captainclam
Maybe that's the key ingredient that's missing from LLM-generated text. Even when there is actual content there, there's this lack of surprise / uncertainty in its delivery that we require to stay engaged. We may not know what will be communicated, but knowing exactly how it will be communicated just kills our innate interest.
Yeah, it is kinda wild how the infinitude of possibility suddenly makes everything so dull.
Exactly. I am not de-facto against the use of AI in art. But artful use of the medium is sparse at the moment.
God what an annoying thing to say. Suggesting that movies will essentially become games, or that future video games will be unimaginably better (presumably because they are driven by generative world models) betrays such a surface level appreciation for what makes art and culture and all this humanity so beautiful as it is.
The entire point of movies is the deliberate choices of the filmmakers! Movies will not be improved by our ability to choose what the main character looks like or add a style filter. Super Mario 64 is great because it is an expression of the very hardware that constrains it. Inevitable future versions where anything can happen because someone hooked the ROM up to a generative world model won't be better for it.
I agree that this technology is absolutely world changing, and am cautiously eager to see what comes of it, but it just bums me out, perhaps needlessly, that the people at the helm can be so artless, unreflective. Whatever.
And a corollary being that without any time spent on the "mundane", almost every single aspect of the work becomes the genuinely consequential decision-making steps.
Which I find exhausting.
But there is so, so much interesting work and research to do at a much smaller scale. I work on drug discovery models, and none of my work requires data or infrastructure that are not generally accessible to the public (it's nice to have the computing resources of my institution but there are other ways to access a GPU).
So if you are really interested in this stuff, I would suggest looking at the endless supply of interesting problems in domains that are not dominated by huge frontier labs.
In 2031: Why on earth not?
Lots of mathematics entails recognizing that a tool/techniques that works in one area can be adapted to a completely different problem. For a human to do this requires having a robust mental model of the technique and the problem itself, and probably having just the "right" mental model to see how they fit together. And we are talking about extremely hard/sophisticated techniques and extremely hard/sophisticated problems, so the ability to deeply appreciate either can require years of study. And on top of that, even if the mathematician has sufficient understanding to develop the intuition that the technique might work, they will need profound fortitude, skill, and patience to see the solution through.
Unlike human mathematicians, who will develop a deep understanding of only a relative handful of techniques and problems in their lifetime, LLMs have ALL written techniques, problems, solutions, etc stored in their internal representations. So when they ably match a problem to a technique, we can imagine the operation as a supercharged autocomplete, or even an extremely proficient search engine. Their stroke of genius is really a consequence of capacity, moreso than cleverness.
Also Tao's reference to "feeling for" Salieri makes a lot more sense, the audience is clearly supposed to feel for him! That's what makes the scene effective.
And why would I want to see AI humiliate Tao?
I'm sorry if I misunderstood your comment. Thank you for the link, it is useful context.
I will also mention that he maintains a realistic, clear eyed attitude with respect to the inevitability of AI in math, while being sensitive to its disruptive nature in his field. Everything here strikes me as constructing a thoughtful, grounded way forward for his community.
I'm sure there will be missteps along the way, but I think Tao is overall an excellent example of maintaining a balanced position between the poles of absolutism that seem to capture so many.
I am curious where you interpret this as gatekeeping behavior.
But from what I gather, the theme of the statement is to expand the scope of participation to include work that is quite literally the /opposite/ of gatekeeping, i.e. taking proofs that are popularly understood to be opaque or difficult to understand (from any source, AI, human, or otherwise) and developing a new way to communicate them that is more accessible to more people.
I do see how it may come off as a slight to the original mathematicians who developed those proofs. But developing new ways to communicate already established concepts should not diminish the original works. There are probably much better communicators/teachers of relativity than Einstein ever was. No one out there thinks any less of Einstein because of Sean Carrol's "Spacetime and Geometry" textbook.
And this to me reads as only embracing the use of AI in mathematics, which is not gatekeeping behavior. Tao continues to emphasize that once proofs become effectively automatable, deeply comprehending and being able to transmit that understanding to others will become an increasingly important aspect of the field, the natural way for mathematicians to use the time that was once occupied by developing the proofs themselves.
Literally all of this is about expanding the accessibility of mathematics, which once again, I perceive to be quite the opposite of gatekeeping. Maybe we have different definitions of that term.
Also I have not seen Amadeus, so no comment about Salieri.
Really wish he had chosen a different example; this particular bullet point has been making the rounds on X/twitter to paint Tao as an example of some sort of gatekeeping luddite who would deny the world a post-abundance future in order to maintain the prestige of his particular career path...which is tough because I cannot think of a more responsible steward of our inevitable AI future than Tao at the moment.
At that point, why even bother with "driving a CLI"? I have a hard time seeing how this all doesn't go away soon. At the current trajectory, I am not seeing a future where software like Basecamp or Fizzy or the cheapest alternative are competitive with "Claude, build a basecamp-style project management tool for my team."
I don't mean to say that thoughtfully built, opinionated software doesn't have intrinsic value, I believe it will always be "better" in certain aspects...I just can't fathom that a market for it will exist in very short order.
I would LOVE to be talked out of this perspective.
The conversations on consciousness though...oh man. I have to steel myself before diving into that mess.
And I completely agree with your point about touting film as "easier" than digital. That's a stretch.
Reducing people's interest to "social signalling" comes off as dismissive.
Even Sam Altman's "Ghiblified" twitter avatar looks nothing like him (at least to me).
Other models seem much more able to operate directly on the input image.
Unfortunately, the discussion around Mandela effects gets tainted by lots of people being so sure of their memory that the only explanation must be fantastical (the timeline has shifted!), giving the topic a valence of crazy that discourages engagement. I find these mass mis-rememberings fascinating from a psychological perspective, and lacking satisfying explanation (there probably isn't one).
So here we're seeing LLMs "experiencing" the same mandela effect that afflicts so many people, and I sincerely wonder why? The obvious answer is that the training data has lots of discussions about this particular mandela effect, ie people posting online "where is the seahorse emoji"? But those discussions are probably necessarily coupled with language that ascertains 'no, the seahorse emoji does not exist.' That's why the discussion is there in the first place! so why does the model take on the persona of someone that is sure it does exist? Why does it steer the models into such a weird feedback loop?
The department of HUD generates this ~771K figure from a "point-in-time" estimate, a single count from a single night performed in January. They literally have volunteers go out, count the number of homeless people they observe, and report their findings.
It's not hard to imagine why this is probably a significant undercount. There is likely a long tail of people that happened to be in a situation that night where they were not able to be counted (i.e. somewhere secluded, sleeping in a friend's private residence that night, etc).
Even if these numbers are correct, to my mind a "crisis" is still more characterized by the trend than the numbers in absolute. From the first link you provided, we saw a 39% increase in "people in families" experiencing homelessness, and 9% in individuals. A resource from the HUD itself suggests a 33% increase in homelessness from 2020-2024, 18% increase from 2023-2024. That is far apace of the population increase in general.
https://www.huduser.gov/portal/sites/default/files/pdf/2024-...
And even then, I would say many people would suggest that the change in visible homelessness they've experienced in the last 10 years would amount to "crisis" levels, at least relative to the past.
It's completely fair to argue that it is not in fact a crisis, but claiming that it is certainly not "baseless."