New Version, Worth Being Seen! #GateAPPRefreshExperience
🎁 Gate APP has been updated to the latest version v8.0.5. Share your authentic experience on Gate Square for a chance to win Gate-exclusive Christmas gift boxes and position experience vouchers.
How to Participate:
1. Download and update the Gate APP to version v8.0.5
2. Publish a post on Gate Square and include the hashtag: #GateAPPRefreshExperience
3. Share your real experience with the new version, such as:
Key new features and optimizations
App smoothness and UI/UX changes
Improvements in trading or market data experience
Your fa
Recently delving into AI agents research, I had a feeling by early 2026 that this thing is really about to take off. It’s not just a chatterbox, but a creature capable of autonomous operation on the blockchain—automatically discovering arbitrage opportunities, dynamically managing DeFi positions, and making betting decisions in prediction markets.
The core pain points are twofold: hunger. Hungry for real-time data, complex computations, and off-chain signals. Traditional data sources only provide price figures; feeding them to the agent is like chewing wax, causing decision-making capabilities to plummet.
Later, I came across the APRO solution, and after careful study, I understood their approach. The core is brutally effective—offloading all heavy computations to off-chain AI nodes. News sentiment analysis, social buzz tracking, multi-source data integration, lightweight model inference—all handled off-chain in parallel. The only on-chain task is data validation and consensus confirmation. Latency is pushed down to sub-second levels, gas costs are almost negligible, and security remains intact—distributed nodes mutually constrain each other, and cheating behaviors are instantly detected.
I actually tried it myself. Deployed a small agent on a certain public chain, calling relevant APIs to fetch real-time betting odds for sports events. The returned data included not just numbers but also AI-processed "win probability distribution + sentiment correction factor." The agent then decided position size and executed trades based on this data, with minimal intervention from me. After running over ten cycles, the profit performance justified the effort.