KGeN collects data from verified humans in the Global South to train Physical AI and LLMs Backed by @AccelIndia @Prosus_Ventures @jump_
Joined February 2023
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$3,400,000+ earned by our AI contributors. In just 2 months.
To put that in perspective, it's what some of the biggest chains in crypto have disclosed as their revenue within the same time span. The difference is this went straight to people.
Our verified contributors are spread across 30+ countries, training AI across 15+ environments and 300+ task types.
Robots learn from humans and those humans deserve the credit and the earnings. Like ours do.
Physical AI learns from real humans, and in September, 30,000+ unique AI contributors helped make it happen.
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.
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.
Before Physical AI learns from a clip, we make sure a real human recorded it.
That's our verified human network.
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.
We've already seen flying cars, are we close to a future where robots will have their own calendars and routines?
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.
KGeN Foundation π© retweeted
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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 conditions.
Thatβs why diverse, real world egocentric data isnβt optional. Itβs crucial.
base:0xf3d5b4c34ed623478cc5141861776e6cf7ae3a1e is live on Bithumb.
A big week just got bigger. Here's a quick recap of everything that happened π§΅
82M Network Strength. $3.4B $KGEN volume. 3.4B user attributes.
Thatβs September β26.
