I'm interested to hear what architecture and regulations prevent the use of something that is foundational to web develpment and backwards compatible by design? Which also, by the way, comes with the advantage of not incinerating other parts of the restaurant (accessibility, user experience...), forcing expensive countermeasures or total rebuilds of the things destroyed every time you turn it on.
> I think these authors are making a much stronger claim that AI is proficient or even an expert at software engineering.
The author specifically says:
> I am sure it is not perfect (I only spent an hour working with the results), but a software engineer would iron out the remaining potential bugs that I could not find quickly (which is one reason we may need more, not less, coders in the future, to help with the explosion of new uses for software)
which acknowledges pretty clearly that engineers bring a level of insight and experience still missing from Mythos. Saying that, I totally disagree with his contention that this will always be true. It's pretty weird that the author of an article stressing the steep improvements in a model's capability can't seem to imagine further improvements in that capability. As if Mythos is where development ends or whatever gap remains between models and experts won't steadily narrow or eventually widen in reverse.
GB News has emerged out of the Reform movement, which in turn is the child of UKIP. And there are good grounds to think UKIP was bankrolled in part by Russia. It's covered in part by Carol Cadwallader in the excellent "Sergei and the Westminster Spy Ring". Alexander Udod (A Russian diplomat) seemed to be the handler for senior UKIP figures.
> The question you always have to ask is what problems does it directly solve
Most directly, human labour. Labour is always a problem for capital. At a certain level of AI competence, businesses don't need to pay humans to complete the work they need doing in order to operate. I don't think anyone would dispute AI competence isn't growing steadily.
> Much like for many the point of chess is that it's played by humans, with truly superhuman AI relegated to a training aid
It's much more than just training. Humans use the engines to prepare openings and find promising novelties. Over time these novelties unearthed by engines fill out theory. It's easy to fine elite games where neither player is out of book for dozens of moves. Modern players are full hybrids in that sense. Looking back at chess, it seems natural that Mathematics will go the same way.
> Otherwise it would be like Intel and Microsoft had decided in the year 2000 that computers are "good enough" now and we would have explored what's possible with that hardware ever since.
I think you've misunderstood what good enough means in the context - which is a model capable of completing the tasks assigned to it without having the breadth of full generalization. Your analogy breaks down because of this - we did get 'good enough' spec profiles for different hardware. That thing you're wearing on your wrist won't have the same specifications as the box you use to play games.
I think you've misunderstood the analogy. Just ignore it, analogies mostly break down anyways.
> a model capable of completing the tasks assigned to it
The thing is, the "task assigned to it" is changing with improved capabilities. If everyone around you in 2036 is using general AI to do amazing stuff, you will probably have little interest in vibe coding slop like it's 2026.
They learn between model iterations. You're right, it isn't the same thing as Junior developers' competence improving with experience - the current model's weaknesses are locked in. But it does mean that much of the Junior level thinking and mistakes will be outgrown by successor models.
But they don't retain anything from your on-the-job training. The next model iteration is yet another junior fresh out of college, and knows nothing about the painful training procedures its predecessor put you through.
Yes... but the next session with the same model is yet another junior fresh out of college that knows nothing about the painful lessons the last session put you through ten minutes ago, either.
Nothing prevents an LLM agent from writing a bunch of "notes to self" and using that. And the next model from picking those notes up and using them. Coding agents already do some of that natively.
Hell, we might eventually get an LLM to say "wow the old AI was an incompetent idiot" after reviewing all the notes and session logs. That's how we know we reached human parity!
> All of that said, AI is going to directly cause job loss, I’m calling it now. Not as much as the doomsayers predict, but more than most people expect.
Unless there is some limit to model development we can't currently foresee, plain economics will see to it that white collar job losses will be close to total. Likewise blue collar if we don't find a limit to spatial AI and robotics development.
The problem with all these discussions is that no-one rubbishing the job-apocalypse forecasts can say why or how progress will peter out - beyond pointing to economic limits ("it's a bubble") which won't apply over longer terms. Given the pace of progress the last few years, and this inability to say why job losses won't scale with the tech, anyone ruling them out is either wish thinking, or showing a staggering failure of imagination.
If there's a reason the losses will be "Not as much as the doomsayers predict", say what it is.
The limit to job loss is completely unrelated to AI capabilities. Rather it is social.
There is a breaking point where if enough people end up jobless it will lead to genuine bloody uprisings. I won't pretend to know where exactly that point is, but I am more than happy to state that it is before "nobody has a job anymore" is reached.
I'm sure someone is thinking that job loss needs to be gradual enough that they can get technology to the point of having killer drones ready to take out any individual instantly, before any uprising threshold is crossed. If the abundance of drones keeps rising and surveillance continues toward "total", then we are headed toward this possibility.
Who wants to uprise if it means instant death for the uprisers and everyone they care about?
And if things move gradually enough we are like frogs in boiling water. Think about how if many of the things openly happening today were to happen 50-100 years ago how much resistance there would have been.
The thing about the whole “frogs in boiling water” thing is that it doesn’t work. They’ll jump when it gets too hot.
To counter it with another idiom, consider the concept of having nothing to lose. Remember I’m not claiming it’ll be fun, easy, or anything like that. What I’m saying is that when push comes to shove and enough people genuinely have nothing to lose, it will not be pretty, and I’m not willing to bet on the rich and powerful coming out on top, regardless of how slowly and gradually they try to make it happen.
