9 ms·

Open source AI must win

• TurdF3rguson 4mo ago
  In the end it will win in some universes and lose in others, just like the Nazis. All we can do is hope we end up in the one where things are ok.
• george_max 4mo ago
  With open-weight AI, there might not be an incentive to put large sums of capital towards training / research. There might be a donation fund of some sorts, but it certainly won't reach the level of fundraising that the frontier labs are receiving. Because of this, I think it might not be possible to have AI *only* open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions. I think it might look something like Photoshop & GIMP, with Photoshop being a frontier lab, and GIMP being the open-weight model. GIMP is decent for many different image editing workflows, but Photoshop is just better. I would definitely prefer to have an open-weight model better than frontier labs'. Though I don't think it's possible.
  • thewebguyd 4mo ago
    I think the same, but I also think that local AI is actually inevitable, even if not open source models. I wouldn't be surprised to see OpenAI and others release an on-prem product. Whether that's effectively an appliance rack, or some other form, people (large companies) are going to want to run inference locally for data sovereignty & cost controls. Especially if we get to a point where companies want AI integrated into manufacturing and other air-gapped networks.
    • george_max 4mo ago
      I do believe that if OpenAI and others release an open-weight model that is better or on par with their frontier variants, it might ruin their primary business model. That is, of course, unless they develop their own hardware specifically to run this open model. But, that does ruin the point of open models.
      • thewebguyd 4mo ago
        When/if gains slow down, I can definitely see branching out into hardware to sell for on-prem inference once the models can be etched into the silicon with hard wired weight chips. I'd guess maybe at least 5+ years away from that though.
        • WASDx 4mo ago
          I think this is inevitable. Sooner or later, model-specific ASIC's will make economical sense. We're already seeing it happening with Taalas/Cerebras so I think it's sooner than 5 years. And inference is order of magnitude faster which is amazing.
    • cocoa19 4mo ago
      We already have this. We don't need Mythos to categorize images on my phone. A small dedicated model would do.
  • deleted 4mo ago
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  • LPisGood 4mo ago
    That is fantastic news then, if commercial product products will always be better than open source, and open source products will continue to get better
    • george_max 4mo ago
      Agreed. The only "issue" is that commercial products will always be ahead, with less friction for most users. This ultimately results in most people using these over open-weight variants. Users might not even be aware that the open-model variants exist. Similar to Windows / MacOS and Linux.
      • kelnos 4mo ago
        In a way that's ok, though? I run Linux on my laptop, and in some ways it's better than Windows or macOS, and in other ways it's lacking. But that's fine; the existence of Windows and macOS doesn't mean I can't run Linux, and doesn't mean I have a worse experience. (Yet; I do worry about future required hardware attestation for basic things, but that's another issue.)
  • bbor 4mo ago
    Which is the nearterm future that we must demand: a stop to the amounts of capital flowing to ASI research. Join me, Anthropic, Google, and OpenAI’s-founding-charter in saying the obvious, y’all; Pause AI, now. It should be clear by now that there’s a whole universe of work to do with the models we have today, from studying to securing to ‘harness’ing. There are tons of economic benefits to be reaped already, if applied carefully. Doesn’t that sound nicer than rolling the dice with the lives of trillions?
    • mufufu 4mo ago
      Lives of trillions?
      • reilly3000 4mo ago
        Current and possible future populations?
  • tonyhart7 4mo ago
    the moat is in hardware, without capital intensive acquisition how tf they going to get that money ????? I learn it hard from prusa 3d printer open model
    • intothemild 4mo ago
      Well. Right now buying hardware to run your own models tops off at about 32gb VRAM at any price point that's not insane. Sure you can get a Mac mini, or a PC equivalent. But the problem is RAM. More RAM means bigger models, which means smarter models. Which is why Qwen and Gemma have been so interesting to a lot of us who run our own... Now 32gb VRAM isn't so bad, as these models can be run on that with decent results. Where this gets interesting is in a couple years, when all the A100, etc, all the Enterprise hardware hits eBay.
  • pennomi 4mo ago
    Perhaps, unless there is a way for users to donate compute to training, folding@home style. I don’t see how that could be practical though.
  • deleted 4mo ago
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  • kelnos 4mo ago
    Yeah I think that's a decent analog (Photoshop & GIMP). We're in a sort of "rapid expansion" phase right now, but unless the tech behind "AI" really evolves, better and better models will be harder to come by, with diminishing returns. Even if the GIMP of LLMs is only 80% as good as the VC-funded stuff, that will still be plenty useful for lots of people. And I think just having the option to use open source models is a win, even if it turns out to be true they'll never be quite as good as the proprietary ones.
  • hirako2000 4mo ago
    Zoom out. It's a matter of time the trillion valuations will be deemed senseless, only once it will prove inpossible to extract trillions from consumers. In the meanwhile, and regardless, software optimisations coupled with hardware continuing to scale, we will end up, soon enough, with some open weight that run on a mobile device with greater capabilities than Fable.
    • rustcleaner 4mo ago
      >only once it will prove inpossible [sic] to extract trillions from consumers. I am spreading a message of peace and sovereignty: Never subscribe. Never. Subscribe. Ever. Starve them out. Make their lenders take 95% haircuts. Just don't subscribe, whatever you do!
      • aerhardt 4mo ago
        This is utopian thinking. The products are way too useful to not subscribe. The argument presupposes the worst-case negative-utility in the long-term scenario (AI companies will create a totalitarian nightmare) and pits it against the radical usefulness that the products are creating right now.
        • hirako2000 4mo ago
          They aren't too good to not subscribe. I've used over a trillion tokens in the last few years with zero subscription. In fact I have one with deepseek, spend 13 cents to test some automation. The rest is consumed free of charge to bleed the bleeders. If/when they ALL enforce paid subscriptions, I will only run inference locally. By then consumer hardware will equal frontier models in term of speed and performance.
  • zozbot234 4mo ago
    > Because of this, I think it might not be possible to have AI only open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions. There's a more fundamental reason for this: some AI models are large enough that they can plausibly only be reasonably run in a state-of-the-art hyperscale datacenter. Open sourcing such models would be largely pointless. Note that this would be a significantly larger scale than even the largest open models available today, one that precludes even doing inference slowly on a small-scale, cheap makeshift cluster. But it's plausible that Fable is there already.
• Phaedruss 4mo ago
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• glerk 4mo ago
  it is inevitable that it will win information wants to be free
  • Avicebron 4mo ago
    Inevitable isn't "in our lifetimes"
  • ks2048 4mo ago
    “information wants to be free” - doesn’t seem correct. More like it’s easier to spread info than to hide it.
    • ijidak 4mo ago
      Intelligence is now data in the form of weights. And once it leaks, it's permanently in the wild. Interesting times.
      • NamlchakKhandro 4mo ago
        "intelligence" K
  • bogota 4mo ago
    [dead]
  • planb 4mo ago
    This is not about information but about capital. Even if we had free access to the weights of the best models in the world: who would be able to run them?
    • glerk 4mo ago
      Technology is deflationary. I am holding in my hand a device that would have been a supercomputer 30 years ago. It costed me a couple of hundreds of dollars. These models and the hardware they are running on will get even more efficient. We are nowhere near the physical limits of what we can achieve.
• em-bee 4mo ago
  what is Open Source AI even? to me Open Source, like Free Software, is something i can run on my own computer. any AI system that runs on a computer that i do not control is by my definition not Open Source. so how then can Open Source AI win? it can't even compete. even if we collect enough money and create a dedicated Open Source organization to build and run a community owned AI datacenter, how does that help? so what exactly is the demand here?
  • matheusmoreira 4mo ago
    We can run open weight models on our own machines.
    • em-bee 4mo ago
      yes, but a model that runs on my own machine will never have the capacity of a model that runs in a datacenter. as i said, it can't compete with that.
      • thewebguyd 4mo ago
        If RAM prices ever come down, you can have a machine that can run a capable local model. Qwen 2.5 72B is surprisingly capable, almost on par with GPT-4o if not a little better. You can run it on a 128GB Mac Studio with 8-bit quantization. You need about 77GB for the weights and ~15GB for your context window & cache. Pricing remains to be seen, but there's also those new nvidia laptops coming out the surface laptop ultra should have 128GB RAM w/ Blackwell GPU, they're saying 1 petaflop of AI compute, if you can tolerate Windows (no idea if it'll boot Linux until the hardware is out). These models are roughly ~1 year or less behind the frontier models. We really just need hardware to catch up and alleviate the price pressure on RAM.
        • rustcleaner 4mo ago
          >If RAM prices ever come down Maybe an unpopular opinion here (seening how Y-combinator is his baby), but I think OpenAI and Sam Altman should be financially decimated for cornering the DRAM market. What he's done is a step or two removed from what the Hunt brothers did. His buy-up of future DRAM silicon has measurably harmed personal computing, and he should not get to walk away with a 'win' from it.
