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Introducing GrokTerm 🖤 A Rust terminal built for Grok Build. A real shell, multi-tab sessions, MCP-ready, and native two-way Grok Voice. A voice agent in the terminal, not a chatbot floating above it. Chapters: 00:00 Intro to GrokTerm 00:17 Testing two way voice conversations 00:30 Create Tetris 00:39 Moon...

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Dan

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20,206 次观看 • 11 天前 •via X (Twitter)

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95,984 次观看 • 1 年前

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맑음쨩 🍏

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.Eric Jang is spearheading AI at 1X. Eric believes 1X is on the path to becoming an AGI company — not just a robotics company. I sat down with him at 1X’s new Palo Alto office to discuss the key AI building blocks needed to bring humanoid robots into homes at scale. 00:00 Eric Jang joins Humanoid Hub 00:27 Move to Palo Alto 01:02 Why 1X targets the home 02:01 The AGI company 02:49 Redwood AI overview 04:01 Unified control, modular stack 06:07 Data labeling at scale 07:10 RL mobility update for NEO 10:03 GPU and onboard compute 11:09 World model explained 13:34 Trusting world models for evaluation 15:05 Synthetic data generation 16:30 A world model Turing Test 17:41 RL in manipulation 20:08 Lessons from early NEO deployments 21:00 Full autonomy 22:18 1X’s unique edge in AI 24:02 Eric asks Devang a question

The Humanoid Hub

96,465 次观看 • 1 年前

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Substack

23,889 次观看 • 2 个月前

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Cursor Complete Guide for AI Coding... 1. The Basics, Composer, Cursor 2.0, Why use Cursor? 2. Multiple Agent Testing, Adding Database, Deploying to Vercel 3. Comparing the big 4: v0, Replit, Lovable, Cursor And more... with Senior Software Engineer Kehan Zhang TIME STAMPS --------------- 1. BASICS: 00:00 Introduction 01:01 Overview of Cursor and Its Features 01:47 Getting Started with Cursor 02:39 Understanding IDE and Vibe Coding 06:00 Cursor For Mobile Apps 10:26 Downloading and Installing Cursor 11:17 Creating and Managing Projects in Cursor 15:14 Building a Simple Game with Cursor 19:10 Advanced Features and Customization 40:28 Fixing Styling Rules 40:53 Redesigning the App 42:17 Exploring Cursor 2.0 Features 43:22 Setting Up the Project Structure 44:17 Adding and Testing Meme Templates 46:08 Debugging Text Issues 2. ADVANCED 49:46 Using Multiple Agents 01:10:40 Creating Custom Commands 01:14:15 Creating Commands in Settings Tab 01:15:11 Introduction to Instant DB 01:16:04 Setting Up Instant DB in Your Project 01:18:24 Building a Full Stack Application 01:19:04 Using the Agent to Plan and Build 01:26:06 Testing and Debugging the Application 01:53:02 Deploying the Application with Vercel 01:55:35 Setting Up the CLI 01:56:15 Understanding Command Line Interfaces (CLI) 01:57:32 Deploying Code to Vercel 01:58:07 Handling Environment Variables 01:58:44 Interacting with the Vercel Deployment 02:00:34 Exploring Cursor's Capabilities 3. COMPARING VIBE CODING TOOLS 02:09:48 Comparing Vibe Coding Tools 02:31:04 Final Thoughts and Recommendations

Riley Brown

65,392 次观看 • 9 个月前

Running Through Ethereum with hamdi (Ep. 1) I started craic overflow because I had questions about where Ethereum is headed, and I wanted to ask them to the people shaping it. I decided to interview Hamdi while jogging because as a software engineer, I honestly spend way too much time sitting on my ass. Never been more bullish on the future of Ethereum. 00:00 - Intro 00:08 - Hamdi 00:40 - What's The Craic? 01:59 - How did Hamdi get into crypto? 02:40 - Why not plasma? 03:24 - Working at OP Labs/Optimism 04:06 - Shipping L2 Interoperability 05:12 - Building on the Superchain 05:30 - Asynchronicity in Solidity 07:00 - Predications for Ethereum 08:46 - What are the hurdles for Ethereum? 09:47 - Stablecoins 10:22 - Application specific chains 11:53 - Wallet UX 13:18 - Quick breather 13:30 - Why are you in crypto? 14:20 - How do you find balance? 16:20 - Hot take on ETH the asset 17:39 - The chains security 18:53 - Market talk 19:45 - Data availability 21:01 - Onchain L2 configs 21:22 - Outro
21:34

