正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

"Most enterprise workflows don't require frontier AI models. Outside of coding, tasks like summarization, document generation, and briefing can often be handled effectively by lower-cost open-source models. The real value is knowing when you need frontier performance and when cheaper models are more than good enough." Michael Mignano What... show more

Harry Stebbings

537,557 subscribers

36,428 次观看 • 1 个月前 •via X (Twitter)

科学技术新闻政治教育

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

The most effective AI systems don't rely on a single model. Frontier models provide state-of-the-art performance for complex tasks, while routers automatically select lightweight, open-source models for simpler jobs to optimize accuracy, latency, and cost. Learn more:

The most effective AI systems don't rely on a single model. Frontier models provide state-of-the-art performance for complex tasks, while routers automatically select lightweight, open-source models for simpler jobs to optimize accuracy, latency, and cost. Learn more:

NVIDIA AI

12,152 次观看 • 5 个月前

Our new Gemini 3.5 Flash is our strongest agentic and coding model yet, delivering frontier-level performance at 4x the speed of comparable frontier models at less than half the cost. We had Tulsee Doshi break down what you need to know about it.

Our new Gemini 3.5 Flash is our strongest agentic and coding model yet, delivering frontier-level performance at 4x the speed of comparable frontier models at less than half the cost. We had Tulsee Doshi break down what you need to know about it.

Google

77,748 次观看 • 3 个月前

Factory (Factory) CEO Matan Grinberg (Matan Grinberg) says "In the next 12 months, 90% of tokens will be going to open models." Enterprises are already shifting rapidly.. "At the beginning of the year, <1% of their tokens were going to open models." "Around March, it crossed 1%... & in May it crossed 10%." "These open models are incredibly performant, incredibly cheap, incredibly fast." While frontier closed models aren't going away: "They'll still have a place, but I think that place will be shrinking—at least in token share." And by the end of 2026? "At least in the enterprise, we'll probably cross the 50% threshold."

Factory (Factory) CEO Matan Grinberg (Matan Grinberg) says "In the next 12 months, 90% of tokens will be going to open models." Enterprises are already shifting rapidly.. "At the beginning of the year, <1% of their tokens were going to open models." "Around March, it crossed 1%... & in May it crossed 10%." "These open models are incredibly performant, incredibly cheap, incredibly fast." While frontier closed models aren't going away: "They'll still have a place, but I think that place will be shrinking—at least in token share." And by the end of 2026? "At least in the enterprise, we'll probably cross the 50% threshold."

Molly O’Shea

120,949 次观看 • 1 个月前

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models. Achieving AGI is bottlenecked by one main thing: high-quality data. Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn. With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

Ali Ansari

332,850 次观看 • 9 个月前

BREAKING: Max Cook (Max Cook), Sector Head at Coatue (COATUE) says.. "The keyboard & mouse are slowly dying." :( Cook also offers a bigger Q for the market: "What happens when OpenAI or Anthropic decide to offer smaller, cheaper, fine-tuned production models as products?" Cook argues the real AI debate might actually not be open vs. closed models It's what happens when frontier labs begin competing across the entire model stack.. Offering everything from cutting-edge reasoning models to smaller, efficient, low-cost, production-grade models for enterprise

BREAKING: Max Cook (Max Cook), Sector Head at Coatue (COATUE) says.. "The keyboard & mouse are slowly dying." :( Cook also offers a bigger Q for the market: "What happens when OpenAI or Anthropic decide to offer smaller, cheaper, fine-tuned production models as products?" Cook argues the real AI debate might actually not be open vs. closed models It's what happens when frontier labs begin competing across the entire model stack.. Offering everything from cutting-edge reasoning models to smaller, efficient, low-cost, production-grade models for enterprise

Molly O’Shea

304,532 次观看 • 1 个月前

$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

11,921 次观看 • 23 天前

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 次观看 • 1 个月前

Meet Amazon Nova 2 reasoning models Nova has introduced its next generation of foundation models that deliver frontier intelligence with industry-leading price performance 1/ Amazon Nova 2 Lite, is a fast, cost-effective model designed for everyday AI tasks. 2/ Amazon Nova 2 Pro (preview), Nova’s most intelligent model built for complex AI workloads. These models offer developers control to manage thinking budgets, native support for agentic workflows, and provide a one-million-token context window for richer interactions.

