hn_throwaway_99

This has to be the most "well, akchually..." comment I've read on HN in a long time.

Yes, Huang was targeted, as obviously he knew he would be. But "ie, an investigation of something that happened to him." Are you for real with that one? Perhaps Huang should try that with his wife: "You see honey, the fact that my penis ended up in the vagina of a Chinese spy was just something that happened to me."

Good grief.

> If the scaling continues to hold we'll be asking the AI to do the exploratory research for us soon enough.

Already happening: https://news.ycombinator.com/item?id=50397994

Obviously we'll see how it pans out, but other approaches feel a bit like trying to ignore the bitter lesson.

Sorry for piling on, but it is shorter to just Google "US census bureau percent home ownership 30 year olds" and see that 49.2% number than to state from your personal hunch and no data that this is an "extremely unbelievable figure".

It's not $7k per year, because that's not how investing works. Even given that, for young people who don't have a lot of fixed expenses besides student loans it's not hard at all for people with a professional salary to save that much per year.

The US Census Bureau says 49.2% of adults 30-34 are homeowners in the US, so clearly many people are figuring out how to save and invest.

> Happiness is a pointless goal anyway.

Spoken like a true robot. For most of us, happiness (and I mean that broadly defined, e.g. "life satisfaction") is the only goal. I certainly thing happiness is a much more critical goal than "increasing shareholder value".

> There seems to be this distinctly toxic trait common among math and CS folks where you don't see work as work, like the median worker, but as intrinsically linked to your self-worth and reason for existence.

I don't see this as a toxic trait at all. Some people have the fortune and luxury to do what they love - I don't think that's a bad thing.

I think this quote from Gauss puts it very well: "It is not knowledge, but the act of learning, not possession, but the act of getting there, which grants the greatest enjoyment." So tons of mathematicians feel like AI is stealing this "act of learning which grants the greatest enjoyment", and I think it's fine that they are lamenting this.

This is inherently my whole problem with the "AI utopianists", who somehow think we'll all be happy once we're sitting around with no disease just eating bonbons all day or something.

My favorite example is WebVan vs. Instacart. What a difference a decade makes.

First movers often lose though in the market. Relevant to today's news about DoorDash acquiring Instacart for a few billion dollars: WebVan came out a decade earlier (i.e. at the wrong time) and went bankrupt after 3 years.

A perhaps more relevant personal anecdote: About a year ago I told a non-technical friend that I'd help him migrate his small business website that was originally set up in WordPress (by a developer who is since long gone) to a format that would be much easier for him to manage with no dev support. I planned to move him over to one of the usual suspects like Wix or Squarespace, but this is one instance where my procrastination was a virtue. In the ~9 months since he originally had an issue with his site, AI capabilities had exploded. Turned out it was a lot easier (and cheaper) to use Claude to fully migrate his site and get it up on Cloudflare workers, and I set up everything so he could manage all the content himself. Plus, it took me less than a day to do the migration off WordPress, and most of that time was just me wanting to learn the ins and outs of Claude Code because I was new to it at the time.

> top-most voted answer was most often the wrong answer

I'm calling bullshit on that one. I don't doubt that some top-voted answers were wrong, but the vast majority of the time I used it, the top-voted answer was correct. This just feels like trying to paint with an extremely broad brush. I'm not denying that SO had problems, but there's no way I'm taking "the majority of top answers were wrong" without any evidence.

Not just out of touch, but downright psychopathic in my opinion. I used to greatly admire Larry Page. He seemed like a really smart, driven, level-headed guy. When the news came out that he was basically fine with AI wiping out humanity, as it would just be the natural evolution of intelligence, and to fight against that would be "speciesist", all I good think was "what a psycho".

And I really don't think I'm exaggerating Page's opinion on this, though I'm happy to be corrected if I'm wrong.

Wow, thanks for pointing this out. I'll do a mea culpa then. I was uncomfortable making Google the final arbiter of place names, as I didn't find a good reason why we should trust Google more than the democratically elected government of our country.

But I really like this policy. Even though it still relies on Google's definition of "common usage", it makes naming much less arbitrary and more sensical.

I was wrong in my previous analysis. Google had a clear, sensible, defined, published policy, and they broke it to appease a wannabe autocrat.

