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SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. clem 🤗, co-founder and CEO of Hugging Face: "There was an interesting study from Stanford published last year showing that 70% of the queries that people ask to ChatGPT could be accurately answered locally on your laptop.... For free." "Most of the AI workloads that people do today with frontier models could be done by models that are cheaper, faster, more customizable, more controllable. And they don't do it because frankly it's a pain to pick the right model." "You're subsidized so you don't have to care because you have your subscription, so you route everything to Einstein. 'Hey Einstein, what's the weather today?'" "In normal life, he would be like, 'I'm not answering your silly question.' But because it's AI and subsidized by the AI labs, all the questions are getting routed to Einstein versus in an ideal world you have different models that are more specialized and better at answering your questions in different domains." "It's possible that routing is gonna redistribute a lot of the value capture from frontier models to a more long tail of models. It's like AI maturing... we are in the first phase where it's very simple, everyone using just one giant model. Now we're moving to the second phase."show more

MTS

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50,185 просмотров • 3 месяцев назад •via X (Twitter)

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Interesting that in three of my recent conversations with Krishna at Anthropic, Dylan Patel, and Gavin Baker, each said that frontier tokens are capturing the majority of the economic value. Gavin: "An overwhelming amount of the economic returns to AI at the model layer have been at the frontier. That's surprising to me, and I think it's been surprising to a lot of people. This is one of the most important questions to be answered, and you need to have a hypothesis on it as an investor." Krishna: "We think the returns to frontier intelligence are extremely high. Customers invest really heavily in more tokens with the newer models. The ones at the frontier clearly are capturing this economic value, driving meaningful ROI for customers. The returns to frontier intelligence are not slowing down." Dylan: "No one gives a crap about GPT-4 class models. They want the frontier because the frontier lets them create the economically valuable things."

Interesting that in three of my recent conversations with Krishna at Anthropic, Dylan Patel, and Gavin Baker, each said that frontier tokens are capturing the majority of the economic value. Gavin: "An overwhelming amount of the economic returns to AI at the model layer have been at the frontier. That's surprising to me, and I think it's been surprising to a lot of people. This is one of the most important questions to be answered, and you need to have a hypothesis on it as an investor." Krishna: "We think the returns to frontier intelligence are extremely high. Customers invest really heavily in more tokens with the newer models. The ones at the frontier clearly are capturing this economic value, driving meaningful ROI for customers. The returns to frontier intelligence are not slowing down." Dylan: "No one gives a crap about GPT-4 class models. They want the frontier because the frontier lets them create the economically valuable things."

Patrick OShaughnessy

121,392 просмотров • 4 месяцев назад

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."

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."

dnap

110,354 просмотров • 2 месяцев назад

.Haseeb Qureshi ＞|＜ calls any team not running its releases through frontier-model security scanning "delinquent": "We are in a world where the previous rules around cybersecurity no longer apply. Because the reality is, if you can find this bug for $2, the team that was building this also could have done security scanning for $2. What were they doing?" "GLM has been out for a while. Kimi obviously more recent, but even just doing this on Opus would have cost probably four or five times that at most. Supposedly somebody ran Claude Code and found this in two minutes." "So what all this tells you is that there are companies that are going to survive this transition, and there are companies that are not. And there's going to be this kind of COVID-like mass inoculation period that we're going through right now in cybersecurity." "It's probably going to be a very centralizing force, because it means there's gonna be more consolidation toward the companies that have good security practices, have enough money to spend real dollars on security engineering, and are gonna be running every release through thousands of dollars of security scanning from frontier-level models." "If you are not doing that now, you are delinquent. You are already behind. You are putting your users and your company at risk." "AI is kind of an everything technology. It's like this background radiation now that is just touching everything that is software based." Dragonfly ＞|＜

