Scott Wilson深知做出反向押注并大获成功是什么滋味。他早期对SpaceX的投资为华盛顿大学的捐赠基金创造了数十亿美元的意外之财。现在，他正在进行另一项反向押注：万亿美元级的AI实验室陷入了大麻烦。Wilson认为，OpenAI和Anthropic承诺了巨额支出，而更便宜的中国模型正在追赶。这一观点让他与Vinod Khosla等AI看多派截然对立，后者认为正是这些大规模基础设施投资将使前沿实验室难以被超越。“这些市值超过万亿美元的前沿公司，不值得它们所承担的负债，”Wilson表示。“将会有大量免费替代品出现。”
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
OpenAI为风投机构以及密歇根大学等学府带来了巨额账面收益，后者早期投资OpenAI 2000万美元，如今价值已超20亿美元。Wilson透露，他也曾有机会早期投资OpenAI，但因不相信该公司能盈利而放弃。此后，他的看空观点愈发坚定。“当我们审视同行参与并大赚账面财富的原始OpenAI交易时，我们持高度怀疑态度，”Wilson说。“随着时间的推移，我变得更加怀疑。”
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
上周，Wilson在Rock Yard Roundup大会上分享了他所谓的“不受欢迎的观点”，这是一个在沃斯堡举行的约100名资产管理者、风投和科技创始人的聚会。在乡村酒吧巡游和参观Stockyards Rodeo牛仔竞技表演之间，他将前沿AI竞赛比作另一种“狂野西部”：在他的眼中，这是一场失控支出和估值的狂欢，不太可能有个好结局。
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
Wilson的警告发布之际，DeepSeek、阿里巴巴通义千问、智谱AI和腾讯等中国模型厂商已在性能上缩小了与美国前沿实验室的差距，同时提供了大幅成本优势。
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
这引发了投资者更广泛的争论：如果客户可以转向更便宜且效果几乎相当的替代方案，OpenAI 和 Anthropic（预计下月上市）能否维持保持领先所需的巨额支出。威尔逊解释说，在与身处中国的一线同事交谈后，他对前沿实验室变得更加怀疑，这些同事见证了开放权重模型的快速进展。在与华盛顿大学投资的公司创始人交谈后，他的担忧加剧，对方告诉他，他们都在转向更便宜的模型。“每当我们与投资组合公司交谈，尤其是那些大量使用 AI 的公司，他们都在积极转向开源模型，”他说。“这就像任何其他高成本的美国商品，必须与低成本进口商品竞争，特别是来自中国的商品。”OpenRouter（一个开发者在其中路由 AI 模型请求的平台）的数据支持威尔逊的论点，尽管这只是一个有限的快照。在 OpenRouter 上，DeepSeek 占文本模型请求的 25.3%，而 OpenAI 为 18.6%，Anthropic 为 2.9%。早期投资 OpenAI 的亿万富翁风投 Vinod Khosla 告诉《商业内幕》，他强烈不同意威尔逊的观点，并表示自己从未像现在这样看好 OpenAI。“持那种观点的人很愚蠢，他们不懂这行是怎么运作的，”得知威尔逊的看法后，他说。“他们有一种观念，认为模型本身就是价值。”Khosla 认为，真正的优势在于控制模型底层更多昂贵的基础设施。闭源模型公司可以围绕自己的模型和服务系统协同设计芯片，就像 OpenAI 与其 Jalapeño 推理芯片所做的那样。他说，这能减少对英伟达硬件和第三方云服务的依赖，从而降低其服务客户的成本，相较于在别人云上运行的开放权重模型更具优势。“我谈的不是价格，是成本，”他说。
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
从电力到数据中心再到芯片，从基础设施软件到推理模型，全栈成本在闭源模型中几乎肯定会比开源模型更低。
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11
您有关于AI实验室的线索吗？请通过Signal安全联系首席记者Ben Bergman，账号为@benbergman.11
Scott Wilson knows what it is like to make a contrarian bet that pays off big. His early investment in SpaceX helped create a multi-billion dollar windfall for Washington University's endowment. Now he's making another one: The trillion-dollar AI labs are in major trouble. Wilson argues that OpenAI and Anthropic have committed to enormous spending just as cheaper Chinese models are catching up. It's a view that puts him squarely at odds with AI bulls like Vinod Khosla, who believes those massive infrastructure investments are precisely what will make the frontier labs hard to beat. "These trillion-dollar-plus frontier companies are not worth the liabilities that they signed up for," Wilson said. "There's going to be a ton of free alternatives." OpenAI has returned huge markups for VC firms as well as schools such as the University of Michigan, whose early $20 million OpenAI investment is now worth over $2 billion. Wilson said he also had the chance to be an early investor in OpenAI but passed because he was not convinced the company would ever make money. Since then, his bearish view has hardened. "When we looked at the original OpenAI deal that some of our peers participated in and made tons of money on paper, we were highly skeptical," Wilson said. "I've gotten more skeptical over time." Wilson shared what he called his "unpopular opinion" onstage last week at Rock Yard Roundup, a Fort Worth gathering of roughly 100 asset managers, VCs, and tech founders. Between a honky-tonk crawl and a visit to the Stockyards Rodeo, he cast the frontier AI race as its own kind of Wild West: a frenzy of runaway spending and valuations that, in his view, is unlikely to end well. Wilson's warning comes as Chinese model makers such as DeepSeek, Alibaba's Qwen, Zhipu AI, and Tencent have narrowed the gap with U.S. frontier labs on performance while offering major cost savings. That has fueled a broader investor debate over whether OpenAI and Anthropic, which is expected to go public next month, can sustain the enormous spending required to stay ahead if customers can switch to cheaper alternatives that are almost as good. Wilson explained that he has become more dubious about frontier labs after talking to his colleagues on the ground in China, who have seen rapid progress in open-weight models. He grew more concerned after speaking with the founders of companies Washington University has invested in, who told him they were all switching to cheaper models. "Whenever we talk to our portfolio companies, especially the ones who are heavy of AI, they are all moving aggressively towards open source," he said. "It's like any other high-cost U.S. good that has to compete with a low-cost import, particularly from China." Data from OpenRouter, a platform where developers route requests among AI models, supports Wilson's argument, though it is a limited snapshot. DeepSeek accounts for 25.3% of text-model requests on OpenRouter compared with 18.6% for OpenAI and 2.9% for Anthropic. Vinod Khosla, a billionaire venture investor who was an early investor in OpenAI, told Business Insider he strongly disagrees with Wilson and said he has never been more bullish on OpenAI. "People like that are silly, and they don't understand how this works," he said when told of Wilson's view. "They have this notion that the model is the value." Khosla argued that the real advantage lies in controlling more of the expensive infrastructure beneath the model. A closed-model company can co-design chips, as OpenAI has done with its Jalapeño inference chip, around its own models and serving systems. That could reduce its reliance on Nvidia hardware and third-party cloud services, he said, lowering its cost to serve customers relative to an open-weight model run on someone else's cloud. "I'm not talking price, I'm talking about cost," he said. "From power to data center to chips, to infrastructure software to inference models, the cost of the stack is almost certainly going to be lower in closed-source models than open-source." Do you have a tip about AI labs? Reach out to chief correspondent Ben Bergman securely on Signal at @benbergman.11