Running Through Ethereum with hamdi (Ep. 1) I started craic overflow because I had questions about where Ethereum is headed, and I wanted to ask them to the people shaping it. I decided to interview Hamdi while jogging because as a software engineer, I honestly spend way too much time sitting on my ass. Never been more bullish on the future of Ethereum. 00:00 - Intro 00:08 - Hamdi 00:40 - What's The Craic? 01:59 - How did Hamdi get into crypto? 02:40 - Why not plasma? 03:24 - Working at OP Labs/Optimism 04:06 - Shipping L2 Interoperability 05:12 - Building on the Superchain 05:30 - Asynchronicity in Solidity 07:00 - Predications for Ethereum 08:46 - What are the hurdles for Ethereum? 09:47 - Stablecoins 10:22 - Application specific chains 11:53 - Wallet UX 13:18 - Quick breather 13:30 - Why are you in crypto? 14:20 - How do you find balance? 16:20 - Hot take on ETH the asset 17:39 - The chains security 18:53 - Market talk 19:45 - Data availability 21:01 - Onchain L2 configs 21:22 - Outro

malone

11,924 次观看 • 1 年前

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:
1:11:41

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:

Shane Parrish

450,952 次观看 • 3 个月前

"Any feature we release, a competitor could release within two weeks." Matan Grinberg (Factory) on why the moat isn't software anymore. dsa (LiveKit) on building the framework for voice, video, and physical AI. George Sivulka (@HebbiaAI) on what it takes to win in vertical AI. They join @jason on This Week in AI, Episode 11: 00:00 Intro & AGI debate 03:30 Factory: autonomy for software engineering 04:29 LiveKit: open source to ChatGPT voice 10:31 Hebbia: AI for capital markets 13:21 SpaceX-Cursor $60 billion deal breakdown 26:28 Moats in the age of vibe coding 38:10 Deterministic agents vs. open chaos 45:56 DeepSeek V4 01:05:23 OpenAI's spend problem 01:12:08 P-doom scores
1:13:42

"Any feature we release, a competitor could release within two weeks." Matan Grinberg (Factory) on why the moat isn't software anymore. dsa (LiveKit) on building the framework for voice, video, and physical AI. George Sivulka (@HebbiaAI) on what it takes to win in vertical AI. They join @jason on This Week in AI, Episode 11: 00:00 Intro & AGI debate 03:30 Factory: autonomy for software engineering 04:29 LiveKit: open source to ChatGPT voice 10:31 Hebbia: AI for capital markets 13:21 SpaceX-Cursor $60 billion deal breakdown 26:28 Moats in the age of vibe coding 38:10 Deterministic agents vs. open chaos 45:56 DeepSeek V4 01:05:23 OpenAI's spend problem 01:12:08 P-doom scores

