If we're nearing the top of a sigmoid curve and are given 10-ish years at least to adapt, we probably can. Advancements in applying the AI will continue but we'll also grow a clearer understanding of what current AI can't do.
If we're still at the bottom of the curve and it doesn't slow down, then we're looking at the singularity. Which I would remind people in its original, and generally better, formulation is simply an observation that there comes a point where you can't predict past it at all. ("Rapture of the Nerds" is a very particular possible instance of the unpredictable future, it is not the concept of the "singularity" itself.) Who knows what will happen.
However if we throw enough money and smart people at the problems and get enough value from the early sigmoid curves, the effective impact of a large number of stacked sigmoids could theoretically average to a linear impact, but if the sigmoids stay of a similar magnitude (on average) and appear at a higher velocity over time, you end up with an exponential made up of sigmoids*
* To be fair, it has been so long since I have done math that this may be completely incorrect mathematically - I'm not sure how to model it. However I think in practice more and more sigmoids coming faster and faster with a similar median amplitude is gonna feel very fast to humans very soon - whether or not it's a true exponential.
I'm honestly having a very hard time thinking through the likely implications of what's currently happening over the next 2-10 years. Anyone who has the answers, please do share. I'm assuming from Cynafin that it's a peturbated complex adaptive system so I can just OODA or experiment, sense and respond to what happens - not what I think might happen.
I know this sounds like "the moderate position" to people but you are accepting that something logarithmic is somehow in fact exponential (these are inverse functions of one another) based on no evidence or argument.
Here is Sam Altman, the one man in the world with the most incentive to overstate AI capability, accepting the extremely-well-known logarithmic growth: https://blog.samaltman.com/three-observations
What we see in reality is a basically-linear growth pattern due to pushing exponentially more resources into this logarithm.
I really wish the term hadn't been mangled so much. Though the originator of the term bears a non-trivial amount of the responsibility for it, having written some rather good science fiction on the topic himself. The original meaning from the paper is quite useful and nothing has stepped up to replace it.
All the singularity means as I explicitly used it here is you entirely lose the ability to predict the future. It is relative to who is using it... we are all well past the Caveman Singularity, where no (metaphorical) caveman could possibly predict anything about our world. If we stabilize where we are now I feel like I have at least a grasp on the next ten years. If we continue at this pace I don't. That doesn't mean I believe AI will inevitably do this or that... it means I can't predict anymore, which is really the exact opposite. AI doesn't have to get to "superintelligence" to wreck up predictions.
I guess you are thinking of Vernor Vinge but the term first came up with John von Neumann in the 1950s:
>...on the accelerating progress of technology and changes in human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue
Basically the ability to reason about first and second order effects
IE, before the cellphone was invented you could have predicted the it, things like star trek envisaged a world of portable communication
What impact the cellphone had was predictable to some people, on the one hand increased convenience of communication as well as the end of making a call and wondering who was going to pick up, which was a definite consideration pre-mobile when you called a place and not a person, now we just assume that when we call someone we'll get them and not their family
The second order effects were less obvious, ease of access to someone meant being always accessible, so now everyone could be contacted whenever someone wanted them, it changed the dynamics of life for many, not to mention the effects of different technologies combining, the personal computer and the mobile phone becoming one in the form of the smartphone gave everyone a computer in their pocket, let alone adding the internet into the mix
Each of these changes were completely unpredictable to the people pre-cellphone, once again, compare modern day trek and the originals
I still vividly remember the moment one of the characters in discovery asked the computer to give her a mirror, the same behaviour of countless people now using the fact that their selfie camera functionally gives them a portable mirror in the form of their phone, that was unpredictable
So that's one form of being unable to predict the future
But there's another interesting dynamic I think, which is each direction of technical development is accelerating, which means that we may soon hit the point that only a subject matter expert will be able to predict or perhaps even be aware of what happens in any particular field, so we may get a period where before we can't predict the future, we may have some strange middle ground where we're constantly surprised by the developments we see around ourselves and when we look into it find this new discovery has been around months or years
I certainly have experienced that once or twice, however I'm wondering if that may become the new normal
It's worth noting that after ~50 years[edit: to preempt nitpicking, yes I know we've been using computers productively quite a bit longer than that, but that's roughly the time when the computerized office started to really gain traction across the whole economy in developed countries], we've only extracted a tiny proportion of the hypothetical value of computers, period, as far as benefits to the economy and potential for automation.
I actually think a lot of the real value of LLMs is "just" going to be making accessing a little (only a little!) more of that existing unrealized benefit feasible for the median worker.
My expectation is that we'll also harness only a tiny proportion of the hypothetical value of LLMs. We're just not good enough at organizing work to approach the level of benefit folks think of when they speculate about how transformational these things will be. A big deal? Yes. As big a deal as some suppose? Probably not.
