Can the New York Times stop advertising for the AI industry? I am sick of companies trying to launder the actions they and their employees have taken that go in the face of what is socially acceptable. They want to sell the idea that this technology is out of their control and that it will commit great crimes and crimes against humanity unless they build it and control it. I'm calling BS. These companies created this product, they've sold it, they've pushed the frontier forward, and it runs on their hardware. This did not happen accidentally or as a natural consequence of any process. These labs have pushed the ball forward, with great effort, requiring more capital deployed than the world's economy has ever known, knowing all the possible risks, every single step of the way and they continue to do so. And the "well if we don't do it the Chinese will" argument is classic "whataboutery". Americans started this and are continuing to lead it for now. Shifting blame is just another tactic to try to wash their hands. However you feel about the productivity gains of AI as a technology, you have to admit the actions of AI the company is antisocial. And I don't think the benefits are worth the cost.
I feel fine about the Chinese doing it. They have a habit there of handing out sever sentences to CEOs for corruption and self-dealing, and I feel like the possibility of actual negative consequences is more of a check on industry than any number of breathless op-eds.
I just see the extremes. You either see people unable to recreate results and them calling people idiots for claiming those results. Or you see people saying that AI will supersede all other ways to develop and calling anyone who doesn't full embrace AI an idiot. Reality is that nobody knows nothing. There are a million factors that could cause the end result to be anywhere between both extremes. I don't know, you don't know, AI doesn't know, least of all the people inside the AI companies don't know. And really the end result will be extremely nuanced I'm sure.
Well cause I don't really care about the code so much as I care that there's someone or some group maintaining it. You've never looked at the last commit time when you want to include some library in your project? I need proof of some buy-in from someone else. That someone is putting their time on the line. Otherwise I know using that package is gonna cost more time than its worth.
For most yes, but the art of picking the right features that interact in the right way is still a delicate craft. AI is like a sledgehammer. It can demolish technical challenges and it can follow patterns but is still completely blind to the "why".
But yeah the majority of startups don't have well thought out reasoning either. In the end, there's no substitute for hard work. AI can reduce the iteration time maybe.
> the art of picking the right features that interact in the right way is still a delicate craft.
It is.
But after you expend the human-in-the-loop effort to build the right software with the right features using your impeccable judgement, what is going to stop your would-be customer from telling an LLM to analyze your solution and reproduce it feature-for-feature for a few dollars in tokens instead of paying you?
Opportunity cost. AI can help with maintenance but do you want to be on the hook for a service or would you rather pay a monthly fee and have someone else bear the responsibility?
Also most of the software that's really successful has some sort of lock in or network effect. The code is not the only valuable service being provided. To wit, there exist open source off the shelf solutions for hosting your own ridesharing, chat services, social networks, internet search, etc. Why isn't anyone pointing agents at those projects to spruce them up and run them? The network is what's valuable.
I mean we already live in a world where extremely valuable software exists right in the open for free. The actual artifact of code is in abundant supply and does not have a very high price. AI can't bring the price down lower than free.
Sure, there are some network-effect focused bits of software that have such moats, but they are a vanishingly small amount of all produced software and all the ones you mentioned already have locked-in incumbents.
How often does a new Uber/Twitter/Google type of service come around with such a clear moat? How much of a sustainable tech economy is it when you have to be that level of unicorn just to not get LLM-washed away?
The point is that phrases like this can be used to try to stop further analysis. But yeah in every day life? Usually just means, "I have nothing else to say on this". And I kind of reject its always in a negative way, sometimes you just need a way to say "I hear you. I care about you. But I don't have anything else to say and I'm worried that mulling this thing over is causing you even greater distress than the event is worth."
The problem is twofold. One, even a monopoly AI provider wouldn't have pricing power against its suppliers. Its suppliers are energy, semiconductors, and real estate. Semiconductors maybe they could get some leverage on but energy and real estate have plenty of other buyers. Two, there's still no evidence of a runaway scenario (ie a small lead turns into a big lead over time) and there's still no evidence that there's some resource that you can deny everyone else that they can't build your product also. You can't hoard energy, compute, memory, data, human talent, or customers.
The net effect is that the most likely scenario is if one big lab fails, they will likely all fail. Their revenues are all correlated.
To go to your dotcom comparison, the winner will be the ones picking through the assets that were written down by orders of magnitude and trying new products with the technology until one sticks to the wall. But I don't know if a dramatic crash is guaranteed either.
