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  • All-In with Chamath, Jason, Sacks & Friedberg
    All-In with Chamath, Jason, Sacks & Friedberg

    1

    All-In with Chamath, Jason, Sacks & Friedberg

    All-In Podcast, LLC

  • Acquired
    Acquired

    2

    Acquired

    Ben Gilbert and David Rosenthal

  • Lex Fridman Podcast
    Lex Fridman Podcast

    3

    Lex Fridman Podcast

    Lex Fridman

  • 硅谷101
    硅谷101

    4

    硅谷101

    硅谷101

  • No Priors: Artificial Intelligence | Technology | Startups
    No Priors: Artificial Intelligence | Technology | Startups

    5

    No Priors: Artificial Intelligence | Technology | Startups

    Conviction

  • 罗永浩的十字路口
    罗永浩的十字路口

    6

    罗永浩的十字路口

    罗永浩的十字路口

  • Search Engine
    Search Engine

    7

    Search Engine

    PJ Vogt

Essentials

  • Hard Fork
    Technology
    Technology

    Every two weeks

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    Technology
    Technology

    Updated twice weekly

  • There Are No Girls on the Internet
    Technology
    Technology

    Updated weekly

  • Endless Thread
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    Technology

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  • Land of the Giants
    Business
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    Weekly series

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  • Uncanny Valley | WIRED
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  • 杨笠×罗永浩!不想成为“靶心”,也无意成为“灯塔”

    1 DAY AGO

    1

    杨笠×罗永浩!不想成为“靶心”,也无意成为“灯塔”

    《十字路口》播客节目简介 本节⽬是⼀档由罗永浩主持的深度播客类节⽬,每集长达三到五个小时。我们与时代浪潮中的⼈物展开对话,聚焦于科技与⼈⽂领域,讲述个体命运故事,探讨时代发展趋势。 本期嘉宾:杨笠 当整个互联网都为她的那个段子争吵、撕裂时,杨笠感受到的是一种极致的荒诞。她人生最黑暗的时刻和最高光的时刻同时来临,让她不知道该如何面对和言说,只能错愕地吞下生活给她的苦果......和糖果。 在这场长达近四个小时,由“中国互联网最招黑体质”的两个人完成的对谈中,杨笠回顾了成长的种种往事,也包括那场席卷全网的舆论风暴。当这场风暴变得越诡谲,越来越复杂的时候,作为一名职业喜剧演员,她决定化繁为简,“只服务喜剧标准”,微笑着继续“冒犯”这个她无法回避的生活。 从河北农村的猪圈旁,到火遍全国的综艺舞台,再到四千人体育馆里为她一个人点亮的聚光灯下,这一路,她没有刻意地选择坚强,当然也从没有考虑过选择退缩,她选择了平静地走到那个可以随心所欲,不强求被喜欢,也不畏惧被讨厌的真实自我。 这一期的播客,是送给所有被误解、被污蔑、被命运作弄,但仍想守住内心平静的那些人的,一个精神上的拥抱。 【你将听到】00:01:30巡演后续 00:15:45回顾童年 00:36:22大学时期 01:00:41毕业之后 01:14:42首次登台 01:38:16一夜爆红 01:52:10关于那次拍灯 02:29:24和粉丝的关系 02:52:44演出的初衷 03:00:34专场、创作与行业 03:10:00《爱江山更爱美人》 03:22:07线下专场分享 03:33:27圈内人 03:38:04终身创作 欢迎关注: 微博 @罗永浩的十字路口 B站 @罗永浩的十字路口 抖音 @罗永浩的十字路口 小红书 @罗永浩的十字路口 商务合作:欢迎发送邮件至 jayci_chen@163.com

    1 day ago

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    3h 43m
  • #494 – Jensen Huang: NVIDIA – The $4 Trillion Company & the AI Revolution

