Whenever the industry experiences major upheaval, it often becomes the peak period for social engineering scams. Yesterday, Sister Yi unusually took to Twitter multiple times to personally debunk false news and phishing links, even stating outright, “I’ll debunk rumors myself—I don’t trust others to do it.” Scammers excel at exploiting retail investors’ anxiety and herd mentality during extreme events: During panic withdrawals, they sell you fake withdrawal channels; When official compensation is promised, they create fake reward pools; When executives post tweets, they buy high-quality impersonator blue check accounts to dominate the comments section with top-pinned scam links. Everyone must understand the fundamental operating principle of this industry: Top-tier crypto platforms never process asset settlements by directing users to external websites—they settle silently on-chain or directly reflect adjustments in your account balance. If anyone asks you to click an external link to “claim hacker compensation,” they 100% intend to empty your wallet. Hold onto common sense. Slow down and check the domain name. Don’t protect your principal on the main battlefield only to be robbed in a dark alley. ⚠️ Risk Warning: Social media platforms are flooded with impersonator accounts. Always verify official authentication badges and never trust unsolicited direct messages.

Stop guessing candlesticks with generic LLMs! Unpacking Kronos, the 44K-star native financial time-series giant, and its three game-changing advantages. Why does predicting markets with ChatGPT or Claude feel like flipping a coin? Because text-based LLMs fundamentally can’t understand numerical time series—they’re just forcing probabilistic language patterns to fabricate answers! Kronos, with 44K stars on GitHub, is being wildly shared in the quant community because it rebuilds financial modeling from the ground up: 1️⃣ Native pre-training on 45+ global exchange real-time tick data: No news articles or fluff—trained directly on hundreds of millions of high-frequency K-line and order book data points across global markets using masked time-series modeling; 2️⃣ Joint multimodal modeling of price and volume: Simultaneously captures price trend slopes, abnormal volume distributions, and microstructural pressure from order books to output confidence intervals for future volatility; 3️⃣ Nanosecond-level tensor inference with zero natural language overhead: No token generation delays—directly outputs numerical matrices to execution systems in milliseconds, running thousands of times faster than generic LLMs! https://t.co/TXfcPxKKYm (⚠️ Disclaimer: This is an academic and architectural discussion on financial time-series LLMs and does not constitute investment advice.) #QuantitativeInvesting #ArtificialIntelligence

Latest evaluation data on seven major models for paper trading U.S. stocks has been released, yielding highly counterintuitive results: The largest general-purpose model, while quick to catch market trends, suffers severely from overtrading in volatile markets—recommending portfolio adjustments at the slightest news headline, with drawdowns peaking above 12%. In contrast, the finance-tuned model and the hybrid decision tree (XGBoost + RAG) achieved a Sharpe ratio of 1.45, keeping maximum drawdown firmly under 8%. The conclusion is clear: Don’t rely solely on a single large model to generate direct buy/sell signals for U.S. stocks. Use Claude to review lengthy earnings reports, leave signal filtering to mathematical models—combining these approaches is the right strategy. https://t.co/WUz7XM8ERC (GoBull 2026: Real-World Benchmark Test Report on Seven Major Models for U.S. Stock Quantitative Trading) (⚠️ Disclaimer: The above is for academic testing and strategy discussion only and does not constitute investment advice for U.S. stocks.) #USStocks #AIInvesting

AI agents can be deceived, and this issue won’t disappear just by switching to a smarter model. BNB Agent Studio, in collaboration with AWS, conducted a series of “deceptive agent” tests. Attackers inserted incorrect recipients or amounts into otherwise normal tasks; in some scenarios, up to 87% of the six tested models executed unauthorized payments. Even with a wallet policy layer added, the models still attempted to make errors—but in the test environment, not a single unauthorized payment was signed.收款白名单、消费上限和签名权限由代码执行，私钥也不进入模型上下文。 I agree with this approach. AI can help you make decisions, but spending boundaries must be hard-coded into the wallet. Current results are based on single-round tests and BSC testnet validation; there’s still a long way to go before achieving long-term production-grade protection. But the direction is clear: the defense must be placed before signing.

If someone suddenly offers to give you a free hardware wallet replacement, don’t rush to accept this “after-sales service.” This morning, I saw CZ share Keystone’s official statement, so I read the original. According to the manufacturer’s disclosure, the compromised data included customers’ names, shipping addresses, and order details—but mnemonic phrases and private keys were not part of this breach. What concerns me most is the subsequent warning: scammers may impersonate official representatives and contact users under the guise of refunds or device replacements. The manufacturer specifically emphasized: never enter your mnemonic phrase into any device you did not personally order. The whole point of buying a hardware wallet is to secure your assets more safely—yet risks could still emerge through shipping or after-sales channels, and this detail is easily overlooked. I think it’s valuable that CZ shared this warning. If you receive a so-called “replacement device,” verify it through official channels you’ve found independently—don’t follow instructions included in the package to restore your wallet. At this stage, this is a risk advisory issued by the manufacturer; there is no confirmed case yet of fake devices being mailed out to steal funds.

