这份文字稿记录了FirstMark的Matt Turk对Astrid Capital创始人Nathan Benneish关于其“2025年AI状况”报告的采访。该报告可在stateof.ai免费获取，是对AI领域的一份全面概述。 他们首先讨论了AI研究的进展，尤其是在**推理**方面。Benneish强调，2025年标志着一个重大飞跃，他指出，大约12个月前，他们只看到了系统展现推理的早期迹象。现在，进展令人震惊，尤其是在可验证的领域，例如数学。他提到了AI在国际数学奥林匹克竞赛中获得金牌，以及模型被用作生物学和科学领域的AI共同科学家，帮助解读疾病新靶点等例子。他指出，这种进步使AI能够应对即使是聪明的人类也无法解决的挑战，不再仅仅是随机的。 对话转向了**机器人技术和“行动链”**，这是一种机器人行动前规划步骤的推理过程。Benneish指出，机器人技术正在经历一场寒武纪大爆发，语言模型正在指导机器人行动。他以CERIAC为例，并表示它确实有效，不仅仅是研究成果。他认为机器人技术的辉煌时刻已经到来，尤其是在工业环境、物流和仓储领域。虽然人形机器人吸引了人们的注意力，但他预测其发展路径将类似于自动驾驶，会出现零星的成功，但在长尾效应方面面临挑战。 谈到**AI的商业化**，Benneish断言它终于赶上了炒作的步伐。他强调了顶级AI公司的收入增长，现在已经达到数百亿美元，以及小型AI公司的快速增长。他引用了Ramp的数据，显示AI订阅的续订率有所提高，客户在AI产品上的支出也大幅增加。他指出，现在有44%的美国企业为AI工具付费，个人使用率更高（95%），反映了组织内部的“影子AI”现象。 他们探讨了**利润率之争**，指出人们对当前基于token的定价模式感到担忧，在这种模式下，不同的客户无论用例如何，都支付相同的价格。这种模式可能会导致垂直AI产品的毛利率较低。然而，Benneish指出，一些公司在其AI系统上实现了非常高的利润率（70-90%）。 关于**AI泡沫**的问题，Benneish承认存在局部泡沫。他将纽约金融圈以泡沫为中心的观点与旧金山更为乐观的情绪进行了对比，后者得益于人才涌入和基础设施建设。然而，他承认该行业正在进行巨额投资，以Nvidia为中心存在循环交易。他还提到了大型公司转移债务以支持其AI野心。他认为地缘政治和宏观经济因素为AI行业带来了脆弱性。 在讨论**物理现实和基础设施**时，Benneish强调电力已成为新的瓶颈。他引用了建设和运行基于AI的数据中心的高昂成本。各公司都在争夺能源，与未来的核电站签订协议，并在短期内依赖燃气轮机。电网限制正在推动数据中心向能源丰富的国家转移，这引发了地缘政治担忧。他提到了数据中心冷却所需的水资源，以及这种做法的可持续性。 对话转向了**Nvidia的主导地位**。Benneish认为它将继续保持领先地位，因为其芯片在研究论文中的使用率很高（90%）。他提到了AMD的崛起以及Broadcom通过为谷歌的TPU定制ASIC以及与OpenAI的交易而获得的复苏。尽管有竞争者，但Nvidia的股票表现明显优于其竞争对手。 他们谈到了**主权AI**，这是由希望控制其AI能力的国家推动的，导致全球范围内的巨额投资。Nvidia甚至将其作为一条新的产品线进行营销。虽然Benneish认为这是一种营销策略，但它与再工业化努力以及各国需要访问AI的需求相一致。然而，他认为对AI的访问可以被关闭。 谈话涉及**开源AI**，包括美国版的中国模型。Benneish认为，OpenAI正是在这种压力下才转向开源的。 他们还深入研究了**AI生态系统中的集中度**，指出Nvidia的大部分收入来自超大规模厂商和新云厂商。这种集中度反映了从个体创新向需要大量资本的大规模努力的转变。他指出了公司哲学为适应新的规模和AI的金融化而发生的演变。 对话触及了**安全、监管和数据权利**。Benneish认为监管未能跟上发展的步伐。他指出，AI已经发展到可以轻松访问，而没有安全参数。 他提到，不良数据集可能会带来高昂的惩罚，Throttic支付了15亿美元的庭外和解金，以避免未来的影响。 关于**网络安全**问题，Benneish指出了模型在网络任务和网络犯罪方面的能力日益增强。 最后，他们讨论了**AI Agent**，强调了它们在垂直产品、搜索、咨询、编码和科学推理方面的潜力。 他还提到，在某个时刻，SaaS可能会变成Agent。 最后，Benneish提出了预测，包括计算/AI建设将变得具有政治色彩，AI的科学发现将获得诺贝尔奖，各国将放弃实现AI主权的希望，转而寻求中立。

This transcript features Matt Turk from FirstMark interviewing Nathan Benneish, founder of Astrid Capital, about his "State of AI 2025" report. The report, available for free at stateof.ai, is a comprehensive overview of the AI landscape. They begin by discussing advancements in AI research, particularly in **reasoning**. Benneish highlights that 2025 marks a significant leap, noting that about 12 months ago, they only had early signs of systems showing reasoning. Now, progress is astounding, especially in verifiable domains like mathematics. He mentions examples like AI achieving gold medals in the International Math Olympiad and models being used as AI co-scientists in biology and science, helping decipher new targets for disease. He notes that the progress has allowed AI to tackle challenges that even smart humans couldn't, moving away from being purely stochastic. The conversation shifts to **robotics and "chain of action,"** a reasoning process where robots plan steps before acting. Benneish notes that robotics is experiencing a Cambrian explosion, with language models informing robotic actions. He uses CERIAC as an example and said it does genuinely work and is not just a research thing. He believes robotics' big moment is here, especially in industrial settings, logistics, and warehousing. While humanoid robots attract attention, he predicts a path similar to self-driving, with isolated successes but challenges in the long tail. Moving to the **business of AI**, Benneish asserts that it's finally caught up with the hype. He highlights the revenue growth of top AI companies, now in the tens of billions of dollars, and the rapid growth of smaller AI firms. He cites data from Ramp showing improved retention rates for AI subscriptions and a significant increase in customer spending on AI products. He points out