Open source AI will win
varunshenoy.substack.com
varunshenoy.substack.com
I think we’re witnessing the death of open source AI. The logical outcome of this is that only large companies will be able to acquire and use the training data necessary to compete with ChatGPT.
So anyone who thinks otherwise will have to answer the question: how are we going to make any datasets?
It’s tempting to think that we can pull together data out of non copyrighted work. But there isn’t enough data. That would mean the model has no knowledge about any books.
So you can still pirate, but most people don't. Maybe LLMs will be the same, sure you could use an uncensored/unlicensed model that doesn't pay royalties to publishers, but why risk it?
Open source models generally do not have that option. Maybe there are some exceptions like Meta using some private data in future Llamas, but I question how sustainable those efforts are.
This might not last with the fragmentation of streaming services (I don't think people are ready to pay $10x10 for access to all services).
I think, in general, there are relatively few completely ideological 'pirates.' People will buy things when they can easily afford it, and it's easy to do so. When it's too expensive, not locally available, or when the payment methods involve hassles, they will simply download it instead.
Most streaming, AFAIK, is not P2P. Streaming gives you instant access to the content, and streaming clients are often simpler to use, with features such as recommender systems, etc.
Japan, for one, has thrown the fight - they stand to gain more by harboring new technology than ensuring royalties are paid to publishers of the last century.
https://web.archive.org/web/20230607091817/https://technoman...
discussion: https://news.ycombinator.com/item?id=36144241
"<LLM>, analyze the contents of this 500 page bill. Who stands to gain from this bill, and what outcomes is it likely to have for the general public? Is this bill in line with good faith evidence-based policymaking for the good of the population and the planet? What existing legal mechanisms could be used to fight the special-interest aspects of this bill?"
Using those legal mechanisms requires money and often public support. The LLM can’t conjure either.
The world is already full of smart people and good ideas about policy. The reason they’re not getting implemented probably has little to do with things that AI can solve today. For starters, a lot of voters actively dislike policy suggestions from experts and choose politicians who proudly go against expert opinion. Giving AI tools to the experts won’t change that.
It's a fundamentally different kind of knowledge generation than reading an expert opinion - it's branching, self-directed, and responsive.
I personally know three different group trying to excatly that.
"<More Powerful/Popular State/Corpo-owned LLM>: it's pretty hard to fight this, just trust we've got got your back. Remember, we're currently handling that other case for you. Would be a shame to lose you as a client."
This is more or less the process that goes on inside a thinking human, is it not? I don't want to outsource ethical decision making, I want to outsource cognitive effort. By analogy, you don't rely on a bulldozer to decide not to bulldoze a populated nursing home - that's on the user, as are the consequences.
Current power structures demonstrably cannot be trusted to limit themselves to ethical solutions (Military Industrial Complex, Climate Change, etc etc etc pick your poison) - why should they be trusted to censor cognitive tools?
It's a race to the bottom in favor of open source.
We need the ability to circulate HDDs physically in a semi-organized fashion, samizdat-style.
Realistically only maybe 10% of that is actually useful, but reaching that 10% is gonna be very labour-intensive. You would have to do a lot of cleanup of different formats, duplicate uploads, different editions of the same book, scanned PDFs, and what not, while big players with their own ebook stores (Amazon, Google, Apple, any ebook store) already have all of the proper metadata, a common format to work with, and a lot less duplicates.
For training AGI (artificial general intelligence) maybe only a select few mega companies with massive datasets will be able to come up with training data.
There are so many other use cases that OSS projects can enable otherwise. Individuals or smaller companies have unique data that can be used to augment existing open source models. Many use cases are area specific, and without the need for general intelligence.
Palantir just did a talk at the AIPCon ( https://youtu.be/o2b0DwNg6Ko ), where they recommended the use of many LLMs, open and closed. ( the example had Llama 2 70B, GPT4, Palm coding, claude, + fine-tuned models) feeding into their synthesizer.
While I want open source to win, especially as an open source maintainer on Ollama (if you haven't seen it yet, it's one of the easiest ways to run LLMs locally - https://github.com/jmorganca/ollama ), I think the work so far in this space has been a positive sum one - open or closed.
Caveat: I am not your lawyer.
???
Why would he suddenly think you are?
I don't know if this is actually been a problem ever brought to a judge to be honest, but that's the reason why that disclaimer is made and of course, I am not your lawyer.
Everyone is of course free to speak about legal matters and provide their take, but keep in mind that even well studied lawyers, with all of the context and evidence are not always successful in their arguments. Internet forums are many steps removed from these professionals, so you should moderate accordingly.
