Internet data fueled LLMs, but the next leap in AI will happen in the real world. ▸ Robots that clean ▸ Vehicles that see ▸ Agents that speak Poseidon is a full-stack data layer for the supply and demand of AI training data. Introducing Subnets in the Poseidon Litepaper ↓

Rumour has it you’re in the market for some high-quality training data.

Your Pipedrive journey starts here! Track your sales pipeline with the easy and effective CRM for closing deals.

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We’re deep in R&D on Poseidon Subnets – specialized data pipelines that coordinate how AI domains collect, curate, and license real-world data. Think of them as high-throughput lanes in the world’s first decentralized data highway. More to come 🔱

Spoke to the doctor, and they said the symptoms expressed here are consistent with data deficiency syndrome. Treatment is a high dose of real-world training data 🔱 https://t.co/EzcWq9KPEa

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“Here’s what I found about the Poseidon Audio dataset compared to other AI datasets.”

“Hey Alexa, tell me about Poseidon’s Audio data quality.”

I talked to a researcher from 1X couple months ago and he told me they can’t get enough data. In this video you see what they mean. Poseidon is gathering massive amounts of training data that no single company could source individually. 🔱

This image of a snowy road is a data point that will improve the performance of self-driving cars. From fog to glare, snow, accidents, and lightning strikes, edge cases help make physical AI safer. Via Subnets specialized for different data types, Poseidon turns real-world

Disciplined Execution

Poseidon connects the two sides of physical AI’s missing market: → Teams that need high-quality training data → And the people who can supply it Labelled, rights-cleared, and ready for commercial use. This is just the beginning: https://t.co/9PzgOpeeu6 ‧₊˚

What has 100 billion parameters and no common sense? A model without real-world data.

The last great frontier in AI isn’t models or compute The real moat is training data For physical AI

Also *training data* but what do I know

Co-founder @SPChinchali breaks down Poseidon at Origin Summit: ▸ Why data is the biggest bottleneck in AI ▸ The need for long-tail, rights-cleared data ▸ Poseidon Subnets and Litepaper reveal Watch the full keynote ↓ https://t.co/XXOMkObjO4

What Poseidon unlocks for physical AI ↓ ▸ A robotics team gets fine-tuned control over what POV footage they need to improve manipulation in cluttered scenes ▸ A researcher trains a speech model on dialectal audio that was never previously licensed or labeled ▸ A

Trick or treat? 🔥

Excited to share that I'm joining @psdnai as a founding engineer. 🧵

Most data acquisition today is locked inside private deals, closed platforms, and siloed infra. Poseidon creates a public coordination layer open to contributors, model builders, researchers, and data owners. Every dataset on Poseidon: ▸ Has verifiable provenance and metadata

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Fixing the AI data economy: demand-first, not supply-first ↓ Most prior attempts to build data marketplaces struggled because they started with supply. They asked: what can contributors upload? Poseidon flips this: ▸ AI teams define what they actually need ▸ Workflows break

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A structured runtime for acquisition, validation, and licensing ↓ Most AI teams build bespoke ingestion pipelines, each one a patchwork of data contributors, vendor APIs, and labeling scripts. Poseidon formalizes this with a composable runtime that handles the full lifecycle

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