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Andrej Karpathy released a project scoring all 342 U.S. occupations on how exposed they are to AI using an LLM & BLS data. The college premium that defined American aspiration for decades may get repriced as AI starts doing knowledge work for free & a skilled plumber can out-earn... show more

Shay Boloor

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84,175 views • 5 months ago •via X (Twitter)

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Andrej Karpathy just dropped a project scoring every job in America on how likely an AI will replace it from 0-10 > Scraped all 342 occupations from the Bureau of Labor > Fed each one to an LLM with a detailed scoring rubric > Built an interactive treemap where rectangle size = number of jobs and color = how exposed that job is to AI The key signal in his scoring: if the work product is fundamentally digital and the job can be done entirely from a home office, exposure is inherently high. The scale: 0-1: Roofers, janitors 4-5: Nurses, retail, physicians 8-9: Software devs, paralegals, data analysts 10: Medical transcriptionists Average across all 342 occupations: 5.3/10. The entire pipeline is open source. BLS scraping, LLM scoring, the visualization. All of it. Much respect for the sensei this is scary and awesome

Andrej Karpathy just dropped a project scoring every job in America on how likely an AI will replace it from 0-10 > Scraped all 342 occupations from the Bureau of Labor > Fed each one to an LLM with a detailed scoring rubric > Built an interactive treemap where rectangle size = number of jobs and color = how exposed that job is to AI The key signal in his scoring: if the work product is fundamentally digital and the job can be done entirely from a home office, exposure is inherently high. The scale: 0-1: Roofers, janitors 4-5: Nurses, retail, physicians 8-9: Software devs, paralegals, data analysts 10: Medical transcriptionists Average across all 342 occupations: 5.3/10. The entire pipeline is open source. BLS scraping, LLM scoring, the visualization. All of it. Much respect for the sensei this is scary and awesome

Josh Kale

1,220,055 views • 5 months ago

For me, our Analyst agent in Microsoft 365 Copilot is like having a skilled data analyst on hand — all the time. It generates insights and helps you visualize complex data. Here's a quick demo on how it can make sense of marketing campaign data and help you get more done at work.

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Satya Nadella

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CHINA: China is illegally using American Ai technology made by $NVDA to build a powerful Ai model called DeepSeek R1. The LLM was released it for free using an open source license. This is a massive blow to US Ai companies like OpenAi and Antropic.

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THE ALPHA YOU WERE LOOKING FOR! Perle Labs a crypto project built on Solana with the aim to help and train AI models using real human knowledge and data. Perle Labs creates a system where experts do AI tasks, all on chain & transparent! Join here :

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What if your personal data became an asset you actually owned? In this May 2026 AMA, Matrix AI Network explores one of the most important questions facing AI, Web3, and the future digital economy: Who owns the data that powers artificial intelligence? As AI models continue to improve, the next major bottleneck is no longer computing power—it is access to high-quality, verified human data. The discussion covers how personal biodata can become a valuable digital asset, how data quality is measured, and why future AI companies may depend directly on users as data providers. Topics include: ✅ Biodata as a new asset class ✅ AI-grade data quality scoring ✅ Wearable devices for raw data ✅ Data ownership and monetization models ✅ Preventing fake data and device spoofing ✅ Real-world applications in healthcare, sports science and mental wellness ✅ Hypnus and the future biodata ecosystem ✅ Project direction The future may not belong to companies that own data. It belongs to the people who create it. Watch now 👇 #AI #Web3 #DataOwnership

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Matrix AI Network

60,855 views • 2 months ago

Exploring Andrej Karpathy Nanochat through a Knowledge Graph Love how this project combines simplicity with power. Want to navigate and understand the entire repo? Check it out here: Plus, you can connect it via MCP to any AI coding assistant and work directly on the repository. Powered by Deep Graph MCP AI at Meta and Groq Inc

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Daniel San

126,642 views • 10 months ago

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

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"AI agents are using the XRP Ledger x402 facilitator to produce better research by paying for proprietary data" That's most of the +1M AI agent transactions currently on XRP. You ask a research question, the AI agent can access data behind a paywall by paying for it via the XRPL x402 facilitator.