    4 DAYS AGO

    2

    #494 – Jensen Huang: NVIDIA – The $4 Trillion Company & the AI Revolution

    Jensen Huang is the co-founder and CEO of NVIDIA, the world’s most valuable company and the engine powering the AI computing revolution. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep494-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/jensen-huang-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: NVIDIA: https://nvidia.com NVIDIA on X: https://x.com/nvidia NVIDIA AI on X: https://x.com/NVIDIAAI NVIDIA on YouTube: https://youtube.com/@nvidia NVIDIA on Instagram: https://www.instagram.com/nvidia/ NVIDIA on LinkedIn: https://www.linkedin.com/company/nvidia/ NVIDIA on Facebook: https://www.facebook.com/NVIDIA/ NVIDIA on GitHub: https://github.com/NVIDIA Nemotron: https://developer.nvidia.com/nemotron SPONSORS: To support this podcast, check out our sponsors & get discounts: Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ Shopify: Sell stuff online. Go to https://shopify.com/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex Fin: AI agent for customer service. Go to https://fin.ai/lex Quo: Phone system (calls, texts, contacts) for businesses. Go to https://quo.com/lex OUTLINE: (00:00) – Introduction (00:26) – Sponsors, Comments, and Reflections (06:34) – Extreme co-design and rack-scale engineering (09:20) – How Jensen runs NVIDIA (28:41) – AI scaling laws (43:41) – Biggest blockers to AI scaling laws (45:25) – Supply chain (47:20) – Memory (53:25) – Power (58:45) – Elon and Colossus (1:02:13) – Jensen’s approach to engineering and leadership (1:07:38) – China (1:15:51) – TSMC and Taiwan (1:21:06) – NVIDIA’s moat (1:26:43) – AI data centers in space (1:30:31) – Will NVIDIA be worth $10 trillion? (1:40:40) – Leadership under pressure (1:54:26) – Video games (2:01:18) – AGI timeline (2:03:31) – Future of programming (2:17:02) – Consciousness (2:23:23) – Mortality PODCAST LINKS: – Podcast Website: https://lexfridman.com/podcast – Apple Podcasts: https://apple.co/2lwqZIr – Spotify: https://spoti.fi/2nEwCF8 – RSS: https://lexfridman.com/feed/podcast/ – Podcast Playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 – Clips Channel: https://www.youtube.com/lexclips

    4 days ago

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  • Four CEOs on the Future of AI: CoreWeave, Perplexity, Mistral, and IREN

    4 DAYS AGO

    3

    Four CEOs on the Future of AI: CoreWeave, Perplexity, Mistral, and IREN

    (0:00) Intro live from Nvidia GTC (0:37) CoreWeave CEO, Michael Intrator (32:58) Perplexity CEO, Aravind Srinivas (1:07:11) Mistral CEO, Arthur Mensch (1:18:57) IREN CEO, Daniel Roberts Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE - https://nyse.com Follow the besties:  https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect

    4 days ago

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    1hr 38min
  • Are Psychedelics the Key to Living Forever? (ft. Bryan Johnson)

    2 DAYS AGO

    4

    Are Psychedelics the Key to Living Forever? (ft. Bryan Johnson)

    (0:00) David Friedberg intros Bryan Johnson (0:54) Why Bryan Johnson did 5-MeO-DMT (12:56) What brain scans actually show (18:36) Psychosis, bad trips, and life-altering decisions (26:23) The next frontier: organoids and gene therapy (33:26) GLP-1s, abundance, and human optimization (35:35) The longevity drug nobody's talking about? Thanks to our partner for making this happen! The Pod by Eight Sleep cools your bed to 55°F and uses Autopilot to optimize your sleep, all night. Use code ALLIN at https://www.eightsleep.com/allin for up to $350 off. Follow Bryan: https://x.com/bryan_johnson https://www.youtube.com/BryanJohnson Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect

    2 days ago

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    38 min
  • E230|1万亿收入预期背后:英伟达的巅峰与软肋

