simias

To be clear I was making a wish for the future, I wasn't saying that Mistral were bad for not doing this today, that obviously wouldn't really be technically feasible.

Given the rate of progress of LLMs, I wouldn't be surprised if we had decent fully open and reproducible models within a decade or so, especially once the current spike in hardware price passes and building a local training cluster will be more realistic.

I'm aware that in 2026 this is science fiction, but if the rate of computer improvement over the next 40 years matches that of the past 40, this is not going to remain sci-fi for extremely long in the grand scheme of things.

I hope that the long term future of AI is more like Linux and less like Windows.

Hotpatching binaries used to be common. It's less so in the modern age but mainly because we moved software to higher levels of abstractions, virtual machines and interpreters, and also because rebuilding even a massive project from source is achievable on commodity hardware. You can still see various hotpatching schemes being developed, for instance to allow partial recompile of the sources while developping.

If in 2080 we can retrain Opus 129.5 directly on dev machines from scratch in <2h, I doubt many will bother messing with the weights directly.

I absolutely want that to be available.

The only way to make sure that a model was trained without hiding weird biases and backdoors is to monitor this process. It also allows anybody (with the hardware resources) to experiment with the model and how it's trained. Will most people want to do that? No, but most people also don't want to recompile their own kernel, that doesn't negate the value of Linux being FOSS.

I hope that, in the long term, I'll be able to use competitive, completely open models in the same way that I can run Linux on my computer.

You're completely right that the licensing of the training data is a big issue though (and I would argue that it should be a much bigger issue right now, even for closed models). I hope that eventually our understanding of the tech will let us build competitive LLMs using purely public domain/Creative Commons-style training data.

I realize that we have a long way to go... but that's a very worthwhile goal IMO.

I think the problem with this "open weights" thing is that it doesn't map well at all with "open source".

If you think about it the actual mapping is more like:

- closed weights -> closed-source web service (e.g. gmail)

- open weights -> closed-source but you get the binaries (e.g. Minecraft)

- Actually open model (with training data, training pipeline etc.) -> open source

Yeah that's me making up a big number to evoke an "AI maximalist" future, where automated labor swallows a huge chunk of the economy.

I'm very pro-union but I feel like at this point attempting to organize will just speed up the process of replacing as many people as possible with machines, not slow it down. It's too little, too late.

I don't understand what kind of society we're building right now. Anthropic and other AI labs at $20T valuations, the 1% monopolizing all the wealth and the rest of us out of a job and fighting for the scraps?

There seems to be some sort of magical thinking within the AI crowd at the moment, that it'll all work itself out in the end.

- Build the God Machine

- ??????

- POST-SCARCITY UTOPIA!

It's a bit insane how it seems that "deterministic and reproducible", what I would consider to be a cornerstone of good software development, has apparently become an afterthought in the age of LLMs. All that for the sake of perceived convenience.

Not even convenience at times, I think that for some the amount of technical-sounding text LLMs can output on demand is comforting. It feels serious. It feels like it's doing something important.

Meanwhile the rest of us have to deal with these low-signal/high-noise walls of text in commit messages and PR comments. Or ask another LLM to summarize them, I suppose. "Doing and undoing, it's all work", as we say in French.

>The operational engineering that goes into serving a frontier model is _highly_ nontrivial, it is not commodifiable. This isn’t a SPA application.

I don't really see it frankly. Admittedly I never tried it (I only played a bit with local models) but conceptually how is it much harder than all the other cloud services that already exist? My educated guess is that building a competitor to Netflix, Youtube or Dropbox seem technically a lot harder to get running than offering inference on demand for instance.

It seems that the main barrier for competing in that market at the moment is getting your hands on the GPUs/RAM and a datacenter to put them in.

Counterpoint: if that was the case, Musk and Thiel wouldn't as successful as they are.

Our modern capitalist societies are, at the very least, amoral.

As a French person myself, I think this antipathy is less strong in non-English speaking countries, where the population (even if they understand English) is less exposed to the antisocial rants of these megalomaniac idiots.

Someone like me who spends a lot of time in the anglosphere puts faces on companies like OpenAI or Anthropic. I doubt that's true for most people, especially outside of the USA. They're just big companies, like 3M, DHL or Toyota. Who knows what the management of these companies think of the future of humankind?

I would expect than personality-driven rejection of American tech from abroad nowadays is driven mainly by Trump and, to a much lesser extent, Musk. Everybody else is just "some guy" to 99% of the population.

The problem for me is that it's really hard to project what this industry is going to look like 6 months from now, let alone 6 years.

What's the endgame once the dust settles? Is it going to be a utility like water or electricity and the cheapest offer will prevail, in which case margins will be crushed? Or is Anthropic (or some other big AI lab) going to swallow everything and become the Google Search of LLMs, with everybody else fighting for scraps?

Or is it local compute, models becoming more efficient and hardware becoming cheaper (again) and companies hosting their own AI clusters like they would run SAP?

I think there is a plausible path where this valuation actually works out, but it's a narrow one IMO. I also want to acknowledge that I personally would prefer if it wasn't the case and a more distributed, open model prevailed.

I am roughly the same age and I grapple with many of the same ideas, although I'm still pretty depressed at this point. I've been coding for 25 years, I'm quite good at it, it's a facet of my personality. Seeing this skillset commoditized within a year or so has been a brutal experience. Payback for all the jobs we replaced with software, I suppose.

I do feel like I should be thankful to be alive right now though. I witnessed the evolution from Kirby on the Game Boy to Half Life 2 to VR to LLMs. The tools we use today were science fiction only a few years ago.

I just wish society was in a better state to make this tech a greater good instead of a tool for advertisement, warfare and wealth concentration. I feel a deep sense of loss because of this. 20 years ago I had no doubt that technological progress was an obviously good thing, that it would improve the lives of everyone. Do I still believe this? I'd like to, at least.

I really struggle with this argument that I see everywhere lately, especially when we see many vibecoders clearly desperate for clout who post "decomps" and automated translations of works they clearly have no interest in and just want to claim a spot on the wall of fame. I'm talking about people bulk-translating old ROMs and not even booting them up to see if they work before releasing them in the wild for instance.

Their lazy cloud-chasing is normal but my high-effort clout-chasing is lame and makes me a fraud?

We're social animals. We like doing cool stuff and getting social status for it. We like breaking new ground. We like going where nobody has gone before.

Is it irrational and emotional? Maybe. Being human is being irrational and emotional sometimes. It's fine.