This Week in AI

103,063 次观看 • 3 个月前

Aidan Gomez (Aidan Gomez) is a computer scientist, co-author of the seminal paper ‘Attention Is All You Need,’ and the CEO of Cohere. In this episode, we discussed his upbringing in the cabin his grandfather built in Codrington, a small town North of Brighton, and the values that were instilled in him through his family. We explored his path from Codrington to his undergraduate studies at the University of Toronto, emailing Geoffrey Hinton, and joining Google Brain where he co-wrote the paper on transformers. We discussed how he met his co-founders Ivan Zhang and Nick Frosst, and his insights on what it means to build a meaningful, successful company in Canada. Aidan shares his conviction about what is at stake — for Canada and for the world at large. This is a conversation about family, values, and what it means to live with conviction. The Other Stuff is hosted by internetVin — filmmaker, entrepreneur, and possibly the most curious man on Earth. Produced by New. The Other Stuff #29 — Aidan Gomez: Empathy and Conviction — Timestamps 00:00:00 Intro 00:03:10 The Malleability of Toronto 00:11:06 Growing Up in Codrington 00:13:50 The Story of Aidan Gomez’s Family 00:27:23 Introduction to the Internet 00:30:39 Values and Work Ethic 00:35:46 University of Toronto’s AI Scene 00:40:48 Emailing Geoffrey Hinton 00:42:16 Google Brain 00:45:15 Dropout: A Simple Way to Prevent Neural Networks from Overfitting 00:49:48 The Beauty of Research 00:54:24 One Model to Rule Them All 00:59:54 Meeting Ivan Zhang and Nick Frosst 01:04:00 The Birth of Cohere 01:06:56 Twitter Influencers and Alex Friedland 01:11:48 Being the CEO 01:12:51 Building for Canada 01:15:01 Three Fundamental Ingredients of Building a Company 01:21:39 Working with the Canadian Government 01:24:39 Reflexivity in Canada 01:36:22 What Is Evil? 01:42:40 The Role of AI in the World
1:46:27

Aidan Gomez (Aidan Gomez) is a computer scientist, co-author of the seminal paper ‘Attention Is All You Need,’ and the CEO of Cohere. In this episode, we discussed his upbringing in the cabin his grandfather built in Codrington, a small town North of Brighton, and the values that were instilled in him through his family. We explored his path from Codrington to his undergraduate studies at the University of Toronto, emailing Geoffrey Hinton, and joining Google Brain where he co-wrote the paper on transformers. We discussed how he met his co-founders Ivan Zhang and Nick Frosst, and his insights on what it means to build a meaningful, successful company in Canada. Aidan shares his conviction about what is at stake — for Canada and for the world at large. This is a conversation about family, values, and what it means to live with conviction. The Other Stuff is hosted by internetVin — filmmaker, entrepreneur, and possibly the most curious man on Earth. Produced by New. The Other Stuff #29 — Aidan Gomez: Empathy and Conviction — Timestamps 00:00:00 Intro 00:03:10 The Malleability of Toronto 00:11:06 Growing Up in Codrington 00:13:50 The Story of Aidan Gomez’s Family 00:27:23 Introduction to the Internet 00:30:39 Values and Work Ethic 00:35:46 University of Toronto’s AI Scene 00:40:48 Emailing Geoffrey Hinton 00:42:16 Google Brain 00:45:15 Dropout: A Simple Way to Prevent Neural Networks from Overfitting 00:49:48 The Beauty of Research 00:54:24 One Model to Rule Them All 00:59:54 Meeting Ivan Zhang and Nick Frosst 01:04:00 The Birth of Cohere 01:06:56 Twitter Influencers and Alex Friedland 01:11:48 Being the CEO 01:12:51 Building for Canada 01:15:01 Three Fundamental Ingredients of Building a Company 01:21:39 Working with the Canadian Government 01:24:39 Reflexivity in Canada 01:36:22 What Is Evil? 01:42:40 The Role of AI in the World

