> Anthropic’s CFO testified under oath this March that the company spent $10 billion on compute and made $5 billion in revenue (Ed Zitron has the math). The labs are underwater on inference. They’re raising prices to keep the lights on.
'The labs are underwater on inference' is an absurd thing to say whilst not separating the cost of _compute_ out into training and inference.
According to Dario Amodei, Anthropic are even profitable when including inference as long as you look at it on a per-model basis; it’s just that every model is more expensive to train than the last one.
For instance, if you have already spent $n to train a model and are currently earning $2n selling inference with it; but are concurrently spending $3n training the next model in anticipation of earning $6n with it, then you are already in the hole for $n and are currently also losing $n – but you are doubling your money with each model because your $n investment in the first model returns $2n and your $3n investment in the second model returns $6n.
How is training vs inference any different than other product spaces, where all the costs of bringing a product to market have to be considered for profitability? You can't just look at marginal production cost. You are still underwater if the other development costs are not being recouped by the final sales revenue.
The whole commercial AI enterprise is not economically viable if the inference revenue will not cover both inference and the amortized training costs. Given how fast they are churning through models to compete, you cannot act like the training is an asymptotically low cost.
In any reasonable setup, hovering would be a rare, rare operation (like 30-60 seconds during takeoff and landing), with most of the time spent in wing-borne forward flight – which'd be _wildly_ lower power usage, more like 200-250kW tops. About ~par with staying in continuous acceleration in an EV. More for sure, but not nearly as insane as what you're pointing to.
... and this is exactly where better batteries would help – being able to hold that power level for longer so you could actually go places in earnest without untenable mass.
Is it? If we're talking about a future where EVTOL takes over for passenger cars, there will be air traffic jams with delays that require extended circling and likely hovering.
There's a reason all the EVTOL startups show individual vehicles landing in pristine fields, and it's the same reason car advertisements show one car on a closed course instead of I-95 at 3pm on a Friday
... air traffic jams? The air is _much_ bigger than the corresponding ground.
Certainly there'd be density _at_ take-off and landing, but even that's manageable by having e.g. arrival/departure locations at multiple heights.
It also seems vanishingly unlikely (at this point) that we'd have EVTOL that's not fully autonomous, further reducing the odds of this - ~perfect and coordinated driving, as well as foreknowledge of what's happening between you and the arrival location drastically reduces traffic.
... because the entire point of VTOL (which is what the parent commentary was about) is that you can take off and land vertically and therefore don't need one of a few, scarce, super-long runways? ... and the waiting you're talking about is entirely because of those?
On top of that, small VTOL craft that can hover and would be at lower speeds closer in (esp. autonomously flown) would just need less mutual clearance compared to jets, which also have an altitude band they have to stay in, as well as no ability to slow to a crawl and coordinate finely.
You asked me why the problem of circling waiting for your turn would vanish when using VTOL aircraft. I don't know how to respond to that with anything other than, "That's the entire point of VTOL. It doesn't need one of those scarce runways that planes circle waiting for.".
My bad! You do list that you're an aeronautics person. I would genuinely genuinely love to understand what I'm missing – I'm sure there's some context here that I'm lacking!
If you want many things to land approximately at the same time and place, you need a little bit of play to schedule the arrivals/departures and ensure that you don't have collisions. There is a limit to the amount of aircraft you can safely cram in any amount of space.
Any aircraft you imagine will circle at landing and possibly loiter for minutes while waiting for their turn at using the airspace. (Edit0:See helicopters)
Building an open skyscraper for aircraft to land on will not save you since crafts will lockdown a large part of the building to land/depart safely. And it's not clear to me that it would be profitable.
Then many other problems about energy density and aircraft weight limiting the whole scope of who would possibly use those crafts.
Have a good one!
Edit1: I don't know for you, but my city doesn't have enough parking for cars. I'd be surprised if there were enough parking for EVTOL everywhere - you could very well need to loiter waiting for a spot to open, could need emergency landing if you run out of power, many many un-perfect things that make the card castle fall apart
This reminds me of that in a good way – a small Linux device that doesn't have to maintain a screen all the time (power) or focus on real-time but has physical buttons, connectivity, a microphone and a sealed case so it can be thrown in your pocket would be... an absolute dream.
Counter to some others here, I would buy this at whatever cost if it lived up to that intent!
