I think the main reason is to minimize the market for closed-source models from US companies.
China knows that doing what Anthropic/OpenAI/Google/... are doing is impossible for them. No one outside of China in any sane condition will send their data to compute farms IN CHINA like people currently do with US-based frontier models. Even if they could muster the inference power.
Hence they do the second-best thing possible to attack the dominance of the US-based corporations: reduce their moat by open-sourcing models that are not fully equal, but practically useful and good enough for easily 90% of typical tasks people use agents for in their daily lives. But way cheaper to run.
As long as this arms race in AI continues, China as "number two" will have some incentive to continue open-sourcing models. But of course the US government might force a change if they continue to enforce limited public access to new frontier models - there is no market to minimize if a model is not allowed to be publicly available.
But at work the calculus is entirely different. There is already lots of exposure to US companies (guess where our emails and tickets life), so the increase in espionage risk from adding another American company is small. Not zero, and trust towards AI companies is limited. But adding the first Chinese company to send data to would be a major risk. One nobody would sign off on, given the general reputation of the Chinese economy for widespread espionage, disregard for copyright and producing copies of successful products using insider information
Not sure why anyone in the EU thinks the US is not a significant espionage risk. Adding any major US supplier would have been a significant espionage risk until really recently.
Before the EU cleaned up Europe's act pretty considerably on corruption, US companies used corporate but also state-level espionage actors to level the playing field against a culture of bribes and they were fairly open about it. They absolutely needed to do it, because of the potential penalties back home if they engaged in bribery abroad.
The tables have turned, now. The EU runs much more cleanly than decisionmaking in DC, which is clearly corrupted and lubricated with cash and opportunities for failsons and faildaughters; it has accelerated radically quite recently but it was heading that way from the first Bush era.
But I'd bet the corporate-state merger of industrial espionage is in full flow.
This would require active participation by people inside Anthropic and OpenAI. Given how generally ideological the people working in these companies are, I'd be willing to bet that we would already be reading Snowden-style leaks if it were true.
I have zero expectation that a similar culture exists inside Chinese companies. If you think these corporate and national cultures are the same, you need to adjust your priors.
> This would require active participation by people inside Anthropic and OpenAI.
Not necessarily of the companies themselves, though; just embedded people at the right hiring level.
> Given how generally ideological the people working in these companies are
History has many examples of truly surprising spies, over the long term. Including in highly ideological environments such as animal rights and eco-campaigning groups. The embedded police spying scandals in the UK make this clear.
It is naïve to think that there are no CIA or NSA employees in some functional role at these two businesses, just as it is naïve to think that they don't have intelligence industry contacts playing them because they are naïve. You only have to look at how the NSA weakened open cryptography to see that two companies staffed by young, absurdly rich people barely out of college with wobbly moral e/acc compasses might be getting played by homegrown spooks.
> I have zero expectation that a similar culture exists inside Chinese companies. If you think these corporate and national cultures are the same, you need to adjust your priors.
I suggested absolutely nothing of the sort — I flatly was not talking about China at all.
FWIW it cuts both ways: in the dim and distant past of the early dot-com era, I remember encountering someone who wafted inexplicably between US and UK multinational companies who I thought was possibly British intelligence. An odd duck for sure.
Anthropic and OpenAI are not just "another American company", their entire business (and industry) was created based on stealing data and using it for profit. You make this point about "another company" so casually that you'd think you added a SaaS bill for generating thumbnails or whatever. The exact same point you make about China can be made much more confidently and with stronger evidence for the entire modern LLM lab industry.
Again I have to echo the previous poster's point: Most people outside of the US really do not see the US as some much better alternative than China. If anything, in the specific area of LLMs, China are the ones doing work benefitting the everyman whereas almost everything the US labs do does not.
That's why I added "Not zero, and trust towards AI companies is limited". Reaching the decision that adding one single US-based LLM provider had more benefits than risks took months. And we were selective about who that would be (hint: not OpenAI). And I know companies who are not willing to go that step, using open-weight models on their own infra instead. But outsourcing inference to China was never even a serious suggestion. The notion is absurd to us
That said, I imagine e.g. South Americans thinking very differently on this front
> given the general reputation of the Chinese economy for widespread espionage, disregard for copyright and producing copies of successful products using insider information
Quite funny because if you use that phrase verbatim except swapping China with the US it could actually fit.