.Haseeb Qureshi ＞|＜ calls any team not running its releases through frontier-model security scanning "delinquent": "We are in a world where the previous rules around cybersecurity no longer apply. Because the reality is, if you can find this bug for $2, the team that was building this also could have done security scanning for $2. What were they doing?" "GLM has been out for a while. Kimi obviously more recent, but even just doing this on Opus would have cost probably four or five times that at most. Supposedly somebody ran Claude Code and found this in two minutes." "So what all this tells you is that there are companies that are going to survive this transition, and there are companies that are not. And there's going to be this kind of COVID-like mass inoculation period that we're going through right now in cybersecurity." "It's probably going to be a very centralizing force, because it means there's gonna be more consolidation toward the companies that have good security practices, have enough money to spend real dollars on security engineering, and are gonna be running every release through thousands of dollars of security scanning from frontier-level models." "If you are not doing that now, you are delinquent. You are already behind. You are putting your users and your company at risk." "AI is kind of an everything technology. It's like this background radiation now that is just touching everything that is software based." Dragonfly ＞|＜

MTS

12,086 просмотров • 1 месяц назад

Today, we're launching Belvedir (YC S26) We're making private AI models cheap and easy so the world can have trillions of them. Private AI models are cheaper, better, faster, and protect your data from frontier labs, but they're still to expensive and difficult to make for startups and consumers. Belvedir makes private AI models autonomously with less than 5 minutes of setup, so that private AI can finally be accessible to everyone

Today, we're launching Belvedir (YC S26) We're making private AI models cheap and easy so the world can have trillions of them. Private AI models are cheaper, better, faster, and protect your data from frontier labs, but they're still to expensive and difficult to make for startups and consumers. Belvedir makes private AI models autonomously with less than 5 minutes of setup, so that private AI can finally be accessible to everyone

Zachary Yu

88,488 просмотров • 1 месяц назад

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.”

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 просмотров • 5 месяцев назад

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Jawwwn

181,054 просмотров • 2 месяцев назад

Sam Altman: "I'm not a jobs doomer at all. I think there are gonna be tons of jobs." "If we could go back to 2019 and show people our latest model, not only would they say that it's AGI, they would say that the economy would have been completely upended. And that has not happened. Anytime you're that wrong and that confident, which I think we were as a field, you have to update. AI is just very jagged. It's like superhuman genius in some ways, like dumb toddler in others. And people have, so far, extremely complementary skills to AI. It's not taste…the world may need a new kind of word for the kind of judgment that people are very good at that AIs seem to really deeply struggle with. You can go hire an AI consultant right now or talk to an AI sales rep or hire an AI engineer. And somehow most people seem to still really prefer interacting with a human. I definitely would rather engage with a person than engage with an AI for almost everything. Human values have value because they're human. We are deeply hardwired to care about people."

Sam Altman: "I'm not a jobs doomer at all. I think there are gonna be tons of jobs." "If we could go back to 2019 and show people our latest model, not only would they say that it's AGI, they would say that the economy would have been completely upended. And that has not happened. Anytime you're that wrong and that confident, which I think we were as a field, you have to update. AI is just very jagged. It's like superhuman genius in some ways, like dumb toddler in others. And people have, so far, extremely complementary skills to AI. It's not taste…the world may need a new kind of word for the kind of judgment that people are very good at that AIs seem to really deeply struggle with. You can go hire an AI consultant right now or talk to an AI sales rep or hire an AI engineer. And somehow most people seem to still really prefer interacting with a human. I definitely would rather engage with a person than engage with an AI for almost everything. Human values have value because they're human. We are deeply hardwired to care about people."

