Or AI has been over promising and under delivering for half a decade. Amazon is just one of the dominos. This is a hedge by Amazon.
"democratization of information", maybe if you were too lazy to click on a google link
It is tools which are the commons (such as FOSS) and tools such as Wikipedia. But also open standards. LLMs cannibalize on these tools.
Furthermore, no customer wants an AI as customer bot. Especially elder people who are a bit computer illiterate can't find the real support (dark patterns). Can AI help a customer support representative? Oh, absolutely. AI can help a skilled person become better/quicker at certain tasks. But it cannot replace them, and it shouldn't either. If we do, we get all these 'fantastic' tools like *claw.
Like, a normal person is not going to open up an arXiv preprint from Google search because for approximately the entire population, it's going to be way beyond the limits of their comprehension. They won't even glance at the link, if Google even serves it up as a result.
But, with a chatbot, they could actually ask questions and get answers in a format they can understand. They may get a very rough understanding of the topic, but I would bet it's 100 times better than the same reference explained by modern "science journalism," which insists on presenting the most clickbait-y interpretation they can find.
And this is not theoretical, I've seen my high-school level kids figure out undergrad (or higher) level concepts like locality sensitive hashing with the help of ChatGPT, and I know they understood it because they could sketch out working solutions using those concepts. They didn't get the Mathematical underpinnings, but they understood the high-level behavior and that was enough.
Everybody can now understand anything if they really want to. Nobody is doing it today because they don't know it's possible. But they can, and we should encourage them to do so.
Downside is that OpenAI is already having ads on their chat interface, so I guess it will be crap any time soon.
My mother-in-law has a complicated set of medical conditions and sees half a dozen different doctors. Fable with max thinking came up with a bunch of interactions between drugs and conditions that her doctors hadn't considered. We've run its recommendations by one doctor so far and he agreed with everything.
My brother has one friend who used a frontier AI to diagnose his wife's uncommon cancer, and insisted on a test for that. It was correct and she's fine now since they caught it early. Brother has another friend whose wife had back pain after surgery; medical team didn't find what was wrong, he uploaded the scan, and the AI said "oh they left in a staple," which turned out to be correct.
I've started using it to work on a cookbook for the medically prescribed diet I'm on.
Sure it has replaced Google for a lot of people. But was that driven more by Google breaking search and actively ranking down good results and putting blocks in the way of seeing even the bad results?
Google had (have?) people using their service out of habit but built a hostile enough environment. We have this "contradiction" where non-tech folks are supposed to be difficult to move off "what they know" yet here we are where they are using ChatGPT to search and be a doctor.
Unless you're specifically meaning microwave ovens, which are of "limited utility" in a full-service kitchen. I'd have to agree there.
My previous microwave oven was so intensely powerful, that I needed to dial down the power to "7/10" so that it would not destroy my frozen meals. I could never run it at 10/10. My current appliance is very nice, and has an automatic button to run until doneness. Works every time now.
It's the same with AI. The technology is here now. My friends in financial advice and market research have not lost their jobs immediately, because of momentum.
2. greatest hacking tool in history
3. greatest corporate espionage tool in history (stealing of Navier-Stokes solution)
4. greatest accountability transfer tool in history (whoops it was the AI that shot those missiles)
5. greatest capital raising tool in history (we use AI in our startup, and you should give us money)
6. greatest scamming tool in history (cloning people voices for scam calls, etc..)
Edit:Whoops, I didn't read "positively"
- File taxes and find issues that "accredited", "certified" entities missed. In one instance, my federal refund increased by nearly $5k. At $20/mo, just the refund is two decades worth of value.
- Appeal health, home and car insurance claims successfully
- Find out details of interesting plants without forking out tens of dollars for an app that claims to do the same but fails to do so most of the time
- Summarize never ending email threads with 20 disinterested parties who would rather not be on the email but have to respond to show they are "engaged"
- Write a convincing email to my mother in law why I cannot meet her this weekend and hold her hand through the tough times she's having with her ethnic neighbor who annoys her with their "ethnic" music and "smell of fish" BBQ
- Locate the user manual for my microwave and what that rapid 3 beeps every 1s for 2 minutes that starts at 10AM since the last 2 days mean
It's 1987: The PC is underdelivering.
It's 2000: the Internet is underdelivering.
It's 2010: smartphones are underdelivering.
The bottom 2/3 of the human market is entirely dead. Their jobs are gone (AI-shored) they just haven't all gotten the forced retirement or pink slips yet, while they click a few more prompts for a few more pay checks. The frontier pushing forward will knock out most of the remaining top 1/3 without breaking a sweat over the next few years. The really good developers will graduate into babysitting AI as managers.
It is legitimately sad, it's millions of high paying jobs just in the US alone. It's going to be brutal on the housing market. Automation came for another field.
