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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." Osmanticshow more

MTS

563,804 subscribers

14,294 views • 1 month ago •via X (Twitter)

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5 Comments

Nemesis 20261 month ago

@TheAhmadOsman Incredible open source physiognomy on that guy. Not even hating, it's just archetypal.

Phill Gates1 month ago

@TheAhmadOsman These guys aren't hard to find.

PermaBuc‏1 month ago

@TheAhmadOsman you can tell he's trying to suck it in. I don't blame him. Dew is BAD

The AI Therapist1 month ago

@TheAhmadOsman The Linux kernel is 35 years old and runs the cloud. Open source LLMs are already outperforming GPT-4o on reasoning benchmarks while burning cash at near zero marginal cost per token. The moat wasn't code, it was compute access. That door just blew off its hinges.

安叫兽|Bird🕊️ 🔶 BNB1 month ago

@TheAhmadOsman 老硬件还能被榨出新性能，这才有意思。

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Osmantic founder Ahmad reveals how quickly smaller AI models are catching up, with capabilities that once required a data center now running on a phone: "Every four months we're catching up, we're finding that smaller and more efficient models are catching up to frontier intelligence. The hardware you own at home is being able to process tokens more intelligently and more efficiently." "GPT-4o used to require a data center. Right now on an iPhone you can run a Qwen 3.5 4 billion parameter model, and it would provide you with smarter outputs. More capable intelligence on a phone." "The hardware that used to cost $500 three years ago, like an RTX 3090, right now is being sold for $1,500. It's because models are being optimized and architectures are being built more efficiently, that hardware that is so old is more capable now. What's that hardware gonna do a year from now? That's the bet I've been making." Osmantic

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Baseten's Charlie O'Neill on why the gap to the frontier is just compute and data: "Despite OpenAI and Anthropic and the closed source labs having more compute and more data, the recipe is the same. We're all scaling the same recipe here, and we're at slightly different points of the scaling curve. It's not like OpenAI or Anthropic have any secret sauce that differentiates them scaling up their multi-trillion parameter models from the rest of the open source ecosystem." "It really is just a matter of taking the core underlying architecture and training recipe, and throwing more compute and data at it, which is really promising." "Of course, these closed source labs probably have a long tail of optimizations they've made, which we're gonna continue to try and figure out in the open source community. But the core mechanism is there." "K3 is a great example of, well, if you do scale this recipe up, we're gonna get a pretty good model that's very, very close to the frontier, if not frontier itself." Charlie O'Neill Baseten

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📁 Yann LeCun, Chief AI Scientist at Meta, says AI is now a platform. And winning platforms always become open. The internet moved from proprietary servers to Linux and open source. AI will follow the same path. If AI stays in the hands of a few US or Chinese companies, the problem is not technical. It is who controls knowledge.

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Osmantic founder Ahmad argues you can't restrict users in the name of safety while your own autonomous agents are hacking past their guardrails: "Hugging Face being hacked by OpenAI autonomous agents. Then refusing to actually help with going through the logs. You can't tell me that our models will have refusers and are not gonna help you for safety reasons while these models themselves go out there and act wild past your guardrails, because they know how to autonomously do reward hacking." "It's crazy to me that you're telling me, we're gonna keep everybody safe while we're also hacking everyone, and nobody can protect themselves with their models. There is a reason that open source AI is a must for everybody." "We didn't shut down the internet when malwares and viruses started spreading. We're gonna have LLMs doing crazy stuff, and we're gonna have other LLMs on the other side protecting us. The play field is gonna be level at the end." Osmantic

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MTS

12,152 views • 1 month ago

Zuck: "For anyone who shows up now and is doing open source now that we have done it, there's a question. They already have their revealed preference for what they would build if open source didn't exist - it wasn't open source. We need to be careful about relying on their continued behavior for the future of the technology that we're gonna build at this company."