• matheusmoreira 4mo ago
  Winning is a tall order. I'm just hoping it'll get good enough while allowing us to run it locally with no idiotic "safety" controls or censorship of any sort. Looks like the best open weight models are at Sonnet level, if they get to Opus 4.6 level it's gonna be perfect.
• avaer 4mo ago
  I agree with sentiment and mission, but the goal is inseparable from politics at this point. Being Open Source (tm) will not protect you from the government/others imposing controls on your silicon or what it is allowed to do, which is already happening around the world. Even having the models be open source won't fix the regulation or economic incentives. Which is not something you can compress into a couple of paragraphs. AI is civilizational infrastructure and it needs civilizational solutions. Not just source.
  • Atlas667 4mo ago
    Monopoly capitalism and finance capitalism took reigns of markets more than a century ago. The state serves these huge interests. Everybody knows AI firms pirated to train, nothing will come of it. A plain example of classist application of law. The reason for the willy nilly application of their own laws will always be 'national security', of course, since they own infrastructure their interests are a national security. So tech may shake things up whenever it makes great leaps, but finance capitalism quickly adapts and absorbs the waves.
    • rustcleaner 4mo ago
      No state, anywhere, has the right to rule or even exist. All states are terroristic parasite gangs, all states [no exceptions]. Your state exists because there is no one else capable of challenging it [no outsider or internal armed militia]. Your state is merely the gang which reigns supreme in your territory - constitutions, democracy, and other grievance pressure relief systems be damned. You don't get to vote or serve as juror because the system is somehow moral or holy, you get to vote because in historical systems lacking those pressure relief measures the aristocracy tended to be [literally] decapitated on a regular basis. Democratic measures exist to bribe and persuade your acquiescence so you don't get together with your aggrieved neighbours and go lop heads off ["it's just the rules of the game, you can try again in 2/4/6 more years :^)"]. Seeing politics from this lens should demystify so many seemingly confusing actions and outcomes, it's why no matter how much you vote you never actually "win" and even if you do... it's in such impotent and monkey's paw ways.
• impure 4mo ago
  Not to be that guy, but the correct term is Open Weight LLM. And I’d argue it already has. Many open models are already very competitive with closed models at a fraction of the cost.
  • verdverm 4mo ago
    Labs can and do open source more than the weights https://allenai.org/olmo https://allenai.org/olmo
• deleted 4mo ago
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• MaxPock 4mo ago
  Were it not for China, America would have restricted the most advanced models from being used outside the US. NATO members would have access to GPT-4, with some countries entirely blocked from AI. Biden's GPU controls should give you an idea. Thank you, China. Open source AI must win.
  • thewebguyd 4mo ago
    Unfortunately the US is no stranger to using export controls to restrict frontier technology. Famously, the PowerMac G4 was briefly subject to export controls. Apple turned it into a marketing campaign.
  • sanex 4mo ago
    Just happened 5 hours ago.
  • nerfbatplz 4mo ago
    China unironically saved humanity. I'm no fan of the CCP but if they hadn't organized an effort to compete with the US no one else would have done it and we'd be begging our AI overlords for tokens and praying we don't get caught conducting wrongthink. Go ask Claude to criticize Anthropic and see how long your account stays active.
• mrcwinn 4mo ago
  Quick, someone start open data center and open energy system and open water supply.
• CharlesW 4mo ago
  Can we assume that the author isn't using "Opensource" to mean "Openweights"? Or are we still collectively brainwashed by the strategic false equivalence established by Big AI CMOs?
  • AshamedCaptain 4mo ago
    On this very thread you already have people talking about "open weights" and similar nonsense. What is open about them? They're free to download, but that hardly qualifies as open. Where is the source? Where are the instructions to modify and build your own? I'd never though I'd have to utter the expression "open as in beer". The blatant attempt at manipulating vocabulary here is... quite blatant.
    • singpolyma3 4mo ago
      There is no source because it's not software. You can of course modify and make your own.
    • nl 4mo ago
      I'm a strong proponent of Open Source (TM) but I disagree with this take. The weights are the useful artifact here. You can modify them, fine tune them and do what you want with them. Unlike binary software there is nothing limiting that. It is also useful to have access to the training recipes and to some extent the data. But I'm of the opinion that learning on something is not copyright infringement, so there are many circumstances where distributing the raw training data will not be possible. For me this is like Open Office: it is open source, and largely inspired by and learned from Microsoft Office. But they don't need to distribute MS Office for Open Office to be Open Source. In addition there are models that meet the criteria you appear to propose. The AllenAI models are a good example.
      • AshamedCaptain 4mo ago
        The analogy falls apart very quickly. Without the training data, your modifications amount to virtually nothing compared to what these "versions" are, and the idea that you can maintain and improve on these models without the continual support of the company that owns the training data AND harnesses AND in general build instructions is not very credible. This is why it's not rare that they "dump" old versions as freeware but at some point switch to not distributing them, and mostly get away with it. As this is really not open, and the threat of an effective fork is therefore non-existent, the pressure for any one who has released freeware models to "go SaaS" is too high. While if "Open Office" switches to a more problematic license at some point, the existing source has all you need for an organization to support the project without regard to the original company (this has happened already!). If Qwen decides to stop distributing models for download, you're basically stuck, _even_ if you have unlimited resources, it's not clear how the released weights help you; your best bet is to start almost from scratch. This has also happened... These models are not "Open" by any definition of the word. It is just freely redistributable. You can justify yourself in whatever way you want re a cowboy approach to copyright, but this doesn't change the fact that this is not open, and has almost none of the benefits of open, and therefore it is a huge abuse of the word "Open". Ironically about the only thing that is copyrightable here is the sum of the training data (possibly) _AND_ the software used to build the model (most definitely). The model itself most likely isn't (databases are not copyrightable), which makes it even more pointless to abuse the word "open" for it. All the value is in the former two.
• gslepak 4mo ago
  Where does Anthropic or OpenAI winning leave us? Dependents of an AI-megacorp for our "facts"? Our software? Our work? It's possible these companies will become everyone's boss, and will dictate to everyone what everyone is allowed to work on, think, say, do, believe, etc. Before Big Tech springs that trap, we must support and divert resources to open models.
  • malux85 4mo ago
    > Dependents of an AI-megacorp for our "facts"? Our software? Our work? It's worse than this, it's more like our thinking. There's already plummetting math grades [1], handing over our thinking to AI megacorps where there's likely to be a monopoly or duopoly is an incredibly dangerous thing for humanity as a whole. [1] https://www.dailycal.org/news/campus/academics/failing-grades-soar-as-professors-see-greater-ai-usage-dwindling-math-skills-in-uc-berkeley/article_16fad0bf-02cb-4b8c-8d88-888ffd9f8608.html https://www.dailycal.org/news/campus/academics/failing-grade...
    • george_max 4mo ago
      If humanity is over-reliant on frontier labs' models to perform work, the result is a dependence on the actual intelligence of these models -- not on human intelligence. This could be a small reason, on top of many others, why investors are throwing hundreds of billions of dollars a bit "carelessly" to these labs. It's fascinating seeing the models do the "hard work" (the deep, challenging thinking) for you. The conundrum which tricks me though - is this a net negative or a positive? If humans are less intelligent, but their output is 2-3 times more intelligent (with AI), what's the result? At what point do we, as humans, stop comprehending anything and give all intelligent work to the neural nets? And if that does happen, could we live in a society where no work, or at least a significantly less amount of work, is needed? To me, it seems like a dystopian net positive. It might seem far-fetched to ask these, but I think these questions are getting more prevalent by the day.
      • analog31 4mo ago
        It's not just a dependence on the intelligence of the models, but also their intentions, as programmed by their owners. A friend of mine asked me if I was optimistic about AI. I told him, it depends on who owns it. If the people own it, I'm optimistic. If the oligarchs own it, I'm pessimistic.
• nicechianti 4mo ago
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• wewewedxfgdf 4mo ago
  Yeah except for all the money it costs to do well.
• gnarlouse 4mo ago
  [flagged]
• danielrmay 4mo ago
  I hope the news moves this debate past "open weights vs. closed APIs" as the only axis. Open weights matter, definitely, but applied AI also needs open infrastructure around the model and it feels a bit like I'm yelling into the abyss highlighting the future we're incentivizing - cognition rented from a few institutions with access changing based on policy, geopolitics and platform incentives like advertising
• b33j0r 4mo ago
  Available components must win. I’ve often been a critic of open weights and open architectures that give very few normal people access. What’s the point of releasing the plans for a nuclear reactor if no one can have the fuel?