If you have a big mortgage and no savings, it’s going to be tough. Stop taking the Waymo now.
My suggestion to anybody staring this down is: do something for yourself while you can, while we're in the early going. Most people still have no understanding of AI, most tech employees are doing absolutely nothing interesting with it other than prompt prompt prompt prompt while at work and effectively doodling at home.
Go high value and go for the users. Do things that don't scale, that actually rings more true now than ever. Focus on areas of tech where it's really hard to get the users, where you have to practically hand acquire them to get started. Users are the moat.
It's not build the software and they will come. That's what nearly everybody has wrong about what is going on right now. The value is not in the software. Users, users, users, users - they should be your primary focus.
Also consider looking at software more as a layer related to something else you do, not as The Thing you do. Related to another service you offer, improving that service.
Let's say you started consolidating in the physical self-storage space ten years ago. You read that it was a very wide open field, where the market was not yet highly concentrated, 3/4 of the market was mom & pop operators. Over the next ten years you built up a lot of storage locations. LLMs can amplify your business, they can help you automate, layer better software on top of your physical business. You know what LLMs can't do? They can't build storage units, and humans love their storage space. That's just one example out of a zillion out there.
What the hell does this even mean? Literally half of the code in operation I the world is still COBOL. The fuck is this nonsense wiped out
Unless you're making the claim that software engineers aren't involved or that only writing code is software development.
One million software developers will lose their jobs in the US over the next ten years.
The big firing waves will begin when valuations decline as the initial AI boom slows. That has started already, although it's early. Companies like CoreWeave will basically collapse. Investors will demand & reward the layoffs, efficiency push, the end of rah rah times will prompt the inflection on employment in tech. And it'll never be like it was ever again.
For 1 million software engineers in the US to lose their job you'd have to shrink the industry by 62.5% and nobody is doing that. We employ more software engineers this year than last year, which was higher than the year before which was higher than a year before. Get off the social media and look at real statistics and news.
This gleeful nihilism isn't health friend
HN is in denial. Just watch what happens over the next ~36 months.
In all likelihood, massive worldwide recession due to combination of oil issues and debt-ai bubble popping. That will be combined with instability due to democracies cracking up, wars popping up faster and faster all the while the richest and most powerful people are increasingly desperate to destroy democracies before it is too late for them.
software is easier to build -> the world builds more software
But yes, the act of translating spec into code as a 'programmer' is gone for good.
Also remember, the majority of all human software development has been wiped out 18 months ago but the dwindling will keep going by the quarter until the majority of all human software development has been wiped out.
There’s no way this is even remotely true. JavaScript alone is probably 90+%, considering it’s on almost every website.
Remember that all of the code in operation includes code like the microcontroller in your mouse, the hundreds of chips in your car doing things like keeping the engine running or "window goes up when I push the button," the DVD menu (which is actually Java code), not to mention all of the staid systems responsible for things like writing your paycheck every other week.
Even quantized local models like Qwen3.8 are good enough to handle a lot of drudgery. For example, I hooked my wife's computer up to a local model, and now she finally has a clean desktop. She just drops spreadsheets or powerpoints or whatever on her desktop and automation takes care of everything.
The caveat is that I developed software for 30 years, so I understand most of what it produces and can guide it to make fewer mistakes and fix what it can't do. The biggest challenge has been keeping my requirements focused - it's very easy to gold plate everything and prematurely optimize.
The biggest question I ask myself is why am I even still doing this. The smart people are probably already trying to figure out how to pipe raw matter and energy to their homes to build replicators.
The future is already here, it's just not evenly distributed.
You don't want to be in the CD selling or radio business with the Internet & digital & streaming & smartphones & iPods bearing down on you. Go for concerts. Notice that humans are spending more than ever on live concerts. Disney World and Disneyland still command extraordinary pricing power, despite everybody hiding inside on their phones.
LLM clones of eg Photoshop will end up being worthless, like ideas generally. The software will be worthless for the same reason ideas are: they're too easy. Users are hard, software will be (relatively) easy.
Is the value in McDonalds in the food? Everybody knows it's not. McD captured consumers, their heft is extraordinarily difficult to displace. Ie habits, brand awareness, location, etc.
I doubt that. If a clone out there offers all the Photoshop's features for free or much lower cost, without additional learning curve, then many professionals will switch to save money.
McDonalds would be gone too if somebody opened a restaurant chain serving similar food for free or 80% lower price. But that's impossible to do profitably, while freeware software has existed for a long, long time.
The many professionals are the ones that could most easily understand how to switch to GIMP, which is free to use. They could save enormous amounts of money. They prefer to spend money and stick with Photoshop instead. That has persisted for a very long time now.
And in before ‘JumpCrissCross chimes in about inference being profitable while ignoring all the investment costs needed to get inference to where it is.