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The problem is twofold. One, even a monopoly AI provider wouldn't have pricing power against its suppliers. Its suppliers are energy, semiconductors, and real estate. Semiconductors maybe they could get some leverage on but energy and real estate have plenty of other buyers.
Concerning the leverage on energy and real estate: don't forget that the AI companies have quite a lot of choice where to build their data centers. So AI companies have lots of opportunities to play several parties off against each other (in particular also for real estate and energy).
"but it can stay there so long as the balance sheet doesn't deteriorate."
Uhm, what? LOL.
People dont value firms based on balance sheets fella. Have you taken a basic valuation class?
Tesla is a nice stock for traders - they like the volatility. Nobody holds Tesla as stock for investing. If you were to truly value it on an intrinsic value basis you'd have to bring in failure risk.
> The act of reverse engineering and porting decades old games to modern environments requires a complex, deeply involved set of tasks from multiple disciplines... It's the quintessential deep, skilled knowledge labor profile out there that people understood as a career protected by depth of skill and knowledge acquisition.
Game development, especially this kind of porting, is an extremely technically demanding task. But it is far more constrained and precise in its requirements than the sort of software development that happens outside of the game world. Most developers deal with vague and (importantly for AI) unverifiable requirements that change continuously as a project develops. AI is not as good of a tool for this type of programming because unlike the tasks demonstrated in the article, there is no verification function an AI can cheaply use to validate if it is approaching completion of the task.
In the example in the article, the bots can look at the entire memory state of the game, interact with it to see how the state changes, and then repeat the process on their working copy of the port. So long as the overall behavior of the port is getting closer to the original, the AI can validate its getting closer to its goals. Extremely impressive stuff. But this verification loop exists in a closed world. No equivalent exists for most programming disciplines. No equivalent can exist because shifting the requirements to fulfill the vague business goals is an essential job of a software developer.
So while I am extremely impressed about what AI can accomplish every day, I also have a loud voice in the back of my mind skeptical of the actual economic impact. Because the market keeps demonstrating that these technically simpler but vague requirement tasks have a lot more value than something like game dev, at least monetarily.
> Because the market keeps demonstrating that these technically simpler but vague requirement tasks have a lot more value than something like game dev, at least monetarily.
Game industry generates hundreds of billions in revenue. There is plenty of value in it. The value happens to not be in decompiling 80s/90s games you have no legal right to sell, of course.
There is more value in remastering old games than you might think. And there always has been. One of my first gigs in the game industry was producing an Infocom Clasics CD-ROM at Activision. That’s games from the seventies and eighties re-released in the nineties.
Was it an issue that Infocom had been shut down? For example for making a version of the Z-Machine for Windows 95 or whatever was current. Did Activision have an archive of all the Infocom development stuff, or were you able to go off of whatever documentation fans had come up with when they were making unofficial Z-Machine interpreters?
Activision bought Infocom. We did have an archive of the Infocom servers which was kind of amazing. I remember notes for an adventure game set on the Titanic. There was a design document for Leather Goddesses of Phobos II.
And I was very happy to purchase BOTH volumes, as a long-time Infocom fan! I still have the discs in storage in a box of old cds in my closet. Of course, now I just have the z-machine files on my computer and run them through Gargoyle...
Once you change the artwork and branding, why is there no legal right to sell? Your defense against cloning are trademark, patent, copyright and trade secret. And the lawyers and money to enforce it and the courts to agree. And if the AI does it, rather than you feeding it copyrighted or trademarked assets, then did you violate copyright or trademark law or did the AI company or does this no longer make sense in a post AI world? The article touches on how current AI services launder copyright and trademark in the 'choose one' section.
> But this verification loop exists in a closed world. No equivalent exists for most programming disciplines.
You can do N-version programming with coding agents and you get tests for free. It is easier to implement something than to test the same thing. This approach turns implementing into automated oracle for testing, takes less time (can implement in parallel), and every divergence between versions is either a bug fix or a requirement clarification. In order to make the N-versions more diverse we can use different model providers, programming language or libraries.
If the main problem is unclear & changing requirements, having 2 different implementations of a system that attempt to implement the vague / changing / missing requirements doesn't seem immediately helpful -- they'll almost certainly disagree, and then you can force one to match the other or so on, and have two implementations of some arbitrary thing.
But none of this "implementing stuff" is making progress to solving the issue of unclear / changing / vague / missing requirements.
You don't try to force them to match. You show a few very different implementations that all satisfy the underspecified the requirements. Not in an antagonistic way, but to help clarify and sharpen the requirements. If any implementation would do, then there's no problem.
But the technology also doesn’t have to be transformative either. I for one am not convinced.
