The AI crypto sector in 2025 will be one of the most overheated. But behind loud tokens are different approaches: from real computations to empty branding. Let's analyze key projects based on facts: GitHub activity, user base, revenues, and architecture.
🔍 Fetch.ai (FET)
Focus: autonomous agents for DeFi, logistics, and IoT
GitHub: active commits, SDK updates
Users: integrations with Bosch, Catena-X
Value: real automation of processes, especially in logistics and micropayments
Conclusion: technologically mature project with practical benefits
🔍 Bittensor (TAO)
Focus: decentralized AI network, model competition
GitHub: high activity, open repositories
Income: TAO — one of the most profitable AI tokens ($6.5 billion cap)
Value: Proof-of-Intelligence — a unique incentive model
Conclusion: a fundamental project, but complex for mass adoption
🔍 Ritual
Focus: modular AI infrastructure, deployment and verification of models
GitHub: activity is growing, architecture is open
Benefit: allows launching LLM and ML models in Web3 protocols
Conclusion: promising, but still in early implementation stage
🔍 SingularityNET (AGIX)
Focus: AI service marketplace, collaboration with OpenCog
GitHub: moderate activity, platform updates
Users: strong community, but weak integration in DeFi
Conclusion: an old player in need of rethinking
📈 How does AI impact crypto?
- Trading: Numerai, Giza — using AI for building stock strategies
- Analytics: AI bots analyze on-chain data, predict trends
- Content: generation of whitepapers, NFT descriptions, UX texts — already automated
❗ Where's the hype?
Projects without open code, without GitHub activity and without real integrations — that’s marketing. If a token is 'AI' — but there are no models, no computations, no SDK — it's just a brand.
📌 Conclusion:
Real value — where AI solves problems: automation, training, verification. Hype — where a token is called 'smart', but does nothing smart.