Good governments try to do things that are in the interest of their population, and yes it could mean opposite interests to your/someone else governments.
No reason to blame US, Israel, China, Russia, etc. They just defend their piece of cake.
China indeed has a general reputation for widespread espionage, so any Chinese company wanting to expand into the European market has to prove it isn't spying on its potential customers. US companies have traditionally been seen as friendly, so their platforms are essentially built around "trust me bro" guarantees.
In a world where both China and the US are now seen as hostile-by-default, this might actually leave some Chinese companies with an advantage in their ability to demonstrate trustworthiness.
The blurring of US state and corporate espionage in the EU is the stuff of legend. They have always spied, and you can easily make the case that in late 1980s/early 1990s Europe they had good reason to, because European businesses were corrupt.
Totally agree, though it is an unpopular opinion here.
It’s the same paradox as people claiming: “we are European, our data is safer in Europe” when actually your privacy is higher when your data is stored in China (or Russia) you are safer because it is out of reach from your local government.
The only thing I dislike, and that’s no matter the service, is that my data or information usage is shared with third-party.
For example, Anthropic conveniently forgets to mention Datadog has tons and tons of information about Claude users, or that your data transits through machines they don’t operate.
Safety has more than one definition. Being able to sue the company in small claims court when it threatens to delete your account is also part of that, and so is being able to pay for the service when Russian companies are once again put on a sanctions list.
China wants everyday people data because some of those people will get power one day, and China wants to be able to leverage knowledge of you, perhaps even "deep dark secret" data, if they need to.
was going to say this.. open sourcing Chinese models will enforce Chinese dominance instead of reducing it. When an open Chinese model becomes the best alternative to inaccessible closed US models guess what everybody will start to use. And that same open model may embed certain narratives and values that please the Chinese government.
Ya. You know enough about China to know: would they be willing to sell users outside of China models that aren't fully pro-China (and won't deflect on tough questions)? Or would that be dirty money that they wouldn't want anyone to make?
Like if they could release Ch-ythos 6 tomorrow BUT it had Western ideals, would they take the fame, clout, attention, & profit, or stick to the party line?
(hope the monolithic brush is appropriate, considering, I mean it's an impressive system/country even if I have my own strong preferences - also I've taken as true reporting about their models deflecting etc. on sensitive topics)
They captured like 90% of the German ticket market by closely watching Ticketmaster and basically repeating their playbook. Eventim also owns some venues, has exclusive contracts with many of them it doesn't outright own, hosts an official fan resale site, offers promotional services and generally integrates a lot of the business around large events vertically.
What's actually interesting is that it seems to be possible to compete with Ticketmaster only by copying their playbook on a large-enough scale, and Germany appears to be large enough. The Netherlands right next to Germany don't seem to have been large enough, as Ticketmaster basically controls them.
The typical job of a CTO is nowhere near "finding out what business needs and translate that into pieces of software". The CTO's job is to maintain an at least remotely coherent tech stack in the grand scheme of things, to develop the technological vision of a company, to anticipate larger shifts in the global tech world and project those onto the locally used stack, constantly distilling that into the next steps to take with the local stack in order to remain competitive in the long run. And of course to communicate all of that to the developers, to set guardrails for the less experienced, to allow and even foster experimentation and improvements by the more experienced.
The typical job of a Product Manager is also not to directly perform this mapping, although the PM is much closer to that activity. PMs mostly need to enforce coherence across an entire product with regard to the ways of mapping business needs to software features that are being developed by individual developers. They still usually involve developers to do the actual mapping, and don't really do it themselves. But the Product Manager must "manage" this process, hence the name, because without anyone coordinating the work of multiple developers, those will quickly construct mappings that may work and make sense individually, but won't fit together into a coherent product.