Before someone else jumps in talking about "unit economics": unit economics only matters if you can sell the units long enough to make the initial (capitalized) investment (i.e., R&D) back. Models aren't commercially viable long enough for the unit economics to work.
I mean, if anything summarizes where we have gotten to as an industry this quote is sure it. From Uber using VC funds to subsidize growth to where the AI players are at...
They have been chasing extreme growth with cheap money. That enabled them to hyper scale at a pace the world has rarely seen before. They have made the correct choice so far.
The absolute dumbest thing they could have done up to this point is slow down to try to turn a profit. They have not needed to. Market capture is the sole thing they should be focused on. Here's a hint: how many users does GPT have now versus three years ago?
There appears to be very widespread confusion about what purpose turning a profit serves and how business operations actually work.
Go back in time and tell Uber in ~2013-2015 that it needs to immediately become profitable and not focus on capturing the market.
Uber has to pay back all the billions of dollars it wasted trying to get people to use their platform, and now I can't afford most Uber or Lyft rides, it's way too expensive. So did market capture really work if they had to raise their prices so much as to make the service unworkable for most people? The only time I take uber is if my company pays for it, and that is getting less often.
AI is also going to have to become way too expensive so they can pay back the billions (trillions?) it is borrowing. And, when everyone is laid-off or fired because AI took their job, then who's going to be paying for AI? I guess the companies that lay off all the humans will, but when the wealthy business owners realize they've replaced everything with AI and nobody is buying what they are selling because there's no more jobs, then what?
Sounds like they should worry about profitability, and a lot of other things too.
Hate to say it, but in this case you’re not the market so you are irrelevant.
Here’s data from Chicago, USA, showing Uber and Lyft dominate the market now, so yes, it worked.
https://toddwschneider.com/dashboards/chicago-taxi-ridehaili...
It feels like a related statement to someone willing to burn their own country to rule over the ashes.
$32b -> $37b -> $44b -> $52b -> $57b
That's Uber's sales growth year by year. And now they're solidly profitable.
The sole threat to Uber is the Waymo / Tesla automation angle. A merger is most likely there.
That's total nonsense. Uber is a luxury, only for people who can afford it.
The price of a given point on the intelligence frontier is only going to get cheaper, likely 10-20x over the next few years.
but profitability is a very narrow view on the labs, and investors are pricing in future free cash flow
you need to take into account the derivative, what is their growth? their opex and capex? their revenue growth? their moat? New product lines and applications?
Not saying that it's a homerun, but there is a case to be made for the labs being wildly profitable in 4-10 years
This isn’t the “hallucinate everything” style of model like the earlier GPT models…
We all feel more productive. But did your rust rewrite or my fancy react dashboard produce more value?
Watch what the open weight models can do. Once they can manage your codebase, you’re safe from gouging.
I am often told humans make mistakes, too. But this is an elementary logical fallacy because the type, frequency and severity of the problems is never the same.
Also, humans are more likely to do as told, whereas AI often takes liberties (i compiled a book from a github repo and it did things on its own in the book though i had explicitly forbidden that).
What exactly will cause that? Hardware costs are (generally) going down, and open weight models are getting smarter. The subsidised subscription prices will go away, sure, but I don't see the average token getting more expensive.
Seriously asking, why would this look like a good business model to be in? If they don't need anyone besides a technical non-developer to create the product, why would this look like a good business? If it's B2B, then most of their customers will have that type of IT person on staff.
So mighty Google can't manage it. But it's a commodity that's easily copied.
Somehow HN can't reconcile the contradiction even though it's laughably obvious.
Hey anybody could go MVP a ride hailing app over the weekend. It's a commodity app. Should be super easy with LLMs.
Oh shit, wait, you mean I'd have to take a billion users away from GPT and getting those users is now 50x harder than it was four years ago? You mean it's drastically harder to peel users away from existing services than if you get to start fresh? Ohhhh.
They have gigantic moats and so long as they don't do anything too stupid, those moats will just get stronger with time.
No VC is giving you money to try to run down OpenAI and Anthropic. Nobody is writing that $100 billion check. It's already over, HN is just in its standard denial phase.
So you could argue their moat is US government, not their model. I don't disagree with you, just saying what is their real moat.
The Chinese models have no great branding with the masses, they have no service layer that any average user understands. Where does Joe go to use the Chinese model that he doesn't even know the name of? Joe has no clue what the difference between DeepSeek and Kimi is, and Joe will never know that.
They all know ChatGPT, they have all been trained on how to use it and what it is. The inertia is enormous and HNers endlessly undercount how that works because deep tech users all want to think the masses view tools like they do and approach tech like they do (which is entirely false).