I think you're both kind of right. The market is exceptional for the best in a very specific niche of tech.

Yes, people with specific, real AI skills (and by "real" I'm specifically excluding the "let me show you the secrets to a good prompt!!" LinkedInfluencers) are making obscene amounts of money. But there are other folks who were experts in their fields and truly the best are now having a mighty difficult time getting hired. There was a front page HN post recently by a guy who headhunters used to trip over themselves to contact, who wrote a number of programming books, who was considering leaving tech because he couldn't get hired. Now, granted, a big reason he couldn't get hired is because he was looking for a fully remote job and that world is largely gone, but I think another big reason is that he was a technology expert in specific programming languages, and that is exactly the type of expertise that AI is making less valuable.

That may be true in an industry that is growing, but the calculus changes a ton in a shrinking industry, or at least one with a ton of near and long term uncertainty.

I mean, suppose you're a star performer at Microsoft. Consider the following:

1. The FAANGs pay better than just about any corporation on Earth.

2. Most of those FAANGs have also had plenty of layoffs of their own.

3. If you are the caliber of person who works at Microsoft who could get a job at a super hot AI company (say NVidia, OpenAI, Anthropic, etc.) my guess is most of these people already left.

I suspect that most of the people who end up taking this offer have already checked out in some way, i.e. people wanting to quit and now this gives them a reason to do so.

For folks who believe that LLM-based AI only operates with the "convex hull" of its training data, I'm curious how they interpret this result.

To summarize, a lot has been discussed recently about whether LLMs are just really, really good at finding connections between existing information (i.e. the world's smartest and best search engine), or whether they are capable of discovering truly unique, novel ideas. Because many of the very impressive recent AI math results were often just tying together ideas and theories that were already known (and I don't mean to minimize those accomplishments), it was surmised (and, just speaking for myself, hoped) that LLMs operated within this "convex hull", and thus there would always be at least some axis where LLM-based AI wouldn't surpass humans.

Now, this idea of the convex hull of training data is not very clearly defined, and people can and have argued about what it means. But in this case, OpenAI disproved a conjecture that was widely assumed to be true. This was a genuinely surprising result that many experts were shocked by. I'm not a mathematician so I'm not qualified to determine if this was a "truly unique" realization, but a really surprising result seems like it would be a candidate for AI solving a problem in a manner "outside the convex hull".

I mean, in the very short term I could buy that scenario - there are a host of "AI consultants" selling their wares.

But even then, I would only buy that for the very short term, because AI is designed to (eventually) implement that step, too. As an analogy, I always wonder who is paying for these "how to use agentic AI" courses I see pop up all the time now. Literally just ask it! I asked Claude to build a course for me to get comfortable understanding agents and harnesses and it did a fantastic job.

I'll just speak for myself then. The "PC revolution" launched in the 80s. A primary goal of the PC (from a business perspective) was to allow individual workers to do much more by themselves, e.g. in the 60s and 70s you had legions of secretaries and assistants for basically every mid level or higher worker.

It was completely obvious in the 80s, and I say this because I lived it, that you would need tons of people building software and in tech generally as PCs and related tech killed off a slew of those admin assistant jobs.

If you look at Microsoft's total headcount over the past decade, it's really not that outlandish, especially if you combine "over hired during the pandemic" with "end of the ZIRP era". In 2019 employee count was 144k, now it's about 223k.

That said, for the past 3 decades at least, tech was a hugely growing sector that provided ever growing employment opportunities. It seems like that time is now over. Even if you take the "Jevon's paradox view" of AI, that is that the cheaper cost of writing software will feed a demand explosion, it's just hard to imagine that many more people will be needed to fulfill that extra demand.

This is why I think it's fair to think "this time it really is different". In past technological revolutions, it really wasn't that hard to see where the new jobs would come from. Now even the leaders of the AI revolution think it will kill tons of jobs. I get a bit worried about the number of young people and friends' kids who decide to major in "business" in college now. It just feels very difficult to imagine a white collar career that will be stable over the next 10 years or so, let alone an individual's 40 year career.

I was thinking about what a great commentary Toy Story 5 was on this topic. I'm surprised Amazon didn't call their tablet a Lily Pad.

