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슬라이드 3장34:35EN
SemiAnalysis· 2026년 10월 23일팟캐스트 · 3명SemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool Ecosystem게스트 Sherry Zhang, Howie · 진행자 Jordan NanosJordan Nanos, Sherry Zhang and Howie examine a track-based bonding design that brings the wafer to the die, then explain why adoption depends on precision, cleanliness, economics and a changing supply chain.Semiconductors인프라와 배포Geopolitics
1:00:39EN
a16z· 2026년 10월 23일팟캐스트 · 3명Amazon CEO Andy Jassy on the $220 Billion AI Buildout게스트 Andy Jassy · 진행자 Ben Horowitz, Erik TorenbergEven at roughly $220 billion of 2026 CapEx, Jassy says Amazon is still turning away AI demand. He tells Ben Horowitz and Erik Torenberg why AWS could become a trillion-dollar run-rate business, and why inference cost, custom chips, and smaller teams matter more than squeezing old customers.AI Strategy인프라와 배포Semiconductors+2
슬라이드 19장1:09:00EN
Dwarkesh Patel· 2026년 10월 22일팟캐스트 · 9명Dwarkesh Patel: What will computer chips look like in 2045?게스트 Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · 진행자 Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.SemiconductorsAI cost & performance인프라와 배포+2
59:41EN
20VC with Harry Stebbings· 2026년 10월 22일팟캐스트 · 3명20VC: Venture Fund Size, AI Valuations and the Changing Software Market게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O'Driscoll debate venture concentration, infrastructure risk, code review and the assumptions behind fast-growing AI companies.Venture CapitalInvestingAI cost & performance+2
슬라이드34:07EN
Zhang Xiaojun Podcast· 2025년 4월 26일팟캐스트 · 3명Ola Källenius on Mercedes-Benz’s Next Transformation: EVs, AI, and Modern Luxury게스트 Ola Källenius · 진행자 张小珺Mercedes-Benz CEO Ola Källenius describes a century-scale shift driven by zero-emission powertrains, software, and AI. He explains why the company is expanding electric models while protecting the craftsmanship, safety, and desirability that define its luxury position.Autonomous DrivingProduct Strategy기업과 전략+2
2:29:41ZH
Zhang Xiaojun Podcast· 2025년 4월 7일팟캐스트 · 4명陈建宇:机器人基座模型如何走向通用 VLA게스트 陈建宇 · 진행자 张小珺从 SayCan、RT-2 到 Diffusion Policy,清华助理教授、星动纪元创始人陈建宇梳理机器人模型从借用语言模型到端到端 VLA 的路线。关键难题仍是多样化数据、跨本体泛化和高频动作控制。Robotics모델과 학습Multimodal AI+2
1:27:02ZH
Zhang Xiaojun Podcast· 2024년 9월 5일팟캐스트 · 3명广密:Self-play RL 可能开启 AGI 的新 Scaling Law게스트 广密 · 진행자 张小珺广密认为,纯靠语言预训练扩展模型的边际收益可能正在减弱,self-play 强化学习是更值得押注的新路径。它能否泛化到代码、视频、机器人和更广的领域,将决定下一阶段的 AGI 竞赛。Reinforcement LearningAGI(범용 인공지능)Scaling Laws+2
49:41ZH
Zhang Xiaojun Podcast· 2024년 8월 17일팟캐스트 · 3명傅盛:大模型是生产力革命,机器人迎来新的窗口게스트 傅盛 · 진행자 张小珺傅盛认为,大模型的核心是逻辑与推理能力,它带来的变化更像蒸汽机,而不是一次普通的互联网迭代。从平民化模型、服务机器人到创业者如何面对低谷,他也回看了自己的判断与心境。AI Strategy모델과 학습Robotics+2
1:07:14ZH
Zhang Xiaojun Podcast· 2024년 8월 17일팟캐스트 · 3명王亚军:情商不是组织的万能解法게스트 王亚军 · 진행자 张小珺龙湖前首席战略官王亚军谈情商、理性与组织协作:个人靠情商适应环境,企业却需要可扩展的共同方法。高管若只靠揣摩和关系维持运转,决策就会逐渐失去现实感。기업과 전략Company BuildingLeadership+2
1:35:39EN
Lenny's Podcast팟캐스트 · 3명Make Time: Pick a Daily Highlight and Build Barriers Against Distraction게스트 Jake Knapp, John Zeratsky · 진행자 Lenny RachitskyJake Knapp and John Zeratsky walk through their four-step Make Time framework (highlight, laser, energize, reflect) and close with a short look at the design sprint.제품과 UXTime ManagementProductivity+3
1:46:33EN
Lenny's Podcast팟캐스트 · 3명From Chaos to a Failure Map: A Hands-On Primer on AI Evals게스트 Hamel Husain, Shreya Shankar · 진행자 Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.평가와 관측 가능성평가(Evals)AI 엔지니어링 리더십+3
1:47:58EN
Lenny's Podcast팟캐스트 · 3명Bridging the Divide: How Community Notes Built a Trusted Fact-Checking System on Disagreement게스트 Keith Coleman, Jay Baxter · 진행자 Lenny RachitskyKeith Coleman and Jay Baxter, the team behind Community Notes, explain how the algorithm works, how a tiny team built it, and why it survived four leaders at Twitter and X.오픈소스와 커뮤니티안전과 거버넌스Product Leadership+3