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.Decagon co-founder and CEO Jesse Zhang says enterprise open-source adoption is falling right now, and that's a sign of adoption rather than rejection: "Even though there's a lot of hype for open-source, the share of open-source inference is actually going down right now." "People are spinning up all these... new use cases, and if you're spinning up new use cases, of course you're gonna use the frontier models until they're working." "Once it's at that point, they're heavily incentivized to use open-source because it's way cheaper and faster." "Enterprises have a lot of desire to move, but they can only do so many use cases at once. There is inertia there, and they have to go through all the model risk governance and all the security things." "I think it'll take time, but it will get there." Jesse Zhangshow more

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11 Comments

Tessa Archer1 month ago

@DecagonAI Jesse's declining-share framing is misleading. Open-source inference volume is growing. New frontier use cases just inflate the denominator faster than migrations complete.

Nam Đầu Tư1 month ago

@DecagonAI Mình thấy y hệt với team fintech ở HN. Họ chạy PoC bằng GPT-4 6 tháng trước, giờ mới bắt đầu audit để self-host Llama.

icefrog.◎1 month ago

@DecagonAI prove then port

安叫兽|Bird🕊️ 🔶 BNB1 month ago

@DecagonAI 先用闭源跑通，再慢慢换开源，很现实

felix negentropy. weallareeuropean1 month ago

@DecagonAI Share can fall while absolute open-source inference grows. Track workload migrations and token volume separately or a fast-growing frontier-model denominator will make adoption look like retreat.

Winston B.1 month ago

Governance review and security signoff don't move at model-improvement speed, so a use case can be proven out for months before procurement clears the switch to open source. That lag is probably where the gap between the hype and the falling spend share comes from. The maturity happens quietly, the queue is what's slow.

techVector1 month ago

@DecagonAI Open source is just getting too complicated for most companies to manage. Makes sense theyd rather pay for something that just works.

Tanishq Saluja1 month ago

@DecagonAI Support is a perfect AI wedge because the value is measurable. The hard part is staying useful when the answer is not already in a help center.

Rabnoor Singh1 month ago

@DecagonAI The migration step is the one that mostly does not happen. Once something works in production nobody gets rewarded for making it cheaper and slightly worse. That incentive is real at the CFO level and completely absent for the person who has to do the swap and own the regression.

sindikitil1 month ago

@DecagonAI Seen the same. Teams prototype on open weights, then swap to Anthropic/OpenAI when legal/security review hits. Open source wins dev mindshare, closes lose procurement.

Julien Active1 month ago

@DecagonAI The $10 customer finally gets the $100K treatment. Next shift is mobile-first, voice and screenshots, not just text.

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"Closed models are cheaper. The reason you need open models is that they give you control". - Nvidia CEO Jensen Huang "One of the things that people misunderstand about open models is this: yes, you can host them yourself, and you can build your own computer. But most people use computers in the cloud. Frankly, I think closed models are cheaper. If you do not build everything yourself, you avoid the significant cost and expertise required to train, fine-tune, maintain, guardrail, evaluate, and keep the model safe. You would also need to build or obtain the computers required to host it. So, there is nothing cheap about doing all of that yourself. The reason you need open models is that they give you control. You can adapt them for your own highly specialized use cases. I think there is a lot of misunderstanding about closed models versus open models. We felt it was important for people to understand that there is a place for both." ---- From "Bloomberg Podcasts" YouTube channel, (full video link in comment)

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David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

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33,291 views • 6 months ago

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Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

The All-In Podcast

64,677 views • 5 months ago

Gavin Baker says open source AI actually makes closed models more valuable "Open source makes frontier tokens more valuable. If you have a 250 IQ intellect that can orchestrate these open source 150 IQ intellects, that makes the 250 IQ intellect more valuable because it can farm out tasks." "If we're going to use the Manhattan Project analogy, everybody talks about Richard Feynman. But they had Oppenheimer and effectively 30 Nobel laureates. But they needed 2,000 physicists who were top 10,000 in the world." "Having more affordable intelligence actually makes the frontier even more valuable. A very plausible outcome is one in which frontier tokens are 65 to 85% of the economic value. Open source tokens are like 80% of the volume. And that's good for everyone. And everyone wins."

