I agree OpenAI won't and can't have anywhere near a monopoly, excluding very unlikely legal shenanigans. The field is too approachable, and ultimately, to pinch into their market one doesn't need GPT-4 level performance. Besides, apparently OpenAI can't scale compute fast enough, so users will end up by default requiring other providers. There's a very good chance of OpenAI/Microsoft being major players though IMHO.
I can however see a possible future where open source is not going to have any significant impact on LLMs, say like Desktop Linux. Either because it gets stuck in a technical realm and doesn't make anything too approachable to ordinary users, or because it lacks the necessary integrations, or because developers get stuck arguing about the license (raw LLAMA not being good enough due to the non-commercial requirement), or because a moral panic ("4chanGPT is radicalizing people!") leads to a form of legal restrictions that makes open source efforts difficult to sustain. This doesn't have to be, so long as the hacker community can avoid falling into complacency.
On integrations, you're thinking about input, but there are still significant challenges there, the output step, API keys, rate limits, various crazy API corners, certifications... LLMs will help, but I expect integration to still be annoying.
For example, the Microsoft example where the Assistant changes the system to Dark Mode. You can't use LLM messy input to get that output on a generic level (and if you could, that would risk the LLM as an attack vector). You might be able to use a software development LLM to help write the code to do that specific thing and make it available to the product LLM, but ultimately that's a generic software productivity speedup - which also 'helps' those writing the API to make it more complicated and do more stuff we'll need to implement...
I agree that pure open source probably won't cross over into general use. Open source is great at tech but bad at product, mostly because product requires doing a lot of boring polish that programmers hate and thus generally have to be paid to do (I have ranted about this extensively here and elsewhere). Consumers also hate choice these days because they're all in a state of continuous cognitive overload. They want the one thing to do the one thing and stop bothering me.
That being said, Linux and open source have had a gigantic effect on the market. This hasn't been by shipping products directly to consumers but by enabling a ton of startups to get there faster and cheaper. OSS enables a ton of innovation and consumers benefit from that.
I'm arguing that the same thing is going to happen in AI. That's all. AI will get faster, better, and cheaper, and the basic functionality will get commoditized. That will lead to more competition and more variation and make it hard for people like OpenAI to have a monopoly.
I'm sure OpenAI will still exist. They might stay a dominant player. I just don't see a world where they "own the tech" and get to be "the only AI" and charge rent to the entire industry because nothing works without their API. That's a fantasy... unless they can legislate it into existence, which is what I think they're trying to do.
On integrations: what happens when everyone uses AI? One of the most exciting possibilities I see for this technology is to entirely toss out the persnickety concept of the API in favor of LLMs talking to LLMs. Making software interoperate in the conventional way frankly sucks. It's a terrible slog through mud. Imagine if I could just say "hey app I just wrote, meet GitHub! GitHub, please explain to my app what you can do and how to access your capabilities... Now tell GitHub to... now tell other app on my machine to... now tell Amazon to..."
We are going to look back at how we did software interoperability the way we look at programming mainframes with punched cards.
Well, I guess we agree here - the basic functionality will be common, Open AI will not have a monopoly (unless lawmakers really screw up), but will likely exist and be a major player. I am not sure about Open Source at all just yet - e.g. it's possible that a panic will lead to restrictions that will make open work rather difficult. I guess we'll see.
what happens when everyone uses AI? One of the most exciting possibilities I see for this technology is to entirely toss out the persnickety concept of the API in favor of LLMs talking to LLMs.
Hmm. Your idea has lower throughput and higher latency, while having not entirely clear security properties. But really, companies will sacrifice nearly all that in the service of faster shipping, paying less to programmers, and easier interfacing. Just look at the history of latency in user systems from the 1980s till today. The only game breaker here is security.
Hm. We implement an internal API that the LLM must use in order to do anything local, and do the limiting/auditing there. So the external interface is language, but what the LLM can do is either use the limited internal API to do approved actions locally, or speak to other LLMs (which will have their own internal APIs) using the user's context (OpenID token, whatever). There's a slight risk in the security boundary here (e.g. make sure the LLM never impersonates - don't allow it to see the actual user context, make sure each LLM instance only has access to the current user context. Also need to make sure it doesn't tell the other LLMs too much), but I think it's handleable?
Regardless, we aren't there yet, and there are still a few issues here (e.g. I expect Microsoft/Google to always have an advantage in Office 365/GSuite integrations somehow). Until we do, integrations will still have a big effect on the market.
Thinking about this a bit more, the main issue is that the LLM is an attack vector. Hallucinations aren't a big deal if the action requires approval or can be easily undone. The only way right now I can see to make LLM interfaces 'safe' would be to give it an internal API and pass the user context so we can set up permissions that way. There are a very few cases where even that might not be enough (basically whenever you pass 'on-behalf-of' transactions _without_ direct approval from the origin via a temporary token - e.g. many backend payment APIs allow this).
However, if you have an internal API which is the real security boundary, you might as well expose it. The effort required to add an LLM is now an extra effort and that flips the incentives to where the LLM really adds value. So adding LLMs as interfaces really makes sense on Windows 11 (practically single user, hallucinations have limited cost) and GitHub (devs have local copy anyway), maybe on AWS (devs would like an easier interface, but there's a need to reassure about safety), and none on Stripe or MailGun (complex security scenarios, usually decided by finance/marketing department which don't care about integration difficulty).
Interesting parallels , there is good possibility for this outcome with respect to Open Source LLMs
I can however see a possible future where open source is not going to have any significant impact on LLMs, say like Desktop Linux.