Patrick OShaughnessy

66,324 просмотров • 1 месяц назад

J-Cal Explains Why Google is UNDERRATED in AI 👀 On E227, the besties discussed Google's value in a post-search world if AI replaces traditional search. @jason broke down why he thinks Google is being slept on: "I think there's a chance that we're underestimating the power of Google's ad network right now." "They have four or five products that are one or two billion users per month. You have YouTube, Google Docs, Android." "They have such a data advantage and such a deep integration into people's lives because they use three or four services, I think Google's gonna figure this out." "It's quite possible that knowing your queries in Gemini, knowing what you're doing in Calendar, knowing what you're watching on YouTube could lead to a stream of more targeted ads that do better and are more valuable." "We've been seeing a number of startups that are figuring out how to use your queries and what you're doing in AI to present to you search results." "So imagine you're doing a Gemini search and on the side of it, it's giving you a rolling list of ads or offers that you might be more interested in." "That could be a better advertising product than even search itself." "I think YouTube search is the place to go all-in." "Right now, when you do a YouTube search, it just gives you 10 links, right? It just gives you that rolling thing." "You should be able to ask a question to YouTube, and you should be able to ask questions to your calendar." "You should be able to say, who have I met with over the last 10 years? Who I'm no longer in touch with and what are they up to?" "And it should do a Gemini search inside of Google Calendar. It's very light right now." "And then if you did that on YouTube, this would train people at the point of pain in a very deep way without sacrificing Google Search queries too aggressively."

J-Cal Explains Why Google is UNDERRATED in AI 👀 On E227, the besties discussed Google's value in a post-search world if AI replaces traditional search. @jason broke down why he thinks Google is being slept on: "I think there's a chance that we're underestimating the power of Google's ad network right now." "They have four or five products that are one or two billion users per month. You have YouTube, Google Docs, Android." "They have such a data advantage and such a deep integration into people's lives because they use three or four services, I think Google's gonna figure this out." "It's quite possible that knowing your queries in Gemini, knowing what you're doing in Calendar, knowing what you're watching on YouTube could lead to a stream of more targeted ads that do better and are more valuable." "We've been seeing a number of startups that are figuring out how to use your queries and what you're doing in AI to present to you search results." "So imagine you're doing a Gemini search and on the side of it, it's giving you a rolling list of ads or offers that you might be more interested in." "That could be a better advertising product than even search itself." "I think YouTube search is the place to go all-in." "Right now, when you do a YouTube search, it just gives you 10 links, right? It just gives you that rolling thing." "You should be able to ask a question to YouTube, and you should be able to ask questions to your calendar." "You should be able to say, who have I met with over the last 10 years? Who I'm no longer in touch with and what are they up to?" "And it should do a Gemini search inside of Google Calendar. It's very light right now." "And then if you did that on YouTube, this would train people at the point of pain in a very deep way without sacrificing Google Search queries too aggressively."

The All-In Podcast

58,275 просмотров • 1 год назад

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Fireside Alpha

162,832 просмотров • 2 месяцев назад

We asked rahul about the global reach of @ChatGPTApp and the emphasis on personality in AI models. "When you want to get to the one to like the remaining 90% of the users, do you want a model that thinks for longer? You want more personality?" "They definitely leaned in on personality, which I think is interesting." "It's kind of different than a (social media) feed in some ways because you have this person you talk to. It's like a relationship and then it just switches up on how it talks to you."

We asked rahul about the global reach of @ChatGPTApp and the emphasis on personality in AI models. "When you want to get to the one to like the remaining 90% of the users, do you want a model that thinks for longer? You want more personality?" "They definitely leaned in on personality, which I think is interesting." "It's kind of different than a (social media) feed in some ways because you have this person you talk to. It's like a relationship and then it just switches up on how it talks to you."

TBPN

92,172 просмотров • 1 год назад

Rivian CEO RJ Scaringe in new interview on self-driving: "Tesla's got a huge fleet. So our approach is we have to catch up with them and compete. And so we're going to have more cameras with better dynamic range. We're going to supplement that with LiDAR that provides better safety for edge case conditions and allows us to train the vision models faster. And the incremental cost to do that is relatively small. And in fact any of the incremental costs that would have been there on its own is offset by the fact that we brought inference in house and reduced the cost of our inference platform so dramatically from what we have in your car. Your car uses an Nvidia inference platform. I say all this because in like the infinite long-term you know, you could make the case that once the models are very very robust you could have less cameras or you may be able to get away with less radar. It's not clear yet if that's the case for covering all these corner cases."