[edit: in positive ways, I mean. I think we're going to see huge boosts in productivity to anti-social enterprises. I'd not want to bet on whether the development of LLMs are going to be net-positive or net-harmful to humanity, not due to the "singularity" or "alignment" or whatever, but because of the sorts of things they're most-useful for]
for example, i am in operations and strategy, but have always wanted to be more technical because i could see the value for many many tasks. however, the learning curve was steep and so learning and doing other things drove better returns for me.
now, LLMs make learning basic concepts and executing simple tasks extremely easy, and i am realizing a higher level of productivity then previously; i used codex to do a test data migration and then evaluate the data quality. i could simply not have done this previously, but it is a meaningful change for me, that i can execute on this.
there is no maintenance burden: i don't have to keep the code alive. it simply sped up an otherwise manual and non repeated task.
i think that's what's so interesting and concerning about this technology: i think power and productivity will flow more broadly across the workforce. this will result in relative winners and losers, and some who will experience no real change at all.
similarly to the costs and benefits of mobile devices diffusing technology access; it changed some things, it created winners and losers and yet our daily lives are recognizable to someone from 50 or even more years ago.
Because they are captives (to a system of incentives that is already "superintelligent" in comparison to any individual) who are hoping for salvation (something to make them free against their will; since it is their will which is captured).
Singularity, then, is the point at which the system itself "finally becomes able to imagine what it is like to be a person", and decides to stop torturing people. IMO, this is unlikely to work out like that.
Not that the singularity has any relevance here, either - except maybe that the robots take over, and the billionaires have missed the boat? I don't know.
Furthermore, regardless of how smart one thing is, it cannot win towards infinite games of poker against 7 billion humans, who as a race are cognitively extremely diverse and adaptive.
AI isn't one thing though. Really its kind of a natural evolution of 'higher order life'. I think that something like a 'organization', (corps, governments, etc) once large enough is at least as alive as a tardigrade. And for the people who are its cells, it is as comprehensible as the tardigrade is to any of its individual cells. So why wouldn't organizations over all of human history eventually 'evolve' a better information processing system than humans making mouth sounds at each other? (writing was really the first step on this). Really if you look at the last 12,000 years of human society as actually being the first 12,000 years of the evolutionary history of 'organizations', it kinda makes a lot of sense. And so much of it was exploring the environment, trying replication strategies, etc. And we have a lot of different organizations now, like an evolutionary explosion, where life finds various niches to exploit.
/schitzoposting
I don't think most are - it tends to regarded as rather cranky stuff, and a lot of people who use the term are a bit cranky.
Even so AI maybe overtaking human intelligence is an interesting thing in human history.
And at the same time, we don't take advantage of the intelligence we already have.
I would say we have certainly seen a bottleneck in the ability of LLMs to handle any kind of broad abstractions or master the architecture of coding. That is the hinge of why "vibe coding" is as trashy of an approach as it is: the LLM can't cut the mustard on any actual software design.
So they have nothing close to the deep understanding required to improve their own substrate.
They can be exceptionally good at understanding what humans mean when they say things, far better than poking keywords into a google search for example, especially when said keywords are noisy and overloaded. And they can be a very good encyclopedic store of concepts (the more general the idea the less likely they hallucinate it, while the details and citations are far more frequently made up on the spot). But they suck at volition, and at state representation (thanks to those limited context windows) which cuts them off at the knees if they ever have to tenaciously search for anything including performing creative problem solving.
We do have AI models which can get somewhere on theorem proving or protein folding or high level competitive game playing, but those only sometimes even glancingly involve LLMs, and are primarily custom-built amalgams of different kinds of neural networks each trained on specific tasks in their fields.
None of that can directly move the needle on actual AI research yet.
The thing that is changing most rapidly, however, is the understanding of how to harness this insanely powerful, versatile, and unpredictable new technology.
Like, those who experimented deeply with LLMs could tell that even if all model development completely froze in 2024, humanity had decades worth of unrealized applications and optimizations to explore. Even with AI recursively accelerating this process of exploration. As a trivial example, way back in 2023 anyone who got broken code from ChatGPT, fed it the error message, and got back working code, knew agents were going to wreck things up very quickly. It wasn't clear that this would look like MD files, Claude Code, skills, GasTown, and YOLO vibe-coding, but those were "mere implementation details."
I'm half-convinced an ulterior goal of these AI companies (other than the lack of a better business model) to give away so many cheap tokens is to encourage experimentation and overcome this "capability overhang."
Given all this, it's very hard to judge where we are on the curve, because there isn't just one curve, there are actually multiple inter-playing curves.
Even using the models we have today, we have revolutionized VFX, video production, and graphics design.
Similarly, many senior software engineers are reporting 2-10x productivity increases.
