I disagree. Google is doing a phenomenal job at capturing use cases at the edge, right where "normie" consumers live. Google's models absolutely suck at coding but if you haven't tried Google Transcribe, you should.
Google has also, far larger distribution and stickiness than Meta.
The title is clickbait. This is important to point out because this, at the minimum, it severely degrades public's perception of how smart, intelligent, qualified the individuals at CYBERCOM are.
I am unaware of who Klippenstein is and whether he's left or right leaning. This article via HN is my first exposure to him, but without any context at all, just by reading the article, I can figure out he's very left leaning.
Why does that matter?
It matters because journalism in 2026 has turned from reporting facts into appealing to a certain spectrum of an audience. It's no longer about providing facts of the matter but about leading an audience to a conclusion that they already had in their minds and re-enforcing it. This is the same echo chamber loop journalists accuse social media of but they are guilty of the very same.
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First, Klippenstein (seems to) imply that it was the Trump administration that began claims of Russian intelligence interference.
Not so. In October 7, 2016 - the Obama administration, via both Department of Homeland Security and Office of the Director of National Intelligence, publicly attributed compromises of political organizations’ emails to the Russian government, connecting the subsequent disclosures to Russian-directed efforts. This was a government intelligence attribution and not merely a statement from the Democratic Party or Clinton campaign
Next, Klippenstein (seems to) imply that CYBERCOM is running the show here. That's not how INT works - CYBERCOM complements, and doesn't replaces FBI/DHS, while CIA is itself foreign focused. CYBERCOM’s role also includes disrupting foreign cyber operations, not just merely investigating them.
Now a very noble interpretation of Klippenstein is he's describing a bipartisan willingness to restrict speech in the name of election security - that his central objection is to the government’s intervention in political expression, not exclusively to which party controls it.
This is a fair argument but if there's foreign intelligence interference, that brainwashes the American public, making them draw conclusions that are factually invalid, whose responsibility is to atleast point that out?
The DoW has, at its disposal, incredibly advanced intelligence dissemination tools (as a requirement for INT operations) that are a great fit for this usecase. Should not the American public, who pay for all of it, not make use of it?
bias does not imply incorrect or factually inaccurate. "trump assassinated world leaders and triggered a full blown war in iran" is not bias. its factually accurate. That it breaks with someones worldview is not bias. And we need to stop pretending that adhering to objectivity is "bias".
By that definition, all medical science is "biased". And until the current administration, it wasnt. Requiring people making claims to demonstrate it with repeatable methods is not "bias".
If the claims in the article are true, military assets are taking direct action, not merely backing up domestic law enforcement.
>whose responsibility is to at least point that out?
Not the military. I agree that work needs done but when you dance close to taking down sites or possibly removing actual human Americans' posts surreptitiously, it should be done with civilian mechanisms and with oversight.
> I'm not sure what happened in recent years, but they definitely switched their strategy to maximize data collection and make sure privacy-savy users are pressured via technical solutions to reveal their identities.
Every scammer, fraudster, scammer-in-training, fraudster-in-training, uses a Google account.
The first company federal investigators often go for data is often Google because that's the start of their lead into their investigation. Google needs to provide answers, sometimes by regulation in countries.
Elsewhere on this page I argued how this reminds me of the PC wars of the mid 90s.
We are all overreacting over a nascent industry, upset that it's increasing prices for everyone and pushing humans out of jobs. This is understandable but the conclusion is wrong. We are letting emotions drive decisions.
> I think the closest analogy we have of the AI boom is the mid 90s browser wars.
Depends on how old you are. This analogy makes sense if you were a teenager in the mid 90s. I am older than that so to me, this same pattern had happened when PCs were becoming mainstream. That was 40 years ago so memory of it might be faint or lost. Also VCs weren't really a huge deal back then either but the fundamentals were the same.
We are all overreacting over a nascent industry, upset that it's increasing prices for everyone and pushing humans out of jobs. This is understandable but the conclusion is wrong. We are letting emotions drive decisions.
> It’s capital intensive, doesn’t easily scale without linear costs, is basically a commodity, and customers aren’t willing to pay what it actually costs
What are some VC funded companies that come to mind that do not fit this profile?
Yeah, which IMO is actually the problem. They got so addicted to the sugar hit of SaaS they lost their way. The game change, the risk profile dropped drastically, but they kept their own economics and upside the same and made an absolute fortune.
The type of investment called out by the start of this thread sounds exactly like the type of speculative "we don't even know if this is technically possible, much less if there's even a market for it" that Silicon Valley was founded on.
