Ever wonder what happens after you prove that decentralized AI inference actually works? That’s where a roadmap becomes interesting. BTTInferGrid isn’t treating decentralization like a switch that gets turned on overnight. The roadmap lays out a gradual transition, with each phase tackling a different piece of the puzzle: reliability, incentives, verification, adoption, and finally autonomy. Here’s how it unfolds: 𝗣𝗵𝗮𝘀𝗲 𝟭 → 𝗣𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗲 & 𝗧𝗲𝘀𝘁𝗻𝗲𝘁 First, prove the system works. Miner nodes, Validator scoring, and challenge-response verification are tested under adversarial conditions, with correctness taking priority. 𝗣𝗵𝗮𝘀𝗲 𝟮 → 𝗠𝗮𝗶𝗻𝗻𝗲𝘁 & 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗔𝗰𝘁𝗶𝘃𝗮𝘁𝗶𝗼𝗻 The network opens up to permissionless participation. Token incentives, staking, and slashing introduce economic accountability, while Miners contribute GPU resources for performance-based rewards. 𝗣𝗵𝗮𝘀𝗲 𝟯 → 𝗦𝘁𝗿𝗼𝗻𝗴𝗲𝗿 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 This is where the trust model gets stronger. TEE attestation, deterministic inference, and ZK proofs are introduced where applicable, alongside improved scoring and aggregation. 𝗣𝗵𝗮𝘀𝗲 𝟰 → 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 Now the focus shifts toward actual demand. Developer APIs and enterprise integrations bring real workloads onto the network, while flexible verification levels support different use cases. 𝗣𝗵𝗮𝘀𝗲 𝟱 → 𝗙𝘂𝗹𝗹 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗧𝗵𝗲 𝗲𝗻𝗱𝗴𝗮𝗺𝗲 𝗶𝘀 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝘆. DAO governance, fully permissionless Validators, fee-driven sustainability, verifiable computation and market-based allocation, with minimal reliance on privileged actors. What I find interesting is the progression: Prove it → activate it → verify it → scale it → decentralize it. That’s a much more deliberate approach to building a decentralized AI compute network. The goal isn’t simply to have distributed GPUs. It’s to build a network where compute can be contributed, verified, coordinated and paid for without depending on a central authority. That’s the bigger vision behind the BTTInferGrid roadmap. Explore more at https://t.co/hijdAPyB4i #TRONEcoStar #BTTInferGrid @justinsuntron @BitTorrent