The Other Stuff Podcast

45,297 次观看 • 7 个月前

From a Thai prison cell to a fintech empire processing $1.6B in international payments across 40+ banks and 250M+ users. Jonathan Low (Jonathan Low). Forbes 40 Under 40. Author of "Cell to CEO." We covered prison, banking for AI agents, RWA projects, the future of crypto in banking, vibe coding for trading, and the businesses that win the next 5 years. ⏱ Timestamps: 00:00:00 — Teaser 00:00:46 — Who is Jonathan Low 00:01:35 — What Jonathan's life was like before prison 00:02:13 — How and why Jonathan ended up in prison 00:02:57 — Prison conditions: expectations vs reality 00:07:33 — Prison became the greatest blessing 00:09:12 — How the entrepreneurial journey began after prison 00:10:34 — Why social capital matters 00:11:06 — Launched own club and took it to the top in 3 months 00:12:09 — Built an Axie Infinity gaming guild during COVID 00:13:49 — The beginning of the BipTap Group journey 00:17:23 — How Jonathan built his own banking system 00:20:07 — How to get a crypto card 00:22:03 — How much it costs to launch a white-label solution with BipTap 00:22:58 — Banking for AI agents 00:25:57 — How to build an RWA project 00:27:45 — Future of cryptocurrencies in banking 00:32:08 — The business verticals within Empire Group 00:32:48 — What Jonathan invests his money in 00:33:54 — How relationships with regulators are built 00:34:43 — Implementing AI in business 00:36:28 — Vibe coding in trading 00:40:06 — Advice for first-time founders 00:43:36 — From construction to trading: Ruslan Khairullin's journey 00:44:57 — Inner peace: why calmness is essential for founders 00:50:39 — Work-life balance for entrepreneurs 00:53:47 — $1.5 million in 24 hours on TST coin 00:55:11 — The best way to capture a market 00:55:57 — Banking for nations Watch the full conversation and let me know which part you liked the most 👇
58:52

From a Thai prison cell to a fintech empire processing $1.6B in international payments across 40+ banks and 250M+ users. Jonathan Low (Jonathan Low). Forbes 40 Under 40. Author of "Cell to CEO." We covered prison, banking for AI agents, RWA projects, the future of crypto in banking, vibe coding for trading, and the businesses that win the next 5 years. ⏱ Timestamps: 00:00:00 — Teaser 00:00:46 — Who is Jonathan Low 00:01:35 — What Jonathan's life was like before prison 00:02:13 — How and why Jonathan ended up in prison 00:02:57 — Prison conditions: expectations vs reality 00:07:33 — Prison became the greatest blessing 00:09:12 — How the entrepreneurial journey began after prison 00:10:34 — Why social capital matters 00:11:06 — Launched own club and took it to the top in 3 months 00:12:09 — Built an Axie Infinity gaming guild during COVID 00:13:49 — The beginning of the BipTap Group journey 00:17:23 — How Jonathan built his own banking system 00:20:07 — How to get a crypto card 00:22:03 — How much it costs to launch a white-label solution with BipTap 00:22:58 — Banking for AI agents 00:25:57 — How to build an RWA project 00:27:45 — Future of cryptocurrencies in banking 00:32:08 — The business verticals within Empire Group 00:32:48 — What Jonathan invests his money in 00:33:54 — How relationships with regulators are built 00:34:43 — Implementing AI in business 00:36:28 — Vibe coding in trading 00:40:06 — Advice for first-time founders 00:43:36 — From construction to trading: Ruslan Khairullin's journey 00:44:57 — Inner peace: why calmness is essential for founders 00:50:39 — Work-life balance for entrepreneurs 00:53:47 — $1.5 million in 24 hours on TST coin 00:55:11 — The best way to capture a market 00:55:57 — Banking for nations Watch the full conversation and let me know which part you liked the most 👇

