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$620,000+ earned by our AI contributors in just 7 days.
AI has been trained on the internet for years without paying the people behind the data.
That’s over. Real contributors. Real environments. Real earnings.
AI has been trained on the internet for years without paying the people behind the data.
That’s over. Real contributors. Real environments. Real earnings.
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Our team visited Robotworld 2026 in Korea and Physical AI is moving faster than most people realize.
We saw robots with lifelike faces and capture rigs that see the world through human eyes. The hardware is ready; the next leap will come from the real-world data that teaches move and interact.
We saw robots with lifelike faces and capture rigs that see the world through human eyes. The hardware is ready; the next leap will come from the real-world data that teaches move and interact.
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Context Matters.
On a factory floor, hand annotation maps every grip, twist and placement as wires are sorted and parts assembled.
The more real work a model sees, the closer it gets to how people move.
On a factory floor, hand annotation maps every grip, twist and placement as wires are sorted and parts assembled.
The more real work a model sees, the closer it gets to how people move.
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Physical AI starts with getting the data right.
Real-world environments. Verified human contributors. Explicit consent.
These are the building blocks of AI that understands how humans interact with the world.
Real-world environments. Verified human contributors. Explicit consent.
These are the building blocks of AI that understands how humans interact with the world.
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Physical AI learns from real humans, and in September, 30,000+ unique AI contributors helped make it happen.
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Context Matters.
One kitchen, one task, three views. From the head, you see the whole counter. From the wrists, you see the small details, like how the packet tilts and where the fingers grip.
The more angles a model learns from, the closer it gets to how people really move.
One kitchen, one task, three views. From the head, you see the whole counter. From the wrists, you see the small details, like how the packet tilts and where the fingers grip.
The more angles a model learns from, the closer it gets to how people really move.
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Great breakdown from @humynlabs.
As robots move into homes and workplaces, what matters is whether real people recorded their training data in the kinds of environments where these robots will actually operate.
As robots move into homes and workplaces, what matters is whether real people recorded their training data in the kinds of environments where these robots will actually operate.
Text models learned from the internet. Robots have to learn from the real world.
Joint trajectories, depth, tactile feedback, all in sync. We break down what physical AI training data looks like, and why diversity matters as much as volume. x.com/i/article/2113…
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Before Physical AI learns from a clip, we make sure a real human recorded it.
That's our verified human network.
That's our verified human network.
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Bad data makes a chatbot say the wrong thing, but it makes a robot do the wrong thing.
That's why AI safety starts at the source, with the data it learns from. x.com/i/article/2112…
That's why AI safety starts at the source, with the data it learns from. x.com/i/article/2112…
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We've already seen flying cars, are we close to a future where robots will have their own calendars and routines?
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In just 7 days, our top 1,000 contributors collectively earned $100K+ by recording real world data to help train Physical AI.
As AI learns to understand the world we live in, the people capturing everyday life are earning from the work they put in to make it happen.
As AI learns to understand the world we live in, the people capturing everyday life are earning from the work they put in to make it happen.
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Context Matters.
Even a simple task like folding clothes changes with the environment. Indoor or outdoor, lighting, shadows and space all affect how the task is performed.
For Physical AI to get it right, it needs to learn everyday tasks across different environments and diverse, real world egocentric data isn’t optional. It’s crucial.
Even a simple task like folding clothes changes with the environment. Indoor or outdoor, lighting, shadows and space all affect how the task is performed.
For Physical AI to get it right, it needs to learn everyday tasks across different environments and diverse, real world egocentric data isn’t optional. It’s crucial.
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base:0xf3d5b4c34ed623478cc5141861776e6cf7ae3a1e is live on Bithumb.
A big week just got bigger. Here's a quick recap of everything that happened 🧵
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