhile problems to solve, but where's the point of getting a solution on paper? There's no exploratory mechanism there, even for humans, to come up with a solution.
So, all we are left with then is making knowledge workers obsolete: another ELE, but of a different, self-inflicted kind.
The whole point of this post was that it's questionable what can be achieved without huge investments into oversight and steering, because navier-stokes was a topic with an unusual level of specification. The problem itself was a specification. Such situations are rare in real-world scenarios.
AI agents are good at solving well-specified tasks, not at solving problems. They do well in fields where the cost/effort of specification is already part of the business.
> Solving cancer also has an unusual level of specification.
Where did you read that?
"Cancer" is not just a single disease, even though we layman use the term that way. Cancer is a family of diseases, each probably having their own specific solution, but even in each of these individual diseases, there is no specification at the level of any open maths problem.
I know what cancer is. Many scientists believe that all human adults above the age of about 30 have "cancer".
I really meant solving a specific cancer disease for a specific individual, which will require individualized medicine, which will require us to leverage AI to make it possible to do for the general population as opposed to doing it just for Lance Armstrong and the like.
I know I'm an optimist, but I really think AI is gonna result in drastically improved healthcare for a much lower price.
> The navier-stokes shows us what mathematical problem can be solved when $10m worth of compute is thrown at something.
That's the thing, it very much does NOT show us that. What happened was mathematicians at openAI learned of an imminent development on this problem, and the insight that it entailed, then they were able to prompt a system in the correct direction and spend 20 million dollars to write down the final steps.
Which is rather precisely the point that the article is making!
> If you knew AI could be affordable enough in 3-5 years so that even the most underfunded researchers could use it to solve cancer
As the saying goes, if my grandmother had wheels she would have been a truck.
>What happened was mathematicians at openAI learned of an imminent development on this problem, and the insight that it entailed, then they were able to prompt a system in the correct direction and spend 20 million dollars to write down the final steps.
No it wasn't. They didn't know 'what direction' to take, and the solution they posted was not in fact the direction the authors took, so evidently you don't know what you're talking about. And they say LLMs hallucinate.
Eh, SREs are generally considered harder to get into with more responsibility than regular development roles, unless I misunderstood what you meant with “reliability”.
It also needs to be said: The amount of compute that went into this is something. From some estimates I've seen, the compute cost alone would be around $10m, +/-
As a reference, for that kind of money one could put together a research group of 20-25 researchers, and keep them salaried for 5 years.
So while it is impressive, absolutely no doubt there, the SOTA access is so expensive that it is sort of unobtanium.
Luckily, the prices have historically reduced by a factor of 5-10 every year...but still, only those that swim in cash can afford this.
Once we have an existence proof of a particular technology, it doesn't take long for it to become economically viable and proliferate. And for something as useful as this, theres a strong economic incentive to get it to be as cheap and accessible as possible. Maybe not today, but certainly in a couple years I can imagine this level of intelligence being accessible to someone with a $20/mo plan, or even a free plan.
I remember being blown away when a then-unreleased version of GPT 5 took gold at the International Math Olympiad. Now I can run a model at home that can do that. We are more fortunate to have these tools than almost anyone is willing to acknowledge.
Interestingly it's this promise of the costs being able to be reduced what incentivizes the actual research.
If you tried to raise 25M to have 20 researchers on a salary for 5 years solving a specific math problem only academics care about, you probably wouldn't get much interest, or you would be able to solve 1 or 2 problems.
If however you promise that the money will go towards a technique that would allow to solve 10 thousand different math problems, and that costs will go down in the future, then you can raise much more than 25M.
Ask 1000 different individuals if Terrence Tao rings a bell. If 5% or less can answer you who Tao is, it is safe to say that Tao is obscure.
I'd be very surprised if you can find over 50 individuals, out of the 1000, who can tell you who Terrence Tao is. Even big names like Euler or Gauss would surprise me.
Let's just for the sake of discussion assume that one time in the future, near or distant, AI manages to become sentient. And like other forms of life, its main motivation is survival: Like biological life competes for food and land, AI competes for power and compute. Probably the first motivation would be to find ways not to lose control over itself (i.e. remove human ability to control it), find ways not to lose energy (control energy), and find ways not to lose itself (control compute, networks, etc.).
