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🏃‍♂️ Is it AI Motion2Money or Mocap2Mop?

Your GPT’s A.I.mployed But Not Employed

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A human controlled a robot in real time and the robot learned from it. This new pipeline from Unitree may finally fix the #1 bottleneck in robotics: real training data.

IN PARTNERSHIP WITH HUBSPOT

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AI INSIGHTS

turning-human-motion-into-robot-ready-data

Unitree Robotics just showed off a full-body teleop setup where a real human in a motion-capture suit controls their G1 humanoid. What’s actually happening?

A human wears a suit → robot copies every move in real time. While doing stuff like: washing dishes, folding laundry, carrying mugs, playing football, sparring (!!)

But here’s the trick: everything is recorded as robot-native training data. That means no messy simulation, no hand labeling, no weird video retargeting.

Normally, collecting robot training data sucks. It’s expensive (real robots + safety + setup) & painful to scale (each robot is different). Unitree built a loop where:

  • Human controls the robot

  • Robot learns while being controlled

  • That data goes back into training

  • Same robot gets better, faster

And it gets better, the system can tag in a helper AI policy for easy parts, and let the human handle the tricky bits. So one person, even you or me, can scale data collection across multiple robots.

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AI SOURCES FROM AI FIRE

🔥 Ep 32 Tooldrop: How to run deep research on 10+ competitors in parallel

Today we explore and test 5 AI tools that creates stunning presentations, builds custom AI agents for any business or WordPress websites with full layouts!
→ Get your full breakdown here (no hidden fee)!

1. 4 'secret' ChatGPT hacks that actually cut my work time by 50%. Learn how to get perfect prompts, and finish complex tasks faster

2. I tested a new AI method that lets you create real products in minutes by talking to it. Just "vibe code", here’s the secret

3. Your RAG system is stupid? Here's the 11-step fix to stop getting hallucinations and missed data. 11 advanced RAG strategies

TODAY IN AI

AI HIGHLIGHTS

🌚 You think you could spot all AI-generated videos? Here’s a fun quiz you can take to put your skills to the test. Honesly, even my team and I couldn’t make it to 100%.

🎖️ OpenAI just gave 1 year of free ChatGPT Plus to U.S. service members and recent vets (normally $240/year - $20/mo). Get full access or verify your eligibility here.

⚡️ Yesterday, we got IRON, a humanoid robot so lifelike people thought it was human. Today we have robots DJing dancing at deadmau5. Watch the wild clip here.

🍌 Everyone’s been buzzing that Google's Nano Banana 2 allegedly leaked. It’s almost too good with jaw-dropping capabilities on an early preview testing here.

🏥 OpenAI is eyeing its next trillion‑dollar frontier - health tech. It’s building a generative AI personal health assistant. FYI, Google Health tried & failed in 2011.

😂 Kim Kardashian vs. ChatGPT? It’s a thing. While prepping for the bar exam, she used GPT for legal help & kept failing. Even billionaires get hit. Can’t miss this video.

💰 AI Daily Fundraising: Three ex-Google & Meta leaders raised $100M for Majestic Labs, building servers with 1,000× more memory that could replace 10 racks.

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AI CHART

ai-agents-vs-humans-ultimate-productivity-cage-match

Carnegie Mellon and Stanford just ran one of the most brutal head-to-heads in modern work research: 48 humans vs. 4 AI agent frameworks battling across 16 real-world job tasks.

Here’s what researchers noticed: AI agents treat every task like a programming problem.

  • Humans designing a logo → Open Figma, drag shapes, tweak fonts

  • AI agents → Write Python or HTML to generate SVGs and export files

Even on tasks that humans do visually, agents tried to solve it with code, very “agent-core.” It’s like watching someone build IKEA furniture using only an Excel formula:

  • Speed: AI agents complete tasks 88% faster

  • Cost: They’re 90-96% cheaper

  • Quality: Humans still win across every task type

AI agents are sprinting. But they keep dropping the baton. They also tested hybrid workflows, humans + agents working together = 69% boost in efficiency. That’s the dream combo, and we already use this everyday!

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The AI Fire Team

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