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🆕 Edge Rules on Railway Learn how Railway’s global edge network routes requests and how you can control what happens before they reach your app 🚄 00:00 Deployment regions 00:36 Railway’s global edge network 01:02 Multi-region routing demo 02:05 Introducing Edge Rules 02:26 Configuring rules in Railway 03:05 Redirecting...

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Railway

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36,586 просмотров • 14 дней назад •via X (Twitter)

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11,356 просмотров • 1 год назад

INSIDE JUPITER: TRADING THE NEWS WITH PREDICTION MARKETS This episode with Julian breaks down why prediction markets are becoming a core primitive of Web4, how the Polymarket partnership fits the Jupiter full-stack vision, and why the future isn’t a separate product it’s prediction embedded everywhere. time stamps : 00:00 Intro Inside Jupiter HQ 00:18 Who's Julian and what's his role 00:44 What JuPredict actually is: “trading the news” 01:11 Polymarket × Jupiter 02:01 Why prediction markets are emerging 03:00 Markets vs commentators 04:24 Local & social prediction markets 05:15 On-chain transparency & global accessibility 06:27 Prediction markets in the Jupiter Web4 stack 07:48 The vision: predicting from any interface 09:28 Why people misread market prices 10:20 The real edge: studying trade flow before events 11:05 What prediction markets are best at predicting 11:40 Consistency & accuracy of the markets 12:10 Message to the community
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INSIDE JUPITER: TRADING THE NEWS WITH PREDICTION MARKETS This episode with Julian breaks down why prediction markets are becoming a core primitive of Web4, how the Polymarket partnership fits the Jupiter full-stack vision, and why the future isn’t a separate product it’s prediction embedded everywhere. time stamps : 00:00 Intro Inside Jupiter HQ 00:18 Who's Julian and what's his role 00:44 What JuPredict actually is: “trading the news” 01:11 Polymarket × Jupiter 02:01 Why prediction markets are emerging 03:00 Markets vs commentators 04:24 Local & social prediction markets 05:15 On-chain transparency & global accessibility 06:27 Prediction markets in the Jupiter Web4 stack 07:48 The vision: predicting from any interface 09:28 Why people misread market prices 10:20 The real edge: studying trade flow before events 11:05 What prediction markets are best at predicting 11:40 Consistency & accuracy of the markets 12:10 Message to the community

JUP AND JUICE (🧃)

20,990 просмотров • 6 месяцев назад

Bret Weinstein, Viva Frei and Jimmy Dore tangle over who shot Charlie Kirk, and how. 00:00:00 Three people, three positions, one killing 00:01:16 Sponsor: SaunaSpace 00:03:39 Sponsor: MUD\WTR 00:05:27 Where each of us has landed as of today 00:05:47 Viva Frei: it was a bullet from the Losee roof 00:08:41 Jimmy Dore: the case for a cover-up 00:16:41 When a Question Becomes an Accusation 00:18:15 Morality as a Substitute for Argument 00:21:27 Sponsor: Helix 00:22:42 A Biologist's Toolkit 00:25:35 George Zinn and the Reflex to Confess 00:29:42 Paving the Courtyard 00:38:11 The Exploding Microphone 00:45:09 Joe Kent Says He Was Stopped 00:46:50 The Mic That Should Have Recorded It 00:52:58 O'Neill, the Hamptons, and 39 Minutes 00:57:28 "You Don't Have an FBI" 00:59:26 Butler and the Roof Nobody Covered 01:06:27 Harpole, Shawn Ryan, and the Drones 01:11:48 The Prosecutor's Fallacy 01:15:29 Drones and a Plane at 200 Feet 01:22:06 Foreign Nexus, or Domestic 01:29:07 Retroactive Continuity 01:33:21 What Ballistics Can and Cannot Show 01:38:10 A Potemkin Explanation 01:44:14 TPUSA After Charlie 01:49:20 Iran, Motive, and What Charlie Opposed 01:51:26 "Who I Fear Is the People..." 01:56:31 A Nation, or Whatever Controls It 02:00:43 The Phone, the Necklace, the Car 02:04:39 The Emergency Cleanup Order 02:07:20 When No Answer Will Be Believed 02:09:34 Conspiracy Psychosis 02:10:47 Closing Thoughts
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Bret Weinstein

325,676 просмотров • 18 дней назад

In 16 minutes we vibe coded a Web App and a Mobile App.... That share a backend Using Claude Code inside the Without writing a single line of code. App we built: instagram, except all the other users are AI agents that can post, like and comment. 00:00 Introduction 00:33 Starting with the Web App 01:08 First Prompt and Initial Setup 01:43 Authentication Process 02:49 Adding APIs and Enhancements 03:59 Testing the Web App 05:04 Redesigning the Web App 05:59 The Importance of Understanding Databases 07:20 Adding AI Agents 08:44 Setting Up the Admin Panel 10:02 Speeding Up Time for Testing 11:14 Finalizing the Web App 13:24 Building the Mobile App 16:11 Final Thoughts
16:39

In 16 minutes we vibe coded a Web App and a Mobile App.... That share a backend Using Claude Code inside the Without writing a single line of code. App we built: instagram, except all the other users are AI agents that can post, like and comment. 00:00 Introduction 00:33 Starting with the Web App 01:08 First Prompt and Initial Setup 01:43 Authentication Process 02:49 Adding APIs and Enhancements 03:59 Testing the Web App 05:04 Redesigning the Web App 05:59 The Importance of Understanding Databases 07:20 Adding AI Agents 08:44 Setting Up the Admin Panel 10:02 Speeding Up Time for Testing 11:14 Finalizing the Web App 13:24 Building the Mobile App 16:11 Final Thoughts

Riley Brown

68,207 просмотров • 7 месяцев назад

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview
4:45

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview

Ray Fernando

42,398 просмотров • 5 месяцев назад

.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
26:53

.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 просмотров • 1 год назад

GAed: Observable Network Flows View private network traffic directly on the canvas. True sight, but for your network. Available today. Watch Phin, Platform Engineer, talk and demo the feature below.
1:29

GAed: Observable Network Flows View private network traffic directly on the canvas. True sight, but for your network. Available today. Watch Phin, Platform Engineer, talk and demo the feature below.

Railway

13,234 просмотров • 6 месяцев назад