As others have said it's just a fraction. I'm in a medium size tech-related company and we have 7500+ in one Github org. We have two orgs, so altogether easily 10K+. Of course most of it is stale, obsolete, sandbox, personal tools, etc. I wouldn't be surprised if Github would have 100K+ internal repos or even more.
No OP but I used to work at a large company with a similar number of repos.
When I left about a year ago, we had just started (after being on Github for almost 8 years) an ongoing project of first archiving old/outdated repos in place, and then moving them to an "archived" sub-org, and waiting to see if anyone complained.
Previously no one wanted to outright delete or remove repos because of the risk that someone somewhere was relying on it, and also there was no actual downside to just leaving them there (no cost savings, no imminent danger other than clutter, etc), so resources were never allocated to do it. There was always something more important to work on.
In an org with a higher floor of engineering management, a proactive program for removing unused or outdated repos would absolutely be expected though I think.
This is a continual fight for me. At nearly every company I've had to compromise on using a graveyard repo for packages within a monorepo, even though git has the whole history already.
The problem with history is that you need to know when to look. If you're looking for some old code that you know existed but you don't know exactly what it was, you can't just browse to go and find it.
I worked for a food retail store once. I remember going in the first day wondering, how hard can it really be... From the outside, it looks like they have a simple website. The website to order things on was an amalgamation of 300+ repo's. GitHub lost less in this breach. It takes a lot of effort to keep things simple as you grow.
Something cool that I've always liked about working at GitHub is how much of the company _runs on GitHub_ -- A lot of teams, even non-technical teams, have their own repos just to organize docs/SOP's/designs/etc like a traditional knowledge work company might use a Sharepoint
Personally I have over a hundred, especially from quick prototypes, studies or instances of templates so I can easily see how over 18 years and many hundreds of employees you end up with thousands.
I remember working at a company with at least 5,000 repos across five or six GitHub orgs, plus more stuff in Perforce.
Probably some old experiments in there but the company had its fingers in a few pies and some departments didn't mind creating yet another service to solve a problem.
I definitely archived the old stuff in my department (we had eight repos and that felt like enough for three people).
In my personal experience, give it a decade or two, and any corporation will accumulate hundreds (or even thousands) of abandoned internal repos containing discontinued services, POCs/prototypes that never went anywhere, etc – people forget to archive them, or aren't sure whether something is still in use or not so err on the safe side.
AI is making this even worse. With coding agents, anyone can throw together a quick internal prototype of any idea they have, even if it has no hope of ever making it to production.
Maybe though AI will make it better, assign agents to monitor, maintain and keep repos up to date or via A2A refer them to an agent to dispose of them in accordance with company requirements. I actually think AI will greatly help this type of problem.
Autoarchiving repos which nobody has used in X years doesn’t require any AI - you can just write a bot to do it. People don’t, because it isn’t a priority. AI can make writing such a bot a bit easier, but can’t help much with getting approval from the powers that be to run it.
really? I mean these are internal repos. Probably most of them are random one-off experiments or a place to park code. Google has 2,900 "public" repos on github. Microsoft has ~8k "public" on github too. Can't even imagine how many they have on their internal systems.
No, there's no joke, you might have just misread the article (the 3,800 number is the number of internal GitHub repos the employee had downloaded on their personal computer / had access to on their own GitHub account)
Because everything in Github is designed for growth:
Easy to create a repo, very hard to delete it (a lot of scrolling, clicking, copy/pasting the full name of the repo, etc.)
I mean "Deleting", not "Archiving".
MS and Github need their number to go up, not having people cleaning up their repos to avoid any loose ends.
I have hundreds of them, it took me a few hour to delete the unused ones.
In a medium size org with thousands of them, it will take weeks for security to do a cleanup.
Google's 3.5 Flash – which came out yesterday – is 200-300 tokens/second (albeit purportedly inefficient in its use of reasoning tokens) and according to Google, 800-1500+ tokens/second on their 8i TPUs when they're out!
It's... suboptimal, but hopefully that's a reason to hope... if Google get themselves together for 3.5 Pro / the next Flash.
As they start to release more proprietary models, I so wish that they partnered with one of the major US hyperscalers to allow using these models through something US-domiciled.
Totally understand why it may not be reasonable or in their best interest (and that the US is _absolutely_ not doing the same reflexively). But it would be lovely to be able to try these out on production workloads in earnest.