Ruslan Khairullin

16,872 次观看 • 1 个月前

We don't know what most microbial genes do. Can genomic language models help? there's only one way to find out! this is a 1 hour and 42 minute interview with an MIT professor (the famous Yunha Hwang) chatting about these questions, her work in solving them at Tatta Bio, and more. zoomer captions are back too Links in reply! Timestamps: 00:00:00 - Clips + sponsor roll from the wonderful LatchBio 00:02:07 – Introduction 00:02:23 – Why do microbial genomes matter 00:04:07 – Deep learning acceptance in metagenomics 00:05:25 – The case for genomic “context” over sequence matching 00:06:43 – OMG: the only ML-ready metagenomic dataset 00:09:27 – gLM2: A multimodal genomic language model 00:11:06 – What do you do with the output of genomic language models? 00:17:41 – How will OMG evolve? 00:20:26 – Why train on only microbial genomes, as opposed to all genomes? 00:22:58 – Do we need more sequences or more annotations? 00:23:54 – Is there a conserved microbial genome ‘language’? 00:28:11 – What non-obvious things can this genomic language model tell you? 00:33:08 – Semantic deduplication and evaluation 00:37:33 – How does benchmarking work for these types of models? 00:41:31 – Gaia: A genomic search engine 00:44:18 – Even ‘well-studied’ genomes are mostly unannotated 00:50:51 – Using agents on Gaia 00:54:53 – Will genomic language models reshape the tree of life? 00:59:18 – Current limitations of genomic language models 01:08:54 – Directed evolution as training data 01:12:35 – What is Tatta Bio? 01:19:02 – Building Google for genomic sequences (SeqHub) 01:25:46 – How to create communities around scientific OSS 01:29:06 – What’s the purpose in the centralization of the software? 01:35:37 – How will the way science is done change in 10 years?
1:42:41

We don't know what most microbial genes do. Can genomic language models help? there's only one way to find out! this is a 1 hour and 42 minute interview with an MIT professor (the famous Yunha Hwang) chatting about these questions, her work in solving them at Tatta Bio, and more. zoomer captions are back too Links in reply! Timestamps: 00:00:00 - Clips + sponsor roll from the wonderful LatchBio 00:02:07 – Introduction 00:02:23 – Why do microbial genomes matter 00:04:07 – Deep learning acceptance in metagenomics 00:05:25 – The case for genomic “context” over sequence matching 00:06:43 – OMG: the only ML-ready metagenomic dataset 00:09:27 – gLM2: A multimodal genomic language model 00:11:06 – What do you do with the output of genomic language models? 00:17:41 – How will OMG evolve? 00:20:26 – Why train on only microbial genomes, as opposed to all genomes? 00:22:58 – Do we need more sequences or more annotations? 00:23:54 – Is there a conserved microbial genome ‘language’? 00:28:11 – What non-obvious things can this genomic language model tell you? 00:33:08 – Semantic deduplication and evaluation 00:37:33 – How does benchmarking work for these types of models? 00:41:31 – Gaia: A genomic search engine 00:44:18 – Even ‘well-studied’ genomes are mostly unannotated 00:50:51 – Using agents on Gaia 00:54:53 – Will genomic language models reshape the tree of life? 00:59:18 – Current limitations of genomic language models 01:08:54 – Directed evolution as training data 01:12:35 – What is Tatta Bio? 01:19:02 – Building Google for genomic sequences (SeqHub) 01:25:46 – How to create communities around scientific OSS 01:29:06 – What’s the purpose in the centralization of the software? 01:35:37 – How will the way science is done change in 10 years?

owl

44,279 次观看 • 8 个月前

How to start your Hermes AI Agent (step-by-step guide for beginners) I'm a beginner, and I spent the last 24h: > Understanding the process > Launching my Hermes Agent (Nous Research) > Recording the whole process > Editing this step-by-step guide So you can do it yourself and understand everything in less than 1 hour! 00:00 Intro 00:38 What is Hermes ? Key concepts every beginner should know 01:16 What is a VPS ? 02:00 What is SSH ? 03:52 What is the Terminal ? 04:03 What is an LLM provider ? 04:37 What is an API key ? 04:52 What is the Terminal Backend 05:34 What is the Messaging Gateway ? 06:10 What is the Memory System ? Step-by-step: Launch your Hermes AI agent 06:53 Step 1 : Get your VPS 08:04 How to generate an SSH key 09:00 Step 2 : Connect to your VPS 10:32 Step 3 : Install Hermes Agent 14:34 Connect your agent to Telegram 17:12 How to fix a mistake during the process 17:48 Gateway testing 18:17 Telegram is working 18:31 Run your agent 24/7 19:16 Thank you Make sure to save this for later and share it with friends who want to start with AI agents. Thanks to Teknium 🪽 for being so active!
20:04