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As AI agents get better at computer and tool use, or writing code on the fly for a task, we're going to be able to solve much broader domains of knowledge work. Here's an example of Box AI with the new Claude Skills to generate a clean powerpoint file from existing data.

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Andrew Ng

85,012 views • 1 year ago

OMG Larry Ellison just exposed the plan to put every American citizen's financial and health data into a single AI database for total control. They are openly bragging about running a psychological operation on the American people to force us to be on our best behavior.

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Furkan Gözükara

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The Genie is out of the bottle! ✨ Meet Genie, Databox’s AI analyst. Ask your data a question. Get an answer, instantly. Use it to: - Analyze performance. - Build dashboards. - Create metrics. All from a simple prompt. Comment "Genie" and we’ll DM you a free month of our Pro plan + our AI Analyst Prompt Playbook.

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11,799 views • 1 year ago

Can Eli Lilly become the largest company in the world? Jordi Visser thinks so. "The reason I believe Eli Lilly has a chance to be the largest company in the world, and the number one AI company in the world within 5 years, is because they are building a specialized model." "They have their own data center with 1,000 GPUs with all the data that $LLY has had [as] a 150 year old company." "They are creating an innovation hub of using data all for human software."

Can Eli Lilly become the largest company in the world? Jordi Visser thinks so. "The reason I believe Eli Lilly has a chance to be the largest company in the world, and the number one AI company in the world within 5 years, is because they are building a specialized model." "They have their own data center with 1,000 GPUs with all the data that $LLY has had [as] a 150 year old company." "They are creating an innovation hub of using data all for human software."

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140,356 views • 2 months ago

.James Talarico: We cannot let artificial intelligence become yet another arena where billionaires write the rules for the rest of us. Working people must get a say and a share of that AI future. We can start by cracking down on the data centers that are jacking up our utility bills and using up all our water. And we can establish an AI dividend, so every American citizen owns a piece of these American AI companies. If they are going to use our human ingenuity and our collective intellectual property, then we want our royalty checks.

.James Talarico: We cannot let artificial intelligence become yet another arena where billionaires write the rules for the rest of us. Working people must get a say and a share of that AI future. We can start by cracking down on the data centers that are jacking up our utility bills and using up all our water. And we can establish an AI dividend, so every American citizen owns a piece of these American AI companies. If they are going to use our human ingenuity and our collective intellectual property, then we want our royalty checks.

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142,696 views • 1 year ago

How to automate data cleaning with AI. Today, I'll show you how to automate data cleaning using my free AI co-pilot available on GitHub. We'll create an AI co-pilot to automate data-cleaning tasks, focusing on cleaning a customer churn dataset. I'll guide you through setting up the co-pilot and using it effectively. This AI agent is a big help. Table of Contents: 00:00 Introduction 02:52 Setting Up Libraries 06:31 Setting Up LLMs 08:31 Creating Data Cleaner Code 11:02 Data Cleaning Process 13:02 Examining Data Cleaner Function 15:02 Final Thoughts Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter:

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Matt Dancho (Business Science)

50,794 views • 1 year ago

With the boom in AI driving the growth of digital data at an unprecedented rate, traditional magnetic tapes that we have been using for 50 years as a storage option may not be enough, according to a UK start-up who are developing a low-energy replacement

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Reuters

30,200 views • 1 year ago

Andrej Karpathy beautifully explains the fundamental difference of learning between a human and an LLM. > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” many of the best minds in this field think LLMs are not really learning anything, and therefore are incapable of surpassing human-level intelligence.

Andrej Karpathy beautifully explains the fundamental difference of learning between a human and an LLM. > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” many of the best minds in this field think LLMs are not really learning anything, and therefore are incapable of surpassing human-level intelligence.

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895,224 views • 10 months ago