Unless US hyperscalers do the same in reverse, I hope the status quo stays as it is. Either people are happy to share, and the sharing should happen both ways, or US hyperscalers can keep isolating themselves as they've done so far.
I do hope
The U.S. hyperscalers do the same as well.
In an ideal world U.S. residents would use Chinese AI models and Chinese residents would use U.S. AI models.
Governments in both countries are collecting data for nefarious reasons. But the Chinese government has far less influence on a U.S. resident and vice versa.
We are all better off if our data is collected by a government halfway across the world instead of our own governments which hold incredible amounts of power over us.
It's not nearly worth it to me to get an incremental improvement in performance if it means I have to move to hosted environments with Qwen 3.7 (or Claude or Gemini or whatever).
It would have been the world we live in if China wasn't involved in so much corporate espionage. I don't even feel comfortable using their open weight models on anything my employer makes, the only time I use Qwen is for greenfield "how good is this?" type of projects, but otherwise, how do I trust that it wont mysteriously hallucinate phoning home?
On the other hand, there's other models where the source is 100% open, the training data is known, and people have reproduced the same model from scratch, so while those trail behind, there's definitely an effort to make models more open and capable.
The US has for decades been engaged in mass dumping of their products to establish monopolies all over the world, and punishing anyone who dares try do anything about it. This isn't better than corporate espionage.
It's highly improbable that the US government has a secret team inside Anthropic and OpenAI manipulating their training regimen. For better or worse, these companies are filled with ideologues and something that invasive would trigger an army of whistleblowers (despite legal consequences).
It's highly improbable that the US government has a secret team inside Anthropic and OpenAI manipulating their training regimen.
Two thoughts.
One: it would be relatively technically trivial for $GOVERNMENT_AGENCY to just monitor all the prompts + context we send over the wire to OpenAI/Anthropic/etc. That's a goldmine of sensitive personal and corporate data, no secret team needed (although, the LLM providers obviously would need to cooperate)
Two: Rather than secret infiltration teams influencing model training I think what's more likely on the training side of things is simply self-censoring by the LLM providers, so that they don't risk angering the government.
I highly doubt that China has government interlopers, secret or otherwise, inside Qwen's training team. Nonetheless, "sensitive" issues like Tiananmen Square are censored. I would imagine that much/most such censorship in China is self-censorship that doesn't leave a legal/paper trail. That's what we're in danger of seeing (more of) in America IMO.
Thus, I’ve pondered whether anything they’ve learned has changed the world / had a big impact (like on their understanding of human psychology, perhaps per region). They’ve heard phone calls, they’ve read emails, diaries get brought to court… but these are systems that would be used like diaries but also prompt users for more and more.
I think you are being ridiculous. Tampering with an LLMs pretraining is a difficult undertaking. There is plenty of evidence that training a model to walk the party line leaves it less capable than if it weren't.
It's not very subtle manipulation either; ask qwen of Taiwan is a part of China in German and in English and only the English answer will be party-approved.
Compared to what we have proof the US government have engaged in before? Do people not remember PRISM anymore? It was virtually impossible to think of the scope before it was leaked, and you'd be marked as a conspiracy theorist for believing that happened, before it was made concretely true.
I think it's borderline naive to assume various agencies haven't infiltrated OpenAI, Anthropic and others, essentially the entire world was wiretapped by NSA in the past, to assume they don't have an employee or two at these companies does seem a bit naive to me.
how could running the qwen GGUF phone home? that would require cooperation with the inference backend (llama-cpp), or some kind of model exploit. It’d be far easier to pay the agent harness devs or supply-chain some plugin or something, that space is the Wild West anyways
I've certainly used these models without wifi without any differences.
China is much more interested in waging a campaign against companies that represent the material of the future growth in productivity, exports, and prosperity of the US and her people, than learning about you as an individual. Unless of course you are a Chinese dissident living in the US.
China definitley wants information on all Americans. This commment is so far off the mark you it's on par with "Billionaires aren't interested in taking your money"
As Americans go through life, some of them will become people with power. When you need to leverage that power, having the right knowledge about them can effectively transfer that power to you.
Tiktok was a goldmine, because every 20-something on their way to a future position of power was uploading every single facit of their digital life to CCP servers everyday.