I recently watched Toy Story 5 on a long flight. I almost felt it should come with a trigger warning - I thought it was a spot on, brilliant yet inherently depressing commentary on our current relationship with tech.

(Minor spoiler alert) One of my favorite scenes was when a slew of toys were running through a house with a family inside. Normally in the Toy Story world when a human see the toys they need to "play dead", but since all the humans were glued to their screens they could run by unimpeded.

FWIW, there was a very good recent NY Times opinion piece titled "I Teach at a Business School. It's Time to Shut Them Down." by a professor at the University of Cambridge business school who argues that these schools have solely promulgated this idea of "efficiency" as their primary output to the detriment of society at large. Worth a read if you're interested in the topic.

FWIW, I agree with pretty much everything you've said. But I don't think it's unique to any profession or individual that they tend to care the most deeply when it hits them directly.

The only thing I don't really agree with is where you say "My parents-in-law started their careers as management consultants. The job in their time was much higher prestige and much higher value than it was when I started my career." I still think of management consultants as some of the highest paid careers around, and getting a partnership track job at one of the Big 3 is one of the most desirable jobs (for MBA types anyway) there is, so I just don't know what you're talking about with this one.

> The amount of sympathy programmers are expecting others to feel about their problems has been kicked up a hundredfold now that its their jobs that have been threatened by AI. Their tribe feels pain more deeply than others, I guess.

Well, just wait then, lots of other professions will soon get to realize the same sort of pain, so you'll be able to be similarly dismissive and condescending to them, too.

A lot of people don't realize that the frontier AI companies are so focused on automating software development first because they are all racing to be the first to get to RSI. I don't know if RSI will actually happen, but many, many other professions will soon be in the same boat. Mathematicians have already felt the pain, and those mathematicians who aren't the few who have tenured professorships are certainly not (generally) some of the most coddled professionals.

But lots of folks low on the salary totem pole (copywriters, paralegals, etc.) are already being hit hard by AI and that blast radius will continue to grow.

I wonder if the bloom is coming off the Airbnb rose (probably not, because these kinds of things are always made a big deal of in tech forums but the company in question usually sees their revenue go up and up).

For me personally I only ever use Airbnb's now for big trips with at least 3-4 bedrooms needed. These types of Airbnbs usually have more professional management in any case. But otherwise I think Airbnb just offers a poor value:

1. For a long time Airbnbs skirted hotel taxes and other fees. Those days are long gone, so I often find Airbnbs to be just as expensive or more than hotels when you factor in cleaning and other fees.

2. Like this article points out, quality control and rules can be all over the map, and people are sick of it. With a hotel you usually know what you're getting, with an Airbnb it's always a crapshoot.

3. A huge benefit with a hotel is that if something goes wrong you can almost always be moved to another room, sometimes a different hotel. With Airbnb, while they may help you rebook it's much more fraught and you don't know what the next place will be.

So for me I use hotels for most stays now, though I am curious about house swapping for longer overseas trips. I have friends that have raved about it so it just seems like a better option.

> I think this and many other questionable UI decisions across the industry in recent years is the fallout of the old guard of UI designers having rotated out for younger replacements in the past decade with little transfer of knowledge occurring.

Not sure about that, given that John Gruber specifically lays the blame for a slew of recent shitty Apple design decisions on Alan Dye (cough liquid glass cough), and also the reversal of these shitty design decisions on changes made when Dye jumped ship for Meta. Gruber also says the Apple design team is much happier after Dye's departure.

Dye must be over 50, so I don't count him as a "younger replacement".

The whole irony is that quote is making the exact mistake his post is about: "eat less" is great advice for people where eating less isn't that hard, but it's not helpful advice for people who struggle mightily with eating less and who live in an environment of calorie rich, nutrient poor foods. I've naturally always been skinny, I often find eating a chore. Eating less is incredibly easy for me, but eating right and exercising enough to maintain muscle is the hard part for me.

I mean, we've been telling people "eat less" for literally decades and Americans are fatter than ever. The only thing that finally brought down societal-wide obesity stats was GLP-1s.

I would push back against your pushback and say nearly everyone knows that, it's just the brain is great at making excuses when things are physically difficult.