that 44% of US businesses now pay for AI tools, with personal usage even higher (95%), reflecting a "shadow AI" phenomenon within organizations. They explore the **margin debate**, noting concerns about the current token-based pricing model, where different customers pay the same price despite varying use cases. This model can lead to low gross margins for vertical AI products. However, Benneish points out that some companies are achieving very high margins (70-90%) on their AI systems. The **AI bubble** question is addressed, with Benneish acknowledging localized bubbles. He contrasts the bubble-centric view in New York finance circles with the more optimistic sentiment in San Francisco, driven by talent influx and infrastructure build-out. However, he acknowledges the gargantuan sums being invested in the industry, with circular deals centered around Nvidia. He also mentions the offloading of debt from big companies to fuel AI ambitions. He considers geopolitical and macroeconomic factors create vulnerabilities for the AI sector. Discussing the **physical reality and infrastructure**, Benneish emphasizes that power has become the new bottleneck. He cites the high cost of building and running AI-based data centers. Companies are scrambling for energy, inking deals with future nuclear plants and relying on gas turbines in the short term. Grid limitations are driving offshoring of data centers to energy-rich countries, raising geopolitical concerns. He mentions water usage needed for data center cooling and the sustainability of this. The conversation moves to **Nvidia's dominance**. Benneish believes it will remain the leader, citing its prevalence in research papers (90% use Nvidia chips). He mentions AMD's emergence and Broadcom's revival with custom ASICs for Google's TPUs and a deal with OpenAI. Despite contenders, Nvidia's stock performance significantly outperforms its competitors. They touch on **sovereign AI**, driven by nation-states wanting control over their AI capabilities, leading to massive investments worldwide. Nvidia is even marketing this as a new product line. While Benneish sees this as a marketing play, it aligns with reindustrialization efforts and the need for countries to access AI. However, he believes access to AI can be switched off. The talk touches on **open source AI**, including the US equivalent of the Chinese models. Benneish believes that OpenAI was pushed into open source due to this. They also delve into **concentration within the AI ecosystem**, pointing out that a significant portion of Nvidia's revenue comes from hyperscalers and neoclouds. This concentration reflects the shift from individual innovation to large-scale endeavors requiring significant capital. He notes the evolution of company philosophy to meet the new scale and financialization of AI. The conversation touches on **safety, regulatory and data rights**. Benneish feels the regulatory is failing to keep up with the progress. He notes that AI has evolved to be able to be easily accessed with no safety parameters. He goes into the fact that bad data sets can have high penalties, with Throttic settling a $1.5 Billion settlement out of court to avoid future ramifications. On **cybersecurity** concerns, Benneish notes the rising capabilities of models in cyber tasks and cyber crime. Finally, they discuss **AI agents**, highlighting their potential in vertical products, search, consulting, coding, and scientific reasoning. He also mentions that at some point SaaS may become agent. To close, Benneish offers predictions, including that computing/AI buildout will become politically charged, scientific discovery by AI will earn a Nobel Prize, and countries will abandon the hope of achieving AI sovereignty in favor of neutrality.