Developers are indeed the people responsible to find out what business actually wants (which is usually not equal to what they say they want) and map that onto a technical model that can be implemented into a piece of software - or multiple pieces, if we talk about distributed systems. Sometimes they get some help by business analysts, a role very similar to a developer that puts more weight on the business side of things and less on the coding side - but in a lot of team constellations they're also single-handedly responsible for the entire process. Good developers excel at this task and find solutions that really solve the problem at hand (even if they don't exactly follow the requirements or may have to fill up gaps), fit well into an existing solution (even if that means bending some requirements again, or changing parts of the solution), are maintainable in the long run and maximize the chance for them to be extendable in the future when the requirements change. Bad developers just churn out some code that might satisfy some tests, may even roughly do what someone else specified, but fails to be maintainable, impacts other parts of the system negatively, and often fails to actually solve the problem because what business described they needed turned out to once again not be what they actually needed. The problem is that most of these negatives don't show their effects immediately, but only weeks, months or even years later.
LLMs currently are on the level of a bad developer. They can churn out code, but not much more. They fail at the more complex parts of the job, basically all the parts that make "software engineering" an engineering discipline and not just a code generation endeavour, because those parts require adversarial thinking, which is what separates experts from anyone else. The following article was quite an eye-opener for me on this particular topic: https://www.latent.space/p/adversarial-reasoning - I highly suggest anyone working with LLMs to read it.
Would you consider cute animal videos that are not AI generated to be so much more worthy of your time? Because I don't really care whether cute animal videos are AI generated or filmed - I simply don't want to spend even a second on them.
And most people I know who love spending time on this kind of content would not care either - because they don't care whether they waste time on real or AI animal videos. They just want something to waste time with.
> Would you consider cute animal videos that are not AI generated to be so much more worthy of your time?
Yes indeed. I do love me some cat and bunny videos. But I hate getting fed slop - and it's not just cat videos by the way. I'm (as evidenced by my comment history) into mechanics, electronics and radio stuff, and there are so damn many slop channels spreading outright BS with AI hallucinated scripts that it eventually gets really really annoying. Sadly, YT's algorithm keeps feeding me slop in every topic that interests me and frankly it's enraging, as some of my favorite legitimate creators like shorts as a format so I don't want to completely hide shorts.
> And most people I know who love spending time on this kind of content would not care either - because they don't care whether they waste time on real or AI animal videos. They just want something to waste time with.
The problem is, these channels build up insane amounts of followers. And it would not be the first time that these channels then suddenly pivot (or get sold from one scam crew to the next) and spread disinformation, crypto scams and other fraud - it was and is a hot issue on many social media platforms.
No one buys into Elon's firms because he's expecting dividends.
His investors are not investing because of his success rate in delivering on his promises. His investors are investing exclusively because they believe that stock they buy now will be worth more tomorrow. They all know that's most likely not because Elon delivers anything concrete (because he only does that in what, 20% of cases?), but because Elon rides the hype train harder tomorrow. But they don't care if it's hype or substance, as long as numbers go up.
Elon's investors are happy with his success rate only in terms of continuously generating hype. Which, I have to admit, he's been able to keep up longer now than I ever thought possible.
Theranos were also hyping a lot and trying to build some stuff. There is some threshold (to be decided where) after which something is more of a fraud than a hype.
Also these days stock market doesn't have much relation to real state of economy - it's in many ways a casino.
Not sure who determines the threshold, he certainly goes to court more than your average person, but these are not start ups, they are large companies under a lot of scrutiny. I don't think the comparison is valid
>he certainly goes to court more than your average person
Yes because he sues a lot of entities for silly things such as some advertisers declining to buy ads that display next to pro-hitler posts, or news outlets for posting unaltered screenshots of a social media site he acquired.
If Theranos promised ten amazing innovations or useful products, got 7 of them to market to great success while revolutionizing their industry I'd forgive them if their other 3 products turned out to be hype.
> The hype to substance ratio isn't quite as important as some choose to beleive
Musk's ratio is such that his utterances are completely free from actionable information. If he says something, it may or may not happen and even if it does happen the time frame (and cost) is unlikely to be correct.
I don't get why anyone would invest their money on this basis.
Remember when people said that Starlink would never happen? What about when "experts" said that a private space company would never launch rockets. Or that no one would by an electric car made by an upstart company? Or when people said that the downsizing at Twitter would cause the company to collapse and that we could expect it to be defunct and dead within a year?
Some combination of the two, for sure. doesn't mean that Musk can't keep doing it. however you describe it or define it, it's a proven strategy at this point. I'm not sure Larry knew how Musk would make him good on Twitter, but he knew enough about Musk to be confident it would happen.