Rivian CEO RJ Scaringe in new interview on self-driving: "Tesla's got a huge fleet. So our approach is we have to catch up with them and compete. And so we're going to have more cameras with better dynamic range. We're going to supplement that with LiDAR that provides better safety for edge case conditions and allows us to train the vision models faster. And the incremental cost to do that is relatively small. And in fact any of the incremental costs that would have been there on its own is offset by the fact that we brought inference in house and reduced the cost of our inference platform so dramatically from what we have in your car. Your car uses an Nvidia inference platform. I say all this because in like the infinite long-term you know, you could make the case that once the models are very very robust you could have less cameras or you may be able to get away with less radar. It's not clear yet if that's the case for covering all these corner cases."

Sawyer Merritt

451,115 просмотров • 6 месяцев назад

Sam Altman: "I'm not a jobs doomer at all. I think there are gonna be tons of jobs.” If we could go back to 2019 and show people our latest model, not only would they say that it's AGI, they would say that the economy would have been completely upended. And that has not happened. Anytime you're that wrong and that confident, which I think we were as a field, you have to update. AI is just very jagged. It's like superhuman genius in some ways, like dumb toddler in others. And people have, so far, extremely complementary skills to AI. It’s not taste…the world may need a new kind of word for the kind of judgment that people are very good at that AIs seem to really deeply struggle with. You can go hire an AI consultant right now or talk to an AI sales rep or hire an AI engineer. And somehow most people seem to still really prefer interacting with a human. I definitely would rather engage with a person than engage with an AI for almost everything. Human values have value because they're human. We are deeply hardwired to care about people.”

Sam Altman: "I'm not a jobs doomer at all. I think there are gonna be tons of jobs.” If we could go back to 2019 and show people our latest model, not only would they say that it's AGI, they would say that the economy would have been completely upended. And that has not happened. Anytime you're that wrong and that confident, which I think we were as a field, you have to update. AI is just very jagged. It's like superhuman genius in some ways, like dumb toddler in others. And people have, so far, extremely complementary skills to AI. It’s not taste…the world may need a new kind of word for the kind of judgment that people are very good at that AIs seem to really deeply struggle with. You can go hire an AI consultant right now or talk to an AI sales rep or hire an AI engineer. And somehow most people seem to still really prefer interacting with a human. I definitely would rather engage with a person than engage with an AI for almost everything. Human values have value because they're human. We are deeply hardwired to care about people.”

Invest Like the Best

20,730 просмотров • 1 месяц назад

$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."

$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."

Fireside Alpha

14,114 просмотров • 1 месяц назад

Engram cofounder Jack Morris just raised $98M to build a new type of AI. He says models don't need to get smarter over time. Instead, they just need to know you better and better over time. Jack describes what he's building: "Our product is a new type of AI. We have a pretty different vision from a lot of the frontier labs, which are working on one model per lab, and trying to make that model smarter every month." "There's another way to think about it, which is that the model doesn't need to get smarter every month. It needs to know you better." "So we're working on a whole different stack, which is a way to train models that train themselves to know your world better and adjust to the things that you say." "So: new ways of training, new ways of running the models."

Engram cofounder Jack Morris just raised $98M to build a new type of AI. He says models don't need to get smarter over time. Instead, they just need to know you better and better over time. Jack describes what he's building: "Our product is a new type of AI. We have a pretty different vision from a lot of the frontier labs, which are working on one model per lab, and trying to make that model smarter every month." "There's another way to think about it, which is that the model doesn't need to get smarter every month. It needs to know you better." "So we're working on a whole different stack, which is a way to train models that train themselves to know your world better and adjust to the things that you say." "So: new ways of training, new ways of running the models."