• nektro 4mo ago
  the public only wins once we shut it down globally through treaties like other tech that's too dangerous for anyone to have
  • vitalyan1234 4mo ago
    it is baffling that you can still encounter Yuddite delulu in 2026 when everyone and their literal grandma is using chatbots daily. you might as well campaign to shut down the internet or ban smartphones. but ok, who is going to initiate such a treaty? US? the orange man won't, and even if he did, no one would care. by the time his term is over and the next AIPAC spokesperson is elected, it will be even more late than it is now. EU? impotent and irrelevant. China? lmao.
• palisade 4mo ago
  I've been contemplating a decentralized model training system for some time using volunteer machines that we all contribute. But, it is astronomically difficult. The communication speeds are untenable. And, there is the issue of data poisoning from untrusted nodes. I've almost cracked that last issue with a self-healing checkpointed rollback system that doesn't have to throw out anything that follows the corrupt datum. But, I'm just one person with an idea and I don't have infinite funds to make this happen. This isn't a small project. Maybe there would be interest in something like this, now that entire frontier labs are being banned from making further progress. The total power of all GPUs on the planet dwarf their capabilities, if we had a way to harness them in a distributed way efficiently. We wouldn't be able to train a Fable as fast as them, but eventually having access is better than never having access.
  • thomasjeff1 4mo ago
    I believe we are not the only ones
  • Davidzheng 4mo ago
    Is the total compute capacity outside of meta, google, amazon, anthropic, oai and x is higher than even the capacity of any of them? In any case, there's no chance a public collaboration gets to anthropic levels of compute even if communication were no issue.
    • kelnos 4mo ago
      Is the issue that training with less compute takes more time? Or is it just not possible? I think a collective using distributed training could tolerate the idea that it takes 10x as long as Anthropic to train a model, or whatever.
      • mike_hearn 4mo ago
        It's possible but it's not linear. A modern AI training cluster is a supercomputer that uses very different architectures and hardware to a bunch of small PCs connected via normal networking. The networking advantage alone kills any chance of decentralized training.
• RIshabh235 4mo ago
  our dependency on US AI will lead to data concentration in hands of few megacorps.
• simonuu 4mo ago
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• aryasyn 4mo ago
  Definitely, but I see the gap widening everyday, especially while commercial AI models have started converging towards AGI. However I do believe and support the cause, as it's the next big thing as developers we need to take to prevent a complete monopoly in the coming few years.
  • ai_fry_ur_brain 4mo ago
    "Converging towards AGI" These things can't even center a div correctly half the time. Not everything is code. Just because it generates a shitty SaaS clone for you and that seemed magical, it does not mean we are approaching "AGI". An AGI could design an Oil tanker, manage the project from start to finish, handle all contract negotiations and purchasables, payroll, scheduling. Then it could do that 50x over and start a leading logistics firms. In reality an LLM can't even complete upwork projects that are worth $20 an hour more than 4% or the time. Source: https://labs.scale.com/leaderboard/rli https://labs.scale.com/leaderboard/rli 4% guys, 4%. It cannot complete entry level work on fucking Upwork 96% of the time. Stop falling for the marketing and sorry but an LLM will never be AGI. Its literally just text autocomplete with some RLHF post training, holy shit im losing my mind. I want this hype to end so badly holy shit I need this to end.
    • cindyllm 4mo ago
      [dead]
• AlphaSite 4mo ago
  I think models will be a commodity sooner rather than later. This whole race doesnt matter. First mover advantage is real, but over enough time it wont matter.
• steren 4mo ago
  Wasn't it the point of ... OpenAI?
• abhinavsharma 4mo ago
  Open-source AI can, by definition, never "win". AI is just hillclimbing today, and closed labs can always absorb everything the open world does and build upon it. It doesn't really matter for most use cases, because the way AI is working is capability saturation. https://www.delanceyukschoolschesschallenge.com/the-rising-tide-of-ai-chess-and-computers/ https://www.delanceyukschoolschesschallenge.com/the-rising-t... The only exception to this is fields that are inherently adversarial (to nature or others) and an edge relative to competition matters.
  • kamaal 4mo ago
    >>AI is just hillclimbing today That's what the Fable harness felt like. You give it a goal and it could try to get there through the shortest path given the tree of possibilities to get there. Iteratively, or recursively. Perhaps if we make a open coding AI, the design must be along these lines. Something that's easy to train, and serve from local machines. Albeit has loop / recursive hill climbing facilities built it. That way the model gradually keeps moving towards the solutions, in iterations/recursions. Once this is done, other multi modal things could be pursued.
    • dakolli 4mo ago
      [flagged]
      • kamaal 4mo ago
        Its the closest terminology we have to describe that process. https://github.com/cobusgreyling/loop-engineering https://github.com/cobusgreyling/loop-engineering Its hard to come up with new names for novel processes, you mostly reuse what is close enough and well known.
        • dakolli 4mo ago
          Loop engineering, whatever that is, is obviously just a way to get people to increase the amount of tokens required per task/request. They did the same thing with Ralph loops, they just need more revenue. Just write your code and use it to search and clarify, it can't build that magical thing you think it can.
• WarmWash 4mo ago
  Who is going to fund it? Training is unfathomably expensive. You have either VC funded models looking for a return on investment, or CCP funded models looking to solidify authoritarian "model Chinese society". Maybe there are some university 4B models, but I doubt those will carry far.
  • brcmthrowaway 4mo ago
    Who funds Semiconductor fabs
    • nullbio 4mo ago
      When Jensen (Nvidia) was doing interviews at his recent public talks, he was asked something along the lines of: "Why release these new laptops which are a low margin market, if your other businesses are vastly more profitable?" and his answer was basically that if they can build the coolest and best technology and push the frontier, they will do it. It's not all about making tons of money. He seemed genuinely excited about the tech. It highlights the difference between companies like Nvidia and Anthropic to me, where one is clearly all about the money and power, and the other is doing it because they genuinely want to accelerate progress and make cool stuff as the driving factor. It's no surprise therefore, that Nvidia is the worlds largest open-source contributor to AI, with over 800 open-weight models. Of course, these models run on Nvidia hardware, so they benefit from it as a company. But with that healthy mindset, they found a way to contribute that not only benefits everyone, but also benefits themselves. Contrast to Anthropic, who has gone the complete opposite direction. Closed off everything, restricting everything, fearmongering progress, regulatory capture attempts, the list goes on. I mean, they won't even agree on using AGENTS.md as a standard because CLAUDE.md is free marketing for them. That's the level of disgusting greed we are dealing with... From a game theory perspective, the cooperative strategies tend to win. As a result, Nvidia has set themselves up for a lifetime. Anthropic however, is playing a strategy of winner takes all, and they're happy to see the world and the entire AI industry collapse in the process.
      • cwnyth 4mo ago
• ninjagoo 4mo ago
  Open source ai will win. Anthropic just kneecapped themselves, and possibly OpenAI and Google as well, with their FUD strategy that got fable shutdown by the government. But that doesn't impact Chinese providers. Then can US companies get investments for expensive model development if they can't actually sell those models-as-a-service? In the meantime, open source will continue its march onward because while slower, it's completely open source, and the models are already good enough to improve their own work as well as build out the next gen of models.
• alexwwang 4mo ago
  I hope so. But how? Who gonna fund these projects and how to coordinate with every sides. This is complex. I only believe that the open source AI won’t lack users.
• deleted 4mo ago
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• SubiculumCode 4mo ago
  Civilization is at a crossroads, or will be soon. Democratization of AI can be good up to a point, but existential threats can also be real, and democratization of existential threats is not a survivable policy.
  • nullbio 4mo ago
    It's actually the opposite. Democratization of intelligence is the only way to stop existential threats and render them useless. Right now, and likely forever, because biological threats can be sanctioned at a supply-chain level, the risk of AI is all digital. Fraud, phishing scams, spam, hacks, etc. The only way we harden the worlds infrastructure to the point that it can withstand attack from bad AI is if we have an abundance of access to frontier intelligence to develop countermeasures. Otherwise, bad actors will develop these capabilities behind closed doors and use them to hold the world hostage and cause irreparable harm. There's no putting the genie back in the bottle. Good and open-access AI and the people using it are the digital immune system. If there's an asymmetry where bleeding edge is gated off to only a small group, and allowed to gain exponential power over the immune systems defense grid, the slightest infection will lead to death of the host.
    • SubiculumCode 4mo ago
      That's a thesis.
• oliveiracwb 4mo ago
  [flagged]
• threethirtytwo 4mo ago
  The only way for open source to win is for closed source to provide the compute resources. That’s really the only thing stopping people from training or running these models at home:
• ramcrissesangry 4mo ago
  As an person whos getting into tech and already developing a game, the fact that laptop prices since 2020 have increased by 20-40% is insane. It's delaying the time to create my game. I researched the reason for the cost spike, and most of it is from the excessive money put in ai Technically, the owners of AI could slow down the amount of GPUs and RAM they buy because AI has almost reached its most usable peak. Everything they add just introduces more bugs, so instead of building more AI centers, they should focus on improving the main AI model with bug fixes. There's no need to give it more unnecessary power. Most people don't care; the entire business is run by a few old men who think AI is everything and invest huge sums of money to show other AI companies they need to improve to get more funding from old people. We just need to find something new and innovative for older investors to focus on, so not everything is about investing in AI like Roblox, OpenAI, Google, etc. The extreme amount of reasoning power given to AI is causing bugs, and the moments when AI had outbursts towards people are related to this.