Gavin Baker says open source AI actually makes closed models more valuable "Open source makes frontier tokens more valuable. If you have a 250 IQ intellect that can orchestrate these open source 150 IQ intellects, that makes the 250 IQ intellect more valuable because it can farm out tasks." "If we're going to use the Manhattan Project analogy, everybody talks about Richard Feynman. But they had Oppenheimer and effectively 30 Nobel laureates. But they needed 2,000 physicists who were top 10,000 in the world." "Having more affordable intelligence actually makes the frontier even more valuable. A very plausible outcome is one in which frontier tokens are 65 to 85% of the economic value. Open source tokens are like 80% of the volume. And that's good for everyone. And everyone wins."

dnap

28,807 views • 1 month ago

Osmantic founder Ahmad explains why open-source AI could compound like Linux did, as thousands of developers keep making even decade-old hardware more capable: "The more open source developers we have in this space, the more optimizations you're gonna unlock, and the better everybody is gonna be. If we keep doing this from now throughout the next five years, everybody's gonna be better off." "If some specific companies out there are successful in banning open source AI with the regulatory capture narrative, there is a risk of everybody falling behind, and taking away that freedom from everybody." "It's not a now or never situation. It builds up and compounds over time. Linux took decades to get to where it is right now. Open source AI is gonna be the same." "I'm seeing somebody optimizing a GTX 1080, which is 12-13 years old hardware. There is still more juice to squeeze out of every piece of hardware." Osmantic

Osmantic founder Ahmad explains why open-source AI could compound like Linux did, as thousands of developers keep making even decade-old hardware more capable: "The more open source developers we have in this space, the more optimizations you're gonna unlock, and the better everybody is gonna be. If we keep doing this from now throughout the next five years, everybody's gonna be better off." "If some specific companies out there are successful in banning open source AI with the regulatory capture narrative, there is a risk of everybody falling behind, and taking away that freedom from everybody." "It's not a now or never situation. It builds up and compounds over time. Linux took decades to get to where it is right now. Open source AI is gonna be the same." "I'm seeing somebody optimizing a GTX 1080, which is 12-13 years old hardware. There is still more juice to squeeze out of every piece of hardware." Osmantic

MTS

14,246 views • 16 days ago

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike

“We have a crisis of open source models in the Western world. Outside of China, there are no good open source models. We don't even have any in the US now. The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset. The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." Everett Randle Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models Demis Hassabis Yann LeCun Aidan Gomez Lilian Weng Jan Leike

Harry Stebbings

63,738 views • 3 months ago

Chamath: Banning Open Source AI Will Crash the Stock Market Chamath Palihapitiya: “If the United States government intervenes, it will tank the stock market. Not debatable. Now, you can debate which companies get tanked. For example, if they said, ‘No more open source. American companies cannot use open source.’ Okay, let's take an average normal company, Coca-Cola. ‘Hey, Coca-Cola, you're trying to use AI to improve your business. You know what? You can only use these two options. And those things cost 50-100x more than your other best alternative that you may use otherwise.’ That will eventually show up in your costs. And so this incredibly important input into your cost model is now orders of magnitude, multiples greater than your competitors that are outside the United States, simply because you're in the United States. So what would the capital markets do? They're going to say, ‘Wow, you have a crazy cost structure. This doesn't make sense.’ You're forced to absorb costs that aren't rational nor market-driven. So then Coca-Cola has to get re-rated. But then you look at the people who are selling those tokens, and this is where Anthropic and OpenAI need to understand, if the government comes in and actually tells you that there's no open source, their valuation will crater. Why? Because all of that revenue is artificially being propped up. It's not being driven by market demand where you're being forced to compete. It's because of regulatory capture where you now get an artificial constraint. But it only works in one market. All roads lead to market chaos if anybody gets involved, so we should just not get involved.”

