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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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-t...

The only exception to this is fields that are inherently adversarial (to nature or others) and an edge relative to competition matters.

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.

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

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.

I agree but we are dependent mostly on Chinese models at this point to pull it off.

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.

I think we need it to prevent slavery happening again.

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?

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.

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.

For open source AI, AI infrastructure must be public just like roads, rail, ...

This should be the top post. Not Anthropic or OpenAI marketing plots. This is existential.

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.

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.

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.

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.

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.

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

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.

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.

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

[1] https://agency-lang.com/guide/handlers.html

[2] https://agency-lang.com/guide/partial-application.html

[3] https://agency-lang.com/cli/serve.html

[4] https://github.com/egonSchiele/agency-lang/blob/main/package...

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!

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.

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…

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.

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.

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.

I think articles this light on content should not be upvoted to front page.

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.

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.

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/

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.

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!

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

I think it's enough to use Open Router to encourage competition in the market place.

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

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.

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.

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.

Well, the crazy thing I'm working on (100% self-funded thus far): 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.

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.

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

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.

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.

Well, open source AI is mostly coming from China. Title should have been China must win.

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.

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?

I vote that you become the next Richard Stallman

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

…just crowdsource your own data centre…

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.

I'm already coding more with DeepSeek than Opus, I'm doing my part :)

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.

If we can't stop these big AI companies, we must to put force that everybody can see what they are hiding from us.

Not to distract from the message, but I appreciate that this is largely plaintext not React vibeslop.

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.

Replace America with „The World“

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.

Are there any platforms to discuss this? (Like matrix/zulip?)

This is obviously in direct opposition to the very idea of America. So if it happens it'll happen in other countries.

I’m sorry I can’t read past the first paragraph

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.

i guess this fits: https://thealliance.ai/projects/tapestry

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.

This should definitely attract a lot of contributors

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!

What about pirated models?

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.

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.

There are no open source LLMs.

it is inevitable that it will win

information wants to be free

I fully support this. How can I help?

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.

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?

Open source AI wins means China wins

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.

our dependency on US AI will lead to data concentration in hands of few megacorps.

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

Totally agreed!

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.

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?

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.

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.

the public only wins once we shut it down globally through treaties like other tech that's too dangerous for anyone to have

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.

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.

It likely won’t based on how SOTA are developed.

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.

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?

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.

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.

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:

This is why I go for codex and not claude code for example altough the models are not os yet.

ok just explain the cyber attack and bioweapons risks like we are 5. Didn't you think of that? come on

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.

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!

BAP BAP BAP goes the Billionaire Alignment Problem

Yeah except for all the money it costs to do well.

Quick, someone start open data center and open energy system and open water supply.

> 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.

Wasn't it the point of ... OpenAI?

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.

Isn't that OpenAI's mission? "Our mission is to ensure artificial general intelligence benefits all of humanity."

/s

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?

> 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