How to start your Hermes AI Agent (step-by-step guide for beginners) I'm a beginner, and I spent the last 24h: > Understanding the process > Launching my Hermes Agent (Nous Research) > Recording the whole process > Editing this step-by-step guide So you can do it yourself and understand everything in less than 1 hour! 00:00 Intro 00:38 What is Hermes ? Key concepts every beginner should know 01:16 What is a VPS ? 02:00 What is SSH ? 03:52 What is the Terminal ? 04:03 What is an LLM provider ? 04:37 What is an API key ? 04:52 What is the Terminal Backend 05:34 What is the Messaging Gateway ? 06:10 What is the Memory System ? Step-by-step: Launch your Hermes AI agent 06:53 Step 1 : Get your VPS 08:04 How to generate an SSH key 09:00 Step 2 : Connect to your VPS 10:32 Step 3 : Install Hermes Agent 14:34 Connect your agent to Telegram 17:12 How to fix a mistake during the process 17:48 Gateway testing 18:17 Telegram is working 18:31 Run your agent 24/7 19:16 Thank you Make sure to save this for later and share it with friends who want to start with AI agents. Thanks to Teknium 🪽 for being so active!

Theo

33,099 次观看 • 4 个月前

How far are we from "Her"? I couldn't help but wonder, given the rapid fire of GPT-Live and Thinking Machines. Turns out, full duplex speech-to-speech is not particularly new. Moshi has been around for more than 2 years. Many thanks to Neil Zeghidour for bringing so much nuance. Check out kyutai who are doing god's work and open-sourcing it (not sponsored!). 00:00 Intro 01:24 ChatGPT Standard & LLM-based cascades 04:08 ChatGPT Advanced & end-to-end speech models 05:35 ChatGPT Live & Her 07:38 Thinking Machines & multi-stream modeling 09:13 Moshi & full duplex assistants 13:24 Moshi’s inner monologue 15:38 Why aren’t full duplex models everywhere? 17:08 Tool calling in full duplex models 18:00 Moshi RAG 19:06 Is the future full duplex? 20:24 How far are we from Her?
21:29

How far are we from "Her"? I couldn't help but wonder, given the rapid fire of GPT-Live and Thinking Machines. Turns out, full duplex speech-to-speech is not particularly new. Moshi has been around for more than 2 years. Many thanks to Neil Zeghidour for bringing so much nuance. Check out kyutai who are doing god's work and open-sourcing it (not sponsored!). 00:00 Intro 01:24 ChatGPT Standard & LLM-based cascades 04:08 ChatGPT Advanced & end-to-end speech models 05:35 ChatGPT Live & Her 07:38 Thinking Machines & multi-stream modeling 09:13 Moshi & full duplex assistants 13:24 Moshi’s inner monologue 15:38 Why aren’t full duplex models everywhere? 17:08 Tool calling in full duplex models 18:00 Moshi RAG 19:06 Is the future full duplex? 20:24 How far are we from Her?

Julia Turc

72,266 次观看 • 15 天前

Scott Jennings has built a reputation for speaking truth to power on CNN, but what stood out to me in this conversation was his honesty, his perspective, and his heart. We filmed this episode over a month ago in Washington DC, and it was the perfect backdrop for a raw and real discussion about politics, faith, and family. We talked about what it takes to sit in the lion’s den night after night, debating politics in front of a national audience, and why authenticity matters more now than ever. Scott opened up about his career path from Kentucky to the Bush White House, to campaign war rooms, and now to CNN, where his voice has become one of the most recognizable conservative perspectives in America. He shared stories about Donald Trump, Mitch McConnell, and the lessons he has learned from decades inside politics and media. We also talked about faith, family, and why staying grounded matters when the world is coming at you full speed. Scott Jennings is sharp, candid, and passionate about America’s future, but what I walked away with was a reminder of his integrity and his courage to stand firm in the face of constant pressure. Chapters: 00:03:08:12 – Thoughts on Donald Trump's presidency so far 00:06:32:00 – How has President Trump improved since 2016 00:08:35:01 – How the incident in Butler PA changed everything 00:13:11:23 – Scott Jennings on CNN 00:18:10:19 – How the debates work on CNN 00:20:52:15 – How does Scott Jennings keep his cool while debating 00:24:25:11 – Any strained relationships on set 00:27:18:25 – Scott Jennings' best and worst moments on air 00:31:06:08 – How does Scott Jennings deal with being outnumbered 00:41:12:23 – Scott's career in politics 00:44:39:16 – Mitch McConnell 00:52:11:11 – Political run in Kentucky for Scott 00:54:37:24 – Family 01:00:11:02 – Closing thoughts 01:03:29:11 – The Yellow Ribbon
1:05:46