These tools are some of the most useful tools of my career. I don't even think the general consumer public needs "AI" in their products. If we just create control surfaces for experts to leverage and harness the speed up and shape and control the outcomes, we're going to be in a very good spot.
These alone will have ripple effects throughout the economy and innovation. We've barely begun to tap into the benefits we have already.
We don't even need new models.
But are they making 2-10x compensation compared to before these tools? If not, these tools are not really useful to you, they are useful to your employer. The most shocking thing I find about LLM-assisted development is how gleefully we are just handing all this value over to our employers, simultaneously believing that they are great because we're producing more. Totally bonkers!
You could turn the table and say that you can now launch your own business with far fewer resources.
Who needs financial capital if you can do it all with solo / small team labor capital?
Gossip Goblin ditched his studio and now a16z is trying to throw him money, which he's turned down. He's turning everyone down.
https://www.youtube.com/watch?v=-Rzl7nUdEs4
Dude is legit talented and doesn't need studio capital anymore.
This is the end of the Hollywood nepotism pyramid, where limited production capital was available to only a handful of directors.
We're kind of at the start of a revolution here. I'd be way more worried if I were Disney or Paramount.
Couldn't you take a sabbatical and end it with a brand new SaaS you own and control? That's entirely within reach now.
The people this is going to hurt are the ICs that don't have a go-getting type personality where they take full-stack ownership: marketing, branding, design, customer relationships, etc. If you can do those things, you're going to be a rock star with total autonomy.
You ought to see what the indie game devs are doing with AI (when they aren't getting yelled at on Steam by the haters). It's legitimately incredible. Game designers are taking on full-stack ownership over the entire experience, and they're making some incredible stuff.
I think we're at a similar point with LLMs. The technical stuff is largely "done" - LLMs have closer to 10% than 10x headroom in how much they will technologically improve, we'll find ways to make them more efficient and burn fewer GPU cycles, the cost will come down as more entrants mature.
But the social changes are going to be vast. Expect huge amounts of AI slop and propaganda. Expect white-collar unemployment as execs realize that all their expensive employees can be replaced by an LLM, followed by white-collar business formation as customers realize that product quality went to shit when all the people were laid off. Expect the Internet as we loved it to disappear, if it hasn't already. Expect new products or networks to arise that are less open and so less vulnerable to the propagation of AI slop. Expect changes in the structure of governments. Mass media was a key element in the formation of the modern nation state, mass cheap fake media will likely lead to its fragmentation as any old Joe with a ChatGPT account can put out mass quantities of bullshit. Probably expect war as people compete to own the discourse.
Literally who wondered that? Drives me nuts when people start off an argument with an obvious strawman. I remember the time period of 2005-2007 very well, and I don't remember a single person, at least in tech, thinking the Internet was done. I don't know, maybe some ragebait articles were written about it, but being knee-deep in web tech at that time, I remember the general feeling is that it was pretty obvious there was tons to do. E.g. we didn't necessarily know what form mobile would take, but it was obvious to most folks that the tech was extremely immature and that it would have a huge impact on the Internet as it progressed. That's just one example - social media was still in its nascent stages then so it was obvious there would be a ton of work around that as well.
There is, of course, the Paul Krugman quote from 1998 that by 2005 the Internet would be no more important than a fax machine. [1]
Here's Wired in 2007 saying, in reference to Facebook, "no company in its right mind would give it a $15 billion valuation". [2]
I remember, being at Google in ~2011, we used to laugh at the Wall Street analysts because they would focus on CPC numbers to forecast a valuation, which is important only if the number of clicks is remaining constant. We knew, of course that total Internet usage was still growing quite rapidly and that queries had increased by roughly 4x over the 2009-2013 timeframe.
And a lot of people will say "If you're so smart, why aren't you rich?", and I'll point out that many people who assumed the Internet had lots of room to grow in 2005-2007 did end up very rich. Google stock has increased roughly 20x since 2007 (and 40x from its 2009 lows). Meta is now worth $1.6T, a 100x increase over the $15B valuation that everyone thought was insane in 2007. Amazon is also up about 100x. It would not be possible to take the other side of the trade and make these kind of profits if the majority of people did not think the Internet was largely over.
[1] https://www.snopes.com/fact-check/paul-krugman-internets-eff...
Almost definitely professional ragebaiters in Wired or Time or whatever, yeah.
You also had numerous telecommunications companies going bust in one of the largest sector collapses in modern financial history, the largest bankruptcy in history (at that time) was WorldCom, followed by the second largest bankruptcy in history with Global Crossing... Lucent Technologies went belly up and the largest telecom company at the time Nortel lost 90% of its value, eventually going bankrupt in 2009.