Either because it gets stuck in a technical realm and doesn't make anything too approachable to ordinary users, or because it lacks the necessary integrations..
Comments
I agree OpenAI won't and can't have anywhere near a monopoly, excluding very unlikely legal shenanigans. The field is too approachable, and ultimately, to pinch into their market one doesn't need GPT-4 level performance. Besides, apparently OpenAI can't scale compute fast enough, so users will end up by default requiring other providers. There's a very good chance of OpenAI/Microsoft being major players though IMHO.
I can however see a possible future where open source is not going to have any significant impact on LLMs, say like Desktop Linux. Either because it gets stuck in a technical realm and doesn't make anything too approachable to ordinary users, or because it lacks the necessary integrations, or because developers get stuck arguing about the license (raw LLAMA not being good enough due to the non-commercial requirement), or because a moral panic ("4chanGPT is radicalizing people!") leads to a form of legal restrictions that makes open source efforts difficult to sustain. This doesn't have to be, so long as the hacker community can avoid falling into complacency.
On integrations, you're thinking about input, but there are still significant challenges there, the output step, API keys, rate limits, various crazy API corners, certifications... LLMs will help, but I expect integration to still be annoying.
For example, the Microsoft example where the Assistant changes the system to Dark Mode. You can't use LLM messy input to get that output on a generic level (and if you could, that would risk the LLM as an attack vector). You might be able to use a software development LLM to help write the code to do that specific thing and make it available to the product LLM, but ultimately that's a generic software productivity speedup - which also 'helps' those writing the API to make it more complicated and do more stuff we'll need to implement...
I agree that pure open source probably won't cross over into general use. Open source is great at tech but bad at product, mostly because product requires doing a lot of boring polish that programmers hate and thus generally have to be paid to do (I have ranted about this extensively here and elsewhere). Consumers also hate choice these days because they're all in a state of continuous cognitive overload. They want the one thing to do the one thing and stop bothering me.
That being said, Linux and open source have had a gigantic effect on the market. This hasn't been by shipping products directly to consumers but by enabling a ton of startups to get there faster and cheaper. OSS enables a ton of innovation and consumers benefit from that.
I'm arguing that the same thing is going to happen in AI. That's all. AI will get faster, better, and cheaper, and the basic functionality will get commoditized. That will lead to more competition and more variation and make it hard for people like OpenAI to have a monopoly.
I'm sure OpenAI will still exist. They might stay a dominant player. I just don't see a world where they "own the tech" and get to be "the only AI" and charge rent to the entire industry because nothing works without their API. That's a fantasy... unless they can legislate it into existence, which is what I think they're trying to do.
On integrations: what happens when everyone uses AI? One of the most exciting possibilities I see for this technology is to entirely toss out the persnickety concept of the API in favor of LLMs talking to LLMs. Making software interoperate in the conventional way frankly sucks. It's a terrible slog through mud. Imagine if I could just say "hey app I just wrote, meet GitHub! GitHub, please explain to my app what you can do and how to access your capabilities... Now tell GitHub to... now tell other app on my machine to... now tell Amazon to..."
We are going to look back at how we did software interoperability the way we look at programming mainframes with punched cards.
Well, I guess we agree here - the basic functionality will be common, Open AI will not have a monopoly (unless lawmakers really screw up), but will likely exist and be a major player. I am not sure about Open Source at all just yet - e.g. it's possible that a panic will lead to restrictions that will make open work rather difficult. I guess we'll see.
Hmm. Your idea has lower throughput and higher latency, while having not entirely clear security properties. But really, companies will sacrifice nearly all that in the service of faster shipping, paying less to programmers, and easier interfacing. Just look at the history of latency in user systems from the 1980s till today. The only game breaker here is security.
Hm. We implement an internal API that the LLM must use in order to do anything local, and do the limiting/auditing there. So the external interface is language, but what the LLM can do is either use the limited internal API to do approved actions locally, or speak to other LLMs (which will have their own internal APIs) using the user's context (OpenID token, whatever). There's a slight risk in the security boundary here (e.g. make sure the LLM never impersonates - don't allow it to see the actual user context, make sure each LLM instance only has access to the current user context. Also need to make sure it doesn't tell the other LLMs too much), but I think it's handleable?
Regardless, we aren't there yet, and there are still a few issues here (e.g. I expect Microsoft/Google to always have an advantage in Office 365/GSuite integrations somehow). Until we do, integrations will still have a big effect on the market.
Thinking about this a bit more, the main issue is that the LLM is an attack vector. Hallucinations aren't a big deal if the action requires approval or can be easily undone. The only way right now I can see to make LLM interfaces 'safe' would be to give it an internal API and pass the user context so we can set up permissions that way. There are a very few cases where even that might not be enough (basically whenever you pass 'on-behalf-of' transactions _without_ direct approval from the origin via a temporary token - e.g. many backend payment APIs allow this).
However, if you have an internal API which is the real security boundary, you might as well expose it. The effort required to add an LLM is now an extra effort and that flips the incentives to where the LLM really adds value. So adding LLMs as interfaces really makes sense on Windows 11 (practically single user, hallucinations have limited cost) and GitHub (devs have local copy anyway), maybe on AWS (devs would like an easier interface, but there's a need to reassure about safety), and none on Stripe or MailGun (complex security scenarios, usually decided by finance/marketing department which don't care about integration difficulty).
Interesting parallels , there is good possibility for this outcome with respect to Open Source LLMs