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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...

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MTS

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14,246 просмотров • 11 дней назад •via X (Twitter)

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Комментарии: 5

Фото профиля Nemesis 2026
Nemesis 202611 дней назад

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

Фото профиля Phill Gates
Phill Gates10 дней назад

@TheAhmadOsman These guys aren't hard to find.

Фото профиля PermaBuc‏
PermaBuc‏11 дней назад

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

Фото профиля The AI Therapist
The AI Therapist11 дней назад

@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.

Фото профиля 安叫兽|Bird🕊️ 🔶 BNB
安叫兽|Bird🕊️ 🔶 BNB10 дней назад

@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
1:32

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

MTS

15,888 просмотров • 11 дней назад

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
1:51

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

MTS

17,404 просмотров • 1 месяц назад

📁 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.
1:33

📁 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.

Jon Hernandez

18,777 просмотров • 7 месяцев назад

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
1:22

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

MTS

12,097 просмотров • 11 дней назад

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."
1:13

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."

Dwarkesh Patel

288,685 просмотров • 1 год назад

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."
2:32

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."

MTS

14,406 просмотров • 2 месяцев назад

We asked Shaun Maguire from Sequoia Capital about his latest thesis on AI models. "My current thinking is that the closest analogy is operating systems." "I think there'll be 10-100 times as many open source models in 10 years, but they won't be as valuable." "There are more Linux servers in the world than Microsoft servers, but the value capture of Microsoft is way greater than Linux." "Foundational models will have hardware moats like cloud and will profit from applications on top." From his appearance on the show in June.
3:07

We asked Shaun Maguire from Sequoia Capital about his latest thesis on AI models. "My current thinking is that the closest analogy is operating systems." "I think there'll be 10-100 times as many open source models in 10 years, but they won't be as valuable." "There are more Linux servers in the world than Microsoft servers, but the value capture of Microsoft is way greater than Linux." "Foundational models will have hardware moats like cloud and will profit from applications on top." From his appearance on the show in June.

TBPN

123,666 просмотров • 9 месяцев назад

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
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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 🐂🀄️

111,477 просмотров • 1 день назад

.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 Zhang
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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 Zhang

a16z

36,735 просмотров • 1 месяц назад

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.
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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 просмотров • 7 месяцев назад

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."
4:16

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 просмотров • 2 месяцев назад

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
1:15

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

40,507 просмотров • 1 месяц назад

🚨 Sam Altman Worries AI Could Be Used to Design the Next Pandemic Pathogen “The thing that first got me thinking that we needed to evolve our approach was this pandemic point in particular … In a few more years some open source model is capable of it.”
1:33

🚨 Sam Altman Worries AI Could Be Used to Design the Next Pandemic Pathogen “The thing that first got me thinking that we needed to evolve our approach was this pandemic point in particular … In a few more years some open source model is capable of it.”

Chief Nerd

18,299 просмотров • 5 месяцев назад

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."
1:22

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

TBPN

34,469 просмотров • 4 месяцев назад

Dave Ramsey says it. 🔊 Do you believe him? "Right now is the best time to buy a house in the next five year. Prices are not going to go down. Some of you are saying, I'm gonna wait for prices to go down." "Fives years from now, houses are going to be more expensive. This is as cheap as it is going to be in the next five years."
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Dave Ramsey says it. 🔊 Do you believe him? "Right now is the best time to buy a house in the next five year. Prices are not going to go down. Some of you are saying, I'm gonna wait for prices to go down." "Fives years from now, houses are going to be more expensive. This is as cheap as it is going to be in the next five years."

Wall Street Mav

5,777,547 просмотров • 2 лет назад

Yann LeCun just said something at Davos that nobody is talking about. The man who built Meta's AI for 12 years. The godfather of deep learning. Said this on stage, in front of the world's most powerful people: "The best open source AI models right now come from China. Everybody in the research community is using Chinese models." Here's what makes this more uncomfortable. He said it in the same breath as warning that the US is making a catastrophic mistake. OpenAI — increasingly closed. Anthropic — never open. Google — more closed every year. Meta — changing direction. Meanwhile China's labs are publishing. Open sourcing. Sharing. And the global research community is downloading their models. LeCun's warning was blunt: "We are slowing down progress in the West because of this." The irony is brutal. America built the open internet. Linux runs the world. The entire software stack humanity depends on is open source. And now the country that invented openness is closing its most important technology. While China does the opposite. The next AI revolution won't be won by the country with the most money. It will be won by the country whose models researchers actually use. Right now that answer is changing.
29:10

Yann LeCun just said something at Davos that nobody is talking about. The man who built Meta's AI for 12 years. The godfather of deep learning. Said this on stage, in front of the world's most powerful people: "The best open source AI models right now come from China. Everybody in the research community is using Chinese models." Here's what makes this more uncomfortable. He said it in the same breath as warning that the US is making a catastrophic mistake. OpenAI — increasingly closed. Anthropic — never open. Google — more closed every year. Meta — changing direction. Meanwhile China's labs are publishing. Open sourcing. Sharing. And the global research community is downloading their models. LeCun's warning was blunt: "We are slowing down progress in the West because of this." The irony is brutal. America built the open internet. Linux runs the world. The entire software stack humanity depends on is open source. And now the country that invented openness is closing its most important technology. While China does the opposite. The next AI revolution won't be won by the country with the most money. It will be won by the country whose models researchers actually use. Right now that answer is changing.