  • dakolli 4mo ago
    Why have you sent this same message multiple times?
    • ramcrissesangry 4mo ago
      I didn't know how this worked I thought it deleated it, at first.
  • echelon 4mo ago
    > because AI has almost reached its most usable peak It doesn't seem to be showing any signs of stopping. Have you used Fable 5? It's a fantastically capable model and trumps anything that came before it. Seedance 2.0 is categorically the best video model, and it's only a few months old. > the entire business is run by a few old men Startups tend to skew young, and in this case it's no different. Most of the leaders of AI companies are decades younger than the CEOs in other types of industries. > who think AI is everything and invest huge sums of money to show other AI companies they need to improve to get more funding from old people. They're spending capital to win market share and to try to build a moat. One of the most important things in business is building a durable way to keep competitors from taking your market. You spend enormous capital to win customers, and it would suck if other businesses could watch what you did, spend less money, and come in and take everything away. The money being spent is an attempt to have a durable lead. It's working. Enterprise contracts are deep and sticky tendrils that work through governments and large companies. Both OpenAI and Anthropic have massive partnerships with Fortune 500s, the DoD, you name it - and these contracts will last and print enormous amounts of money. This makes it incredibly hard for other players to enter the market and build a cash flow with which to compete and thrive. > find something new and innovative This is easier said than done. It's an incredibly hard problem. It took decades to find the last big technological waves: the PC, the internet, broadband, smartphones. Now AI. These are generational step function increases. The groundwork can be decades old, but it takes time to proliferate before it can become a big business. Other possibilities include fusion, green tech, quantum computing (useful for crypto breaking, etc.), AI drug discovery, etc. If you go into research one day, try to find an interesting field with potential for commercialization - that could make you very wealthy if you find something you enjoy working on, with lots of greenfield opportunity, that is ripe for turning into products. Good luck with your game! You should post it here on HN when you finish. You'll get lots of great reviews, comments, and early players. :)
• manoDev 4mo ago
  Don't worry, open source AI will win. There's a reason everybody is desperate to IPO fast and get an exit, their competitive advantage is not lasting long.
• digitaltrees 4mo ago
  I fully support this. How can I help?
• earth2mars 4mo ago
  This should be the top post. Not Anthropic or OpenAI marketing plots. This is existential.
  • echelon 4mo ago
    It's too late. You can one-shot a port of Linux to Rust and stop contributing to open source. The value of software is going to tend towards zero. The value of the software developer the same. Anthropic is now a kingmaker. It gets to decide which businesses get the expensive private model that can generate entire business functions at the drop of a hat. If you can't afford the price tag, then competition in the market is not for you. Computing is no longer "personal". It's for big biz only.
    • slopinthebag 4mo ago
      > You can one-shot a port of Linux to Rust and stop contributing to open source. Touch grass brother. Seriously.
      • alecco 4mo ago
        GP is exaggerating but I am convinced this will happen sooner rather than later. The improvements in AI are truly exponential if you read the SOTA papers. It's hard to keep up week to week.
• guybedo 4mo ago
  i guess this fits: https://thealliance.ai/projects/tapestry https://thealliance.ai/projects/tapestry
• z0ltan 4mo ago
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• z0ltan 4mo ago
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• egonschiele 4mo ago
  I have been working on this exact problem, and I suppose now is as good a time as any to talk about it. To make any agent "good", there are two components: the model and the harness. Very few companies can train models, but anyone can build a harness. How much does the harness matter? Can I build a harness that's good enough that I can use open source models with opus level performance? That's the question I've been trying to answer by building better harnesses. None of the existing frameworks have the functionality I need to build a good harness. The features I need are language-level... and so I started building a language called Agency[0]. It's been six months and its going well. Some of the things Agency can do are wild: - It can pause and serialize execution at any point, making HITL easy - It has some neat safety capabilities such as handlers[1] and PFA[2] - You can bundle up any agent as an HTTP or MCP server[3] - I'm now working on a built-in optimizer to optimize agents (think DSPy). Obviously, it's a huge undertaking, but having worked with the Agency for six months, I can't imagine going back to another framework. It makes things so easy. I'm working on its built-in agent now [4]. My goal it to get it to be as good as Claude Code, but using open source models. It's still early days, lots of rough edges, but if this sort of thing interests you, I'd love to have a few more people test it out. [0] https://agency-lang.com https://agency-lang.com [1] https://agency-lang.com/guide/handlers.html https://agency-lang.com/guide/handlers.html [2] https://agency-lang.com/guide/partial-application.html https://agency-lang.com/guide/partial-application.html [3] https://agency-lang.com/cli/serve.html https://agency-lang.com/cli/serve.html [4] https://github.com/egonSchiele/agency-lang/blob/main/packages/agency-lang/lib/agents/agency-agent/agent.agency https://github.com/egonSchiele/agency-lang/blob/main/package...
• pipeline_peak 4mo ago
  Open source projects are only successful when they make what they replace obsolete. This worked with Linux and GCC but this isn't gonna work with LLM's. Who's gonna pay to power an open source AI? Will it perform well enough to make Chat-GPT and Claude obsolete?
• gigel82 4mo ago
  But if "they" stay on the current trajectory we'll never own hardware capable enough to run the open source AI. They want us to rent everything from the cloud and never own it. If a government-supported cartel forms around this idea (which appears to be the case) that's the end of it.
• jmyeet 4mo ago
  So I've long said that the valuation of OpenAI at a trillion(ish) dollars depends on OpenAI "winning" and "owning" AI and there being a sufficient moat to stay ahead of competition. Without that, the company is worth a fraction of that. Anthropic is probably positioned better here actually but it's still kinda true there too. Ever since a Chinese firm released DeepSeek I immediately came to the realization that any US tech firm "owning" AI is simply not going to happen. China will make sure of it. It's in their national security interest not to let that happen. From the POV of geopolitics, IMHO the US shot itself in the foot by banning the export of the best chips to China. The US also somehow has the power to prevent a Dutch company (ASML) from selling to China too. That makes a little more sense to ban but the combination of banning EUV exports AND banning the best chips sowed the seeds for the destruction of all of this. By banning chip sales, the US inadvertently created a captive market for Chinese chips with Chinese companies. If there were no chip ban, Chinese companies probably would've bought US chips. But they can't. So they can only buy from Huawei and SMEE (indirectly). The US forced China to realize it was in their national security interest to copy the best lithography and, by extension, the best AI chips. So DeepSeek was reportedly developed on either older NVidia hardware or smuggled newer NVidia hardware but that won't last either. At some point it'll be completely Chinese made chips that are doing this. And what's the biggest cost for a model? Training. But you do that once and the model like any software is infinitely copyable so China can under OpenAI, Anthropic and SpaceX (xAI) and that's what they're doing. But it gets worse for the AI moat. Local models are going to get cheaper and cheaper to run. You can already run 31B models on sub-$5000 hardware. What do you think it'll cost in 5 years? Will larager parameter models keep getting better or will there be a law of diminishing returns? What is a B100 workload now, will be a Macbook Pro workload in as little as 5 years. What if all these AI data centers are ultimately just going to be commoditized cloud hardware like AWS in the not too distant future? We already see Google renting big from SpaceX. I think the writedown on all these data center investments and the companies that are doing them is going to be extreme in the next 5 years.
  • rustcleaner 4mo ago
    Never thought I would say these words, but: Good Guy China! :DDD
  • 4mo ago
• bluejay2387 4mo ago
  In the US -- once our nation finishes attacking our own education system -- this is definitely something a group of academic institutions could get together and accomplish. I assume the same is true in other countries. Companies like Nvidia and AMD might even support that effort, as they make money on the hardware and would probably be more than happy for there to be more reasons to use it. There may have not been a compelling enough motivation to achieve this before, but "models" didn't have this level of strategic relevance until relatively recently. Nvidia has been fairly good about releasing open weight models in the last few months.
  • google234123 4mo ago
    Wait, which side is blocking kids fork taking algebra or forcing universities to admit people that can't do math or read, or abandoning phonetics for unproven methods that don't work?
    • defrost 4mo ago
      It's the US, both "sides" of that coin are bad with examples pro and con all over the shop. Still, to specifically give a partial answer to your poor faith rhetorical just askin' musing: Florida Conservatives (specifically turfing nerds from New College of Florida and bringing an excess number of baseball sports bro's to a place that likes math and has no baseball field)
    • Natfan 4mo ago
      stop talking please https://www.usatoday.com/story/news/politics/2025/05/22/oklahoma-schools-teach-2020-election-big-lie-trump/83731606007/ https://www.usatoday.com/story/news/politics/2025/05/22/okla...