> speculative "we don't even know if this is technically possible, much less if there's even a market for it" that Silicon Valley was founded on
yes and that's the entire point of Silicon Valley.
It's also why you can't have another Silicon Valley in Europe or Asia where almost no one is willing to suspend belief and reality like this.
I've been invited to meetings and conferences from places in Sweden, Amsterdam to Thailand, and investors in all of those places balk at the kind of mindset you need to invest in startups. They are more comfortable with loans than investing. They lose confidence faster or require a higher ROI than would make sense. SV is really special and the reason why the best talent from all the over the world gather there.
VCs become rich not because they are smarter and better than Warren Buffet but because they are willing to place bets that Buffet would never take on.
You’re right, but your argument also has a lot of survivorship bias in it. There are rich VCs. There are also VCs that lose their shirts making bad bets. You just don’t hear about those as much.
> They are more comfortable with loans than investing. They lose confidence faster or require a higher ROI than would make sense.
I don't think this model is inherently bad. If an idea is good, is it not saner to get a loan instead of dilluting ownership?
This, of course, is predicated that parties are operating in good faith. SV has been for quite a while a sort of grift. Money is dumped on whatever can reach the exit event, no matter how unhealthy or senseless the business is in general.
I call it a grift even if it indirectly benefitted me. I avoid startups like the plague (both as labor and as user), but this grift did soak up engineers and raised salaries across the board. Alas, sometimes it's important to call a spade a spade.
In which sense? You want me to evaluate if the ideas are good? Or if I would take a swing at bringing them to fruition?
More importantly, how does my vague notion of the ideas are good or bad tie back to my original point that investors willing to loan instead of taking ownership is perhaps more sane?
If your stance is that you're correct with your perspective on loan vs equity, we shouldn't continue to engage but if that's not the case, ask yourself: how would the terms of a loan look like to a young teenager who is just getting into the workforce vs an established professional who has a proven credit history?
> More importantly, how does my vague notion of the ideas are good or bad tie back to my original point that investors willing to loan instead of taking ownership is perhaps more sane?
First, no one is forcing you at gunpoint to respond to me, so feel free to engage and go as deep as you want, as much as you care to, or not at all.
Second, investing, typically in shares of a company, is very different from giving a loan to the same company. Loans are typically based off collaterals, even if it's "unsecured" - it's always secured by something, even if as nebulous as just a credit history or "ability to pay".
No one reasonable in 2026 will argue collaterals with sama or OpenAI today, but I assure you, there was an entire universe of companies that would not give sama a loan in the early 2000s when he struggled to live paycheck to paycheck, or even OpenAI itself (a loan) in 2016 when they were exploring household and gym robots. I'll make the exact same argument for NVIDIA late 2018 to early 2020 post the cryptocurrency demand correction or even before that 2010 to 2015 - go look at the tickers back then.
So again, with the complete power of retrospect:
- Is NVIDIA a company you would loan your own money to?
- Is Dropbox a company you would loan your own money to?
If you get caught up in details like "how long is the term" or "what's the expected ROI of the loan", be generous with those details.
> Second, investing, typically in shares of a company, is very different from giving a loan to the same company.
No shit. This is essentially my point.
I don't care what companies will or will not exist on each model; What I care about is the sort of incentive each model creates.
In a model where investors give loans to nascent companies as a mean for those to have needed capital, the incentives are there for a company to make sense, grow organically, and chase profitability. In other words, the incentive is there for companies to be economically viable.
The model you defend creates an incentive for destructive growth. Investing in exchange of equity only makes sense to reach the exit event, no matter how ruinous things are as a result. It's a model that creates this shitty hustle-culture grift-economic. I will have trouble to express politely how much I think it makes the world a shittier place.
As I said, I indirectly benefitted from it, but I recognize that this model sort of sucks.
So, it doesn't really matter if I would have loaned money to those ventures (in a scenario where I am someone in the position of loaning money). But for the sake of entertaining you, I'll reply:
- NVidia: Maybe. The hardware business is cutthroat, but I think a company can be sustainable producing computer hardware.
- Dropbox: Probably not. Neat idea, but easy to copy by larger players or other upstarts.
- Diffusion LLMs: No. Too experimental, and I likely would not have seen potential for it early on.
If Uber operated like most AI startups its business model would be to buy new cars every 6 months, sign agreements with every automaker to buy every car they make for the next 5 years despite having neither the cash nor cash flow to pay for that, and sell rides for a fraction of what all this costs them. All while providing a service only moderately better than the boring taxi service that costs the same price and that taxi service just released an app to hail rides. It would then claim it’s worth 100x the valuation of the taxi service.
