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Why human insight still matters in AI… AI isn’t replacing human instinct anytime soon. Why? Because AI is only as insightful as the data it's fed. Good data isn't merely about quantity; it's about the human insights embedded within that data. So, without human context, AI

Gm! Decentralized data is powerful. Verified data is unstoppable. We talk a lot about AI models. But what about the trust in the data underneath? In a world of hallucinations, how do we build systems that keep humans in control? Curious what do y'all think: What does

2+ years of work. 9000+ engineering hours. 51,500+ lines of code. All building toward this moment. Andromeda is ready TODAY. Global validator upgrade begins NOW. Takeoff in T-minus 7 days.

Happy Bitcoin pizza day from Tadz to y'all! 🍕 📸 Lora Lab

Gm, let’s break another AI illusion. Too many still believe bigger = better in LLMs. Let’s clear it up. ❌ Myth: Larger LLMs always perform better. ✅ Fact: Bigger doesn’t always mean smarter. More parameters without better data = more noise. Intelligence doesn’t scale if

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Web Version = Bigger Data Engine for AI. What’s coming next? The Ta-da Web Platform. We’re moving beyond the mobile app to something bigger, open, and more powerful. Our upcoming Web version will give AI projects the flexibility they’ve been asking for and give

Gm 🫡 What’s the first rule in AI ?! . . . . .

Why good DATA is more important than ever… AI is evolving at a rapid pace, but it’s only as effective as the data it’s trained on. That’s why having access to verified, high-quality, and diverse datasets is crucial for building smarter, more reliable AI models. Ta-da is

Gm! Good Data or Fast Data? AI can scale fast. But the real question is: can it scale right without quality input? If models are trained on random data, we’re just speeding up confusion. What matters more: faster results or trusted data? AI fam, what’s your take? 👀 Image

Data is the real moat in AI. As the AI stack matures, the friction won’t just be about model architecture or frameworks. It’ll be about who controls the transparent, most valuable datasets. And for AI agents, the importance of trustworthy training data only grows with scale.

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More task variety = More rewards for users We’re saying it about every day: AI models need one thing above all - real data from real people. That’s what Ta-da was built for, with a focus on Voice AI. But now, we’re going further. Our upcoming Web version will unlock the

❌Myth: AI hallucinations are just a temporary bug that will get patched. ✅Fact: Hallucinations are a result of incomplete, low-quality, or biased data inputs. No amount of compute can fix flawed data. Better models come from better data; structured, clean, and verified by

Gm fam 🫡 The data you feed, shapes the AI you get. But we now have a chance to build better from the ground up. What would you change in the way AI data is collected today? Image courtesy: Lora Lab

the future of building AI agents with Ta-da: ~ 10x leverage through human-in-the-loop verification ~ accelerate AI model training with human-generated data ~ build on top of transparent and verified data models ~ growth via open data sharing and incentivized

Ta-da V2: Your Data, Your Rewards. Now on Web. The new Ta-da Webapp is almost here, and it’s about to change how you earn from your data. With Ta-da V2, we’re going web-first, unlocking real flexibility in how you work and how you get paid. Here’s what’s new: ✅ Access tasks

❌ Myth: AI can learn on its own like a human. ✅ Fact: AI needs structured input, training data, and constant updates. It doesn’t grow independently. No AI wakes up smarter tomorrow. Behind every improvement is human data, curation, and training. It’s more dependent on people

Gm! Every time your agent replies with confidence and no bias... A crowd of humans probably made that possible. IYKYK😌