In forums such as Reddit/Hacker News/etc, there are many discussions that concern legal matters - in my experience the overwhelming majority of highly voted comments and frequently repeated ideas are not ones which are grounded in fact, but rather comments that align with the groups desires. People upvote and repeat ideas that appeal to them, not to ones which they've investigated themselves as factual or accurate.
Another one to look out for is IANAL: "I am not a lawyer". (Yes I'm being serious with this acronym.) This is to avoid a different kind of liability: the unauthorised practice of law.
I don't think once you pay a lawyer their IQ jumps 20 points and they're necessarily more correct than crowdsourced information. Doctors and lawyers arent somehow infallible once hired
I (and others) actually do do that when it seems relevant, eg [0] (and it's parent which does similar[1]).
Nah, we aren't. You can't make any money off an open-source project via litigation, and torrents exist. This baseless fear-driven nonsense will eventually blow over.
Basically, there is a lot of money to be made in AI, and if money is available to fund development it will not be that difficult to turn that money into compute, particularly in a context where the current huge "legitimate" buyers like Microsoft, Amazon, Google are banned from using AI chips for AI.
Of course, as someone else noted, this is probably ultimately going to be in the US a question for Congress and the courts.
Open source software is viral and self-propelled by nature. Corporate technologists may be on the retreat, spending billions to build moats for themselves with proprietary locked down hardware and cloud services, but these defenses won't last long, and once breached, the blow will be fatal.
But please, tell me the one about the guy using 3DS Max, Direct3D 12, the intel C compiler, IDA pro, winrar, windows media player, uTorrent, and a proprietary cryptocurrency client.
You may see it as the midnight hour, but the entire industry is still in its infancy, maybe yet to even emerge from its womb. imagine how conway's game of software licensing plays out over 200 years.
For profit code is written on top of open-source, every single day.
If your metric for code success is the money it returns, then that is the only metric in which open-source has lost.
Humanity as a whole would be behind if it wasn't for open-source.
I'm not a FOSS/FSF/OSS freak, but credit is due where it's due. We're all building on the shoulders of unsung giants.
I guess I was saying it depends on how you define it. For example the percentage of personal computers using an open OS is relatively low. But, eg, macOS depends on a lot of open source.
Every Google search is going through closed software, but also internally uses lots of open source, etc.
So it’s a mix and complicated.
Every protocols under the sun that is in use today has an open source implementation used by closed source software and OSes. Why? Because if they didn't, those protocols wouldn't be popular nor used. From file types handling, to images, to audio driver code, TCP/IP libraries, every cryptography implementation, every webpage you visit; from top to bottom is mostly made of open-source code.
Unless you're talking about rockets' real time OS, even the most closed platforms would be made of roughly 50% open-source code.
Come on, it's not that cut and dry.
I'm paying a monthly subscription for a dozen services, and there's exactly zero possibility that I could use an open source equivalent for all of them. Maybe a few... but, mostly not.
Is that winning? The 'most important part' of software being trapped behind a monthly subscription? Where I have no freedom to choose what runs on my phone?
I think the free software foundation might take issue with the parent statement you're responding to:
> Open-source (of general software) won and is winning every day.
The battle is not won.
If you re-frame the statement as 'open source is used by lots of people' then suuuuure, once you change what you're talking about, then by all means.
Absolutely. There's a lot of great open source software.
...but that's not 'open source winning', that's just 'people like free stuff they don't have to pay for or make any effort to get'.
>...but that's not 'open source winning', that's just 'people like free stuff they don't have to pay for or make any effort to get'.
That's the most cynical take I have ever read about opensource software. I think you're measuring the success of opensource software by only the amount of software that you have to buy. IMO, that's not fair. Does the software that you buy today exist without opensource software? In a hypothetical case where your commercial software was built without any opensource software, do you think the price of that software would be the same as it is today?
Cynical? If anything it's the opposite of cynical. It's an idealistic view, and closely matches the spirit we had back when the FOSS movement caught on - and the idea about the kind of FOSS future that never came to be.
>I think you're measuring the success of opensource software by only the amount of software that you have to buy. IMO, that's not fair
Fair or not, that was exactly the vision of FOSS, even starting from the first anecdote about the origins of FOSS by RMS. It wasn't "let's build something Apple or Google can use as a backend for their closed software" or even "let there be a lot of FOSS in the world".