Chamath: Banning Open Source AI Will Crash the Stock Market Chamath Palihapitiya: “If the United States government intervenes, it will tank the stock market. Not debatable. Now, you can debate which companies get tanked. For example, if they said, ‘No more open source. American companies cannot use open source.’ Okay, let's take an average normal company, Coca-Cola. ‘Hey, Coca-Cola, you're trying to use AI to improve your business. You know what? You can only use these two options. And those things cost 50-100x more than your other best alternative that you may use otherwise.’ That will eventually show up in your costs. And so this incredibly important input into your cost model is now orders of magnitude, multiples greater than your competitors that are outside the United States, simply because you're in the United States. So what would the capital markets do? They're going to say, ‘Wow, you have a crazy cost structure. This doesn't make sense.’ You're forced to absorb costs that aren't rational nor market-driven. So then Coca-Cola has to get re-rated. But then you look at the people who are selling those tokens, and this is where Anthropic and OpenAI need to understand, if the government comes in and actually tells you that there's no open source, their valuation will crater. Why? Because all of that revenue is artificially being propped up. It's not being driven by market demand where you're being forced to compete. It's because of regulatory capture where you now get an artificial constraint. But it only works in one market. All roads lead to market chaos if anybody gets involved, so we should just not get involved.”

The All-In Podcast

211,679 views • 2 months ago

Baseten Head of AI Model Training Charlie O'Neill says the future is many specialized LLMs dedicated to specific tasks, with bigger labs deployed on the frontiers of areas like science and math: "People are thinking about intelligence capabilities in the wrong way. People are thinking about intelligence relativistically. They say, 'OK, the open-source gap is like 6 months behind closed-source, and GLM 5.3 is as good as Opus 4.8,' or whatever." "The best way to think about what models can do for you, and for the world, is in an absolute sense." "So for any given task that you want to do with an LLM, there's some intelligence threshold where below that you can't do the task, and above that you have very diminishing returns to more intelligence on the task." "So when you think about it that way, the game of LLMs over the last 5 years has been, 'OK, we have these things we want to do with them. Closed source hits it first... but open-source can eventually do that task. And then for many reasons, once you have the base level of intelligence required to do it, you probably do want to swap to open-source." "It's not really about the [frontier lab] God model being better. Like, if I'm filing a tax return, there is a limit to how much intelligence I need to do that particular thing." "So I think the world is going to look like — frontier closed-source labs are going to continue to push the frontier. You do want to use the most intelligent model. You have very inelastic demand for intelligence when you're doing frontier science or frontier math." "But for a lot of the economically valuable things, it looks a lot like, 'I'm a Cursor, or I'm one of these big companies who are realizing I can't just be a wrapper anymore. I've been through the life cycle of building a product that people love. And I should be using that information to make my model better at the things that I care about, and not at anything else.'"

Baseten Head of AI Model Training Charlie O'Neill says the future is many specialized LLMs dedicated to specific tasks, with bigger labs deployed on the frontiers of areas like science and math: "People are thinking about intelligence capabilities in the wrong way. People are thinking about intelligence relativistically. They say, 'OK, the open-source gap is like 6 months behind closed-source, and GLM 5.3 is as good as Opus 4.8,' or whatever." "The best way to think about what models can do for you, and for the world, is in an absolute sense." "So for any given task that you want to do with an LLM, there's some intelligence threshold where below that you can't do the task, and above that you have very diminishing returns to more intelligence on the task." "So when you think about it that way, the game of LLMs over the last 5 years has been, 'OK, we have these things we want to do with them. Closed source hits it first... but open-source can eventually do that task. And then for many reasons, once you have the base level of intelligence required to do it, you probably do want to swap to open-source." "It's not really about the [frontier lab] God model being better. Like, if I'm filing a tax return, there is a limit to how much intelligence I need to do that particular thing." "So I think the world is going to look like — frontier closed-source labs are going to continue to push the frontier. You do want to use the most intelligent model. You have very inelastic demand for intelligence when you're doing frontier science or frontier math." "But for a lot of the economically valuable things, it looks a lot like, 'I'm a Cursor, or I'm one of these big companies who are realizing I can't just be a wrapper anymore. I've been through the life cycle of building a product that people love. And I should be using that information to make my model better at the things that I care about, and not at anything else.'"

TBPN

50,531 views • 22 days ago