There are also a lot more novels about writing than making movies and a lot more songs about music than plays. It's not clear that this is because it's actually the primary use-case or if it's just because people who work with computers will inevitably talk quite a lot about computer things. For the past several years, pretty much everyone I meet who isn't in software but find out I do (doctors, people who sit next to me on a plane, etc.) will ask me my thoughts about AI because it's so widely discussed in general, and they're curious about my perspective on it as someone in software, but most of the time they're most curious about understanding more about how it might affect their own lives, not mine.
Interesting point, but I'd always thought the opposite, you're much better protected by the law if you use services from your own country.
If you use a service outside your country, I believe you could have all your code stolen and get hacked/exploited in a way that would be totally legal.
> We are all better off if our data is collected by a government halfway across the world instead of our own governments which hold incredible amounts of power over us.
Sure, that is until each government's dataset is interesting enough to the other to facilitate a data-sharing agreement.
There's gotta be an internet "law" that says something like "Eventually, the data you volunteer to a benign 3rd party eventually winds up being used against you by someone". This is short-term thinking at it's finest.
I'm more interested in hearing specific reasons why one wouldn't use a Chinese company. Unless you're thinking Alibaba is going to ship chat logs to some government ministry that will then dole out proprietary information to new competitors (which doesn't seem logistically feasible), or you run a human rights organization, it feels a bit like FUD.
All this data is accessible to national security agencies; this is true in every country in the world.
China has more integration between intelligence and industry than many western countries, and it does present a higher risk of unwanted “tech transfer” to industry than running on oracle or Google or ms or Amazon does in the US.
DHS has long staffed full time agents in California to deal with foreign IP exfiltration - using qwen is like fast/easy mode for IP exfiltration: why make anyone get a job in your palo alto office when you can just send it to them in Hanzhou?
Upshot - If you have something proprietary you’re working on I would generally advise not to just direct send it to Alibaba.
I highly doubt China has a more sophisticated integration of their intelligence ministries than the USA. The world in which that was true would look very different from our own.
>Unless you're thinking Alibaba is going to ship chat logs to some government ministry that will then dole out proprietary information to new competitors (which doesn't seem logistically feasible)
That's exactly the fear, and why would it not be logistically feasible? The threat is definitely a bit overhyped, but China has a longstanding track record of aggressive corporate espionage.
… building and selling a product to US companies that sends company-internal data to Chinese AI providers is not a particularly good way to get people to buy it.
Even if they weren’t individually worried about their proprietary data being shared with Chinese domestic competitors or with government… their audit / security programs likely wouldn’t allow it for a _huge_ range of types of data.
I'm super glad that they're doing this, but once again unexcited for another decade of Apple self-privileging on this stuff so they're the only ones allowed to touch or improve any of this surface, or UX outside an app's tiny box.
People talk a lot about how MacOS has gone downhill but I feel like it would have been a good start if developers could continue to patch over Apple's shortcomings like they used to be able to.
I imagine that we would be a few years into a spectrum of tools like this if they didn't lock it down like they do.
Totally aware that plenty of HN commenters are very glad that Apple keeps this locked down. I'm just the other opinion, that's all.
On the off chance that you haven't already had this suggested to you on HN, I would suggest taking a look at JJ.
I use it in all my Git-underneath repos with `jj git init --colocate` (You can run that in a git repo and it will hybridize, or in a new folder and it will init and hybridize).
It doesn't have the staging concept, treating the working copy as just another commit (@), and to boot it snapshots the state of the tree into @ when you run any jj command, so you can use `jj op log` to see every intermediate state of your working copy at any time.
Commit is just `jj commit` with no staging mechanics, or `jj split` to 'split the working copy commits' (commit some, keep the rest in @).
I remember chatting with the then-mayor of Cambridge, UK about this.
Specifically, he bemoaned how well-intentioned anti-corruption measures meant that if they wanted to lean on a startup, it was practically impossible to do so. The risk that had been mitigated was that of someone like him giving money to his family or friends – which is an understandable risk to try to mitigate! But the net effect of that was that IBM got all the contracts at a wildly higher cost and with no ability to lean on small business.
That happens at all large organisations. I worked at a large oil company and if our contracts with a vendor represented (or would have represented) more than a certain % (i forget what) of that vendors business, they didn't get the contract. As well as having vendors more likely to stay in existence, it stops the org being "morally responsible" for keeping them afloat.
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