And then of course the great recession hit, tech companies took a massive blow, Microsoft, Google, Intel, Apple and other tech giants lost 50% of their stock value in a matter of months. You don't lose 50% of your value because people think you have a promising future.
It wouldn't be until the explosive rise of smart phones and close to zero percent interest rates that sentiment turned around and tech companies ballooned in value in what would end up being the longest bull run in U.S. history.
>followed by white-collar business formation as customers realize that product quality went to shit when all the people were laid off.
These will be rare boutique affairs. Based on how mass production and cheap shipping played out, most people value price over quality. The economy will rearrange itself around those savings, making boutique products and services expensive.
>mass cheap fake media will likely lead to its fragmentation as any old Joe with a ChatGPT account can put out mass quantities of bullshit.
We have this today. And that's not a "same as it ever was" dismissal. Today, there are a lot of terminally online people posting the equivalent of propaganda (and actual propaganda). Social media pushes hot takes in audiences' faces, a portion of them reshare it, and it spreads exponentially. The only limitation to propaganda today is how much time the audience spends staring at the "correct" content provider.
In managing a large to enterprise sized code base, I experience the opposite. I can guarantee a much more homogenous quality of the code base.
It is the opposite of slop I am seeing. And that at a lower cost.
Today,I literally made a large and complex migration of all of our endpoints. Took ai 30 minutes, including all frontends using these endpoints. Works flawlessly, debt principal down.
I don't doubt it completed the initial coding work in a short time, but the fact that you've equated that with flawless execution is on the concerning-scary spectrum. I can only assume you're talking "compiles-runs-ship it"
The danger is not generating obvious slop, it's accepting decent and convincing outputs as complete and absolving ourselves of responsibility.
This is either a very remarkable or a very frightening statement. You're claiming flawless execution within the same day as the change.
If you're unable to tell us which product this is, can you at least commit to report back in a month as to how well this actually went?
Social media would like a word...
We are in era of pre pentium 4 in AI terms.
A peasant villager was sentient without a single book, film or song. You don’t need this much data to be sentient. They’re using a stupid method, and a better one will be discovered some day.
[1](https://tailstrike.com/database/01-june-2009-air-france-447/)
The poor captain found out I the last 10s what he had been doing but it was too late.
A couple accidents occurred largely due to Airbus averaging conflicting inputs with nothing more than a small warning light when it occurred. I'm pretty sure they would have gotten the Boeing treatment if social media was more entrenched at the time.
> At the same time he made an abrupt nose-up input on the side-stick, an action that was unnecessary and excessive under the circumstances. The aircraft's stall warning sounded briefly twice due to the angle of attack tolerance being exceeded
...
> The crew's lack of response to the stall warning, whether due to a failure to identify the aural warning, to the transience of the stall warnings that could have been considered spurious, to the absence of any visual information that could confirm that the aircraft was approaching stall after losing the characteristic speeds, to confusing stall-related buffet for overspeed-related buffet, to the indications by the flight director that might have confirmed the crew's mistaken view of their actions, or to difficulty in identifying and understanding the implications of the switch to alternate law, which does not protect the angle of attack.
Its a complicated interplay of systems, where autonomous control systems are changing modes and receiving bad information during a complex, raplidly developing situation.
74 times the stall warning blared [1]
Of the 3 pilots in the cockpit, only one thought he had to pull up, see page 31, unfortunately he was one of the ones in control.
>raplidly developing situation.
It was the same situation from when it began to the end, stuck pitot tubes. Though the stall warning only started blaring when the pilot stalled the plane. Bad airspeed indicators don't stall the plane, and are something pilots are supposed to be able to handle, that's why 2 of the 3 were shocked one did the exact opposite in the situation.
It was pilot error. Just look at the report, every finding starts with "the Crew". Planes aren't supposed to crash into the ground just because an air speed sensor failed.
[1] https://bea.aero/uploads/tx_elyextendttnews/annexe.01.en.pdf
My other immediate thought -- Tesla's autopilot. I've never used it so I'm not sure I'm fully correct here, but apparently it requires you to be vigilant and take over in certain situations? Wonder how well that works out in practice.
> If enough people lose their jobs we may be able to mobilize sufficient public enthusiasm for however many trillions of dollars of new tax revenue are required. On the other hand, US income inequality has been generally increasing for 40 years, the top earner pre-tax income shares are nearing their highs from the early 20th century, and Republican opposition to progressive tax policy remains strong.
I think we are in general a highly naive, gullible class of people: we were conditioned, programmed and put into environments where being this was the norm and rewarded. The leaders and those extracting resources, who we gullibly allow to trample over our dignity and our rights, take advantage of this and reinforce it through lobby and influence of the mainstream culture and media campaigns around us. Further, if social media becomes a threat to their statuses, they have been shown to employ their influence there too through censorship and more; we therefore, may be best to learn how to not to be gullible and grow some balls.