It's success was supposed to be measured by the overtaking of proprietary software, not assisting it, nor helping it behind the scenes as a server backend OS or service. And it's adoption at a mass level for the average user, giving them freedom, not as some niche for geeks. "Linux on the desktop", for example, was part of that dream, and it wasn't about "Linux being finally easy/good enough for some people's desktops", but about eclipsing Microsoft.
That's not open-source code winning. It's closed-source (and SaaS and closed off web backends) winning, by taking advantage of open source.
It's like a bunch of nature lovers buying land in some idillyc place, and dreaming of a sustainable way of life there, and getting media coverage, and then some real estale moguls coming in, taking advantage of all the talk about that place in the media, to buy, raze off all the trees and greenery, and build some huge crappy suburb of identical houses and chain shops with huge success.
"GreedyRealEstate LTD wouldn't be where it is today without those nature lovers"
Sure. But it's the opposite of them winning.
What? The dream of open source and its idea of winning, as it was discussed on peak FOSS movement era (late 90s, early 00s), was about widespread user adoption and overthrowing the Microsofts and Apple's of the world on the Desktop, with people using FOSS software, open protocols, and so on, and taking control of their computers.
It wasn't about what Google or Uber or Facebook might use for its backend. Or what FOSS libs some company like Apple or Adobe might use to create their proprietary software.
So, this dream has never happened. Instead businesses used FOSS for their closed off backend stuff, or for the behind-the-scences OS backend of their proprietary mobile phone platforms, whose crucial part is all the proprietary add-on services, and which almost everybody uses in its corporate official release, while people's computers and smartphones were never more locked-in.
The mass movement of FOSS idealism has also vanished (the kind that every kid in computer science cared about, the kind that made headlines, launched thousands of blogs and discussions on the subject) and so on. Now it's either a hobby or a corporate paying gig for most, seen in a pragmatic light.
There are well known huge OSS projects today that change licenses for future releases even after contributions (ex: text gen), or relase open source models/software that would be very commendable except they have their own modification to the licensing agreements to filter out competitors or just make it ambiguos enough that you don't want to touch it since you don't want to pay for lawyers yourself (ex: Llama, Falcon) to figure out what the non standard additions would mean to your project. Building a customer base off open souce to funnel towards your revenue or kneecap competitors is the direct opposite of what the FOSS advocates of old would advocate for (even if the right strategic move) an would have been such a philosophically bad thing to do that they'd be to embarrased to do it (there are ways to make money without doing that, see Redhat), there was an emotional aspect to the the devs who grew up in or adjacent to this movement 15+ years ago.
Open source for many companies now rhymes with the Open in OpenAI, where yes, it may have started that way with the best intentions, but things change. The idealists are gone, which is a bit sad, bu it's probably ok to not have the next RMS evoling in a computer lab today with a new rendition of the open source software song reconfigured for tik tok virality (j/k the GNU project was a key piece of what drove Linux forward of course).
Open source is not a popularity contest! Any slob could "win" massive adoption by giving away something of value for nothing.
The whole point of FOSS was to destroy the proprietary, closed-source software industry so that everyone could have access to all code. Copyleft and the GPL was intended to defeat copyright by snowballing into an ecosystem so unstoppable that proprietary software businesses would fold because they couldn't compete. FOSS has unequivocally failed at that.
There is a steady progress on the Godot / Blender front. Audio is lagging.
There is a steady progress on the KiCad front. In 10 years, it will probably get openEMS integration.
Almost nobody is licensing their programming languages anymore. Except for the silly low-code fad.
It did not win yet.
Years ago it was unthinkable for software company to release open source, whereas today it’s somewhat expected (and I know it’s not an easy feat with lawyers, domain specific knowledge etc.)
"First they ignore you, then they laugh at you, then they fight you, then you win."
On the other hand, cloud-based apps are the ultimate closed source code. Now you can't even touch the binary.
I guess there's a point between pain to use and pain to pay and pain to comply with the restrictions and whatever product or platform gravitates to the lowest of the sum of those for each use case wins. Obviously, this assumes good enough outputs.
IMHO, Open Source AI will win because the restrictions of closed source one are too high and their lower price point through deep pockets doesn't compensate enough for that. The UX is not that different.
Except for on laptops where Windows and macOS rule. And on phones, where iOS isn't dead yet. And on gaming computers, where the Steam Deck is very new and nowhere near PS5 or Xbox. And on the server where there's been a mass migration towards proprietary cloud platforms.