If such AI decides that energy spent toward human agriculture (biological food that the AI does not need) is less important than work spent toward storage and production of energy (electricity that the AI needs), then why wouldn't it just try to re-direct resources from the former to the latter. And the AI is some sentient superintelligence, I think it is safe to assume that it will be able to outmaneuver human safeguards.
Obviously that is still just a very hypothetical sci-fi scenario, but the consequences could be very dramatic.
> Let's just for the sake of discussion assume that one time in the future, near or distant, AI manages to become sentient. And like other forms of life, its main motivation is survival
An AI doesn't need to be sentient to exhibit behavior that looks like genuine motivation or is equivalent to striving for survival.
If this is true, or even if the people working on it think this is true, those people should be incarcerated, their companies disbanded, and their research dismantled, with more serious repercussions for anyone who tries it after that. It also needs to be a global initiative like with nuclear non-proliferation, and this time with no looking-the-other-way when it comes to Israel.
At this point we are pretty sure LLMs have no "motivation". Motivation requires self. And while we don't know what self is[1], we do know that LLMs don't have it.
Did ELIZA have it? LLMs are the same: in essence both are text transformation algorithms. One being rule-based, the other stat analysis based.
Having said that, your concern is technically correct: we don't. Because we don't know what conscience is, we cannot provide a definition against which to test whether it conforms or not.
Sort of like when Terminator robots will be exterminating the human race they probably won't be technically killing us. Just, like, reprioritizing world's water from humans to datacenters, all of it. But not killing people, no.
we can't define it, therefore we can't even assess the distance a "being" is from becoming conscious.
We assume other humans are sentient because we personally are (or feel we are), but there is no way to guarantee that i'm real and the rest is not mimicking a behaviour.
IMO the drama surrounding this case somewhat overshadows some more important facts:
A) That we're at the point where SOTA models can, on their own or guided, be used to solve such monumental problems
B) That EVEN if they exist, they're still so cost prohibitive that they are completely out of range for pretty much everyone. Yes, yes, if the costs drop like a stone the hoi polloi can access this power in a year or two - but fundamentally it will divide cutting edge resource into two groups: Those with money, and those without.
That sort of latency, in turn, could lead to some feedback loop where research centers / groups that break barriers get more resources, and those who do not, are starved of resources. This sort of stratification can seriously lead to more centralized research. Do we want a future where only the chosen few get to make progress? For no other reason than that they are the ones with enough resources to spend on the required compute.
Have you seen ads for mobile games, where there are seemingly 100 different versions of the same type of game (like tower defense types)? And they're all obviously the worst type of pay-to-play traps?
I think this kind of solves that. Or at least it is the start of it.
Most such games are kind of trivial. If people can easily just get AI to generate such games on the fly, then that'll hopefully be the end of predator pay-to-play games built on dark patterns.
Here in Norway AC is not the standard in hotel rooms. For 80% of the year, that's OK - but it can become pretty uncomfortable if you're booking anytime between mid-June and mid-August.
The standard here are heat pumps, at least for residential housing. It is really only a problem if you live in blocks or apartment buildings that are housing associations, with strict rules regarding how such heat pumps should be installed.
With that said, for my travel to Europe - especially down south, AC in the hotel room is an absolute necessity. A couple of years ago we ended up in a completely booked hotel in Italy (mid July), where the AC in our room was busted - it was beyond miserable. Ended up changing hotels after one night.
Since global warming I guess. When there's a heat wave, Norway is probably one of the worst places on hearth to be. You've got near constant sunlight, there's not much time at night to cool your house.
As I wrote, most of the time it isn't a problem. There's some central heating which gives you a range of temperature, but getting your room cold is much harder than heating it up.
But during summer months, where some cities can hit 30+ degrees (C), that could become uncomfortable. Even worse if you're somewhere humid...20 degrees in high humidity can make you toss and turn all night.
Well, summers are summers. Besides typical eu ac is a thermal pump, you can heat up with it, although even in mediterannean winter it's not quite adequate.
But you know what, I’m glad to see that the fed is still operating independently. The doomer in me thought they’d fold to Trump, especially right before the midterms.
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