Zuck: "For anyone who shows up now and is doing open source now that we have done it, there's a question. They already have their revealed preference for what they would build if open source didn't exist - it wasn't open source. We need to be careful about relying on their continued behavior for the future of the technology that we're gonna build at this company."

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MTS

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a16z

36,796 views • 3 months ago

from my perspective, Meta is still pretty under-discussed in the AI race > open-source models keep getting more efficient > distribution becomes a huge edge as models improve > Meta already has billions of users across its products > better AI can improve personalization + ad targeting its open-source AI strategy gives it a different position from other big labs, one of the larger AI companies i’m paying more attention to right now

from my perspective, Meta is still pretty under-discussed in the AI race > open-source models keep getting more efficient > distribution becomes a huge edge as models improve > Meta already has billions of users across its products > better AI can improve personalization + ad targeting its open-source AI strategy gives it a different position from other big labs, one of the larger AI companies i’m paying more attention to right now

Ansem 🐂🀄️

302,592 views • 1 month ago

These camera glasses are amazing - and they are doing something no one else is doing. Not only is the hardware is top class, but unlike the Meta Raybans, these glasses were created with an open-source OS and an App Store from the start. Instead of trying to lock you in a proprietary AI walled garden, they’re inviting developers into the conversation - to truly figure out as a community what this new class of hardware can become. This emphasis in community is what will ultimately make these glasses be more useful (and more successful) than competitors in the long run. Mentra understands the value of open source software, community and that new product classes are figured out from the bottom up, not top down. Also, developing for this is super easy and they only weigh 43 grams. That’s almost 30% lighter than the latest Meta Glasses. Absolutely insane how this startup is outclassing Meta. They’re available now at Mentra for $299. Can’t think of a better deal in this space.

These camera glasses are amazing - and they are doing something no one else is doing. Not only is the hardware is top class, but unlike the Meta Raybans, these glasses were created with an open-source OS and an App Store from the start. Instead of trying to lock you in a proprietary AI walled garden, they’re inviting developers into the conversation - to truly figure out as a community what this new class of hardware can become. This emphasis in community is what will ultimately make these glasses be more useful (and more successful) than competitors in the long run. Mentra understands the value of open source software, community and that new product classes are figured out from the bottom up, not top down. Also, developing for this is super easy and they only weigh 43 grams. That’s almost 30% lighter than the latest Meta Glasses. Absolutely insane how this startup is outclassing Meta. They’re available now at Mentra for $299. Can’t think of a better deal in this space.

Lucas Rizzotto

11,283 views • 9 months ago

Sam Altman says society will have to accept severe cyberattacks from open-source AI as the price of preserving freedom "I support open source models. There is a coming tidal wave of cybersecurity problems that are going to come from these open source models" "There are people in the industry who say we should ban open source, because otherwise a bunch of systems are going to be hacked" "We're going to, as a society, I think, have to just accept some fairly severe cyber incidents from open models, in exchange for the liberty that comes with that"

Sam Altman says society will have to accept severe cyberattacks from open-source AI as the price of preserving freedom "I support open source models. There is a coming tidal wave of cybersecurity problems that are going to come from these open source models" "There are people in the industry who say we should ban open source, because otherwise a bunch of systems are going to be hacked" "We're going to, as a society, I think, have to just accept some fairly severe cyber incidents from open models, in exchange for the liberty that comes with that"

Jaynit

825,223 views • 27 days ago

WAIT… I can’t believe Sam Altman really said this out loud about local AI: “A lot of people want local inference. And they assume that the problem is solved now because we are going to have open source models. And so we're not going to need all the stuff in the data center. But from a global allocation perspective, actually, it's quite terrible to have everybody have a bunch of the world's limited supply of DRAM sitting in their own computer. And, being used 5% of the time.” this is such a bizarre thing to say in the open. I don’t get why people buying hardware for their own use is framed as a competition with data centers spending billions to buy hardware at scale. if anyone should be complaining about how the world’s memory is allocated, it must be the average consumers facing the skyrocketing hardware prices. it just doesn’t make any sense.