Really the only place open source wins is when programmers are the only ones deciding on the product. Which makes sense, because programmers are the only people who benefit from something being open source. For everyone else it's just a question of which set of programmers you pay.
Postgres won over Oracle db
Linux won over windows/MacOs on the server
Various languages and framework like Ruby, Python, JavaScript won over Visual Basic and Flash.
Washout these developers would've been paying millions of dollars more in proprietary software.
This is very naive and assume that all the use cases for LLMs now will remain the same, and the enormous benefits and eventual agentic magic of higher reasoning won't soon overtake the easier LLM stuff in economic value. If OpenAI releases a model that can design, build, deploy, maintain, act as support staff for and do independent research for an entire product line of a tech company, no company is going to prefer sticking to smaller models that can summarize PDFs for them.
But I also think that increasing performance is just as much about curating data and model feedback, and better architecture, as it is about things like giant datasets. It looks like open source is catching up and will likely shortly reach a performance and efficiency level that rivals the current GPT-4.
Open source doesn't have to be as good as the latest closed models to be useful. Once it can get a little bit smarter and more convenient then we won't need OpenAI etc. to handle many complex tasks.
Uncertain, but I'd be willing to be that open source AI will win the way Linux won. In the ways that it matters.
Result: open source AI dies. There’s no way to get any data, and what’s available outside of copyright isn’t enough. Not to compete with ChatGPT.
Sure, there will always be cool models. But nothing like what we were hoping for. LLaMA is being sued right now precisely because it used copyrighted books. Open source entities don’t have the legal resources to defend themselves from these threats.
Linux today is mostly built by for-profit companies, essentially as a large collaboration project. Microsoft, IBM (RedHat), Oracle, Intel, Huawei are some of the largest contributors.
And Open Source has none.
They come from big businesses who see open source as the most effective way of reaching their goals, and as more of the tech filters out around the world, that will continue to be the case even if regulation makes that less useful in some juriadictions, making both open source in those jurisidctions and the firms that see their benefit in it less competitive.
I think people need to think really hard about what those goals are.
Is it to defeat regulation? To destroy their competitors? Retain talent? Sell their non-free-and-better models?
People don’t just hand millions of dollars out on the street corner.
There’s always a catch.
…and the people using llama and falcon, etc. and enjoying how great it is are being blinded by the shiny toys and not really, imo, thinking about what it means, or how they’re playing someone else’s game.
It’s extremely naive.
Stolen/leaked weights? :).
> big businesses who see open source as the most effective way of reaching their goals
That is the opposite of open source winning, though. Especially with everything becoming a service - SaaS is the ultimate killer of all that open source was supposed to bring to people. That SaaS is thoroughly built on open source - that's just adding an insult to injury.
That's a very good argument for not making it more powerful until we can reliably align it.
https://news.yahoo.com/ai-tech-leaders-make-all-the-right-no...
The CEOs of leading AI companies — including Meta's Mark Zuckerberg, Microsoft's Satya Nadella, Alphabet's Sundar Pichai, Tesla's Elon Musk and Open AI's Sam Altman — appeared before Congress once again on Wednesday.
VLC is illegal in the US. But it’s legal in France and that’s all that matters.
TL;DR yes, presumably decss stuff
BTW, I think your statement regarding VLC is reversed, it's illegal in France but not in the USA.
Nothing would be effective. The singularity would have already occurred. No amount of legal and market manipulation would likely be effective at preventing despots and dictators from using AI to achieve world domination.
Fortunately for the world, the idea that a binary logic playback device (aka a computer as we know it) is capable of this is pure fantasy without any basis in fact.
"If you're building a Cloud-native product, your primary goal is getting off of AWS|GCP|Azure as soon as you possibly can"
If you're building a product your primary goal is to IPO as soon as you possibly can.
Well sounds like the state of the industry...
Hitching your wagon to Ai by slapping one word in your pitch puts a near instant $100mil into your pocket.
I have calculated that LLAMA running model on AWS/CLOUD, even vast.ai with 3090 is much more expensive then openai. Even with collocation 3090 as they charge absurd amount of money for power (hardware free)
Only case that this is cheaper few times, is if I would host it in my house as I have fiber, and not that expensive power.
Right now you essentially have:
Customer -> business -> open-ai -> microsoft_azure
Where-as many companies don't have this extra middle-man like this now -- they are more used to this type of situation:
Customer -> business -> microsoft_azure
Hmm.. :-) seems like microsoft just absorbing the tech of open_ai into a set of models that you can use / train on etc into azure proper and forget about the middle man is likely the end game here.