> If Uber operated like most AI startups its business model would be to buy new cars every 6 months, sign agreements with every automaker to buy every car they make for the next 5 years, and sell rides for a fraction of what all this costs them. All while providing a service only moderately better than the boring taxi service that costs the same price and that taxi service just released an app to hail rides. It would then claim it’s worth 100x the valuation of the taxi service.
Uber and Lyft literally "sell rides for a fraction of what all this costs them" upto early 2025. I don't know how old you are but I started to use them back in 2012. I was one of their early users when you could sit next to the driver. From then upto 2025, Uber and Lyft used to literally cost me less than what just gas would cost me to drive the same distance.
This is true too: "It would then claim it’s worth 100x the valuation of the taxi service" - there was literally a website (might be up even now) that literally made this argument and why Uber was doomed to fail anytime now.
Your first two points are also true for Uber Lease - a product that was rolled out for drivers - they could choose to lease specific models and Uber in turn signed agreements with specific automakers. An exact parallel for these points, esp. the circular financing is hard to make because they are not even the same product but I imagine one would agree, on the whole, we are in the conception stage of LLMs and this industry is brand new and figuring things out.
This same pattern had happened when PCs were becoming mainstream. That was 40 years ago so memory of it might be faint or lost. Also VCs weren't really a huge deal back then either but the fundamentals were the same.
We are all overreacting over a nascent industry, upset that it's increasing prices for everyone and pushing humans out of jobs. This is understandable but the conclusion is wrong. We are letting emotions drive decisions.
You make some valid points, but the bigger fact remains that Uber survived because its model was not capital intensive. Yes it burned cash for a while but on one-off costs like setting up new markets. Had it signed contracts to be buying new cars every 6 months in the way AI startups have committed
to future expenses it would have gone bankrupt.
> that Uber survived because its model was not capital intensive. Yes it burned cash for a while
I would say you are either very young or unfamiliar with Uber as a business. Uber was and continues to be extremely capital intensive and you need to qualify your "while". Uber burned cash for 14 years.
The one argument I can agree with is Uber didn't burn as much cash as Anthropic or OpenAI does but they are very different businesses with very different impact on humanity.
> Uber and Lyft literally "sell rides for a fraction of what all this costs them" upto early 2025. I don't know ...
Yes, and AI is the same sort of monopoly grab. Except not for Taxis, but for computing. Make a compute intensive process a necessity (that's where AI comes in) and buy 100% of all compute capacity, eventually buying up all the fabs and locking everyone out of acceptable general purpose computing, forced to move everything to the cloud.
> Make a compute intensive process a necessity (that's where AI comes in) and buy 100% of all compute capacity, eventually buying up all the fabs and locking everyone out of acceptable general purpose computing, forced to move everything to the cloud
This is overly dramatic and pointing that out is necessary because this could cause someone else, even if not you, tremendous anxiety and pessimism about the future: None of which is good for your health.
First of all, no one's been forcing anyone to use AI or "move everything to the cloud". AI is tremendous leverage. It's exactly as useful as a jet or FSD is for commuting. It expedites significantly intelligence-related tasks. No one is forcing anyone to use AI. However, just like a person who owns a jet gets to a place faster than a person without, or a FSD allows you to get work done instead of staring at other cars, a person using AI will get their tasks done quicker than a person without. But that doesn't force a necessity.
Moving "everything" to the cloud is also not going to be financially smart. Companies like Apple, Google, Cloudflare, etc are aggressively moving compute to the edge, locally on device. This increases your own chances of running services locally on device because the device manufacturers will build their hardware to match the demand.
Second, compute capacity has always been elastic. Supply constraints have forever been an issue and that's how markets work. Supply gets constrained, suppliers react to demand, market reaches equilibrium.
In 1996, I had a real tough time getting a T1 line to my office. By 1998, it was no longer an issue. By 2000 there was more fiber than we knew what to do with.
I had a real tough time hiring good, quality engineers 2020 through 2024. That was a constraint in the supply. The market reacted and now there are a lot more good, quality engineers.
Yes, there's a severe constraint now but the market is going to respond and we will have a very different situation in 2030.
Capitalism works. It's not always roses though and not everyone benefits all the time.
It's just that I am a good engineer but I don't have a clue about running a company and so I can't progress beyond the point I'm at. Literally no idea what to do.