TBPN

70,635 просмотров • 2 месяцев назад

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 просмотров • 22 дней назад

Hacktron founder s1r1us on why frontier models are still far ahead of open models for real-world hacking: "The frontier models are insanely capable. There's a huge gap. You don't even want to use Kimi K3 when you have access to GPT 5.6." "We can't really use Opus 5 anymore. Every time there's a new model release, you kind of don't want to work with the previous model." "Open models, we don't really use them. It's incredibly hard to hand hold them to do the exploitation. They're not yet there." Hacktron AI Harsh Jaiswal

Hacktron founder s1r1us on why frontier models are still far ahead of open models for real-world hacking: "The frontier models are insanely capable. There's a huge gap. You don't even want to use Kimi K3 when you have access to GPT 5.6." "We can't really use Opus 5 anymore. Every time there's a new model release, you kind of don't want to work with the previous model." "Open models, we don't really use them. It's incredibly hard to hand hold them to do the exploitation. They're not yet there." Hacktron AI Harsh Jaiswal

MTS

15,129 просмотров • 7 дней назад

Databricks' Ali Ghodsi on why most companies wouldn't even notice if frontier AI models stopped advancing: "The models are smart enough, but they just don't have the context that exists inside any organization. They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes." "There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?' [The models] don't have that context." "If you just fused that and gave that context to the AI models... I think there are so many productivity gains you could get for any organization on the planet. For that, we actually don't need smarter models." "We don't need a smarter model that can solve Navier-Stokes or conjectures or do better on Humanity's Last Exam." "If the frontier doesn't advance, it doesn't actually matter, I think, for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff." Ali Ghodsi

Databricks' Ali Ghodsi on why most companies wouldn't even notice if frontier AI models stopped advancing: "The models are smart enough, but they just don't have the context that exists inside any organization. They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes." "There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?' [The models] don't have that context." "If you just fused that and gave that context to the AI models... I think there are so many productivity gains you could get for any organization on the planet. For that, we actually don't need smarter models." "We don't need a smarter model that can solve Navier-Stokes or conjectures or do better on Humanity's Last Exam." "If the frontier doesn't advance, it doesn't actually matter, I think, for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff." Ali Ghodsi

a16z

55,243 просмотров • 8 дней назад

Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now: "I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek and with Qwen, but I would much rather prefer that the leading models are American." "Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed." "There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in." "The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure." "It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that." Sriram Krishnan

Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now: "I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek and with Qwen, but I would much rather prefer that the leading models are American." "Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed." "There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in." "The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure." "It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that." Sriram Krishnan

MTS

61,234 просмотров • 2 месяцев назад

Tether CEO Paolo Ardoino explains QVAC, Tether's AI product for people who can't afford OpenAI and Anthropic "In 2026, when we launch our first AI product, we don't go to all the people that are using today OpenAI and Anthropic services. Those people have already access to the financial industry anyway, because they can pay for a subscription." "So Tether goes to all the people that cannot be served by the traditional financial system, because these people are very excluded, and since they are excluded, they cannot even afford an OpenAI or Anthropic subscription." "Tether is building an open source AI stack called QVAC. It's optimized for small large language models and can run on every single device, from a very basic cheap smartphone to a laptop." "We design AI tools that can run locally, without the need of a connection, because these people most of the time cannot even pay for a connection subscription."

Tether CEO Paolo Ardoino explains QVAC, Tether's AI product for people who can't afford OpenAI and Anthropic "In 2026, when we launch our first AI product, we don't go to all the people that are using today OpenAI and Anthropic services. Those people have already access to the financial industry anyway, because they can pay for a subscription." "So Tether goes to all the people that cannot be served by the traditional financial system, because these people are very excluded, and since they are excluded, they cannot even afford an OpenAI or Anthropic subscription." "Tether is building an open source AI stack called QVAC. It's optimized for small large language models and can run on every single device, from a very basic cheap smartphone to a laptop." "We design AI tools that can run locally, without the need of a connection, because these people most of the time cannot even pay for a connection subscription."

The Wolf Of All Streets

35,593 просмотров • 25 дней назад