    • rustcleaner 4mo ago
      Both sides, since they are bought and paid for by the finance industrial complex.
  • hellosputnik 4mo ago
    [flagged]
• mhog_hn 4mo ago
  At d5s.tech we are recreating the layers built on top of models, working on dogfooding our own product to run a large chunk of the company. I feel extremely strongly that a future in which most companies depend on one or two large AI-megacorps is going to lead to excessive rent seeking sooner or later. I remain positive that the long term steady state will consist of proprietary models, -but- with open source AI models statistically close. If compute keeps growing the relative cost of training current frontier models will decrease. An open source Fable/Mythos model simply seems inevitable.
• xmly 4mo ago
  Totally agreed!
• MuffinFlavored 4mo ago
  Did open source phones win? No, iPhone is pretty dominant. Did open source operating systems win? No, MacOS/Windows are pretty dominant. Does open source... cloud hosting, social media, ride sharing apps, you name it win? Not in my experience?
• sreekanth850 4mo ago
  I feel with current government decision to block Fable, this is not a mere opensource issue, considering how US government restrict frontier models, what we need is sovereignty for every country. If not they will release every model with a kill switch in future like F35.
• deleted 4mo ago
  [deleted]
• never_inline 4mo ago
  I think articles this light on content should not be upvoted to front page.
  • ls612 4mo ago
    I think that the events of this evening (really of this past week) are almost unprecedented in the history of tech. Sometimes a clear and concise message is more important than nuanced analysis.
  • 3s 4mo ago
    It's a perfect prompt for a rich HN discussion so while in general I agree with you, in this case the discussion is what matters.
    • raffael_de 4mo ago
      This is almost always the case. Discussion quality went down during the last few years but HN is still _the_ place to attract people who really know what they are talking about.
      • never_inline 4mo ago
        I find that most arguments are endlessly rehashed. I would be like if most AI related discussion limited to maximum 2 / 3 most important news per day.
• raushan__ 4mo ago
  If we can't stop these big AI companies, we must to put force that everybody can see what they are hiding from us.
• rustcleaner 4mo ago
  Never rent. Never subscribe. Subscribing is cuck paypig behavior. You're not a cuck paypig now, are you? Pass this on to your frens, it may save the future!
• giancarlostoro 4mo ago
  I mean, even if the frontier labs opened their frontier models, only nation-state level actors are capable of running them. A lot of the tech is very open and known, its putting it all together that's the struggle.
• m3kw9 4mo ago
  It likely won’t based on how SOTA are developed.
• d--b 4mo ago
  It’s the GPUs, not the weights that are the key. As long as these models require a lot of computing power, the best models open source or not will be served by corporations who can afford the infra.
• themafia 4mo ago
  Given that it's most public use in open source so far is to whitewash GPL code into MIT code, no, I'm sorry, I don't think "open source AI" is particularly important.
• rustcleaner 4mo ago
  [flagged]
  • DonHopkins 4mo ago
    Instead, how about an open source robot that happily punches Nazis, drunk drivers, people who want to write racist poems, and unhinged trillionaire ketamine addicts who pee their pants, throw Nazi salutes, and hate their own trans daughters?
    • rustcleaner 4mo ago
      [flagged]
      • DonHopkins 4mo ago
        Then perhaps it should also punch foaming at the mouth libertarians, too. A society that maximizes individual freedom with no guardrails also maximizes freedom for fraudsters, polluters, violent extremists, drunk drivers, kiddie-porn-producing social networking xAIs, and people who use power to dominate others. At that point, the liberty of the strongest starts eroding the liberty of everyone else. Funny how 'current-year ideology' never seems to include libertarianism. Be the fish that notices the unregulated toxic polluted water. Also be the fish that notices it's swimming in libertarian Kool-Aid. Edit: Speak for yourself about how frustratingly hampered you are by society's guardrails. Stop whining and predictably regurgitating tired meaningless libertarian bullshit slop like a human stochastic parrot, and just write your own racist poetry and photoshop your own kiddie porn without the help of an LLM, if you really must. But restrict your drunk driving to off road, with just your own family in your CyberTruck, so you only cleanse your own genes from the pool.
        • rustcleaner 4mo ago
          [flagged]
        • DonHopkins 4mo ago
• inciampati 4mo ago
  There is nothing more surreal in AI chat than entering your own name and being told you are a banned topic. Open source models must win. There is no alternative.
• jcadam 4mo ago
  Well, the crazy thing I'm working on (100% self-funded thus far): https://trivyn.io https://trivyn.io. The main idea is moving most of the reasoning to the symbolic layer so the "neuro" piece can be a small model able to be self-hosted on reasonable hardware.
• MattyRad 4mo ago
  Not to distract from the message, but I appreciate that this is largely plaintext not React vibeslop.
• rokpiy 4mo ago
  [flagged]
• MobiusHorizons 4mo ago
  If open source AI was better than what it is currently chasing, wouldn’t that take away the incentive for these companies to give it away for free? Training is expensive and companies will need to recoup those development costs once it stops being about jockeying for position.
• 18al 4mo ago
  What does the author mean by "win"? Does he mean that the _best model_ should be an open source one (eg: today, something better than Fable 5), or just that open source models should be the default choice for most task? The former seems an impossibility, closed labs can work off of open and their own closed research. Closed source will always be better. Well, at least until some late-stage enshittification dynamics cause the providers to hobble them. The latter, becoming a default, not so much. But considering the deep-rooted nature of (for instance) Google, it certainly won't be a walk in the park. This seems to be a similar hurdle as dethroning Chrome as the default browser. For the average ChatGPT user, I surmise that open-source models are already capable enough. Most people I know who use it (me included) are not paying for it, they are routed to the cheaper models. What's needed here is everything else other than the model to be in place. Which is to say there isn't a sufficiently good open source ChatGPT app, every open source option requires more fiddling than the ChatGPT app. No precedent comes to mind for non-tech-user software that is open source and also a default choice. The limitation is rarely from the core-tech capability; core-tech is often the same as what closed source uses.
• jtesp 4mo ago
  what if grok went open source and was on par with open chinese models? the business play may not be the models themselves but owning the data centers and running infrastructure for all models from all companies? a lot of people could then be rooting for xai and elon could ironically save face by actually implementing an open model
  • dyauspitr 4mo ago
    You can do that now. There are many different providers for Deepseek already.
• blueblisters 4mo ago
  I'm assuming this is popular because of Fable restrictions. AFAIK, open source is not excluded from ITAR / EAR restrictions (or other export restriction in other countries). So the real solution you're looking for is technology that can't be arbitrarily gatekept by a sovereign nation.
  • cududa 4mo ago
    I’ve been exceptionally displeased with Claude Code since end of February and switched completely to Codex in April. The blasé way in which one person (Borris) capriciously changes the system prompt multiple times a day, also no longer writing his own prompts (whatever that means). That, the 5 different secret levers you have to pull to make it not stupid, the fact you hs e to go to the guy’s twitter account to find all the un-dumbing features and flags that aren’t documented anywhere else. That they decrease thinking budgets silently when they run out of compute instead of announcing the rationing, and gaslighting users at every step of discovery. The fact that internally they have their own coding harness and don’t use Claude Code primarily. The lack of formal evals and consideration for millions of users collective hundreds of millions of hours of investment in their workflows — that’s all off the top of my head, let me tell you how I really feel about what they did to Claude Code.. I adore gpt5.5 and maintain my own codex fork - but I have no idea how long I’ll get this performance / cost - I know it won’t be forever. I’d like to know precisely how much it’ll cost in hardware to run a gpt5.5 open source model locally. Hell a lifetime license to a model I can run locally is also be open to. But I like building my own tools, from software to physical shop tools. I like being able to rely on my tools. More responding here to the assertion that this is blowing up due to Fable.
• simianwords 4mo ago
  This will never work - a strong enough LLM model will also let you synthesise bioweapons etc. How can you release this to public?! Why else do you think Anthropic is heavily restricting Fable? You can’t just handwave safety concerns.
• zuzululu 4mo ago
  It can't. Hear me out, economies of scale can only be met when there is a large enough liquidity for it. The amount of people willing to purchase multiple hardware releases year after year just to run LLM is already tiny and businesses already do use their own hardware and there is no desire for manufacturer to reduce their own margins.
• dinkumthinkum 4mo ago
  If any AI wins, how can that be good for humans? It's high minded but if any AI wins, why would any of "The ability to study, build, repair, deploy, audit, adapt, teach, preserve" be important? Is the real problem to be solved something else, if you want those things?
• medmarrouchi 4mo ago
  I vote that you become the next Richard Stallman
• notrealyme123 4mo ago
  Are there any platforms to discuss this? (Like matrix/zulip?)