I think it’ll suck a lot for everyone, and specifically I’d be willing to put money on the rich and powerful wishing they’d had a little more empathy and foresight.
I was thinking this months ago and asked AI what would be done.
IT quickly spit out a half dozen things it expected to be issues and the counter measures that would be deployed instantly and likely proactively.
It showed me videos of things like these 24/7 drones for people detected and less lethal things like soundwaves as deterrents.
It showed me videos of cables hardening and other systems being used to prevent cutting cables and stealing electricity.
Discussed the size of the jails that will be built, an expected number of people that move into a few groups of cybercrime (and which would continue to thrive with that) -
Had numbers of number of people that will be eating mealworms for lunch, the political and cult shifts that will occur, all sorts of interesting things.
I'll be putting out a movie about all this that AI already knows and expects to happen. And this is all with currently known and in use technologies.
Millions will be leaving many cities, and direct to needy from farms systems may keep people alive. Office buildings being converted to mealworm and similar farming may happen.
I do not see the millions of people who make a living via call centers to be able to find similar paying jobs. Most of them, and the people who currently make a living supporting them (sandwich shops, cleaning, etc) - will be competing for delivery jobs, which will depress wages, and they will be competing with robots and x-tunnels, etc.
I need to get a working title for all this info I gathered and come back and edit.
> If there's a reason the losses will be "Not as much as the doomsayers predict", say what it is.
OK, I'll make an attempt:
1. AI capabilities have obviously exploded at an amazing rate over the past few years, but I think most people in the field view a lot of the "Bobby grew a ton by age 13, he'll obviously be 100 feet tall in a few years"-type analysis of a few years ago to be wrong. Or, at least, people see limits to current AI tech, and that completely new/unknown approaches will eventually be needed. Of course, AI never really gets worse, and I can easily see a lot of problems (e.g. hallucination rates) being greatly improved even with just existing tech.
2. I think tons of jobs will get obliterated. I think you'd have to be insane to go into radiology as a med student right now. Tons of people currently make their living driving, and robots can already do a lot of that. More broadly, there are already lots of jobs that are basically "data in, one unambiguously correct answer out" that AI will excel at. Creative jobs will also be affected. I read a report recently about how AI dramas are all the rage in China, and they're already displacing jobs for actors.
3. But I disagree that losses will be "close to total". There will still be a strong desire for humans to actually decide on the "what do we make?", even if it's mostly made by the AI/robots. For a particular depressing and macabre analogy, think of the American South during slavery. Even though most of the actual labor was done by slaves (in the analogous case AI/robots), there were still jobs directing the work to be done.
So I guess I'm in the "it will be a shit show of epic proportions" camp, but that's still not as bad as some of the worst doomsaying I've seen.
3 seems the strongest of these arguments. The 'other techs plateaued' argument ignores that this is the first tech ever to convert electricity into thought and agency. There isn't a precedent for AI, and until intelligence stops scaling with compute, any assumption of a limit - that may not even exist - being reached in the few years left before jobs are wiped out is arbitrary faith.
I agree though, that business leadership roles will still survive - with some industries, wherever some principle or vision needs to be maintained - with the normal little adjustments humans might prefer to feel out for themselves. Perhaps also politicians, sportsmen, escorts, priests, anyone involved in spiritual and new age therapy. But this is still close to total. And aside from ownership/leadership which can earn in power and influence, it isn't clear how any of these jobs would be paid.
Hinton was probably right, even in 2016. When a med student chooses their residency, they want to choose a career that will be around in 40 years. The tech obviously wasn't there in 2016, but it is tantalizingly close today. I have a family member who is a radiologist who works for a group that deploys AI tools as an adjunct, and is was pretty eye opening the first time that tool caught a critical finding he missed.
Interestingly, there is currently a huge shortage of radiologists because the tech (but, more importantly, the regulatory framework) isn't quite there yet, but again people choosing a medical specialty aren't looking at today or a year or two out, they want a career that will sustain them into old age after investing years and hundreds of thousands in training. People are worried at what the landscape will look like in 5 years, let alone 20, 30 or 40.
Job loss can only be measured in relation to time. If it's gradual enough, it's not job "loss" it's job transition.
My point isn't so much about how many jobs will be replaced by AI, but how quickly. In my mind the doomsayers are predicting 30-70% job loss in the next 3-5 years. I'm not saying the job loss won't be that high; I'm saying it won't be that soon. If I had to guess, I'd predict 5-15 years, which won't be a party for anyone, but it's not immediate devastation.
And of course previous job loss situations were supported by other jobs people could migrate to. If this situation doesn't -- if AI swallows a substantial portion of the entire job market -- then eventually it will come down to whether we have an acceptable way to share the abundance that results.
I also think there will be significant displacement and change, but the size of the pie will grow tremendously, and there will be many, many jobs people haven't thought of to address the bottlenecks.
The pace of progress is precisely why many people qualitatively assume the curve will flatten soon: J curves are generally (obviously not always) unsustainable.
You're arguing that the limits will appear because they usually do. (Correct my paraphrase if this is unfair.) Apart from being blind faith, this argument is oblivious to the fact that capability so far has scaled directly with compute and that the experts developing the models expect that to continue.
That is the lowest effort of lame responses. Look at the actual authors on the paper then. Or, I don't know, actually make a substantive comment about the research in the paper beyond your 8th grade redditor "Ha ha Siri sucks" response.
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