The two things being true may as well be: LLM will not be transformative and the LLM business is mangled in terms of ROIC vs CoC.
In fact given the behavior of AI companies, I actually consider it more likely then not that the effects of the technology is severely over-hyped. I for one do not trust the words of the people who mangle their business in terms of ROIC and CoC. Why should I?
The world looks pretty different today. Even if the model maker companies go out of business (I’m skeptical), the model weights would stick around (many are open freeware already).
I know many software engineers who haven’t written code this year. AI chatbots are regularly used as alternatives to searching manually by many people. Agents are becoming a valuable new enterprise tool, and now consumers tech consumers are hopping on board.
The US spends a bit less than $400B/yr creating software and the worldwide spending is around $675B/yr.
Even if you eliminate 100% of the people involved in creating software, that's still not enough money (and of course, that's not going to happen because someone has to know what to build).
Everyone is adding agents to enterprise stuff, but an overwhelming majority of the general population now hate AI for most things -- especially the "AI support" these companies are using. I think most people would rather suffer through overseas call centers with absolutely terrible representatives than deal with AI support (studies seem to indicate 80+% prefer a human to AI for support in general).
AI as a search engine is useful, but a very different animal. Proficient users want a way to check the AI like Google's AI search does (though the links sometimes don't agree with the summary), but these run very small models (8b or so) with the RAG backend doing the real work.
How many competitors does this space need? Companies can build their own proprietary RAG search engines, but users would almost always prefer the company make that public data available to Google and just use one well-optimized search engine instead of dozens of bad copies.
What about profitability? Google enshittified their search to increase retention and ad time, but AI search should reduce retention/ad time AND costs a lot more money to run too meaning it should lower their bottom line. If that weren't enough, their RAG system is almost certainly more replaceable by users with alternatives than their traditional search system. This seems like all downside for Google.
> The US spends a bit less than $400B/yr creating software and the worldwide spending is around $675B/yr.
The currently well-served market for AI is not software engineering, it's approximately all of white-collar work, ranging from accounting and law, through medicine, general office work, to school administration, education, NGOs and governance.
Not everyone is going to just publicly brag about their AI use, but it's an open secret everyone is either using LLMs for half their work, or - if for some reason they're not busy enough to arrive at this idea on their own - under pressure to start using them.
It is becoming increasingly hard not to see it as transformative. The man hours needed to do my work has been cut down by orders of magnitude. Wether this transformation is wholly a good thing is to be seen.
LLM's are already transformative. I get thinking it isn't going to solve all the world problems, but, companies throughout the entire world are already using it at enormous numbers. Transformative means it changes the world, it already has. It does not mean it changes your life.
By this metric then leaded gasoline and the Deep water horizon oil spill, and Reagan era deregulations were also transformative, so was the Apollo mission, the SETI program and even Eurovision. Arguably Alchemy was also transformative even though it was unsuccessful, because the scientific funding that went into various attempts led into many vital discoveries.
If this the criteria we are using form something being transformative, then being transformative is truly unremarkable in this context, to the point of being a distraction.
If LLMs are "only" transformative in the sense of leaded gasoline or the Apollo mission, that's a massive change all by itself.
If LLMs are "transformative" in the same sense as counting "alchemy because of the scientific funding that went into various attempts led into many vital discoveries", what's going to be our version of "actually we can turn lead into gold now, we just have better things to do with the capability"?
We do have the means today to turn literal lead into literal gold.
The energy is better spent on almost anything else and the gold is radioactive afterwards, but we can do it.
The closest analogy I'd have for vibecoding is combustion engines. Historical antecedent was a toy, early industrial ones took a lot of fuel and were only useful to pump water out of the coal mines that supplied that fuel, but kept getting improved until they made a critical quality leap that took them from "slightly worse than a horse" to "marginally better than a horse" and then there were suddenly a lot of unemployed farriers.
But literal-lead-to-gold took a while longer than that, and a different set of inventions behind it.
Yeah I'm not sure where I stand. It does seem like the industry keeps throwing in new hype cycles just as sentiment is about to turn on the last one. But I also can't deny some results are remarkable.
If agents really are superpowerful at programming tasks why not just have it rewrite the tool that the majority of your customers use and have it recreate the bugs? I mean presumably its the primary force behind the current version so what's the major cost there?
I imagine it comes down to economics.. there isn't much upside to fixing the last 20% of issues that the dumber faster models are missing.
The cost to serve, latency profile ,and internal demand for a maximal intelligence model would probably keep it pointed at harder and more valuable problems most of the time.
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