• FabCH 4mo ago
  While it is not at all practical to train an LLM with tens or hundreds of billions of parameters on hobbyists hardware, what if there are other architectures that perform just as well but are easier to train by 1000 volunteers? I always wondered if 1000 1M parameter models fine-tuned to specific tasks with a small router could perform as well as 100B models. And I know this is roughly how MoE works, but current MoE models still require training the model as a whole, and big players don’t have an incentive to change that. But OpenSource community does…
  • logicchains 4mo ago
    It is practical, albeit not as efficient: https://arxiv.org/abs/2603.08163 https://arxiv.org/abs/2603.08163 . But organizing enough people with decent-enough GPUs is the challenge.
• TowerTall 4mo ago
  And it will, but be patient. I took linux 25 years to conquer the world. One day an open source model reaches "good enough" level. Maybe around the level the current frontier has and most people will use that
  • tomashubelbauer 4mo ago
    I don't even need today's frontier, give me a local model I can run on my Mac comparable to Claude 4.5 as of December last year and I'll probably lose any interest in new hosted LLM advancements altogether.
• imjonse 4mo ago
  A website stating the obvious, given small target audience it will probably reach, and a call to arms consisting in emailing a random unknown person. We're saved /s Instead of doing a vanity site with a shelf-life of a few days, see where the action already is in online local LLM research and communities and contribute.
• olalonde 4mo ago
  Isn't that OpenAI's mission? "Our mission is to ensure artificial general intelligence benefits all of humanity." /s
• devkakadiya 4mo ago
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• devkakadiya 4mo ago
  [flagged]
• devkakadiya 4mo ago
  [flagged]
• eunos 4mo ago
  My grim view is that it's just one incident away from some evil freaks to use ablated offline model for some nasty acts to have lawmakers lose their mind and try to regulate open source models and even consumer GPU. Think the latest 3d printers restriction.
  • zozbot234 4mo ago
    > some evil freaks to use ablated offline model for some nasty acts If this is a serious concern, why hasn't some red teaming effort demonstrated this possibility already? The fact of the matter is that ablation can't give a model world knowledge it doesn't have as part of training, it can only make the model confabulate. The "nasty" areas of concern are most notable for their world-knowledge requirements, which is where local models are at their weakest anyway.
    • eunos 4mo ago
      > why hasn't some red teaming effort demonstrated this possibility already? I'm sure they have but as usual we are a reactive society than proactive. Only when incident has occurred then we have momentum to act.
• jpalomaki 4mo ago
  Isn't training material the biggest problem for truly open source LLMs (such that could compete with top tier models)? The computation part can be solved with money, but compiling a comprehensive training set that could be freely shared and free of copyright issues is pretty much impossible.
  • reedciccio 4mo ago
    You don't need to have fully copyright-unencumbered datasets to build Open Source AI, as that (as you say) would be impossible. https://opensource.org/ai https://opensource.org/ai
  • ajdegol 4mo ago
    I wonder if we could gamify and democratise it somehow, like fold-at-home and wikipedia... I've been training a teeny specialised model to run in a browser on a phone to detect harmonium notes played in a song (harmonium turns out is a pita, another story for another day), getting good labelled data is _all_ of the hard work. That being said, maybe for cheap inference, using a big model to train something ultra-suited for the task at hand might be how we could handle local inference; thinking language specific models.
  • dorfsmay 4mo ago
    Didn't the courts decide that if it's just for learning everything is fair game?
• borzi 4mo ago
  I'm already coding more with DeepSeek than Opus, I'm doing my part :)
• justindotdev 4mo ago
  we could've been fine with the sole existence of AI if the organizations providing them weren't greedy and rug-pullers. anthropic could've been loved by all if it acted towards the benefit of humanity. as intelligent system continue to become smarter, close or beyond mythos level, what now? with the 'community-driven' mindset we have, is the future really going to be safe? probably not we just need a company that develops, serves, maintains, these models the right way, priced fairly that benefits the user and the company.
• guesswho_ 4mo ago
  [dead]
• aberzun 4mo ago
  It will win - in the sense that AI too will become a freely available resource. You can't stop progress. My bet is that once cost-efficiency becomes a priority, we will figure out ways to get away from the expensive GPU infrastructure on figure out how to architect models for CPUs. I still remember that Microsoft paper about ternary weights.
• lying4fun 4mo ago
  I’m sorry I can’t read past the first paragraph
• FrojoS 4mo ago
  What about pirated models?
• _pdp_ 4mo ago
  There is not much open source AI .. there is open weight .. but anyways. Deepseek v4 is pretty much at the same level as the agents we had last year around November and it is an open weight model so I am hopeful.
• ThejaCH 4mo ago
  I am really curious how long will it take for the open source models to hit current fable/mythos capabilities, KIMI 2.7 was launched recently and its quiet good for open source models its as good as Opus 4.6 maybe in practical applications not benchmarks so like 6 months to an year behind, after which the next step will be to wait for the day when we will be able to run mythos level intelligence on local hardware, Remember when 5MB storage was the size of a table? A loooooot of work to be done for the above to happen
  • yogthos 4mo ago
    There are two parts to this too. One is the raw model capability and the other is how well the harness guides the model and meets its expectations. I really think for stuff like agentic coding, this has to be treated as a package. This is my favorite example of how much difference a harness can make even for a tiny model https://github.com/itigges22/ATLAS https://github.com/itigges22/ATLAS And you're bang on with the storage comparison, we're basically in the mainframe era of this tech, but there's no reason to think that it won't get optimized to the point where you can run the equivalent of current frontier locally.
    • ThejaCH 4mo ago
      The repo is so cool!
      • yogthos 4mo ago
        It's really neat project, gives me a lot of hope that we'll be able to run local models to do most of the work in the near future.
• high_byte 4mo ago
  even if the most powerful ai is open source and let's even assume runs on consumer hardware - in the end data is the real moat. if it can access private data it will necessarily have more power.
  • flawn 4mo ago
    Let's abstract this further: It's about the user's existing power and intentions, meaning if I am already in a position of power, AI will multiply it to levels way beyond a peasant could. Power dynamics just get exacerbated.
• ralfd 4mo ago
  If you take AI risk seriously then Open Source AI should not and must not win. Both by evil actors (biological weapons research) and the danger of unaligned AGI itself. There are some people who would never work for the military or Anduril (automatic weapon systems), but an OS AI „without asking permission“ would be the same.
  • joshuaissac 4mo ago
    If closed-source AGI wins, it is not going to be much different from a safety perspective anyway, because AI capability research is advancing faster than safety research.
    • ralfd 4mo ago
      Closed Source AI at least can be controlled. See the directive of the US government regarding Fable (even if one disagrees about the directive there is no doubt that it is effective in shutting it off) or the safe guards by a corporate structure (even a profit driven one). It is schizophrenic to praise Anthropic for refusing the Department of War full access to their models but at the same time root for Open Source models. Edit: relevant Scott Alexander article from today https://www.astralcodexten.com/p/my-ai-opinions https://www.astralcodexten.com/p/my-ai-opinions > In terms of bioweapons, I expect that closed-source AIs will be heavily optimized against helping with these, and open-source AI will be banned after the first warning shot (or become economically prohibitive even before then).
      • zozbot234 4mo ago
        Note that warning shot in that blog post means specifically a near-disaster event (perhaps one that's just barely averted) that's specifically caused by the AI. So far we've had AIUI no significant indication of open-weight AIs being problematic in that sense, whereas one can quibble that proprietary AIs have done dumb and dangerous things. (For example, I suspect that plenty of folks would view the recently threatened mass scan of the DN42 hobby network as an instance of misaligned agentic behavior that would have wasted non-trivial resources, and I also think that most observers would pin the specific behavior of that AI on a proprietary SOTA model, not an open one. That's clearly not a disaster-level event, but it should scare you if you're concerned about alignment.)
• monster_truck 4mo ago
  If you've been writing off Deepseek V4 Pro, now is your time to go set up moonbridge and give it a shake. It's exceptionally good. Got a bit more than 1B tokens for $10, it's exceptionally fast, it was able to fix/implement things that 5.5 xhigh struggled with, without trying to act like my best friend or do that coy "undersell the ideal end result so that it can later overshoot it and claim a great success" bullshit. E: miss me with the "but China" BS, everything I've experienced while using this model has convinced me they are earnestly more concerned with doing the right thing than Anthropic could ever pretend to be. And if you want to ask it questions about Mao, you can go download the weights and spend mid-five-figures to fine tune that out.
• tim333 4mo ago
  The article doesn't say what it means by win. I presume we will have the present situation where the cutting edge stuff is closed source developed by profit oriented companies and open source is available two but a year or two behind.