[0] https://www.bma.org.uk/news-and-opinion/medical-degree-appre...
Medical doctors are a special case, but eg iron workers theres the official list people get called up from, but you're not getting called up from that list if there's no work. You get work through knowing the right person aka networking. Which is where software engineers find themselves today.
All other engineering (civil, chemistry, mechanical, electrical, ...) and semi-engineering (architecture) disciplines.
Also you forgot the link?
My one ask is people seem to put “CEOs” on a pedestal any time things come up, like they’re an alien life form and oh no they’re going to do something terrible. There are good company executives and shitty ones. You should try to start a company and see if you can be one of the better ones.
I highly recommend reading Marx. Your content has related Marxist topics like the 'Fetishism of Commodities' (Software as Witchcraft) and the Labor Theory of Value.
Might I suggest a viewing of the 2025 film "Bugonia"?
And who are you? An account created for one post? There is a pattern of green account with usernames vaguely related to the subject matter of their comments.
An unintended side effect that I’ve noticed is that it normalizes bad behavior of CEOs for those who invest a lot of “CEOs bad” grist (Reddit, Threads, even Hacker News). When someone, usually early career, takes a job with a bad CEO after years of reading “CEOs bad” content online, they can go into a learned helplessness mode because they think the behavior they’re seeing is normal. They don’t believe changing jobs would help because they’ve learned from social media to believe that their CEO’s bad behavior is actually normal.
This has becoming a frequent topic when in a rotational mentorship program where I volunteer: Early career folk join some toxic startup and stay because the internet told them all CEOs are like this. We have to shake them free from those ideas and get them to realize that there are good and bad companies out there and they have options.
I literally did this 12 years ago based on this reasoning, its good you're trying to counter that with the next generation.
With that said, I do wish there was more discourse around systemic issues rather than the usual finger-pointing towards rival social groups. Unfortunately I feel like our language gets in the way, systems issues are more abstract, but "bad people" are more visceral and easy to talk about.
> We have to shake them free from those ideas and get them to realize that there are good and bad companies out there and they have options.
Not everyone does have options, though. This is why instead of telling people to just avoid the bad CEOs, workers should unionize and collectively bargain against the bad CEOs. I'm sure I'll be seeing a lot of class warfare generalizations about "unions bad" in response to this suggestion.
Mainly because "CEOs and billionaires" have fucked us over time and again, with their with their lobbying and bribing, with their power grabs, with their consolidation of news, entertainment, streaming, and social media properties, with their participation in the millitary industrial complex, with their censorship and partisanship, and with their rent seeking and worsening of their products...
>They don’t believe changing jobs
Um, yea, where did you get these ideas.
Most CEOs want to be CEOs for the potentially vast amounts of wealth they can make from the position. When you're making 20-200x the average person going back to a regular job is pretty much out of the question.
Then when you start making that kind of money you quickly become disconnected from the rest of humanity. [Insert meme: "How much does a banana cost? Like $10 dollars?]
Vast wealth disparity commonly causes the issues that you are saying being normalized by people online, so I think you'd need quite a bit more evidence that is the case then with the already existing hypothesis.
The endless re-rise of Marxism has made people assume that any punching is appropriate in the first place, and it's just a question of who. Saying "these are the people it's okay to punch" is dystopian.
I always struggled with coding before 2023, but i made ends meet and put food on the table and could work sane hours and knew what I needed to do. Logically I should have been happy that I did not have to grind on code — and some days I truly am — but it would yield such poor quality of life at such a high cost was not what I expected...
What I do feel the issue is with I just having to do everything to keep costs down because hiring another dev vs doing it with AI consideration is real and it has collateral damage: I spend more time trying to build AI agents to do the work and there is 1 or 2 fewer jobs I create.
I would encourage folks to look at the following industries: nuclear safety, commercial aviation, remote surgery. These industries have dealt with the issues of automation for much longer than we have as programmers.
In the research I've done, these industries went through a similar journey in the 20th century as we are now: once something becomes automated enough, the old way simply won't work. You have to evolve new frameworks and procedures to deal with it.
So in the case of aviation they developed CRM and SRM - how to manage the airplane as a crew and how to manage it as a solo operator. Remember that modern airplanes are highly automated!! The human pilot is not typically hands-on-wheel for most of the flight.
In the case of surgeons, they found that de-skilling without regular practice can occur in as little as four weeks! So to combat that, some surgeons are now required to practice in simulated environment to keep their skills sharp.
My feeling is that 'aphyr is right in the short-to-medium term. Current market forces and US regulatory posture (or lack thereof) makes it so that there are less rules and less enforcement. IMHO the results are depressingly predictable but the train has left the station with enough momentum that there's no stopping it. If we survive long enough to make it past the medium-term things will change.
