Wish everyone a complete goodbye to being trapped in a losing position or missing the entry—every day the market surges higher, your wallet gets thicker, and your trading goes smoothly from start to finish.
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Technical and Market Focus (Recommended) The evolution of exchanges is here with @grvt_io The proposal to combine the speed and efficiency of a CEX with the full privacy and on-chain custody of a DEX is exactly what the market needs to regain trust. Monitoring its hybrid model and the integration of real-world assets (RWA) shows us that institutional liquidity is looking for this kind of robust infrastructure. Without a doubt, a key project to keep an eye on this quarter.
Ethereum uses AI to find vulnerabilities, but 9 out of 10 are “false positives”—human judgment is still required
Recently, the Ethereum Foundation公開 the latest security research results from its Protocol Security team, explaining how AI smart agents (AI Agents) help the core development team with vulnerability discovery and security analysis.
AI’s contribution: The Foundation uses AI Agents (coordinated, operating AI smart agents) to assist in reviewing Ethereum’s core code, including the protocol layer, the P2P network (e.g., libp2p Gossipsub), cryptographic libraries, system software, and smart contracts.
Practical results: AI successfully discovered real vulnerabilities—for example, a recently fixed libp2p Gossipsub vulnerability (CVE-2026-34219). This is a remotely triggerable issue that has been patched and publicly disclosed. AI can quickly generate attack scenarios, trace call flows, propose hypotheses, and even produce PoCs (proofs of concept), greatly accelerating initial scanning.
Core challenge: The proportion of false positives is extremely high. Roughly, for every 10 suspected vulnerabilities, only 1 is a real one that needs to be fixed; the other 9 are false alarms. The reports AI generates are often very thorough (including attack flows, root causes, and impact), making them sound highly convincing, but many are based on incorrect assumptions.
Binance has actively promoted AI applications in recent years
On compliance and risk management: Deploying more than 24 AI projects, and 100+ AI models, covering anti-fraud, AML (anti–money laundering), KYC (identity verification), transaction monitoring, abnormal behavior detection, and more.
Claims of impressive results: From early 2025 to Q1 2026, the AI system helped block more than $10.53 billion in potential fraud losses, protecting millions of users; in a single quarter alone, it stopped tens of millions of attacks, and the rate of card fraud dropped by 60–70%.
However, the false-positive problem is indeed real and widespread. Similar to Ethereum’s case, in the risk-control domain, AI’s false-positive rate is often relatively high—yet in high-risk environments, extensive manual classification and verification are still required. Binance officials emphasize that AI is an assistive tool and will be combined with human review, but in actual execution, users often feel that “the machine decides,” with cumbersome appeal processes and slow responses.
With hundreds of millions of users worldwide, it’s impossible to rely on manual review alone. AI is the only scalable solution. While it blocks large volumes of fraud, “sacrificing” the user experience becomes the trade-off outcome. $ETH $BNB
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