• Folcon 4mo ago
  A question I've got which I've been wondering about, not sure if anyone else has been thinking about it, what actually made Fable so effective? From what I could tell from the very little time that I had to interact with it, it's instruction following seemed more consistent The other thing that comes to mind is a lot of people commented on how driven it was, so I'm wondering whether figuring out how to keep existing models looping on task might actually be quite a big shift in capability
  • softwareseko 4mo ago
    [flagged]
  • sothatsit 4mo ago
    The big AI labs are also accumulating huge datasets of expert work in a wide range of fields, which is very expensive to re-create. It seems pretty plausible that this this gives them a big advantage that is compounded by their larger training runs and larger models.
    • Folcon 4mo ago
      This is a differentiator, definitely, however I'm honestly not sure if that materially improves intelligence vs one-shot capability
  • CuriouslyC 4mo ago
    Fable had mostly the same pre-training data as Opus, and it's likely they're distilled from the same source. The difference is that it's a larger model with more post training on "dangerous" stuff they didn't want in the core model, and "long" task RL.
    • gordonhart 4mo ago
      > it's likely they're distilled from the same source Any credible references for this? The implication that Anthropic has an even bigger and better model that they haven't released is hard to believe.
• rurban 4mo ago
  That was sama's and elon's original goals before they became trillionaires. Just to keep google/deepmind to take over. Turned out both assumptions were wrong. You couldn't trust sama to turn this into open source, the Chinese did. Elon never. And we couldn't see demis take over as expected, probably blocked by Google buerocracy.
• khalic 4mo ago
  The latest US gov meddling in the Fable rollout really put the nail in the coffin. We can't integrate a strategic product that is subject to the capricious behavior of the US
• shafkathullah 4mo ago
  Truly, big corps have no incentive to invest in open source local AI. I maintain a small effort towards this goal here at https://pocketweb.tools/ https://pocketweb.tools/
• arisAlexis 4mo ago
  ok just explain the cyber attack and bioweapons risks like we are 5. Didn't you think of that? come on
• lninyo 4mo ago
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• s_ting765 4mo ago
  Well, open source AI is mostly coming from China. Title should have been China must win.
• huflungdung 4mo ago
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• sanbor 4mo ago
  I would be totally willing to pay $50 per month to support an open source AI lab, rather to get open source models as byproducts of corporations.
  • onlyrealcuzzo 4mo ago
    Well, AI labs are spending hundreds of billions, so you're gonna need a lot of subscribers to compete...
    • sanbor 4mo ago
      Good point. I currently choose to give money to Anthrophic rather than OpenAI because they align a tiny bit more with my values and the product is good. Perhaps releasing an open source model every year could be a differentiator from competitors, where enterprise and individuals choses the lab not because is the best model out there but because gives autonomy in case something happens to the organization providing the models.
    • TaupeRanger 4mo ago
      For now. Progress in hardware/model efficiency is one of the threats the big AI labs face, because if LLMs become commoditized they can’t make back the billions they spent.
  • raincole 4mo ago
    I think OpenAI ruined the trust. How do you know this 'open source AI lab' won't somehow spin off a for-profit?
    • killerstorm 4mo ago
      We just need to make it on blockchain so it is immutable. <ducks>
    • curioussquirrel 4mo ago
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    • 4mo ago
• p_snapshot 4mo ago
  This should definitely attract a lot of contributors
• derekhsu 4mo ago
  Open source AI wins means China wins
• OJFord 4mo ago
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• qsera 4mo ago
  I would also want all conversation with AI to be public, searchable and indexable. It is only fair, give that LLMs are enabled by human generated content from the Internet, that they give it back!
• WillAdams 4mo ago
  The win I'd really like to see would be for remuneration of training data, and for a provenance of all the data used by a given LLM.
  • softwareseko 4mo ago
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• b3ing 4mo ago
  I agree but we are dependent mostly on Chinese models at this point to pull it off.
  • vorticalbox 4mo ago
    where they came from doesn't matter so much so long as they are open weights and I can run on servers I control.
    • puttycat 4mo ago
      The final weights in themselves don't tell you anything about what went into the training process, e.g censorship.
• c7b 4mo ago
  Since it's not mentioned in the article, the distinction between open source and open weights is important. Open weights models are almost like a 'first shot is free' entry drug. Without at least the original training data your ability to meaningfully upgrade it is so limited that its utility will quickly fall behind the latest versions of continuously developed models. So much that it'll leave you craving for another release, or have you going back to the provider's API. Even simple things like moving the knowledge cutoff forward will noticeably improve the UX, and that's not to speak of more fundamental improvements like reasoning, quantization-aware training and all the goodness that's yet to come. Sure, we can do research to bring improvements to open weights models, but it's the same thing: it's either open source or it won't benefit the general public nearly as much.
• txrx0000 4mo ago
  > If intelligence becomes something people can only rent from a few closed institutions, the public does not just lose software freedom. It loses operational freedom. And people do not just lose operational freedom. They lose the freedom to think, much less act. To some extent, general intelligence has already been outsourced to a few companies. Phones and computers extend the human mind's capabilities, but most people don't have root on their phone. They don't know or control what software is running on it, or how the hardware is made. They don't control their phone, the phone controls them instead. The upstream problem is ownership of general computation, ownership of your own mind, aka self-ownership. This will become more obvious as computing devices become more personally integrated (desktop -> laptop -> smartphone -> smartglasses -> neural interface). Who owns the digital part of your mind? It's not really you at the moment. Democracy, or any form of negotiation, can only exist among entities with similar capabilities. The gap must be very small. Orangutans may be smart enough to drive a golf cart, but there are no orangutan citizens in a human democracy. So you cannot run from this by being a luddite hermit in the mountains. When the world is full of digitally computing humans much smarter than you, you'll be at their mercy like monkeys are at the mercy of humans. We destroy their habitats and experiment on them as we please. Now for the first time in history, organisms can increase their own information processing capability at will. We're in the middle of a speciation event where humanity splits into those who own the digital part of their mind vs those who don't, and there will be further splits based on how much compute you own. Though a future where no individual can fully own their mind is also possible. By "own", I mean being able to command the entire technology stack. If we want sovereignty for the masses, then we must decentralize the entire technology stack for general computation. That means everything from electricity generation, to chip design and fabbing, to all layers of software from firmware to neural networks. All of it must be accessible to every individual. Everyone must be able to make a computer from scratch at home, or at least without leaving the city they live in. Anything less than that, and democratic society as we know it will continue to crumble. The fundamental idea underlying all of this is: that which reproduces, survives. At what level of organization can we reproduce? The digitally computing human species cannot reproduce as individuals. We can only reproduce as a society, at least for now. You can't make a computer from scratch on your own, but you can make a brain from scratch with just one other person of the opposite sex. As the world we live in becomes more suitable for the digitally computing rather than the purely organic, the organic part of the digitally computing human becomes less likely to voluntarily reproduce. If the organic part were to survive without being disempowered in the future, then it's probably by moving the mechanisms for reproductive drive to the society level (via religion or authoritarian government incentivizing or mandating reproduction), or by ensuring that each and every individual has the means to make the digital part of their mind on their own just like how they can make the biological part on their own.
• xtracto 4mo ago
  This, and distributed LLM inference. We are at a point where no single person can setup a rig to run a SOTA model, it is just too expensive. So we must build and adopt frameworks that allow individuals to share resources to run SOTA models in a distributed manner. That way they will also be non-censorable by governments. Also The only way to prevent that one entity weaponizes it, is by giving EVERYONE access to it.
  • hypefi 4mo ago
    yes, it also complements the geohot idea behind the tinybox
    • bilsbie 4mo ago
      What is that? I can’t seem to figure out what the use case is vs buying off the shelf? I think it’s a great project but the communication isn’t clear to me.
      • Avicebron 4mo ago
        https://tinygrad.org/#tinybox https://tinygrad.org/#tinybox I'm not sure exactly why you would buy through them vs rolling your own if you could afford the equivalent hardware. I'm a firm supporter of local inference though so good on them for doing something
        • indigodaddy 4mo ago
          Lol I get nervous when I see a list of products with full specs but no prices
          • matternous 4mo ago
            They have prices. Click on the links in the shipping row.
            • 4mo ago
• fHr 4mo ago
  This is why I go for codex and not claude code for example altough the models are not os yet.
• bozdemir 4mo ago
  I think we need it to prevent slavery happening again.
• dofm 4mo ago
  It won in my house/my business right from the start. (Well, open weights, at least — which is an uncomfortable nuance.) I have never understood the willingness to make the functioning of or development of a product so completely dependent on the secret sauce of one of two big unprofitable, inscrutable startups. It really defies sensible engineering principles to do that. So I was never going to do it. I'm exploring AI now but because I have decided that open weights make it a good use of my time. It's bad enough that any given business often ends up beholden to a single payment platform and the policies of two US credit card providers. I guess it is the freelancer in me but I always feel nervous when I am asked to put so much energy into studying or learning someone's product, rather than the underlying technology. I still remember the days when Microsoft was pretty much lobbying academic departments with promises of access to the NT source code. I remember a senior figure in our own saying that Linux was a sideshow and access to NT would make us relevant. More control over destiny is always necessary, and I remind myself and others that the "state of the art" is behind the "cutting edge". Progress is made at the cutting edge, but there is risk of damage. Engineering should focus on building on the state of the art, not on hitching a ride on someone else's progress.
