🚀 DataHive Raises $3.5M Seed to build the world’s largest decentralized data factory for AI. - Compute is a commodity, - Model architectures are open, -> The real edge in AI is data! DataHive delivers the hardest-to-collect web data - collected, cleaned, labeled, and AI-ready.

A true bee 🐝

Hive fam 🐝 We cooked up some recipe for your holiday table, a honey‑glazed turkey recipe straight from the hive! 🦃 Rub with salt, pepper, and herbs. 🍯 Glaze mix = honey + soy sauce + butter + Dijon + orange juice + garlic. 🔥 Roast at 325°F, basting every 30–45 min. ⛺ Foil

GM, Hive! Have a good day!

Crawling helps AI understand the world. Data creation helps AI grow beyond it. And DataHive AI will combine both into one ecosystem where anyone can contribute, earn and shape the next generation of AI. The Hive is just getting started. 👉 https://t.co/gzLTbLAJpl

That’s where DataHive AI is heading. In the future, users will not only contribute public web data but also create new, high-value datasets designed specifically for AI training. Real people generating real signals - not recycled or outdated content.

This includes tasks like: - creating new labeled images - recording audio samples - generating metadata that doesn't exist online yet - producing specialized content for targeted AI training - building domain-specific datasets from scratch

AI improves fastest when it learns from datasets that are: - fresh - diverse - structured - created with a specific purpose - and built to fill gaps that crawling alone can’t reach

Data Creation over Data Extraction: Building AI with Purpose Crawling and collecting public web data is a powerful way to help AI models understand how the world looks today. DataHive AI already supports this through our decentralized network of user devices. But the next

How many devices are grinding DataHive AI points for you right now?

GM, we’ve launched a blog on our website 🐝 This is where we’ll drop project updates, deep dives and everything about data and AI we’re building in the Hive Check out -

We’re deeply sorry...

5/ Bias is not just a technical flaw. It’s a data flaw. If we want AI that works for everyone, we need data that comes from everyone. Decentralization isn’t only a scaling strategy. It’s how you build fair AI. 🐝 DataHive is making that ethical future possible. Join the Hive.

4/ This is exactly what DataHive AI makes possible. A decentralized network of user devices collecting small pieces of public web data at scale: images, audio, video metadata, JS-rendered content and more. No centralization. No uniform patterns. No single-source bias.

3/ Diverse data sources change everything. When thousands of users contribute from different regions, devices, browsing habits, and environments, models learn the real world instead of a small fraction of it. More diversity means: - fewer blind spots - better accuracy globally

2/ Most AI bias comes from three simple factors: - Over-representation of some groups or behaviors - Lack of geographic and cultural diversity - Data collected from identical device types or usage patterns When signals look the same, models become blind to everything else.

Reducing Bias in AI Models: Why Diverse Data Sources Matter AI doesn’t get biased randomly. Bias happens when models learn from narrow, incomplete data. If you feed the machine one worldview, it will output one worldview. So the fix starts with diversity.

GM! Who’s got the most points?

5/ The result is a data layer that’s transparent, privacy-safe, and ethically sourced - ready to train AI models the right way. Responsible AI begins with responsible data. © Uncle Bee 🐝

4/ - Local filtering. Data is pre-processed on the user’s device to remove anything non-public or sensitive. - Anonymization. All data is stripped of identifiers and aggregated before sharing, with zero link to any user. - Decentralized flow. No central servers, the network

3/ - Permission-based activation. Data collection runs only when users choose to stay online. - Public scope only. The system targets open web elements like images, audios, videos metadata, and public information from JavaScript-rendered pages that standard crawlers can’t reach