📢 Gate Square Exclusive: #WXTM Creative Contest# Is Now Live!
Celebrate CandyDrop Round 59 featuring MinoTari (WXTM) — compete for a 70,000 WXTM prize pool!
🎯 About MinoTari (WXTM)
Tari is a Rust-based blockchain protocol centered around digital assets.
It empowers creators to build new types of digital experiences and narratives.
With Tari, digitally scarce assets—like collectibles or in-game items—unlock new business opportunities for creators.
🎨 Event Period:
Aug 7, 2025, 09:00 – Aug 12, 2025, 16:00 (UTC)
📌 How to Participate:
Post original content on Gate Square related to WXTM or its
In today's rapidly developing field of artificial intelligence, we face a tricky question: how can we ensure that AI's output is trustworthy? Although AI can demonstrate astonishing capabilities, from writing poetry to solving problems to market analysis, its reliability has always been questioned.
As we become increasingly reliant on AI for decision-making, whether for investment advice or medical diagnosis, the question of 'Is the AI's answer correct?' becomes critical. However, a groundbreaking technology is attempting to address this challenge.
The collaboration between Sentient AGI and Lagrange is developing a revolutionary AI system. This system can not only answer questions but also provide verifiable proof of its answers. This innovative approach is called 'Zero-Knowledge Proof' (ZK Proof), which provides a 'mathematically secure trust certificate' for the output of the AI.
This new type of AI is no longer a mysterious 'black box'. Traditional AI models often only provide answers without explaining their reasoning processes. In contrast, this new type of AI not only gives answers but also proves the correctness of its responses without revealing the details of its internal workings.
This technological breakthrough could fundamentally change the way we interact with AI. It not only enhances the credibility of AI but also paves the way for its application in more critical areas. When AI can prove its reliability, we can rely on it more confidently to make important decisions.
However, this technology is still in its early stages and faces many challenges. How can we ensure the reliability of proofs without excessively increasing the computational burden? How can we make this complex mathematical concept user-friendly for the average user? These are all issues that need to be addressed.
Nevertheless, the concept of 'verifiable AI' undoubtedly opens a new chapter in the development of AI. It not only enhances the transparency and credibility of AI but may also support its application in more sensitive areas. As this technology continues to improve, we might be witnessing a significant shift of AI from 'intelligent' to 'trustworthy'.