Meet Amazon Nova 2 reasoning models Nova has introduced its next generation of foundation models that deliver frontier intelligence with industry-leading price performance 1/ Amazon Nova 2 Lite, is a fast, cost-effective model designed for everyday AI tasks. 2/ Amazon Nova 2 Pro (preview), Nova’s most intelligent model built for complex AI workloads. These models offer developers control to manage thinking budgets, native support for agentic workflows, and provide a one-million-token context window for richer interactions.

Amazon Web Services

3,958,154 次观看 • 8 个月前

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 次观看 • 1 个月前

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Milk Road AI

280,929 次观看 • 1 个月前

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 次观看 • 13 天前

CNBC described China’s open-source AI as “pushing the U.S. to compete at the lower end of the value chain,” initially trying to save face for Silicon Valley. The comments section immediately tore that framing apart: "Chinese models are approaching frontier-level capability while remaining absurdly cheap." "This is not the 'lower end' of the value chain." It is forcing expensive American models to answer a much uglier question: Why are you charging tens or even hundreds of times more for the same work? The most revealing part was that people saw through the euphemism immediately: “Lower end” is just cope. American labs are not protecting the high end. They are protecting high profit margins. China’s open-source models are turning frontier capability into a commodity, crushing prices, and freeing developers from brand worship. Suddenly, the American myth of closed-source superiority, premium pricing, and inflated valuations looks less like technological leadership— and more like an ordinary handbag with a luxury label.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

10,646 次观看 • 23 天前

Jensen says Open Source can be MORE expensive for enterprises, Brad Gerstner explains why: Brad Gerstner: “Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence, that they're much cheaper, etc. And Elon comes out and says, ‘Not so fast. We're entering the singularity, and the frontier models are way further ahead than people think.’ I believe that to be true. And then Jensen came out this week and said, ‘Closed models are actually cheaper if you don't have to build it for yourself, the training costs, and a lot of expertise to fine-tune, and maintain, and guardrail, and keep it safe. So he's basically making the argument that not only are the frontier models further ahead, but that the cost differential between the two is not what everybody's making it out to be, which I think explains why (closed models) continue to run away with it on the revenue side of the equation. For the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the frontier labs. I think that's what we want to see.” $NVDA

Jensen says Open Source can be MORE expensive for enterprises, Brad Gerstner explains why: Brad Gerstner: “Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence, that they're much cheaper, etc. And Elon comes out and says, ‘Not so fast. We're entering the singularity, and the frontier models are way further ahead than people think.’ I believe that to be true. And then Jensen came out this week and said, ‘Closed models are actually cheaper if you don't have to build it for yourself, the training costs, and a lot of expertise to fine-tune, and maintain, and guardrail, and keep it safe. So he's basically making the argument that not only are the frontier models further ahead, but that the cost differential between the two is not what everybody's making it out to be, which I think explains why (closed models) continue to run away with it on the revenue side of the equation. For the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the frontier labs. I think that's what we want to see.” $NVDA

The All-In Podcast

61,649 次观看 • 20 天前

Introducing Agent Mode: Agentic AI is now measured in the Arena. Agent Mode can do deep research, create reports, generate images, build websites, debug code, and more. It completes more complex tasks by using tools like web search, bash in a sandbox environment, image generation, file writing, and asking follow-up questions. Frontier models are waiting for you in Agent Mode to take on real-world tasks. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and top open models. Test them yourself.

Introducing Agent Mode: Agentic AI is now measured in the Arena. Agent Mode can do deep research, create reports, generate images, build websites, debug code, and more. It completes more complex tasks by using tools like web search, bash in a sandbox environment, image generation, file writing, and asking follow-up questions. Frontier models are waiting for you in Agent Mode to take on real-world tasks. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and top open models. Test them yourself.

Arena.ai

449,353 次观看 • 2 个月前

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

121,110 次观看 • 3 个月前

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."

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."

