以下是将A16Z播客节目的描述翻译成中文： 本期A16Z播客节目邀请了普通合伙人马克·安德森（Mark Andreessen）、维杰·潘迪（Vijay Pande）和朱利尤（Juliyu），探讨了人工智能（AI）改变医疗保健行业的潜力。对话涉及当前体系不断上涨的成本、糟糕的结果和复杂性，同时探讨了技术，特别是AI，是否可以成为积极变革的催化剂。 讨论首先对美国医疗保健系统进行了批判，指出尽管拥有先进的技术和熟练的医生，但它仍在与高成本和不尽人意的结果作斗争。小组成员辩论解决方案是政策监管还是技术进步。他们承认，治愈癌症等疾病可能比解决医疗保健交付的复杂问题更容易。 探讨的主要问题是，医疗保健领域的本土公司还是科技领域的局外人将领导医疗保健领域的人工智能革命。维杰主张成立一家“AI原生”且“医疗保健原生”的初创公司，认为现有企业面临惯性和难以适应的问题。马克反驳说，AI工具可以集成为全栈“劳动力单元”，甚至可以作为在现有医疗保健框架下运营的独立业务，但内部经济和可扩展性将发生根本变化。共识是成功需要对医疗保健和人工智能都有深刻的理解。 小组成员探讨了将AI应用于医疗保健某些领域的问题。他们预计AI最初将应用于护理和初级保健等亚临床领域，然后再逐渐进入临床领域。他们预测，将其应用于脑外科等专业领域将更加困难，尽管机器人设备正在为AI创造数字入口。马克强调了“莫拉维克悖论”，解释了为什么AI擅长抽象的、数据驱动的任务，但在物理的、混乱的和不可预测的情况下却举步维艰。 讨论转向医疗保健领域技术采用速度缓慢的问题，将其归因于医疗保健企业内部的低IT预算。他们讨论了将劳动力预算分配给AI解决方案的可能性，用能够处理亚临床任务的AI驱动工具来替代未填补的职位。 马克回答了我们是在等待更好的数据还是更好的算法来彻底改变医疗保健的问题，并以特斯拉的自动驾驶汽车为例。通过将神经网络放入汽车中，让它们从真实世界的数据中学习，特斯拉在自动驾驶技术方面取得了显著进展。这突出了将AI暴露于真实世界情况以收集数据并提高其性能的重要性。 对话触及了医院的中心化如何使个人消费者难以获得个性化护理的问题。他们相信技术可以改变医疗保健的发展轨迹。小组成员讨论了未来AI可以分散医疗保健交付，使其在家庭和社区环境中可访问且负担得起的潜在未来。 马克解释说，由于供应受限和需求受补贴，教育、住房和医疗保健等行业的生产力增长持平或负增长。他还讨论了博莫尔的成本病（BOML's cost disease），即尽管缺乏生产力，但医疗保健的成本却越来越高，因为工人们有动力在生产力更高的行业工作。安德森强调需要技术来打破成本曲线并推动生产力增长。他指出了药物应用的重要性，区分了美国擅长的急症护理和经常处理不当的慢性护理。 讨论的重点是监管严格的医疗保健系统，以及我们的支付监管是否会改变未来治疗的应用方式。小组成员一致认为，不仅仅是医疗保健受到严格监管，而且它也受到补贴并且供应有限。他们相信技术是解决方案。 小组成员认为，赋能消费者是医疗保健的未来。该小组讨论了一个人们可以用自己的预算做出自己的医疗保健选择的系统。在这种模式下，保险模式可能侧重于急症护理，而消费者可以在更灵活的基础上决定他们的保险范围。 他们最后谈到了健康科技的更广泛概念以及这个领域的新兴。马克分享了 V.I. 列宁的观点，即技术的应用需要几十年。他强调同伴之间的学习以及向健康发展的趋势。他们提到越来越多的医生加入 TikTok 并分享有关该行业的信息。小组成员认为这些都是技术应用于医疗保健的令人鼓舞的迹象。 小组以轻松的语气结束了关于健康科技采用的讨论。安德森分享了他儿子对技术的矛盾态度，以及年轻一代在采用新技术方面将拥有的优势。他们相信孩子们会拥有学习新技术和技能所必需的玩世不恭的态度。

This podcast episode from A16Z features General Partners Mark Andreessen, Vijay Pande, and Juliyu discussing the potential for AI to transform the healthcare industry. The conversation tackles the rising costs, poor outcomes, and complexities of the current system, while exploring whether technology, particularly AI, can be a catalyst for positive change. The discussion begins with a critique of the American healthcare system, noting that despite having advanced technology and skilled doctors, it struggles with high costs and subpar outcomes. The panelists debate whether the solution lies in policy regulation or technological advancements. They acknowledge that curing diseases like cancer might be easier to address than the intricate issues of healthcare delivery. The primary question explored is whether a healthcare-native company or a tech outsider will lead the AI revolution in healthcare. Vijay advocates for a startup that's "AI native" and "healthcare native," arguing incumbents face inertia and difficulty adapting. Mark counters by suggesting that AI tools could be integrated as full-stack "labor units" or even as standalone businesses operating under the existing healthcare framework, but with radically different internal economics and scalability. The consensus is that success requires a deep understanding of both healthcare and AI. The panelists explore the question of applying AI to certain areas of healthcare. They expect AI to be applied to subclinical areas like nursing and primary care initially, before inching into the clinical side. They predict it will be much harder to apply to specialized areas like brain surgery, although robotic devices are creating digital inroads for AI. Mark