OpenAI's future is as an ad platform in terms of its business. That's at least 2x-4x larger as a business opportunity than anything they have going on now. Which is to say $80-$160 billion minimum. That requires they maintain the giant userbase, we'll see how that goes. Losing it requires someone take it from them. Joe isn't just going to wake up tomorrow and go seek out how to use Kimi.
The LLM space is worth a minimum of half a trillion dollars per year in ad revenue. It will subsume all of search. Search becomes merely a service of an LLM, which will perform the function on your behalf. Google is on top of that shift, so OpenAI has its work cut out for it competing with Google there.
Of the US big three, Anthropic is by far the one most threatened by the persistence of the Chinese models. Anthropic will probably never stop being chased by them and will have to endlessly race to try to stay ahead. Anthropic has to figure out how to build out the LLM+ equivalent of AWS before China figures out how to beat them, ie build a very deep service / tool moat around Claude that the userbase gets stuck to. In short dramatically increase the difficulty in peeling away users, it has to become a big chore to switch (which eventually this is exactly what someone will figure out in that area of LLM competition).
Turns out there are ways to monetize commodities, to the tune of double-digit billions in revenue per quarter.
Separate question: "now that AI is here and development isn't a moat any more, how does a business defend itself from competition?"
That second question is a direct result of AI. Five years ago the amount of cost and effort spent on software development was a moat. Now it's not. So that answers the first question completely, I think.
As for the second question - market sector knowledge, customer contacts and industry reputation, all the usual non-technical things that make a moat. Also, we may now be living in a world where software companies cannot expect to be monopolies in their markets any more. This company will have to compete with many similar competitors for market share, like in most other markets. I think this is a good thing. Less enshittification will ensue.
I can't think of any, I'm sure there are some, but I would really like to know. I just don't think for most business the software is so much of a moat unless it's very complex.
[0] https://www.afr.com/technology/ai-can-make-free-copies-of-ad...
Value was destroyed.
The hope is that all these unemployed engineers can somehow generate value? Even if they do they need to generate enough value that would employ 4 engineers.
If a business can create software cheaper, then it can charge its customers less for that software (or, conversely, if a business can use an AI to create bespoke software for cheaper than it would cost to buy that software) then the customer business saves money. It, in turn, can use that money to improve its offering to its customers. They, in turn, and so on.
Having cheaper things means everyone gets more things. The value created is created further down the supply chain.
[0] https://en.wikipedia.org/wiki/Parable_of_the_broken_window
Where will people work on if both blue and white collar jobs go away? In brothels?
I loved the article that was on HN a while back (original article here [0] be warned it's a quite a long read). It compared the current revolution we're undergoing to the Mercantilist revolution when we stopped being farm workers and started doing other things instead, driven by technological change in agriculture.
The answer they came up with: we don't know yet. Much like the move from subsistence farmers who started working in a factory had to rely on other people to feed them, we have to answer this question ourselves and it'll probably involve doing something very different. And wonderful - subsistence farming is a shit life (despite all the influencers saying how amazing being in touch with the land is) and we would all prefer to be working in an nice clean office than trudging knee-deep in muck in the rain trying to keep our crops alive and pest-free. The same will probably be true once the dust settles on this revolution and we'll all be profoundly glad that AI came along.
The big problem we have to face as a society is that we cannot allow all the value from this technology to be captured and retained by the wealthy few. Our ancestors had to fight the same conflict with factory owners during the Industrial Revolution, and they didn't manage to win that war completely despite all the blood shed and battles won.
[0] https://contraptions.venkateshrao.com/p/cognitive-mercantili...
For decades, velocity, time to market and features all drove the industry. But AI puts speed in everyone's hands.
But quality is still hard. Maybe harder than ever.
Maybe you could use an AI assistant to help you write better HN comments.
ship fast go-to market features in the blink of an eye when it becomes necessary
Necessary go-to market features are useful
But make no mistake. Being more productive does not equal higher profits because your customers think you've added value. Both value and productivity are highly subjective terms which is why it is measured differently depending on where you work.
Most businesses adapted to AI by shipping a lot more features in smaller increments of time. What they should have done is become much more ambitious and build moon shots in two quarters instead. You need to go big or go home if you're going all in on AI.
i add more value to my company because it lets me ship much faster, debug issues faster, onboard new people faster
total enterprise ai spend is climbing https://ramp.com/data/ai-index#adoption#overall
i know multiple stealth startups with 9 figure revenues and profitable and growing
lab arr is climbing
given the recent crackdown on token spend and from speaking to execs they are very focused on the exact ROI they will get from AI
Note that business revenues in competitive markets may actually not change that much, because if everyone is using the same models there's no competitive advantage from using AI. but if one of them didn't use AI they would fall hopelessly behind
And it's measurable. We don't just feel more productive; we get grants, we build systems, and we make plans we simply couldn't have before.
Advances are still coming rapidly -- we have quite a bit of time before this settles.