OK and which of the companies that I listed above do not fit the profile below and specifically which portions:
> It’s capital intensive, doesn’t easily scale without linear costs, is basically a commodity, and customers aren’t willing to pay what it actually costs
The only portion any of those companies fit is that they're capital intensive, which is surely true of any large web-based company. Can you explain how you think all of them DO fit that profile?
> It’s capital intensive, doesn’t easily scale without linear costs, is basically a commodity, seemingly has negative cashflow forever, and customers aren’t willing to pay what it actually costs. It’s basically the worst tech business model and yet somehow VCs caught a spell and threw every available penny into the fire.
We already agree on the first two. So the following remains:
"commodity, and customers aren’t willing to pay what it actually costs"
To that I say:
- AWS, Uber are all commodity
- Most customers of AWS, Uber aren’t willing to pay what AWS, Uber charges them
First of all, I don't agree with "doesn’t easily scale without linear costs" either. Also you're just repeating your claims without explaining them..
HOW are AWS and Uber commodity? What commodity are they?
In what possible way could customers not be willing to pay what they're charged? Both companies saw billions in profits last year – is that paid unwillingly? Are they extorting their customers? If they're both commodities why wouldn't the customers just purchase from a different provider?
The conclusion of the article is wrong - that the Economics of AI Don't Work.
A better report would have been how the "Economics of AI Wrappers Don't Work".
Character.ai was likely paying frontier LLM API rates (which are known to be ridiculously expensive at 90% margins) and then had their own R&D plus lawsuit overhead. Most people can use a $20 Claude or ChatGPT sub to build a completely custom Character.ai. Once Character.ai employed MBA Strategy #3 (aka enshittification), churn killed the company (as it should)
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What doesn't work is attempting to build an AI Wrapper. Those companies had a good run 2022-2025, but with how good both open weights and cheap frontier models have become, AI Wrappers can no longer demand fat margins.
I'm sure people will now argue what exactly AI Wrappers are in the comments below, but for now I'm more interested in understanding what the HN hivemind's take is on the topic as a whole.
Known to someone who doesn't trade on a heavily AI indexed market (in 2026 all companies, even Tyson or Chevron is an AI play but not as heavily AI indexed as those say 2 degrees away from Anthropic or OpenAI) - likely not.
So if the point you're making is your typical barber doesn't know about this, I am guilty.
If you want to do your own research into this, there are a lot of private reports and publications on the topic.
If you don't want to spend any money, there is even a recent public analysis using a 92% API gross margin.
Anthropic's October 5, 2026 analysis also points to a 92% API gross margin that SemiAnalysis based their report on.
OpenAI reported paid-user compute margin reached 70% in October 2025 - a year ago.
DeepSeek has similar reports. The frontier labs are comfortably in the fat inference margin territory.
I didn't have information at all, and I wasn't trying to imply anything specific about the data. I just wasn't aware that there was public information that would point to such a specific number for their margins.
It's interesting to read this data. A lot of the "common wisdom" was that subscriptions were heavily subsidized, but in actuality they're just not quite as outrageously profitable.
> A lot of the "common wisdom" was that subscriptions were heavily subsidized, but in actuality they're just not quite as outrageously profitable.
Both can be true! Assume that it costs you $10 to support inference of 1MM tokens, and you sell that for $100. So you have a 90% profit margin.
Now you also have flat rate subscriptions for $200/month, where you sell upto 100MM tokens. That costs you $1000, but you're selling it as a loss leader because that drives up demand, bottom up - for your product, which is good for long-term profitability specially when your investors are not yet sensitive to you burning cash.
I have multiple $500/mo OAI subs. Still cheaper than buying my own hardware for equivalent performance.
Doesn't Windows do some drama if its not activated and has been running without a license for more than 48h or similar?
I don't use windows but have to run windows 11 VM to access special devices. I don't want to bother with licenses, although I have them, and creating a new incus QEMU VM from scratch everytime from an ISO takes ~5m, freeing me up from worrying about all the activation and license drama.
If the activation and license setup was easy/automated in QEMU, I would imagine snapshots would be way easier. I would prefer not needing to connect to the internet.
> Doesn't Windows do some drama if its not activated and has been running without a license for more than 48h or similar
Your info might be like decades out of date, since windows 10 it's just been an overlay and locking out some appearance customizations (you can still set them via other means though).
I disagree. Google is doing a phenomenal job at capturing use cases at the edge, right where "normie" consumers live. Google's models absolutely suck at coding but if you haven't tried Google Transcribe, you should.
Google has also, far larger distribution and stickiness than Meta.
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