MTS

50,185 次观看 • 2 个月前

The first real evidence that the days of LLM Scaling laws are over. Introducing SCOPE: the world's most efficient Neural Planner. 🔍📊 We tested SCOPE vs Frontier LLMs for planning tasks on TextCraft (text version of Minecraft) and here are the results: ⤵️ - SCOPE Runs 55x faster than GPT 3.5 (3 seconds vs 164 seconds) - SCOPE is 160,000 smaller than GPT 4o (11M parameters vs 1.8T parameters) - SCOPE is more accurate on Planning tasks (56%) than frontier LLM models The age of efficient AI models starts now. 🔗📌 Read the full write up here:

The first real evidence that the days of LLM Scaling laws are over. Introducing SCOPE: the world's most efficient Neural Planner. 🔍📊 We tested SCOPE vs Frontier LLMs for planning tasks on TextCraft (text version of Minecraft) and here are the results: ⤵️ - SCOPE Runs 55x faster than GPT 3.5 (3 seconds vs 164 seconds) - SCOPE is 160,000 smaller than GPT 4o (11M parameters vs 1.8T parameters) - SCOPE is more accurate on Planning tasks (56%) than frontier LLM models The age of efficient AI models starts now. 🔗📌 Read the full write up here:

Skyfall AI

49,052 次观看 • 7 个月前

Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge. 🌎 Forge bridges the gap between generic AI and enterprise-specific needs. Instead of relying on broad, public data, organizations can train models that understand their internal context embedded within systems, workflows, and policies, aligning AI with their unique operations. We have already partnered with world-leading organizations, like ASML, DSO National Laboratories Singapore, Ericsson, European Space Agency, Home Team Science and Technology Agency (HTX) Singapore and Reply to train models on the proprietary data that powers their most complex systems and future-defining technologies.

Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge. 🌎 Forge bridges the gap between generic AI and enterprise-specific needs. Instead of relying on broad, public data, organizations can train models that understand their internal context embedded within systems, workflows, and policies, aligning AI with their unique operations. We have already partnered with world-leading organizations, like ASML, DSO National Laboratories Singapore, Ericsson, European Space Agency, Home Team Science and Technology Agency (HTX) Singapore and Reply to train models on the proprietary data that powers their most complex systems and future-defining technologies.

Mistral AI

444,201 次观看 • 5 个月前

A New Episode of the Hivemind is Live! This week Tommy joins us to debate whether AI frontier companies can justify their valuations, the rise of open-source AI, and where enterprise spending is actually going. We also cover SpaceX’s IPO, Hyperliquid’s growth, and the latest around Zcash’s private Bitcoin thesis. Timestamps: 00:00 Introduction & Market Outlook 05:00 OpenAI, Anthropic & Enterprise AI Spending 08:53 Open Source vs Frontier Models 24:41 Are We In An AI Bubble? 35:17 SpaceX IPO & Equity Issuance 38:13 AI Regulation & Political Risk 53:36 Hyperliquid & HYPE 1:04:14 Zcash & The Private Bitcoin Thesis 1:13:16 Final Thoughts

A New Episode of the Hivemind is Live! This week Tommy joins us to debate whether AI frontier companies can justify their valuations, the rise of open-source AI, and where enterprise spending is actually going. We also cover SpaceX’s IPO, Hyperliquid’s growth, and the latest around Zcash’s private Bitcoin thesis. Timestamps: 00:00 Introduction & Market Outlook 05:00 OpenAI, Anthropic & Enterprise AI Spending 08:53 Open Source vs Frontier Models 24:41 Are We In An AI Bubble? 35:17 SpaceX IPO & Equity Issuance 38:13 AI Regulation & Political Risk 53:36 Hyperliquid & HYPE 1:04:14 Zcash & The Private Bitcoin Thesis 1:13:16 Final Thoughts

Delphi Digital

21,214 次观看 • 2 个月前

David Sacks says the data kills the open-source-is-winning narrative, closed models just went from 81% to 89% of enterprise spend. "This is why the share of wallet of closed models 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... Anyone who's saying these closed models are somehow losing, you're just not seeing it in the data." "Nikesh Arora said enterprises would like what he called model fungibility. They would love to commoditize these models and just hot swap them, headless. But then what do you do about memory, context, history? No one's really figured out a way to abstract that stuff away from the model yet."

David Sacks says the data kills the open-source-is-winning narrative, closed models just went from 81% to 89% of enterprise spend. "This is why the share of wallet of closed models 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... Anyone who's saying these closed models are somehow losing, you're just not seeing it in the data." "Nikesh Arora said enterprises would like what he called model fungibility. They would love to commoditize these models and just hot swap them, headless. But then what do you do about memory, context, history? No one's really figured out a way to abstract that stuff away from the model yet."

Fireside Alpha

54,383 次观看 • 1 个月前