Learning to Learn by the late Dr Richard Hamming. See especially Chapter 2.
A point Hamming makes is that when transitions from hand to machine production occurred, usually what is built ends up changing as the old techniques don't transfer 1:1 from the old world.
So for instance, we went from nuts and bolts to rivets and welding (Dr Hamming's literal example). This required builders to produce an equivalent product to the old, built with different techniques - and crucially! - under tighter control limits.
The reason things are going all over the place with AI at the moment is that it's speed, speed, speed. They had an all hands at my company recently where the top brass talked about AI. The only thing mentioned was speed - go faster, do more, etc. Not a single soul talked about quality.
But if you know your software engineering wisdom you know that you can only pick two when it comes to speed, scope, or quality. It's going to get real dumb for a while until people realize/remember quality is how you achieve speed.
I can only guess as to how much content you would have to explore on that axis.
This sort of prompting is only necessary now because LLMs are janky and new. I might have written this in 2025, but now LLMs are capable of saying "wait, that approach clearly isn't working, let's try something else," running the code again, and revising their results.
There's still a little jankiness but I have confidence LLMs will just get better and better at metacognitive tasks.
UPDATE: At this very moment, I'm using a coding agent at work and reading its output. It's saying things like:
> Ah! The command in README.md has specific flags! I ran: <internal command>. Without these flags! I missed that. I should have checked README.md again or remembered it better. The user just viewed it, maybe to remind me or themselves. But let's first see what the background task reported. Maybe it failed because I missed the flags, or passed because the user got access and defaults worked.
AI is already developing better metacognition.
(There may be an argument here re: the move from dense to MoE models, but all research I am aware of suggests that MoE models are not dramatically more efficient than dense models - i.e., active parameter count is not the overriding factor, and total parameter count is still extremely important, though it does seem to roughly follow a power law.)
I recently discovered an example of this phenomenon in a completely unrelated area: navigation. About a week ago, I realized that I couldn't remember the exact turns to reach a certain place I started driving to recently, even after having driven there about 3-4 times over a period of a month. Each time I had used Google Maps. When I used to drive pre-Google-Maps, I would typically develop a good spatial model of a route on my third drive. This skill seems to have atrophied now. Even when I explicitly decide to drive without Google Maps, and make mental notes of the turns, my retention of new routes is now much weaker than it used to be. Thankfully, routes I retained before becoming Google Maps dependent, are still there.
> And so it is that you by reason of your tender regard for the writing that is your offspring have declared the very opposite of its true effect. If men learn this, it will implant forgetfulness in their souls. They will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks.
For example I'm now relying on Soteria, the greek goddess of safety, salvation and preservation from harm to act as my database administrator.
But, thanks to all the companies working on open-weight models, I'm starting to think this might no longer happen. Currently open-weights models are said to be just months behind the top players (and I think we should really try to do what we can to keep it that way).
I'm wondering what the predictions would be in the case where AI becomes very powerfull, but also models are generally available.
Two possibilities come to mind, the first one where all the money no longer spent on employment would go towards hardware. New hardware manufacturers or innovators could jump in and create a bit more employment, but eventually it would probably all progress in one direction, which is the only finite resource in the chain, the materials/minerals needed for the hardware. Those materials might become the new "petrol". It's possible that eventually we would have build enough chips to power all the AI we need without needing more extraction, but I wouldn't underestimate our ability to waste resources when they feel aboundant.
In the second possibility, alongside a very powerful open-weight LLM, there could be big performance advancements, which would make the hardware no longer the bottleneck. But I'm struggling to imagine this scenario, maybe we would all be better off? Maybe we would all just be deppressed because most people won't feel "usefull" to society or their peers anymore?
Now what? How does this benefit the average person who just wants to have a 9-5 job and go home and hang with family / enjoy some hobbies? Not everyone's idea of utopia is "all the code I could ever think of writing at my fingertips 24x7".. I mean, I sometimes code for fun, etc. But I also do other things. I don't WANT to be able to do 25x my current amount of work just because. Imagine if you're sick for 2 weeks - now you're so far behind you'll never catch up?
The older I get, the less I want all the latest tech everywhere. I just want dependable things that work. And ESPECIALLY stuff that isn't spying on me.
If AI can replace anyone who today uses a keyboard/mouse/screen or does something adjacent (for example, teaching) - what's left? If the AI bros are in it for the $$ (many are, I think) - what if a few hundred people in the world had, effectively, all the $$$?
Will I still be able to retire in a few years, or will my $$ be worthless? Will I only be allowed to live/buy food/have medical care if I swear allegiance to one of a few tech overlords?