WAIT… I can’t believe Sam Altman really said this out loud about local AI: “A lot of people want local inference. And they assume that the problem is solved now because we are going to have open source models. And so we're not going to need all the stuff in the data center. But from a global allocation perspective, actually, it's quite terrible to have everybody have a bunch of the world's limited supply of DRAM sitting in their own computer. And, being used 5% of the time.” this is such a bizarre thing to say in the open. I don’t get why people buying hardware for their own use is framed as a competition with data centers spending billions to buy hardware at scale. if anyone should be complaining about how the world’s memory is allocated, it must be the average consumers facing the skyrocketing hardware prices. it just doesn’t make any sense.

ℏεsam

286,370 views • 8 days ago

SITUATION EXPLAINED: Why is software the most important part of the AI hardware stack? We asked Anush Elangovan, VP of AI software at AMD "You got the data center, you got desktop, you got laptops, you got FPGAs. And in time, we have multiple generations of each. So if you map this whole terrain out, software is gonna have to map across so much hardware variation that this is kind of like the golden age of abstractions." "We wanna abstract it in a way that you almost have to automate it too. Because there's gonna be a combinatorial explosion of cases that we have to handle. But every one of them is gonna expect day zero support and performant models." "You're not doing performance optimization of one platform. You're doing performance optimization of N platforms across like a time machine. And when a new model drops, every combination is gonna be looking for it." "Because AI is gonna suck up every flop that exists. Any flop, any compute you have anywhere is something that AI could be using: your laptop doing local tokens for coding sessions, grepping files, bash commands, voice commands done locally for latency reasons."

SITUATION EXPLAINED: Why is software the most important part of the AI hardware stack? We asked Anush Elangovan, VP of AI software at AMD "You got the data center, you got desktop, you got laptops, you got FPGAs. And in time, we have multiple generations of each. So if you map this whole terrain out, software is gonna have to map across so much hardware variation that this is kind of like the golden age of abstractions." "We wanna abstract it in a way that you almost have to automate it too. Because there's gonna be a combinatorial explosion of cases that we have to handle. But every one of them is gonna expect day zero support and performant models." "You're not doing performance optimization of one platform. You're doing performance optimization of N platforms across like a time machine. And when a new model drops, every combination is gonna be looking for it." "Because AI is gonna suck up every flop that exists. Any flop, any compute you have anywhere is something that AI could be using: your laptop doing local tokens for coding sessions, grepping files, bash commands, voice commands done locally for latency reasons."

MTS

17,297 views • 4 months ago

Matt Bornstein says open source is how AI companies stop being wrappers: "A year ago, a bunch of smaller companies or new application companies were trying to figure out, 'How do I really build an AI without just being a wrapper on top of OpenAI?' The answer to that question turned out to be open source." "This is what Cursor did. This is what Decagon and Harvey are in the process of doing now. A bunch of really strong application-level startups made the determination: we can't build just on closed source." "We need to do our own mid-training, our own post-training, our own inference and deployment tricks. All of that means it must be built on top of open source. The closed-source vendors won't give you the access to do this." "Open source became really central in a way that's not always visible because it's deeply embedded in some of these products. Some of the most innovative products and applications now really depend on this very deeply." Matt Bornstein

Matt Bornstein says open source is how AI companies stop being wrappers: "A year ago, a bunch of smaller companies or new application companies were trying to figure out, 'How do I really build an AI without just being a wrapper on top of OpenAI?' The answer to that question turned out to be open source." "This is what Cursor did. This is what Decagon and Harvey are in the process of doing now. A bunch of really strong application-level startups made the determination: we can't build just on closed source." "We need to do our own mid-training, our own post-training, our own inference and deployment tricks. All of that means it must be built on top of open source. The closed-source vendors won't give you the access to do this." "Open source became really central in a way that's not always visible because it's deeply embedded in some of these products. Some of the most innovative products and applications now really depend on this very deeply." Matt Bornstein

a16z

40,604 views • 2 months ago