highlights "Moravac's Paradox," explaining why AI excels at abstract, data-driven tasks but struggles with physical, messy, and unpredictable situations. The discussion shifts to the slow rate of technology adoption in healthcare, attributing it to low IT budgets within healthcare enterprises. They discuss the possibility of allocating labor budgets towards AI solutions, replacing unfilled positions with AI-powered tools capable of handling subclinical tasks. Mark addresses the question of whether we’re waiting on better data or better algorithms to revolutionize healthcare and points to Tesla's self-driving car as a case study. By putting neural networks into cars and letting them learn from real-world data, Tesla achieved significant advancements in self-driving technology. This highlights the importance of exposing AI to real-world situations to gather data and improve its performance. The conversation touches on how the centralization of hospitals has made it difficult for individual consumers to access personalized care. They believe that technology can change the trajectory of healthcare. The panelists discuss a potential future where AI can decentralize healthcare delivery, making it accessible and affordable in home and community settings. Mark explains how industries like education, housing, and healthcare suffer from flat or negative productivity growth due to constrained supply and subsidized demand. He also discusses BOML's cost disease, the phenomenon whereby healthcare is increasingly expensive despite lacking productivity because workers are incentivized to work in more productive industries. Andreessen emphasizes the need for technology to break cost curves and drive productivity growth. He points out the importance of how medicine is applied, distinguishing between acute care, where the U.S. excels, and chronic care, which is often treated inadequately. The discussion focuses on the issue of heavily regulated healthcare systems and whether our payment regulation is going to change how therapies are applied in the future. The panelists agree that it's not just that healthcare is heavily regulated but that it's also subsidized and has a limited supply. They believe technology is the solution. The panelists believe empowering consumers is the future of healthcare. The panel discussed a system where people can make their own healthcare choices with their own budgets. In this model, the insurance model may focus on acute care, and the consumers can decide on their coverage on a more flexible basis. They conclude by addressing the broader notion of health tech and how new this field is. Mark shares the views of V.I. Lennon and how the application of technology takes decades. He emphasizes peer-to-peer learning and movements toward health. They mention that more and more doctors are joining TikTok and sharing about the industry. The panelists believe these are encouraging signs for the application of technology to healthcare. The panel ends on a light-hearted note regarding the adoption of health tech. Andreessen shares his son's ambivalence towards technology and how younger generations will be at an advantage to adopt new technology. They believe the kids will have the playful attitude that is necessary to learn new technology and skills.