Scott Jennings has built a reputation for speaking truth to power on CNN, but what stood out to me in this conversation was his honesty, his perspective, and his heart. We filmed this episode over a month ago in Washington DC, and it was the perfect backdrop for a raw and real discussion about politics, faith, and family. We talked about what it takes to sit in the lion’s den night after night, debating politics in front of a national audience, and why authenticity matters more now than ever. Scott opened up about his career path from Kentucky to the Bush White House, to campaign war rooms, and now to CNN, where his voice has become one of the most recognizable conservative perspectives in America. He shared stories about Donald Trump, Mitch McConnell, and the lessons he has learned from decades inside politics and media. We also talked about faith, family, and why staying grounded matters when the world is coming at you full speed. Scott Jennings is sharp, candid, and passionate about America’s future, but what I walked away with was a reminder of his integrity and his courage to stand firm in the face of constant pressure. Chapters: 00:03:08:12 – Thoughts on Donald Trump's presidency so far 00:06:32:00 – How has President Trump improved since 2016 00:08:35:01 – How the incident in Butler PA changed everything 00:13:11:23 – Scott Jennings on CNN 00:18:10:19 – How the debates work on CNN 00:20:52:15 – How does Scott Jennings keep his cool while debating 00:24:25:11 – Any strained relationships on set 00:27:18:25 – Scott Jennings' best and worst moments on air 00:31:06:08 – How does Scott Jennings deal with being outnumbered 00:41:12:23 – Scott's career in politics 00:44:39:16 – Mitch McConnell 00:52:11:11 – Political run in Kentucky for Scott 00:54:37:24 – Family 01:00:11:02 – Closing thoughts 01:03:29:11 – The Yellow Ribbon

Sage Steele

111,471 次观看 • 10 个月前

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100
1:04:08

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100

Founders Inc

19,492 次观看 • 3 个月前

I rebuilt most of OpenClaw's core in a single workflow: - 25 blocks - 29 connections - Short + long-term memory - Multi-channel (Telegram + Slack) Didn't build it manually. Stack is fully open-source. Self-host, run local models, own it end-to-end. Full walkthrough: Chapters: 00:00 - Intro 01:00 - SimClaw in action: planning my day, finding meetings, sending email 04:05 - Long-term memory capability 05:52 - Inside the workflow: how it's wired 12:09 - The plot twist 12:50 - Building an entire workflow using a single prompt 15:42 - Why this is an OS for your AI workforce 17:00 - Try it yourself If you want to see the open-source stack that powers all of this, check out Sim on GitHub and drop a star if you find it useful:
17:21

I rebuilt most of OpenClaw's core in a single workflow: - 25 blocks - 29 connections - Short + long-term memory - Multi-channel (Telegram + Slack) Didn't build it manually. Stack is fully open-source. Self-host, run local models, own it end-to-end. Full walkthrough: Chapters: 00:00 - Intro 01:00 - SimClaw in action: planning my day, finding meetings, sending email 04:05 - Long-term memory capability 05:52 - Inside the workflow: how it's wired 12:09 - The plot twist 12:50 - Building an entire workflow using a single prompt 15:42 - Why this is an OS for your AI workforce 17:00 - Try it yourself If you want to see the open-source stack that powers all of this, check out Sim on GitHub and drop a star if you find it useful:

Akshay 🚀

65,756 次观看 • 3 个月前

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks
1:15:17

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks

The Knowledge Project

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