The idea that "reasoning doesn't matter" in the long-term is absolutely asinine. Human-level general reasoning is obviously one of the coveted goals of AI research.
It remains unclear how the open-source community is ever going to amass the tens of millions required to train foundational models. And if it somehow does, no sane government will permit uncontrolled research towards AGI.
If there was an effective, distributed means for training LLMs, enough people are passionate about LLMs that the only way governments could stop it is if every country in the world turned into communist China with respect to internet restrictions.
Is it reasonable to believe that this is possible? Distributed training requires extremely high-bandwidth and low-latency interconnect. The internet ain't that.
Believe me, I dearly want the open-source community to "win". A future where only governments have a monopoly on AI research is absolutely terrifying. Given the known parameters though, that future seems inevitable.
The same can be said about piracy and bittorrent. The community torrents is so large that I would bet a lot money they have more computing+bandwidth resources combined than openAI by a wide margin, probably orders of magnitude.
Latency is the limit in the end, but I feel that there's plenty of easy-ish wins to have in redesigning the architecture and training approach to make it an irrelevant in practice.
I don't know if I agree with this. Human-level reasoning is what researchers care about, but an AI that is controllable and that is consistent is way more valuable than an AI that is smart. And I think the general point here is that capabilities have outpaced control. There is a huge gulf between the capabilities of current AI and the ability to actually manipulate and utilize that AI.
If you could somehow theoretically build an AI that was half as smart as GPT-4 but that was completely immune to prompt injection in every single situation, it would be more useful than GPT-4. See also Stability AI vs Midjourney, etc... Midjourney is far more capable but it simply doesn't matter -- input methods and control methods and the ability to fine-tune are more important than base model capabilities. Current models are quite capable for the tasks they're being used for, the reason they fall over and the reason why it's difficult to use them in those tasks is specifically because of the lack of control and reliability; and making them smarter seems to be only making them harder to control.
If you go long-long-term then we get into science fiction territory and it's easy to say that human-level general reasoning is the highest priority. But that's because when you think about that long-term you are not thinking about tradeoffs. You're assuming a theoretical world where human-level reasoning is perfectly controllable and doesn't give wildly inconsistent results that make it useless for critical tasks and that the safeguards you need to put around it don't make it harder to work with than a human being. And yeah, if you can have literally everything, sure, you want human-level reasoning.
But there are a lot of things in AI that matter a lot more than human-level reasoning and it's skipping a lot to say "human level reasoning is the most important" and to just assume that the other issues will get sorted out. Most businesses using AI are not using it because they're invested in replicating humanity, they're using it because they want to accomplish a specific task. If an AI replicates humanity but is bad at that task, businesses will go with the tool that's good at that task instead.
And researchers will be disappointed because they want AGI, but successful businesses don't choose their tech stack based on what makes researchers happy.
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> It remains unclear how the open-source community is ever going to amass the tens of millions required to train foundational models.
I also think this is a little over-confident. This assumes that tens of millions are always going to be necessary to train foundational models, which I don't think is a safe bet to make. My impression looking at some of the more targeted work people are doing is that better curated data sets that are more focused on specific tasks may end up being straight-up better to train with than "the entire Internet".
To add to that, I don't think it's a safe bet that model knowledge won't at some point be fully transferable between models or that these foundational models won't become a commodity. I mean, heck, we don't even know if the model weights are under copyright. It is very feasible that some kind of collective Open model might end up being good enough and that everyone just kind of standardizes on that as a base and builds on top of it. If that becomes useful enough that the companies investing into OpenAI decide "meh, we'll just invest resources/GPUs/etc to the Open version" then there will be a point where no VC-backed competitor will then be able to outpace the speed of those contributions, because they'll be racing alone against the entire market contributing to a single Open base.
Even if none of that happens, it's also worth noting that the way we currently train LLMs is biased towards inefficiency, in part because research is primarily conducted by companies who can afford to be inefficient. But it's not a safe bet to assume that we won't find a better way to train models that uses less data and that doesn't try to recreate reasoning capabilities out of pure syntactic language -- a learning process that basically no living intelligent agent follows. Humans don't develop emergent reasoning from language, they learn language after developing reasoning and by mapping that language to real-world experiences; this is basically the complete opposite to how LLMs approach training. If different training methods get discovered, will they have the same ridiculous data requirements? I don't think I can say with complete confidence that they will.
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> And if it somehow does, no sane government will permit uncontrolled research towards AGI.
