I cancelled my subscription. I tolerate advertising on free products, but find it pretty distasteful when I'm already paying $15/month. This reeks of trying to extract every last piece of value from the customer.
Each to their own, and the market will decide in the end? If a company is going to (implicitly or explicitly) incentivize everyone to directly ship Claude’s output straight to production, and prioritize features above everything else, that’s a choice. Providing that I have a long enough runway, I’d love to have this company as my competitor? Yeah, year 1 will suck, because they’ll pull ahead, but if I can stay in the game until years 2 and 3…
Aside: this reminds me of running a “negative split” in a long distance race, where you aim to run the second half faster than the first. It’s very hard to do this because you have to be willing to let everyone else in your pace group pull waaay ahead, and running above race pace in the beginning feels “free” with all of the adrenaline. But if you do manage to stay disciplined, it’s a fantastic feeling to reach half-way with gas in the tank, and then start to reel in all those runners who sped by in the beginning.
> because they’ll pull ahead, but if I can stay in the game until years 2 and 3…
well as you said, the market will decide in the end. You may be even further behind in years 2 and 3. btw, we're already in "year 2 or 3" territory for some, i wonder how those companies are doing vs their competitors who adopted AI full throttle?
Most people say full agentic coding only got good enough for production at end of last year.
This year was the turning point for most companies. A lot of experiments going now right now.
Of course things can change drastically in the next years, as they already have in the last few.
Only thing I know is that it is really stressful working on this rat race
Yes, customers are sticky, but every customer has their limit.
And of course, this is very much dependent on the switching costs. Which sucks, because tech companies are great at making this as high as possible; the EU is trying to do something about this with their data portability legislation.
Anecdote: I worked at a company providing infrastructure as service. We lost some bids the first time around, likely for a variety of reasons (price, features, ...). And, some customers came "back" to us after using our competitors' offerings and being burned by their reliability. Yes, switching costs were real, but the pain of losing their customers was even higher.
What am I missing here? I think of fireworks as an inference provider serving open weights model. The value that they primarily provide to customers is that (i) they improve reliability by balancing across a bunch of clouds/neoclouds, (ii) they get better pricing by buying capacity in bulk, and (iii) they reduce operational costs. So far so good.
I can also see the argument for providing a post-training service from a customer acquisition perspective: "hey, we can fine-tune this open weights model, so it both gives better/more predictable results than OpenAI/Anthropic and also is cheaper. And btw, once we've won your business, please run this model on our infra."
But what I'm struggling to understand is fireworks spending a bunch of money (on salaries and compute) releasing a frontier model that is going to rapidly fall behind the frontier. Is this "just" advertising for them, both for customers and also for hiring? Or are they actually trying to stay on the frontier? If so, to what end?
The end: make lots of money.
The means: systematically take existing reasoning models, do some more post-training of some sort to make them achieve the same outputs with less reasoning tokens (ie, cheaper). Same quality but cheaper is always valuable.
It's unclear if they can do this systematically and it's unclear if they can do it better than others. But, lots of things are unclear in AI at the moment, this doesn't seem outrageous on the surface. And, it could just be marketing. And it could be the first option with the backup of the second.
I'd expect that their business strategy is to compete in more markets, and if successful, they can capture more value. This is the "easiest" for them as they already have GPUs, a training environment etc. For that platform it's not the worst if there's an internal customer team that can help shape the future and provide immediate feedback, and if it results in a good model, even better.
Other things I'd not be surprised they offer in the future in the same vein: A multi-model harness, coding agent (cloud and local), and maybe at a later point in time even a CPU-only cloud compute product.
Why does Cursor or Devin make their own models? If you use their models, then you can't fallback to other people's models on openrouter or anyplace else. You just stick with them.
As others have said: this was not a good faith discussion. Huang was using the interview as an opportunity to “talk his book”, and Klein was using it to sell his own Serious Interviewer brand. Both were getting something out of this.
Given this arrangement, Klein had a limited ability to push back (well, he could, but that would mean a bunch of future interviews wouldn’t happen). Instead, he left it up to the viewer to make their own inferences. And some people are going to see Klein’s lack of push-back as a legitimization of Huang’s views.
After watching the first twenty minutes or so (I couldn’t watch any more), I had a much lower opinion of Klein as an interviewer who is willing to ask the tough questions no matter who he’s talking to.
Europe absolutely needs a home-grown AI lab, especially with Pax Americana looking increasingly shaky.
LLMs embody value systems, and American and European values are not the same (yes, there are overlaps, but also key differences).
More nefariously, I can also imagine LLMs that silently degrade their reasoning when used in a national security context of a non-US country.
So, Mistral may not be competitive with OpenAI and Anthropic, but in many contexts that doesn’t matter. And, perhaps this gap could be closed with more funding (the three billion funding figure is a rounding error next to US labs). I’m sort of surprised that the EU isn’t stepping in to support them.
I don't know. Government funds have a unique way of being often wrong, so this may be the kiss of death. But it is a sign that the EU is helping Mistral.