    2 DAYS AGO

    5

    E230|1万亿收入预期背后:英伟达的巅峰与软肋

    本期播客是硅谷101在GTC 2026大会期间的线下特别录制,我们从老黄在Keynote上抛出的那几个大数字开始聊起: 1万亿——这是黄仁勋预期到2027年底,Blackwell和Vera Rubin两个平台带来的订单收入。 7块——这是大会一次性发布的Vera Rubin新芯片数量。 10倍、35倍——这是Vera Rubin NVL72 AI机架系统,相比Blackwell,它的推理效率提升了10倍,每瓦Token产出性能是之前的35倍。 但我们聊的远不止数字本身,也不只是芯片的故事。当推理拐点全面到来,算力狂奔的路上,芯片设计、代工产能、推理架构、软件生态、电力基建、云服务运营……这些环节都在被重新丈量。 在这场串联起AI全产业链关键节点的线下对谈中,我们试图穿透英伟达庞大的AI生态帝国表象,看清它真正的护城河,以及那些潜伏在高速增长背后的软肋与隐忧。 【主播】 泓君,硅谷101创始人,播客主理人 【嘉宾】 张璐,Fusion Fund创始管理合伙人 Dr.Mark Ren, Agentrys创始人&CEO,前英伟达研究总监 Dr.Zhibin Xiao, ZFLOW AI创始人&CEO,前CASPA主席与董事会顾问 Alex Yeh,GMI Cloud创始人&CEO 【你将听到】 万亿野心背后的产业现实 03:21 万亿目标背后,推理业务正成为英伟达关键收入来源 05:50 供应链瓶颈:CoWoS产能成最大挑战,硬件周期非资金可突破 09:03 七芯齐发的关键:英伟达全公司都在用 Coding Agent 做芯片 10:10 Groq的优势:纯SRAM架构专攻低延迟 15:43 推理芯片创业还有机会吗?关键:找英伟达短板 19:07 未来数据中心是异构的,系统级优化比单芯片更重要 21:25 OpenClaw引爆TOKEN消耗,英伟达NemoCloud能让人惊艳吗? 24:27 SaaS面临挑战:未来软件公司卖的不是软件,是AI劳动力 28:36 未来企业架构:CEO同时管员工和智能体,HR、财务都可外包 30:07 英伟达芯片设计模型ChipNemo,硬件代码也能写,难点在于优化 31:47 谷歌TPU系统能力强,但英伟达的护城河已从CUDA扩展到全栈基础设施 35:28 英伟达的护城河:执行力与供应链 36:14 未来挑战:垂直领域、边缘端与私有化部署的崛起、推理市场红利被分流、资本压力 40:16 观众提问1: 英特尔是否有望成为代工第二源? 42:56 观众提问2:CUDA护城河是否会被Coding Agent削弱? 一线云服务商谈数据中心瓶颈 46:30 数据中心竞速:靠自发电与预制集装箱加速 50:22 谁在引爆GPU云需求?模型训练、视频生成、AI Coding以及OpenClaw 53:39 模块化、标准化、全套打包的AI工厂方案 56:57 不止GPU缺货,数据中心核心配件供应趋紧 58:42 运营GPU云的核心能力:先有卡,再稳得住,SLA是生死线 01:01:04 GPU折旧比资本市场预估更耐久 01:02:08 观众提问3:AI云服务商的差异化策略 【监制】 泓君 【后期】 Amei 【运营】 朱婕 【BGM】 Pulse Runner - Helmut Schenker Interstate 895 - Bonnie Grace Unfinished Stories - Lennon Hutton Seven Daughters - Fabien Tell AI sing-along recaps GTC keynote 本期节目不构成任何投资建议 【在这里找到我们】 公众号:硅谷101 收听渠道:Apple Podcast|Spotify|小宇宙|喜马拉雅|蜻蜓FM|荔枝FM|网易云音乐|QQ音乐 其他平台:YouTube|Bilibili 搜索「硅谷101播客」 联系我们:podcast@sv101.net Special Guests: Alex Yeh, Dr.Mark Ren, Dr.Zhibin Xiao, and 张璐.