Some of those super-dev-brand-marketing-everything guys will be able to spin up a business in a weekend - to what end? What products would they sell? They're a prompt away (not man-years) from someone else copying their product - so why would I give you $10 for it? So you effectively have ZERO $$ from software sales. What's the purpose of self-driving cars if no one has $$ to go anywhere?
Do I think we'll get there? I (mostly) don't - but I also don't understand the thinking behind those who DO want to get there at all costs.
But since we are now in this reality I want to try and understand what the future might be, so I can prepare, and maybe if possible also influence it. If I could influence it by trying to limit AI I would, if I can't then at least I would like for the models to be accessible to everyone, to limit the "a few rule the world" scenario.
Yes, AF447 crashed due to lack of training for a specific situation. And yet, air travel is safer than ever.
Yes, that Tesla drove into a wall, and yet robotaxis exist, work well, and are significantly safer than human drivers.
Yes, there are a lot of "witchcraft" approaches to working with AI, but there are also significant accelerations coming out of the field that have nothing to do with AI.
Yes, AI occasionally makes very stupid mistakes - but ones any competent engineer would have guardrails in place against.
And so a lot of the piece spends time arguing strawmen propped up by anecdotes. And that detracts from the deeply necessary discussion kicked off in the second part, on labor shock, capital concentration, and fever dreams of AI.
The problem of AI isn't that it's useless and will disrupt the world. It's that it's already extremely useful - and that's the thing that'll lead to disrupting the world.
Specifically, AI companies want to inflate the utility of AI because that's how they make money. There should be guardrails where appropriate. Unfortunately, as usual, we need to make mistakes before we can learn from them.
Robotaxis do exist, but they are not made equal. Tesla's for instance are 4x worse than humans: https://electrek.co/2026/02/17/tesla-robotaxi-adds-5-more-cr...
I didn't miss that point. I'm saying it's blown out of proportion, and that diminishes the value of the actually important content.
It feels like hexing the technical interview come to real life ;)
Only if you let it. You can own the means of production. I self host my daily driver LLMs in hardware in my garage.
Never given money to an LLM provider and never will. I only do work with tools I own.
I wonder if he self censored here regarding potential futures here as concentration of stupendous wealth in generational hands and obscene wealth disparity coupled with machines that can do what "bodies" can naturally points to depopulation as a goal for the elite and their (future) spawn that are not on the choping blocks.
https://www.theregister.com/2025/02/06/uk_online_safety_act_...
According to the Ofcom regulation checker [1] (linked to by The Register article), the Online Safety Act does not apply to this content.
Here's the most pertinent section (emphasis mine):
> Your online service will be exempt if... Users can only interact with content generated by your business/the provider of the online service. Such interactions include: comments, likes/dislikes, ratings/reviews of your content including using emojis or symbols. For example, this exemption would cover online services where the only content users can upload or share is comments on media articles you have published...
[1]: https://ofcomlive.my.salesforce-sites.com/formentry/Regulati...
It’s only fair that they would receive the same amount. But then how can the former category continue to fulfill their obligations?
They can't. Just like the steel workers who lost their jobs in the 1970's.
Humans are also distinctly bad at noticing certain kinds of bugs in software. Think off-by-one errors, deadlocks, or any sort of bug you've stared at for days and not noticed the one missing or extra semicolon. But LLMs can generate a tsunami of subtly wrong code in the time a reviewer will notice one typo and miss all the rest.
Fruit flies like a banana. Time flies like and arrow.
[1] The movie Arrival is based on this novella.
I believe the technical term is vigilance degradation?
We have to remember that the results of our prompting is a synthesis, formed on the mass psychosis of a humanity which is simultaneously capable of being completely and utterly heinous to each other, and gloriously noble and kind as well - with nought but a stray new word and a thousand old forgotten to keep us all together or not.
In any case, all culture is a lie, which only persists in the re-telling. The past is a lie, too, somehow, someday, forgotten the day nobody remembers it. Hope you make some tunes into the winds and they echo on forever. And by you, I mean, not an AI/ML-based entity, but rather, the source of all lies, the human soul itself.
<h1>Unavailable Due to the UK Online Safety Act</h1>>> You would fire these people, right?
Okay, now imagine a different colleague. One who writes a solid first draft of any boilerplate task in seconds, freeing you to focus on architecture instead of plumbing. A dev who never gets defensive when you rewrite their code, never pushes back out of ego, and never says "that's not my job." A pair programmer who's available at 3 AM on a Sunday when prod is down and you need to think out loud. One who remembers every API you've forgotten, every flag in every CLI tool, every syntax quirk in a language you use twice a year, or even every day.
You'd want that person on your team, right? In fact, you would probably give them a promotion.
Here's the thing: the original argument describes real failure modes, but then commits a subtle sleight of hand. It personifies the tool as a colleague with agency, then condemns it for lacking the judgment that agency implies. But you don't fire a table saw because it doesn't know when to stop cutting, right? You learn where to put your hands.