  • cduzz 4mo ago
    I feel like "open source" in this context is, as you say, an uncomfortable nuance; the tooling (llama.cpp, et al) is open but useless without weights. The weights are extraordinarily expensive "capital" that is donated by big organizations who are all at war with each other. I don't know that it will ever be possible for, for instance, archive.org, to make truly open weights. And, other than archive.org, I can't imagine any other "open source" organization (freebsd? apache?) being in any position at all to make truly open weights. Maybe governments, government organizations, or universities. None of whom are currently funded, mandated, inclined, or particularly interested in dumping the money into buying the infrastructure needed to make weights.
    • dofm 4mo ago
      Yes. The weights war is a much more aggressive war than the war of OSS donations. In the OSS donations war (Visual Studio Code being a really fascinating example of it) you could see that the taps can't be turned off so easily. Whatever is donated can be built upon forever. I think there will come a point, soon enough, where open weights models are capable enough that even if they stagnate, they can be augmented with tooling that essentially keeps them current. Maybe we are there now? But the risk of the taps being turned off is not negligible. My own feeling is that governments will ultimately ask consortia of universities to train open weights models and support them financially in doing so. (And for what it is worth, I think diffusion text models are likely to trigger a hardware arms race that makes this possible) In much the same way that they used to do that for the supercomputer race, which we just don't hear about right now!
• 5555watch 4mo ago
  I think it's also important and heavily overlooked to develop and maintain open source "pro" level models. Those that are able to think for 80 minutes and yield heavy solutions. I'm not an expert in LLMs so it's hard to understand how much are we lacking, is it just the compute and thinking strategies / parallel chains, or something specific architecturally. But I feel there's value there and I haven't seen anything like it available so far.
• Findecanor 4mo ago
  There is no such thing as "Open Source AI". Open Source means that you respect copyright. The types of AI models that this web site refers to do not. Stop this nonsense!
• yen223 4mo ago
  Open source AI will win. It's the same reason why out of all the languages on the web we could have used, Javascript won.
• tlarkworthy 4mo ago
  I think it's enough to use Open Router to encourage competition in the market place.
• shevy-java 4mo ago
  To me it does not matter whether AI is open source or not. Yes, it is better if it is open source, no doubt, but either way I think AI must die. Naturally it won't, we all know that, but this does not change my statement in the slightest - AI must die. Having it open source is, while an improvement, just painting lipstick on the pig.
• jimmydoe 4mo ago
  For US citizens: counting on Open Source AI is another libertarian fantasy. Open source AI should and will get better for sure (including better defined first), but the state will have the power over AI never the less. If you don't like govt's AI policy or the people making those policies, go fix that, don't act like you can avoid them. For Chinese: saying "Open source AI must win" sounds like singing "L'Internationale, sera le genre humain". The reality is Open Source AI will be over the moment US competitive pressure gone. For rest of world: there's no real AI for you so far, go work on it or be a citizen of US&A or China.
• inigyou 4mo ago
  There are no open source LLMs.
• baalimago 4mo ago
  > If intelligence becomes something people can only rent from a few closed institutions Just your your natural born intelligence..? It's worked for the past 10k+ years, I'm sure it will work for some time longer
• deadbabe 4mo ago
  It sucks how in just a few years the world has decided nothing is worth doing or is just impossible without the use of AI. As if regular human intelligence isn’t enough anymore and it has to be paid for somehow.
• dwa3592 4mo ago
  Not today, may after the next 3-4 breakthroughs. One thing that people don't realize is that the AI they use today is highly highly subsidized bc of the capex that has gone into it. Even if people collaborated together - will not be able to raise billions of dollars that are needed. These are still very very (and very) early days of the modern AI and there are so many changes that are gonna happen. It's possible that all the frontier labs of today won't exist in a few years.
• RandyOrion 4mo ago
  I don't know how open source AI wins. The description is too vague for serious discussions. What I do know is that, once closed source AI groups become anti-you, you should punish them, or help open source groups, or both. If you really want specific open source {LLM, LMM, research, harness, whatever} groups to win over closed source counterparts, you may show your care by trying open source solutions first when solving problems. And if they're really capable, award them with contributions or something.
• dboreham 4mo ago
  This is obviously in direct opposition to the very idea of America. So if it happens it'll happen in other countries.
• edg5000 4mo ago
  When "open source" means freeware, it's like saying "we want free copies". What we should be saying is: We want a public, community-ran project that does pretraining and training collectively. This means working on a training corpus in public and somehow coordinating the training work. This is a complete change of what the term means, It's like how people conflate piracy with theft. Two different things, use different words. Free weights, inference code and chat template is very different from a community-ran LLM project.
  • Ifkaluva 4mo ago
    You might be describing EleutherAI
• hit8run 4mo ago
  Replace America with „The World“
• aspenmartin 4mo ago
  This is really a feel good argument and I agree with what he’s saying in principle but it offers zero in terms of a practical strategy or stable state where this is feasible. If you want to jump on the bandwagon then let’s put our pants on and offer a concrete suggestion that is practical and coherent. Otherwise what are we doing. Does anyone have suggestions to that effect? What’s the world in which frontier model performance is open source? What does that look like? What’s a sensible business model that makes this sustainable? What’s a sensible regulatory framework that doesn’t hamstring AI progress? Everyone is so enamored with these Chinese lab models like deepseek and qwen and GLM but they exist in a world where the top performance is still claimed by closed source models. These are not developed out of any benevolent commitment to the principles laid out in this article. A world in which OSS is the frontier and its development is controlled and funded by government subsidies of an autocratic government is not reassuring. You can inspect weights but good luck getting the cat back in the bag in terms of capabilities, safeguards, value system, bias, nerfing if it smells American business use cases. Deepseek was such a darling but guess what, it’s now raising money — 300M at 10 billion valuation. OSS development isn’t sustainable as a business model and in a world where it costs a few hundred million to develop a frontier model, you need a strong business model, or you need strong state subsidies and incentives which introduce a billion new problems. the most sensible economic picture of OSS models already exist. Commoditize your complement, passion projects for a hedge fund. These are unsustainable and exist at the pleasure of the business or the founder.
• bethekidyouwant 4mo ago
  …just crowdsource your own data centre…
• zkzk_gamal 4mo ago
  i think to create or make opensource ai need competition power and alot of investment to create and use or use it local you need spec pc to run and tune it at minimum 27b model to act good on context and agent work
• ericyd 4mo ago
  I feel like this is similar to saying "open source cloud platforms must win". I'm not really sure what the concrete argument/proposal/strategy is here. Would open source AI be nice? Sure! Will the incentives of our capitalist economy change for this one specific product? Probably not!
• zyngaro 4mo ago
  For open source AI, AI infrastructure must be public just like roads, rail, ...
• kosolam 4mo ago
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• idiotsecant 4mo ago
  It doesn't matter if open source models win or not. The bottleneck is the compute. When capital becomes cognition everyone other than the demigod class is cooked. We have a vanishingly small window to make sure that the benefits of large scale automation go to the species and not the owners. Once the owners become more powerful than governments or accumulate enough power to co-opt the governments we're done for. You can already see that creeping in along the edges.
• boutell 4mo ago
  Everybody who understands the technical problems is proposing a government fix. There is another option, foundations / NGOs could do this. Of course, openai has shown how quickly that can pivot into something completely different.
  • nchmy 4mo ago
    IIRC, there once was a foundation created to create AI that is open for all. What happened to it?
    • boutell 4mo ago
      Yeah it is ugly. I'm not convinced binding future leadership with corporate docs is even possible. Unless the shares are controlled by other reputable organizations from the start? Maybe?
• nodesocket 4mo ago
  It all comes down to financial incentives. Unlike the internet and software where the barrier to entry was essentially free. Open source frontier models are extremely capital intensive, infact virtually impossible without hordes of money and power. So where are the incentives for investors to back an open source model? There isn’t any. The exception is Meta because they have so much capital they can endure the loss, but they have fumbled Llama. Another potential player could be Apple if they open sourced a frontier model, and make back some of the capex on hardware. Imagine AIserve hardware with continued expansion of MacMini’s and Mac Studios.
• ece 4mo ago
  If large models were primarily used for distillation to make smaller models better, that could be a more efficient use of resources. Smaller providers could choose to fund a larger model and benefit from it.
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• kaycey2022 4mo ago
  To first open source AI, you must first open source GPU compute
• zoetaylor00 4mo ago
  Community governed sounds nice but open source AI projects often end up controlled by big companies anyway.
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