    2 days ago

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    1hr 6min
  • Formula 1

    2 MAR

    6

    Formula 1

    Formula 1 is three competitions in one: a 200mph battle of the world's best race car drivers, the world cup of engineering where thousand-person teams spend hundreds of millions designing cars from scratch, and — as one of our listeners perfectly put it — the “Real Housewives of the Garage”, a soap opera of billionaire egos, team politics, and paddock drama that makes for incredible reality television. It's also the world's most popular annual sporting series with over 827 million fans globally — a fact that would shock most Americans, who until a recent viral Netflix series had barely heard of it. Today we tell the story of how a chaotic, deadly, and gloriously dysfunctional European racing series became one of the greatest business stories in sports. For decades, brilliant engineers and daredevil drivers dedicated their lives (and too often lost them) to a league controlled for 45 years by a single man: a former London car dealer named Bernie Ecclestone, who centralized power and extracted billions, while also undeniably single-handedly making the sport successful. Then, in a move no one saw coming, the American company Liberty Media bought the whole thing in 2017, installed a team of Fox Sports and ESPN veterans, and did what Bernie never would — professionalized it. All of a sudden famously money-losing F1 teams turned into real businesses, with the average team valuation today clocking in at an astounding $3.6 billion. Buckle up for one of our most-requested episodes: the wild story of Formula 1. Sponsors: Many thanks to our fantastic Spring '26 Season partners: J.P. Morgan PaymentsServiceNowVercelStatsigLinks: Sign up for email updates and vote on future episodes!The Formula by Joshua Robinson and Jonathan CleggDrive to Survive on NetflixF1 The Movie on Apple TVAdrian Newey, How to Build a CarSenna documentaryWorldly Partners' Multi-Decade Formula One StudyAll episode sourcesCarve Outs: Cirque du Soleil EchoSuper Bowl LX Mic'd UpTonalPrincess Peach: Showtime! on Nintendo SwitchDaloopa for historical financial dataMore Acquired: Get email updates and vote on future episodes!Join the SlackSubscribe to ACQ2Check out the latest swag in the ACQ Merch Store!00:00:00 Intro00:05:52 Origins of F1: Britain, Italy, and Monaco00:30:43 Bernie's Entrance00:37:42 Bernie Consolidates Power00:50:33 F1 as a Global TV Sport (Except America)01:08:08 F1's Incredible Engineering Achievements01:19:34 Senna's Crash and a New Era for Safety01:33:18 The Many Owners of F1, and Bernie's Liquidity Drama01:57:48 FOTA: The attempted breakaway series02:05:07 RedBull, Mercedes, and Reinventing the Sport02:42:33 Liberty Media buys F1 and Brings it to the Modern Era03:05:03 Drive to Survive03:26:45 Apple, TV Rights, and Success in America03:41:52 F1: The Business Today03:56:23 Analysis: Why Did F1 Work… and Was Bernie Necessary?04:05:40 7 Powers04:08:23 Bear vs. Bull Cases04:16:32 Quintessence04:20:08 Carve-Outs + Outro ‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