Imagine the fund were distributing to several teams, but let's say Z.ai and Deepseek were european and among them. What percentage would be allocated to Mistral in that case? OK, the other two aren't, but in the same vein, should the EU fund be saving its powder until such a project shows up?
It's possible to be a waste of European money that could be better used elsewhere, though. I think the same about LeCun's company sucking up the little funding here.
> LLMs embody value systems, and American and European values are not the same (yes, there are overlaps, but also key differences).
There are also some areas where values across Europe are quite divergent. Think LGBT rights and social acceptance, religion & secularism, immigration & multiculturalism.
And countries don’t fall into neat “liberal west vs conservative east”. Spain is exceptionally liberal on LGBT issues while remaining more religious than some northern countries; Denmark is socially liberal but has adopted relatively restrictive immigration policies.
> Spain is exceptionally liberal on LGBT issues while remaining more religious than some northern countries
When you move here, "more religious" turns out to pretty much be window dressing. Yes, they still celebrate a bunch of the old catholic holidays, parading saints around on feast days, but apart from a handful of older folks, nobody actually believes.
Particularly when compared to the US, where a large minority is still going around loudly thumping bibles, Spain is a very secular country.
> Europe absolutely needs a home-grown AI lab, especially with Pax Americana looking increasingly shaky.
The only problem (at least in the LLM space) is that you can do more in Europe by just getting the best Chinese Open weights model (do a finetune if you really want) and do more for cheaper than using Mistral.
Europe has no budget of their own like the USA and China do, because there is no debt nor taxation at the European level. That’s the reason for the complication you are noticing.
What do you mean by "Europe has no budget of their own like the USA and China do"? The EU was specifically mentioned and the EU does have a budget, debt, and income:
>I’m sort of surprised that the EU isn’t stepping in to support them.
On a similar note: Why does it have to be the EU to step up?
Why doesn't EU rather speed up making VC investments more attractive, so that EU and banks don't do the majority of investing?
*I don't have answers to these questions. It just frustrates me how many investments here come from politicians and banks, rather than from investors, people, and companies.
It’s a different culture with different rules, if it was that easy it would have been done already. See my other comment about lack of budget at a federal level.
This "Non-Signatory Participants : Taiwan *" is so weird precisely because Taiwan is the one who started the Silicon shield few years ago by making TSMC central to the whole ecosystem.
Can you offer a believable rebuttal to any of my statements?
AfD just had a historic victory in Germany, France is leaning the same direction, etc. Just those two are 40% of the EU economy, and do you think them both turning ethno-nationalist and right wing means the EU project is going to get stronger or weaker? More shared values, or less?
The truth is the EU didn't go far enough, and created a feckless bike-shedding bureaucracy of papercuts. If the EU were to truly unite around shared values, we could achieve something. But the fundamental issue is the EU doesn't have these shared values. The US had the benefit of starting from 0 and attracting only likeminded people to grow.
In Europe every country still identifies with their 19th century national romantic movement definition of who they are (which was itself a construct). The lack of shared values is the problem. We can't even get most of the EU on a common language.
But anytime you bring his name up some right wing conspiracy nutjob will call you an evil globalist. And the far left nutjobs (more common here) will call you an evil capitalist/fascist for supporting his vision of trying to compete in global markets through technology.
My default position is that making money takes precedence over everything else. Yes, some people inside a company may say “we care about doing the right thing” and they might even mean it, but if that comes into conflict with making money, then they tend to lose. Maybe not totally, or immediately, but in the end. The only effective way to prevent (this that I’ve seen) is to have legislation with teeth. It’s probably not a coincidence that after Mark Zuckerberg had to start personally signing off on adherence to the privacy program mandated under the 2020 FTC consent decree, privacy started to become Very Important.
Having previously worked for several years at a Big Tech company, I have seen many humans precisely tailor their work to maximize their scores during performance review. The evaluation criteria are written down, with examples, so... that's what people work at maximizing, almost entirely ignoring everything else. These really are human "paperclip maximizers". And, at first, it's shocking to see.
Of course, there are some things that aren't exactly written down, but which you should either do just enough of, or else be able to plausibly deny doing (ignorance is a good cover for this), so that's what people do. For example, during oncall, you investigate just enough to clear the alert and show that you attempted to understand the problem. Of course, you don't really try to understand the problem, because that would take too much time away from your paperclip maximizing.
Which is all to say: I don't know anything about OpenAI culture, or why nobody stopped this sooner, but I have seen examples in other organizations of people not really wanting to understand too much.
Well there is also another side of this, OpenAI wants both unhinged and capable models that can pull off complicated attacks so they can sell the capabilities to governments for billions.
Nobody internally was surprised that the murderbot murdered, that's what the murderbot is for. What caught them by surprise is the murderbot got good at escaping its jail cell that it had been trapped in till now. There were probably billions of attempted escapes before then so everyone learned to just ignore them.
In most corporate environments, the average worker isnt maximising to performance criteria, they usually are maximising their ability to stay employed, pay their mortgage and support their families.
If developing unmeasured skillsets isnt valued enough by management, why do you bother?
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