Every flaw in that list is, at the end of the day, a flaw in the workflow, not the tool. Code with security hazards? That's what reviews are for. And AI-generated code gets reviewed at far higher rates than the human code people have been quietly rubber-stamping for decades. Commits failing tests? Then your CI pipeline should be the gate, not a promise. Deleted your home directory? Then it shouldn't have had the permissions to do that in the first place. In fact, the whole "deleted my home directory" shit is the same thing as "our intern deleted the prod database". We all know that the response to the latter is "why did they have permission to prod in the first place??" AI is the same way, but for some god damn reason people apply totally different standards to it.
Er, just to be clear, I am not personifying these tools. This entire section is a critique of the attempt to frame LLMs as "coworkers".
If I purchased a table saw and that table saw irregularly and unpredictably jumped past its safeties -as we've plenty of evidence that LLMs [0] do-, then I would [1] immediately stop using that saw, return it for a refund, alert the store that they're selling wildly unsafe equipment, and the relevant regulators that a manufacturer is producing and selling wildly unsafe equipment.
[0] ...whether "agentic" or not...
[1] ...after discovering that yes, this is not a defective unit, but this model of saw working as designed...
Scary scenarios like AIs deleting home directories are the result of the developers explicitly bypassing those safeties.
You noticed that I mentioned that this hypothetical table saw has poorly-designed, entirely inadequate safeties? Things like Opus treating the data it presents to the user as commands that it should execute [0] is definitely [1] a sign of solid, well-designed safety mechanisms.
You might choose to retort "Well, that's because the user isn't running the tool in the mode that makes it wait for confirmation before doing anything of consequence!". In reply, I would point in the general direction of the half-squillion studies indicating that a system whose safety requires an operator to remain vigilant when presented with a large volume of irregularly-presented decision points (nearly all of which can be safely answered with a "Yes, do it.") does not make for a safe system. [2] It -in fact- makes for a system that's designed [3] to be unsafe.
You might also choose to retort "That's never happened to me, or anyone that I know about.". Intermittent failures of built-in safeties that happen under unpredictable circumstances are far, far worse than predictable failures that happen under known ones. I hope you understand why.
[0] <https://old.reddit.com/r/ClaudeCode/comments/1sex28q/opus_46...>
[1] ...not...
[2] I would also -somewhat wryly- note that "An AI Agent that does all of your scutwork, but whose every decision you have to carefully scrutinize, because it will irregularly plan to do something irreversibly destructive to something you care about." is not at all the picture that "AI" boosters paint of these tools.
[3] ...whether intentionally or not...
(And before anyone brings pitch forks out, this is what they wrote in a previous article:
> “Cool it already with the semicolons, Kyle.” No. I cut my teeth on Samuel Johnson and you can pry the chandelierious intricacy of nested lists from my phthisic, mouldering hands. I have a professional editor, and she is not here right now, and I am taking this opportunity to revel in unhinged grammatical squalor.
My life was made poorer for knowing that semicolons are apparently a sin, but richer for the rebellion.
There it is, an actual em-dash in the wild, written by hand.
For what it's worth I think it's pretty reasonably good prose, not merely somewhat passable
Read up on Cluster B personality disorders (borderline, narcissism, sociopaths/psychopaths) and you see the similarities. Love bombing, gaslighting, a shared fantasy, etc. It's very interesting and scary at the same time.
That seems very practical and well-reasoned to me.
Welcome to web development buddy
> how ML might change the labor market
Human labor is expensive. If LLMs do make things cheaper and faster to produce, you don't need that many humans anymore. Again, assuming the improvement is real, there absolutely will be shrinkage for existing businesses in headcount. What remains to be seen is how much cheaper machines make work. 1.5x? 2x? 10x? 100x?
> unlike sewing machines or combine harvesters, ML systems seem primed to displace labor across a broad swath of industries [...] The question is what happens when [..] all lose their jobs in the span of a decade
It's more like hand tools -> power tools; a concept applied to many things. Everyone will adopt them, and you'll need fewer workers who'll work faster with less skill. You get a gradual labor force shrinkage, but also an increase in efficiency, so it's not like a hole is opening up in your economy. A strong economy can create new jobs, from either private or public sources.
> ML allows companies to shift spending away from people and into service contracts with companies like Microsoft
The price of hardware, as it always has been, is a downward trend, while the efficiency of open weights is going up (it will plateau eventually but it's still going up). We already spend $20,000 on servers, whether it's buying them once on-prem, or renting them out in AWS. ML is just another piece of software running on another piece of hardware
> if companies are successful in replacing large numbers of people with ML systems, the effect will be to consolidate both money and power in the hands of capital
That ship left port like 30 years ago dude. Laborers have no power in the 21st century.