🫡 @irys_xyz isn't working on the model itself, but on the underlying data infrastructure, giving AI a truly long memory. With on-chain memory that can be stored, retrieved, and verified, AI no longer has to start from scratch every time, but can instead grow smarter over time, like a real "human." When most people talk about AI, their first reaction is that computing power is insufficient, and the models need to be bigger and the chips need to be faster. While this seems reasonable, the real bottleneck hindering AI development isn't processing power, but memory. The "memory" mentioned here isn't simply about caching one or two conversations; it's about persistent, reusable, and growing memory. For AI to become smarter, it doesn't rely on piling up data; it needs to remember every interaction with people, understand your preferences, habits, and even your mood swings, and be able to share this information with other models. The reality is, most storage systems are still stuck in the old ways, adapted for information from the file era, not the interactive and programmable intelligent data of today. Traditional databases are slow, expensive, and inflexible, let alone blockchain-based. Using these legacy systems for AI right now is like asking a top chef to cook on a wood stove—they'll get something done, but they'll fall far short of their true potential. #Starboard The key is that it's featured on @KaitoAI. Recently, @arbitrum @Aptos @0xPolygon @shoutdotfun $ENERGY has also been trending.