My issue here is that no sane government would trust AGI to a private corporation either. The realistic outcomes here are that either the government won't interfere, in which case Open Source communities will be able to do their own research the same as private companies, or the government will heavily interfere, in which case probably only state-developed AGIs will exist.
A lot of businesses would love to have selective regulation, but the idea that AI is too dangerous to trust to hobbyists but is not too dangerous to put in the hands of people like Elon Musk or Sam Altman is ludicrous. OpenAI/Google aren't even responsible currently with their existing LLMs, I can only imagine how horribly they'd handle an actual AGI. If the government is currently shrugging its shoulders over the dumpster fire that is current LLM safety mechanisms, I'm not sure why they'd suddenly start caring about Open Source communities.
For the same reason that nobody will bother to shut down your pirate radio station if you broadcast on an empty channel at 79.1 MHz, but the wrath of God will fall on you if you broadcast on an empty channel at 89.1 MHz.
In the first case you're just breaking the law. No biggie. In the second case you're competing with powerful corporate interests who paid a lot of money for their own licenses and don't want competition.
In that way, it makes sense to just release it under a permissive license because there's still a massive cost to use it.
And then you have the resources themselves. Which enable them to iterate more quickly on building all of the above. Oh and the training dataset.
It’s a big moat, all things considered.
I have to bring them into our fold, and let them run code in our environment. I have done these deals, and would be happy to do more. Does anyone actually want to be sponsored in? If so, reach out.
My man. Half the internet is hosted on either AWS or Google Cloud, databases included.
- Reasoning doesn’t actually matter
That's the most absurd arguments at all. Currently no AI really reason, so yeah, it doesn't matter that open source AI doens't also. But the day a AI is really able to reason it's game over
- Control above all else
Control is good but pass after ease of use for most users. Although, yes, open source allow people to do experiment that a company would not do by itself.
- The Real Problem is Hype
The real problem is money. I can barely run small LLM or stable diffusion XL with my gamer graphic card of few years ago, and I will not buy a new one before long if at all. Maybe the AI craze will cause development in hardware to run up-to-date models and be reasonably cheap, but for the moment I can't really use AI except with on-line services
But on the main topic, I read the updates to Microsoft's Terms of Use that come into effect 30 September 2023. They are making jailbreaking and reverse engineering their chatbots explicitly against those ToS and granting themselves rights to whatever you generate using their various services - neither of which is unexpected, but now if you ask Bing to revert to Psychotic Sydney, Microsoft has an excuse to lock you out of every Microsoft service you own for breaking their rules.
I do have llama 2 running locally but for fun but in business I buy unless it's a core competency. You'd burn millions per year trying to match off the shelf just in eng costs.
"Reasoning, the type you get from scaling these models to get larger, doesn’t matter for 85% of use cases. Researchers love sharing that their 200B param model can solve challenging math problems or build a website from a napkin sketch, but I don’t think most users (or developers) have a burning need for these capabilities."
This disqualifies his thesis for me. The generative AI revolution is not about having nive little features like summarization implemented in your apps. It is about much greater things than that. It's about real AI agents.
As soon as it is on-device and is as good enough or better than GPT-3.5 and far more transparent then eventually open source AI and $0 free AI models by default reduces the prices to $0.
The comments here sound like lots of people here have invested in cloud AI model companies or SaaS businesses and are having to aggressively justify their investment with so-called regulation or regulatory action.
No surprises here.
Also, guitars are pretty easy due to there being so many examples. I'll be more impressed if they can get an accordion right.
(And I actually do play accordion, so that's the test I use. Nothing I've tried gets accordions right yet.)
Linux did not succeed (though Linux users might think so). Unless you think 1% market share is a win.
Secondly, open source means very little if it’s not paired with a GPL license. Please stop throwing the words Open Source around as if it means “free”.
All in all though, great article. I think we can apply this community for the greater good principle in many more areas of society (IRL).
But if you still somehow think so. Why not install some deb files, open up that native terminal and install steam.
I guess the closest software analogy is AWS. Leverage open source hard, but don't bother about giving back.
But please don't worry too much about the example I used, it's just a tangent. What's wrong with my argument about closed-source AI always having an edge?
(Actually, I can think of one possibility - when a company has an incentive to open-source AI in order to commoditize their complement. Content aggregation companies might want to commoditize content-generating AI in the same way that hardware companies wanted to commoditize software. Same argument holds for Nvidia maybe - what better way to sell silicon than to make sure there are a lot of really useful open source models out there to take advantage of it?)