    2 Mar

    •
    4h 30m
  • GTC 2026:AI的下一个战场不是模型,而是「推理系统」| S10E04

    2 DAYS AGO

    7

    GTC 2026:AI的下一个战场不是模型,而是「推理系统」| S10E04

    2026 年 3 月,英伟达年度开发者大会 GTC 在美国 San Jose 开幕。这一年的 GTC 气氛与往年明显不同——黄仁勋不再需要向市场证明 AI 的价值,因为 Agent 爆发和开源模型崛起已经让算力需求成为行业共识,Token 消耗量正在以百倍速度增长。 本期节目,Diane 在 GTC 现场为大家带来了第一手的观察,也专访了推理优化初创公司 Eigen AI 的联合创始人。Eigen AI 由三位 MIT 背景的创始人于 2024 年中创立,主攻开源大模型的推理加速与企业定制化部署。这次 GTC,他们的推理速度跑分直接登上了黄仁勋 Keynote 的大屏幕,是当前推理速度最快的团队之一。 节目里我们深入聊了为什么推理层正在成为 AI 行业最重要的竞争战场、GPU 和 LPU 各自在推理过程中扮演什么角色、英伟达斥资约 200 亿美元收购 Groq 背后的战略逻辑,以及当前 AI 应用的商业模式为何正在面临系统性挑战。 本期人物 丁教 Diane,「声动活泼」联合创始人、「科技早知道」主播 Di Jin,Co-founder at Eigen AI 主要话题 [00:11] 今年 GTC 最大的不同是什么? 黄仁勋状态明显更放松,不再需要向市场"推销" AI 的价值 Agent 爆发让 Token 消耗量指数级增长,算力需求已成行业共识 开源模型崛起打开了推理层的商业空间,这一层开始变得关键 [09:13] Eigen 是一家什么样的公司,在做什么? 三位 MIT 背景创始人,专攻模型压缩与推理加速 Post Training 帮企业定制模型,Inference 加速让模型跑得更快更便宜 GTC 开幕前两天完成技术突破,推理速度登上黄仁勋 Keynote 大屏幕 [13:24] 过去一年 AI 行业最大的结构性变化是什么? 模型训练层高度集中,GPU 成本比人才成本贵 10 到 100 倍,中小公司已基本出局 Reasoning(推理时扩展)成为新的性能提升路径,让固定模型通过多花算力输出更好结果 Agent 工作流让 Token 消耗量远超对话场景,推理层的优化价值随之暴增 [23:34] 英伟达为什么要花约 200 亿美元收购 Groq?GPU 和 LPU 各自擅长什么? AI 生成回答分两阶段:读懂问题(Prefill)适合 GPU 并行处理,逐字生成答案(Decoding)适合 LPU 串行提速 当前最快模型约每秒 1000 个 Token,Agent 场景未来可能需要每秒 10000 个,GPU 单独难以跨越这道坎 GPU 负责前段、LPU 接手后段,两者组合是目前长序列推理的最优解 [34:04] 推理优化的技术路径有哪些,分几个层次? 底层是 CUDA 算子优化,针对不同模型的矩阵计算特点做精细调整 中间层包括量化(降低数字精度)、剪枝(删除冗余专家模块)、投机解码(小模型预测 + 大模型验证) 最上层是调度与路由,核心是把请求打到存有对应 KV Cache 的 GPU 上,避免重复计算 [44:05] 推理优化怎么在速度、精度和成本之间做取舍? 完全不掉精度、少量掉精度、需要后训练恢复精度,三类方案对应不同客户需求 对话场景最看重 TTFT(第一个字的响应时间),Agent 场景更看重整体任务完成时间 语音交互场景存在天花板:模型再快也超不过人能听懂的速度,快到一定程度就没有意义了 [47:28] AI 应用的商业模式为什么正在出现系统性问题? SaaS 订阅制是历史遗留:以前软件边际成本接近零,现在每用一次 AI 都在真实烧钱 重度用户轻松"用穿"月度套餐,公司不得不限流,引发用户强烈反弹 更合理的方向是按任务完成量收费,但用户心理锚点还没有完成迁移,行业仍在震荡期 [53:52] 开源模型能追上闭源模型吗?推理层未来最大的机会在哪? 行业最大的非共识:开源模型到底能不能真正追上闭源,以及 AGI 算不算已经到来 推理层几乎只能服务开源模型,开源能力的拐点直接决定这个赛道的天花板 一旦开源模型达到拐点,Token 将像电力一样渗透各行各业,推理层的市场规模将彻底打开 黄仁勋的「AI 五层蛋糕」模型 名词解释 LPU(Language Processing Unit) Groq 公司研发的专用芯片,专为大语言模型的文字生成(Decoding)环节优化,通过把高带宽内存直接集成在芯片上,大幅提升了逐字生成的速度,但牺牲了通用性。 TPU(Tensor Processing Unit) 谷歌专为自身 AI 需求定制的芯片,性能强劲且价格相对便宜,但目前仅面向 OpenAI、Anthropic 等少数大型客户供货,缺乏开放的开发者生态。 Quantization(量化) 降低模型内部数字精度以节省存储和计算量的技术。好比把精确到小数点后 10 位的数字改写成精确到 2 位——计算量大幅下降,但对最终输出影响有限。精度从高到低依次为 FP32、BF16、INT8、INT4,越低效率越高,但掉点风险也越大。 Pruning(剪枝) 识别并删除模型中冗余参数或模块的技术。以 MoE 架构为例,模型内部有大量从未被有效训练的"伪专家",将其删除后模型精度几乎不受影响,但推理速度和效率显著提升。 Speculative Decoding(投机解码) 先用小模型快速"草拟"若干 Token,再让大模型批量验证并决定是否采纳的加速技术。当草稿被采纳的概率足够高时,整体推理速度可提升 50% 以上。 