I think this is why he gets away with it. A "win" is a product delivered years late for 3x the promised MSRP with 1/10th the expected sales. With wins like these, what would count as a loss?
He gets away with it for one reason only, and because he consistently delivers good returns on capital.
Most of Tesla's revenue derives from Model Y and FSD subs. I agree that Cybertruck was a marketing ploy. Don't think it was ever intended to be materially revenue generating.
Revenue has flatlined, but investors' confidence comes from Musk's track record for delivering good returns to investors. I think we can agree Musk succeeded in 2020 to 2025 in this regard. Whether you are confident he can do it again over next five years is the key question.
I'm personally more persuaded by the argument that Tesla is a meme-stock at this point - like much of crypto, it runs on "vibes", not solid fundamentals.
But even if share price is the metric for success, 33.6% over 5 years is like 6% compounded annually, which is okay I guess? [0]
Tesla's sales have suffered, yes, and Elon's image is a significant contributor to that, besides all the reasons directly related to the cars themselves.
But Tesla's stock price is still stuck in irrational heights, not even remotely justifiable by the company's performance.
It just seems that people reconsider purchasing a physical object way quicker than they reconsider a stock investment. Maybe because the stock investment, especially in TSLA, is considered more like a gamble - "as long as others also think that this stock will skyrocket, even just because they think that others like me think it will skyrocket - as long as that's the case, I'm good with buying shares".
Actually, discount grocers operate on razor-thin margins of 2-4%. If your inaccuracy is geared to the benefit of your customer (because otherwise you'll be out of business due to the regulatory bodies) and thus removes just one percent of that, you suddenly lose a quarter to half of your earnings! And that goes ON TOP of the additional cost incurred with all that computer vision tech.
In addition to that, you'll have the problem of inventory differences, which is often cited as being an even bigger problem with store theft than the loss of valued product. If the inventory numbers on your books differ too much from the inventory actually on the shelves, all your replenishment processes will suffer, eventually causing out of stock situations and thus loss of revenue. You may be able to eventually counter that by estimating losses to billing inaccuracies, but that's another complexity that's not going to be free to tackle, so the 1% inaccuracy is going to cost you money on the inventory difference front, no matter what.
And to add to that, it's not a neutral environment. If there's 1% of scenarios that are incorrect, people will figure out they haven't been billed for something, figure out why, and then tell their friends. Before you know it every teenager is walking into Amazon Fresh standing on one foot, taking a bag of Doritos, hopping over to the Coca Cola stand, putting the Doritos down, spinning 3 times, picking it up again and walking out of store, safe in the knowledge that the AI system has annotated the entire event as a seagull getting into the shop.
Which is mostly the result of clever engineers that produced a machine no other company in the world can assemble, but that is absolutely crucial to businesses valued at double-digit trillions of dollars.
You don't really need an army of sales managers to sell such a product. Going lean on management and more heavy on engineering is therefore a good idea if you want to keep the lead you have.
No, but ASML's product is so complicated that they do need a lot more than just engineers - they have 5000 suppliers apparently, coordinating that takes a lot more than clever engineers.
Clever engineers are usually able to pick up basic supply chain management capabilities. At least as long as it's about suppliers of things in their technical domain.
For non-technical supply chain managers to pick up enough technical chops to understand the stuff they are supposed to manage the supply chain of is comparatively more difficult.
Especially when fierce negotiations to push the price down are not the highest priority, but robustness of supply chains, having alternative options that technically work, and ensuring quality according to tight specs are paramount. Which is how I assume ASML supply chain management to work.
China knows that doing what Anthropic/OpenAI/Google/... are doing is impossible for them. No one outside of China in any sane condition will send their data to compute farms IN CHINA like people currently do with US-based frontier models. Even if they could muster the inference power.
Hence they do the second-best thing possible to attack the dominance of the US-based corporations: reduce their moat by open-sourcing models that are not fully equal, but practically useful and good enough for easily 90% of typical tasks people use agents for in their daily lives. But way cheaper to run.
As long as this arms race in AI continues, China as "number two" will have some incentive to continue open-sourcing models. But of course the US government might force a change if they continue to enforce limited public access to new frontier models - there is no market to minimize if a model is not allowed to be publicly available.
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