Shruti

31,597 просмотров • 4 месяцев назад

.Josh Wolfe: Anybody Using DeepSeek App Is 'Absolute Fool' "Anybody using the DeepSeek app is an absolute fool. If you're using DeepSeek on companies like Together Compute, one of Lux's companies, which can get rid of the CCP censorship, then it's probably okay. But remember, the open-source movement is something we deeply believe in. Most great technologists, entrepreneurs, and venture capitalists are on the side of open source. The closed-source models that have consumed tens of billions of dollars are the ones that are really going to be at risk. When you look at Hugging Face, a major repository, or Together Compute, Runway ML, and a lot of Lux's companies, they have been pioneers in open source. Now, why am I not worried about open source, even with the DeepSeek model? As long as you don't have the CCP censorship on it, the models with their open weights allow people to run on their proprietary data. This means companies like pharma or defense companies that have their own siloed, proprietary data—think about Bloomberg with their proprietary longitudinal data, or Meta with their data—are the ones who will have the edge. Even as open source takes hold, these companies will still dominate. I’m not worried about open source being the problem. I’m more concerned about people overfunding closed models with no proprietary source. A lot of capital is going to be burned there, and we’re already seeing that with people worried about OpenAI in some aspects."
1:27

.Josh Wolfe: Anybody Using DeepSeek App Is 'Absolute Fool' "Anybody using the DeepSeek app is an absolute fool. If you're using DeepSeek on companies like Together Compute, one of Lux's companies, which can get rid of the CCP censorship, then it's probably okay. But remember, the open-source movement is something we deeply believe in. Most great technologists, entrepreneurs, and venture capitalists are on the side of open source. The closed-source models that have consumed tens of billions of dollars are the ones that are really going to be at risk. When you look at Hugging Face, a major repository, or Together Compute, Runway ML, and a lot of Lux's companies, they have been pioneers in open source. Now, why am I not worried about open source, even with the DeepSeek model? As long as you don't have the CCP censorship on it, the models with their open weights allow people to run on their proprietary data. This means companies like pharma or defense companies that have their own siloed, proprietary data—think about Bloomberg with their proprietary longitudinal data, or Meta with their data—are the ones who will have the edge. Even as open source takes hold, these companies will still dominate. I’m not worried about open source being the problem. I’m more concerned about people overfunding closed models with no proprietary source. A lot of capital is going to be burned there, and we’re already seeing that with people worried about OpenAI in some aspects."

Josh Caplan

40,039 просмотров • 1 год назад

We asked the CEO of HuggingFace clem 🤗 what the risks of releasing powerful open source models are. He says restricting AI creates more risk than openness. "Six, seven years ago, at the time it was GPT-2, and there was already a lot of people saying that it was too dangerous to release in open source." "Mythos, when it was announced was crazy dangerous... In a few weeks or a few months, everyone is gonna be using Mythos, and not destroy the world as a result." "For cybersecurity, the biggest risk is that a few players have capabilities that other people don't have... If you make it more open, it's usually easier for defenders to react and make the whole system safer." "The idea of restricting a technology like AI based on risks is like saying, 'Some people can punch other people, so let's tie down everybody's hands.'" "Otherwise you slow down progress, you create massive gaps in terms of controls, in terms of capabilities, and you create actually additional risks."
3:51

We asked the CEO of HuggingFace clem 🤗 what the risks of releasing powerful open source models are. He says restricting AI creates more risk than openness. "Six, seven years ago, at the time it was GPT-2, and there was already a lot of people saying that it was too dangerous to release in open source." "Mythos, when it was announced was crazy dangerous... In a few weeks or a few months, everyone is gonna be using Mythos, and not destroy the world as a result." "For cybersecurity, the biggest risk is that a few players have capabilities that other people don't have... If you make it more open, it's usually easier for defenders to react and make the whole system safer." "The idea of restricting a technology like AI based on risks is like saying, 'Some people can punch other people, so let's tie down everybody's hands.'" "Otherwise you slow down progress, you create massive gaps in terms of controls, in terms of capabilities, and you create actually additional risks."

MTS

318,827 просмотров • 4 месяцев назад