KV Cache(键值缓存) AI 在生成回答过程中,将对前文的"理解结果"缓存起来,避免每次都重新读取和计算全部历史内容。合理调度 KV Cache 是 Agent 场景下降低延迟和成本的关键技术之一。 MoE(Mixture of Experts,专家混合架构) 模型内部由多个"专家"子模块组成,每次推理只激活其中最匹配当前任务的少数几个。DeepSeek、Qwen 等主流开源模型均采用此架构,可在维持大参数量的同时显著降低实际计算开销。 SLA(Service Level Agreement,服务水平协议) 对服务质量的量化约定,例如"首字响应时间不超过 300 毫秒"或"每秒至少输出多少个 Token"。推理层的大多数技术决策,都是围绕在成本约束下满足客户 SLA 要求来展开的。 TTFT(Time to First Token,首字时延) 从用户发出请求到收到第一个输出字符的时间间隔。对话类产品中这一指标最为关键,直接影响用户对系统响应速度的主观感受。 「Knock Knock 世界」 上周「Knock Knock 世界」更新了「数字收藏」话题:一段视频、一个表情为什么也能成为博物馆的收藏品?点击这里收听节目👉https://sourl.co/8F55vV 「Knock Knock 世界」是一档适合9岁以上青少年收听的播客,你可以听到全球新鲜事,还能成为「全球观察员」,报选题、参加选题会。2026 年的节目正在持续更新中,可以在各大音频平台搜索订阅。 幕后制作 监制:Yaxian 后期:迪卡 运营:George 设计:饭团 商业合作 声动活泼商业化小队,点击链接直达声动商务会客厅(https://sourl.cn/9h28kj ),也可发送邮件至 business@shengfm.cn 联系我们。 加入声动活泼 声动活泼目前开放商务合作实习生、社群运营实习生和 BD 经理等职位,详情点击招聘入口详情点击招聘入口 关于声动活泼 「用声音碰撞世界」,声动活泼致力于为人们提供源源不断的思考养料。 我们还有这些播客:声动早咖啡、声东击西、吃喝玩乐了不起、反潮流俱乐部、泡腾 VC、商业WHY酱、跳进兔子洞 、不止金钱 欢迎在即刻、微博等社交媒体上与我们互动,搜索 声动活泼 即可找到我们。 期待你给我们写邮件,邮箱地址是:ting@sheng.fm 欢迎扫码添加声小音,在节目之外和我们保持联系。 Special Guest: Di Jin.

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    Jensen Huang LIVE: Nvidia's Future, Physical AI, Rise of the Agent, Inference Explosion, AI PR Crisis

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    In blue cities throughout the country, unions and politicians are fighting to ban driverless cars. We travel to Boston, where the fight has reached a fever pitch, and where the cars themselves will create some very unusual political alliances. (This is part two of a two part series, listen to the beginning here.) ⁠⁠Support Search Engine! To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

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    The “Hard Fork” team is off this week, taking a much-needed break. While we’re away, we wanted to draw your attention to a recent episode of “The Ezra Klein Show.” In this conversation, Ezra speaks with Jack Clark, a co-founder of Anthropic, about how he is using A.I. agents; how the technology is leading to meaningful changes in the ways we work and think; and how policy can or must change to anticipate potential job displacement on the horizon. We’ll be back with a new episode next week. Guest: Jack Clark, a co-founder and the head of policy at Anthropic.  Additional Reading: A full transcript and video of this episode can be found here. We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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