I'm not sure if it's just the US and Canada, but doctors here (in my experience) are absolutely atrocious and not properly trained when it comes to getting off benzos (but in fairness my experience was from the mid/late 00s).

Many years ago my partner at the time was prescribed Klonopin, primarily as a sleep aid. When he decided to go off it, he talked to his psychiatrist and was given basically no helpful guidance on how to go off. In retrospect I consider that malpractice. It was absolute hell and it took him well over 18 months to finally kick it (and it's not like he had a large prescription in the first place).

One reason I was so pissed is that as he was going off it I did some research and discovered that the NHS in the UK had an entire extensive protocol for people getting off Klonopin that required months of tapering and replacing Klonopin with a less powerful benzo (I think it was diazepam, or Valium) so you could taper at a more gradual pace.

It's insane to me that it's not required for doctors to explain the withdrawal procedures before writing a prescription for any drug that is physically addictive.

Yes, I agree. The reason we highlight truly original, unique bits of genius is that they're so rare. So while I hold on to the idea that there is something humans will still exceed at, the vast, vast majority of things we do obviously aren't of that nature, and AI will vastly change the nature of work and society in the very near future.

FWIW, I totally agree with you, that's why I wrote "Digital recording and powerful search features certainly change the calculus".

But my point was just that it's absolutely not a fait accompli given the current makeup of SCOTUS. Gorsuch' rationale doesn't fit within Kagan's at all and is wholly dependent on the private relationship between Google and the consumer, so that brings it to 5-4, and I could easily see Roberts or Kavanagh (who voted with the majority in Chatrie) finding enough differences between the circumstances in Chatrie compared to Flock to change their vote.

Or no job. I feel like so many people are stuck in the current capabilities of the models they use - what happens if AI ends up surpassing humans in all domains? Not saying that's guaranteed but it's certainly possible, and I feel like so many folks telling optimistic stories about how "AI focuses on the tedious stuff" have not really grasped with the implications of much more advanced AI.

Thanks, looking forward to reading his rationale.

Edit: OK, I found his rationale in the comment section, and I don't find it particularly convincing:

> (1) Einstein and Gödel and Gauss and Shakespeare “merely filled out some points in the convex hulls” of everything that came before them, if you take an expansive enough view of what those convex hulls actually were. What a pathetic piece of cope.

> (2) Dana tells me she now mostly understands the proof of the UGC, and is amazed by the new ideas in it, and wants to give talks about it soon. So, maybe people can listen to that and then lecture her on how it’s “just a point in the convex hull” of the ideas that she’s worked with for 20 years!

First, to just use Einstein as an example, I remember reading many years ago (like at least a decade plus) that many scientists felt like if Einstein had never lived, the theory of special relativity (i.e e=mc^2) likely would have been found pretty quickly in any case - the work had already been done putting the nail in the "luminiferous ether" coffin, and people were starting to connect the dots. I think most people would agree that special relativity was within the "convex hull" that existed at that time. However, I've also heard that general relativity was so far outside the bounds of scientific thought of the time that if Einstein hadn't discovered it that in may have been 50-100 years or more before we figured it out - it was far outside the bounds of the convex hull of that time.

All that said, I'm not a mathematician qualified to determine whether what has been discovered by OpenAI is inside or outside the convex hull, and I do think that the vast majority of human intelligence operates within the convex hull in any case, and what AI can do is hugely, immensely powerful. Still, I'm more inclined to agree with this other commenter on Scott's blog:

> I am a little more in the “convex hull” camp when it comes to AI creativity. In my own interactions on research problems, I find the AI to be singularly uncreative. But these are not math problems.

> From my own introspection, my creative ideas come from a kind of visualization: situating myself in a quasi-physical abstract place that is very difficult to explain. But from there I can simply “see” things by “looking around”.

> This seems to me to be a byproduct of being an embedded agent, not just a prompt-responder. Embedded agents reflect and cogitate using their model of the world. Yann LeCun in particular pushes this as a necessary requirement for true intelligence.

> That said, I don’t agree with LeCun’s claim of necessity. Just as reasoning turned out to be something mysteriously emergent from language in the LLMs, so too could this kind of creative behavior. But I have no idea how.