Dear #BinanceSquareFamily readers, as someone who works as #SocialMining at @DAO Labs , today we will take a look at the interview conducted by Dr. Chen Feng, Head of Research at #AutonomysNetwork . The market is trying to move with $BTC , $BNB , $XRP price movements, #TrumpVsMusk discussions, #CUDISBinanceTGE news. It is always good for you to read different articles.
⭐ When we look at the visual, we see that 2 people working for Autonomys have similar thoughts. I shared my content about the CEO's article the other day. Today, according to Dr. Chen Feng, Associate Professor at the University of British Columbia and Head of Research at Autonomys, I will talk about TEEs (Trusted Execution Environments). Do TEEs really form the basis of Secret Artificial Intelligence? Today, artificial intelligence and many issues related to it are rapidly gaining strength. However, this power also challenges confidentiality and trust. According to Dr. Chen Feng, it is necessary to build castles to solve problems. In other words, it is necessary to use Trusted Execution Environments (TEE).
👉 What is TEE and Why is it Different?
Trusted Execution Environments (TEE) refer to hardware isolated, secure processing environments. They can protect the confidentiality and integrity of data and code even in a hostile system. In Dr. Feng's words, TEEs are "like castles we build in an untrusted area."
When comparing TEEs with other privacy technologies, ZKP (Zero-Knowledge Proofs) is strong but computationally expensive. MPC (Multi-Party Computation) is effective but has problems in terms of coordination and latency. FHE (Fully Homomorphic Encryption) is not yet widely used in terms of performance. According to Feng, “If we wait for cryptographic solutions to mature, we may have to wait until the end of the century.” TEEs are working today.
👉 So Why Does Autonomys Network Use TEEs?
Autonomys is a project positioned at the intersection of artificial intelligence and Web3. Its mission is to establish a more secure, decentralized and fair AI infrastructure. In this direction, they state that TEEs meet two main needs at the same time:
📌 Trust layer for Web3: TEEs have an ideal structure for decentralized trust mechanisms.
📌 Privacy for AI: Model architectures, user data, and inferences must remain confidential
Feng says that trust starts with confidentiality and that the most mature solution for this today is TEEs.
🤖 The Age of AI Agents and Scalable Privacy
In the future, not only humans but also billions of AI agents will take their place as users in blockchain networks. The need for privacy for these agents will become as critical as humans. Feng adds, “If AI agents are going to be users, they deserve privacy too.” His solution proposal on this issue argues that instead of giving each agent a separate TEE, designing an architecture that manages privacy at the infrastructure level is the solution. Feng’s big vision is a secret, decentralized, and fair superintelligence. He has another emphasis on this subject. “If only two or three companies control artificial superintelligence, that’s dangerous,” he says. They share the same thoughts as the CEO of Autonomys.
✍️ Finally, Dr. Feng believes that they can build a better AI future. He foresees that these goals will be achieved by thinking big and starting today.
