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Ketanji Brown Jackson Needs To Be Impeached. This Dangerously Idiotic Dissent Is PROOF. TIMESTAMPS: 00:00 - 26:11 Ketanji Brown Jackson Needs To Be Impeached. This Dangerously Idiotic Dissent Is PROOF 27:45 - 39:02 Kristi Noem's Husband Outed As A Cross-Dresser 40:13 - 47:50 Judge Rules Trump Administration Must Restore...

20,411 views • 5 months ago •via X (Twitter)

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Timestamps of the 47 topics addressed by Elon Musk a few hours ago in Pittsburgh. 1:49 Special guest: Senator James McCormick 7:22 Winner of the $1 million prize 10:43 Importance of registration 11:58 Risk of assassination attempts 13:55 The left is against free speech 17:06 It's illegal to show voter ID 19:24 We want to do exciting things 21:40 Key reasons to reelect Trump 27:14 No wish to do politics but stakes are high 33:02 How to support business opportunities 35:01 Is Elon considering running in 2028? 39:10 Abortion and education around having kids 44:25 Nuclear power is safe 48:42 Be wary of AI 49:37 There will be an increase in robots 53:01 Elon's son will go to college in Pittsburgh 55:01 Protecting children 57:38 Stopping propaganda for children 58:53 Every expenditure should serve people 59:55 Subscribe to X Premium 1:02:14 Optimism grounded in realism 1:04:30 Approving drugs faster 1:08:26 Medical tech should be approved faster 1:10:06 AI and medicine 1:13:02 Solve back pain 1:13:24 Children sex-trafficking 1:15:07 How to handle puppet masters 1:17:16 The more government, the less freedom 1:19:53 Taxes are getting out of hand 1:21:02 Big pharma 1:22:34 New technologies should help people 1:24:50 Ban voting machines 1:28:04 No incentive for nothing 1:30:16 Crypto is good against central control 1:31:09 Many expenditures should be 0 1:33:23 Respect for those who are useful 1:34:23 Aliens must be subtle 1:36:03 Don't damage art 1:37:58 Dogecoin is the most fun crypto 1:41:06 People should worry less and have kids 1:41:53 There will be opposition to reducing spending 1:42:57 The risk is an oppressive totalitarian state 1:46:36 Doing things that are important 1:50:06 We should allow teachers to protect students 1:52:27 Why are some voted not counted 1:56:22 AI will be help people understand 1:57:47 Be loud about your concerns

ELON CLIPS

6,379,905 views • 1 year ago

Updated: Vocals & Rap - #성화 #Seonghwa 00:00 Still Here 00:15 Wonderland 00:36 Halazia 00:47 Answer 01:21 Cyberpunk 01:27 Wave 01:37 Utopia 01:50 My Way 02:00 With U 02:16 Be With You 02:54 Star 1117 03:21 Turbulence (야간비행) 03:39 Days 04:26 Promise 04:38 Fever 04:54 Sunrise 05:19 Mist 05:43 Take Me Home 06:11 Better 06:34 All About You 06:43 Aurora 06:55 Blue Summer 07:23 Diamond 07:46 Time Of Love 07:58 Stay 08:07 Desire 08:21 WDIG 08:28 New World 08:35 Dreamers 08:53 Not Too Late 09:03 The Letter 09:19 One Day At A Time 09:28 Dazzling Light 09:40 Light 09:50 The Ring 10:04 Paradigm 10:18 This World 10:38 Bouncy 10:51 Not Okay 11:15 The King 11:23 Inception 11:52 Fireworks 12:03 Limitless 12:19 Precious 12:28 Rocky 12:41 Let’s Get Together 13:07 White Love 13:17 The Leaders 13:27 Crazy Form 13:43 Arriba 13:57 Silver Light 14:06 Dreamy Day 14:26 Matz 15:15 Outlaw 15:23 Twilight 15:31 Dune 15:38 Hala Hala 15:43 Deja Vu 15:50 Horizon 15:54 Say My Name 15:57 Sector 1 16:02 Good Lil Boy 16:09 Don’t Stop 16:12 Still Here (Acoustic Ver) 16:19 Siren 16:31 Guerrilla 16:45 We Know 17:00 Empty Box 17:28 Wake Up 17:40 Dancing Like Butterfly Wings 17:49 Work 18:09 Thanxx 18:26 If Without U 18:45 Shaboom 19:01 Outlaw 19:18 Treasure 19:33 Eternal Sunshine 20:03 Django 20:31 Turbulence Japanese Ver. 20:55 Blind 21:16 Pirate King 21:24 Forevermore 22:00 Birthday 22:11 Deep Dive 22:26 Ice On My Teeth 22:50 Man On Fire 23:10 Selfish Waltz 23:25 Enough

Hwanakin

62,764 views • 1 year ago

I'm often asked for the best public example of AI evals done right for a real, production product. I finally have an answer. Teresa Torres shares how she shipped an AI interview coach, and used evals to rapidly squash bugs and improve the product. Teresa shows how she: 1. did error analysis FIRST to find real issues (instead of using generic metrics) 😍 2. used Jupyter notebooks to analyze errors 3. built custom annotation tools + custom widgets in notebooks 4. built a LLM-judge and assertions to test for specific errors 5. iterated through this feedback loop until it worked. 6. kept things simple the whole time It's also probably the best commercial for Jupyter notebooks you can imagine. 🥰 Chapter summary below. Link to YT in next thread 00:00:00 - Intro 00:01:45 - The Product: Building an AI Interview Coach 00:06:34 - The Problem: How Do I Know if My AI Coach is Any Good? 00:10:15 - Using Airtable for Traces and Annotation 00:12:15 - Discovering Jupyter Notebooks and Designing the First Evals 00:15:15 - Example Evals: LLM-as-Judge vs. Code-Based Assertions 00:21:00 - Learning Python with ChatGPT to Analyze Eval Results 00:31:00 - VS Code, Custom Tools, and an Eval Investigation Notebook 00:39:45 - Building a Custom Annotation Tool with Claude 00:41:00 - From Personal Project to Production App 00:46:02 - How Should PMs and Engineers Collaborate on AI Products? 00:55:45 - Q&A: Capturing Feedback and Annotations from End Users 00:58:11 - Q&A: Is a Technical Background Necessary to Build AI? 01:02:28 - Q&A: What's Next for Teresa? 01:03:13 - Q&A: Unpacking the Micro-Decisions of Building an AI App

Hamel Husain

51,376 views • 1 year ago