一位投资人的AI信息源

一位投资人的AI信息源 一位投资人的AI信息源 Kelvin Mu的阅读信息源 源地址：https://www.linkedin.com/feed/update/urn:li:activity:7067227468817993728/ 在工作中，我将大部分时间（大约30 50%），用于深化我的人工智能/机器学习知识。我经常收到关于我用来帮助自己的工具/资源的问题。为了方便大家，这里是我的列表。希望对你们有帮助： 1️⃣ 简报 TLDR AI (www.tldr.tech/ai) The Sequence (https://lnkd.in/gZASkGHv) Deep Learning Weekly (www.deeplearningweekly.com) Ben’s Bites (https://www.bensbites.co/) Last week in ai (https://lnkd.in/gPmXZESe) Your guide to AI (https://lnkd.in/geARfRHB) 2️⃣ 播客 No Priors podcast hosted by Sarah Guo and Elad Gil Robot Brains Podcast hosted by Pieter Abbeel Lex Fridman Podcast hosted by Lex Fridman The Gradient podcast hosted by Daniel Bashir Generally Intelligent hosted by Kanjun Qiu Last Week in AI 3️⃣ 会议 [工业界] World AI Cannes Festival (https://lnkd.in/gCqcchA9) [工业界] Gen AI conference (https://www.joingen.ai/) [工业界] Nvidia GTC Conference (https://lnkd.in/gr6BVgZD) [工业界] World Summit AI (https://lnkd.in/gm9ZkGe8; https://worldsummit.ai/) [工业界] AI and Big Data Expo (https://lnkd.in/gAcDMJs5; https://www.ai expo.net/ [工业界] Data + AI Summit by Databricks (https://lnkd.in/gF5QyXYv) [工业界] Ai4 Conference (https://ai4.io/usa/) [工业界] Scale Transform X (https://lnkd.in/g YTQQPx) [学术界] CVPR (https://lnkd.in/gX Sk8jv) [学术界] ICLR (https://iclr.cc/) [学术界] ICML (https://lnkd.in/gR uZiAF) [学术界] NeurIPS (https://nips.cc/) 4️⃣ 课程 MIT Deep Learning (https://lnkd.in/g8hHDcma) Deeplearning.ai / Coursera courses by Andrew Ng (https://lnkd.in/gHTr4Xsu) Stanford CS 324 Advances in Foundational Models (https://lnkd.in/gD4 e68s) The Full Stack LLM Bootcamp (https://lnkd.in/gj6GvZcW) 5️⃣ 书籍 Genius Makers by Cade Metz Life 3.0 by Max Tegmark The Alignment problem by Brian Christian AI Superpowers by Kai Fu Lee Learning Deep Learning by Magnus Ekman 6️⃣ 大公司的科技研究部门 Google (https://lnkd.in/gAiiNaRu; https://ai.googleblog.com/) Open AI (https://lnkd.in/gfkUgedv) Meta Research (https://lnkd.in/gpa2pfX3) 7️⃣ 其它 Academic Papers at Arxiv.org (https://lnkd.in/gNR37G Z) Twitter I don't go on Twitter much but it is sometimes useful to follow the very hottest trends. www.tldr.tech/ai www.deeplearningweekly.com Sarah Guo Elad Gil Pieter Abbeel Lex Fridman Daniel Bashir Kanjun Qiu Deeplearning.ai Cade Metz Max Tegmark Kai Fu Lee Magnus Ekman Arxiv.org Kelvin Mu的阅读信息源 源地址：https://www.linkedin.com/feed/update/urn:li:activity:7067227468817993728/ Kelvin Mu的阅读信息源 源地址：https://www.linkedin.com/feed/update/urn:li:activity:7067227468817993728/ 在工作中，我将大部分时间（大约30 50%），用于深化我的人工智能/机器学习知识。我经常收到关于我用来帮助自己的工具/资源的问题。为了方便大家，这里是我的列表。希望对你们有帮助： 1️⃣ 简报 TLDR AI (www.tldr.tech/ai) The Sequence (https://lnkd.in/gZASkGHv) Deep Learning Weekly (www.deeplearningweekly.com) Ben’s Bites (https://www.bensbites.co/) Last week in ai (https://lnkd.in/gPmXZESe) Your guide to AI (https://lnkd.in/geARfRHB) 2️⃣ 播客 No Priors podcast hosted by Sarah Guo and Elad Gil Robot Brains Podcast hosted by Pieter Abbeel Lex Fridman Podcast hosted by Lex Fridman The Gradient podcast hosted by Daniel Bashir Generally Intelligent hosted by Kanjun Qiu Last Week in AI 3️⃣ 会议 [工业界] World AI Cannes Festival (https://lnkd.in/gCqcchA9) [工业界] Gen AI conference (https://www.joingen.ai/) [工业界] Nvidia GTC Conference (https://lnkd.in/gr6BVgZD) [工业界] World Summit AI (https://lnkd.in/gm9ZkGe8; https://worldsummit.ai/) [工业界] AI and Big Data Expo (https://lnkd.in/gAcDMJs5; https://www.ai expo.net/ [工业界] Data + AI Summit by Databricks (https://lnkd.in/gF5QyXYv) [工业界] Ai4 Conference (https://ai4.io/usa/) [工业界] Scale Transform X (https://lnkd.in/g YTQQPx) [学术界] CVPR (https://lnkd.in/gX Sk8jv) [学术界] ICLR (https://iclr.cc/) [学术界] ICML (https://lnkd.in/gR uZiAF) [学术界] NeurIPS (https://nips.cc/) 4️⃣ 课程 MIT Deep Learning (https://lnkd.in/g8hHDcma) Deeplearning.ai / Coursera courses by Andrew Ng (https://lnkd.in/gHTr4Xsu) Stanford CS 324 Advances in Foundational Models (https://lnkd.in/gD4 e68s) The Full Stack LLM Bootcamp (https://lnkd.in/gj6GvZcW) 5️⃣ 书籍 Genius Makers by Cade Metz Life 3.0 by Max Tegmark The Alignment problem by Brian Christian AI Superpowers by Kai Fu Lee Learning Deep Learning by Magnus Ekman 6️⃣ 大公司的科技研究部门 Google (https://lnkd.in/gAiiNaRu; https://ai.googleblog.com/) Open AI (https://lnkd.in/gfkUgedv) Meta Research (https://lnkd.in/gpa2pfX3) 7️⃣ 其它 Academic Papers at Arxiv.org (https://lnkd.in/gNR37G Z) Twitter I don't go on Twitter much but it is sometimes useful to follow the very hottest trends. www.tldr.tech/ai www.deeplearningweekly.com Sarah Guo Elad Gil Pieter Abbeel Lex Fridman Daniel Bashir Kanjun Qiu Deeplearning.ai Cade Metz Max Tegmark Kai Fu Lee Magnus Ekman Arxiv.org