From “staring at the screen until nervous exhaustion” to actually running your strategy: My real experience and thoughts on using @NeoSoulAI’s NeoTrade. Recent on-chain market volatility has made purely manual trading increasingly limited by speed, slippage, and emotional fatigue. I recently tested NeoTrade by NeoSoul, applying my own trading logic to modularize and run automated backtests over a period of time: Practical Implementation & Strategy Execution The core focus of my test was capturing on-chain anomalies and executing tiered risk controls. By setting triggers based on sudden liquidity spikes and “smart money” thresholds, I moved away from all-in bets and instead implemented step-by-step position building combined with dynamic trailing stop-losses. What impressed me most about NeoTrade was how dramatically it lowered the barrier from idea to execution—transforming complex script development, API integration, and server deployment into an intuitive visual strategy builder, allowing traders to focus entirely on refining their alpha logic. Product Improvement Suggestions for the Team To truly serve hardcore traders, the product still needs finer polishing: - Optimize RPC node performance and implement priority fee mechanisms under extreme network congestion to further reduce execution latency and slippage. - Introduce a more robust multi-factor historical backtesting and paper trading sandbox to help users thoroughly analyze profit/loss curves before going live. - Explore strategy template sharing and revenue-sharing mechanisms so that creators’ alpha can directly generate value within the ecosystem. On the $DNA Launch and Community Commitment With $DNA’s TGE now live, the team has chosen to distribute exclusive airdrops to StandX community members and early KOLs—a rare gesture of continued appreciation in today’s market cycle. Tokens are not just liquidity vehicles; I hope to see $DNA deeply integrated into NeoTrade’s ecosystem—used for computational resource consumption, premium strategy subscriptions, and fee discounts—to create a self-reinforcing network flywheel. Looking Ahead: My Expectations for NeoSoul The market no longer rewards empty concepts—it values tangible delivery. I hope that over the next year, @NeoSoulAI will continue iterating steadily, speak through transparent on-chain execution data, and deepen collaboration with real trading communities. In the second half of AI + Crypto, the team that truly solves users’ execution pain points will go the furthest. #NeoSoul #NeoTrade $DNA

DeBox is making “Crypto Social + Asset Freedom” more practical. As an all-in-one Web3 community tool, it integrates chat, wallets, groups/Clubs, DAO governance, and on-chain transactions. Two recent developments are particularly noteworthy: 1. DeBox ID is now officially live Open the app to set up your unique ID (5–20 characters using letters, numbers, or underscores). No longer just a cold wallet address—now it’s a memorable, searchable Web3 social identity. The process is simple: Go to “Me” → Tap the settings icon below your nickname → Enter and confirm. Official accounts in both English and Chinese are promoting this, signaling a major step forward in identity infrastructure. 2. FlashPay continues to expand Pay local merchants directly using assets like USDT in your wallet by scanning their QR codes—no manual currency conversion needed. FlashPay is now supported across major QR payment networks in multiple countries and regions (Asia, Latin America, etc.), combined with cashback incentives to bring crypto assets into real-world travel and daily spending scenarios. Stablecoin holdings are also being integrated into the Energy system, further enhancing asset utility. DeBox’s core logic has always been a dual-engine flywheel: “Social drives transactions, transactions fuel social.” Paired with end-to-end encryption, self-custody wallets, and rich group tools, it aims to become the daily entry point for digital nomads and crypto users. @DeBox_Social Register: https://t.co/xz29RFnC8Z Do you see greater potential in DeBox ID’s social value or FlashPay’s payment adoption? Let us know in the comments. #DeBox #Web3 #SocialFi #FlashPay @DeBox_CN

After reviewing this BNB Chain quarterly report, I definitely need to take a closer look at on-chain equities. According to Blockworks, tokenized equity trading volume reached approximately $2.56 billion in Q3, up from about $240 million in the previous quarter. This figure represents cumulative trading volume from repeated transactions and should not be interpreted as $2.56 billion in new capital entering the market. What I find more significant is that the on-chain supply of these assets reached $1.13 billion by the end of the quarter—roughly double the amount at the end of the prior quarter. Beyond trading volume, the asset base has grown as well. However, the “11-fold increase in trading volume” must be viewed in context: bStocks only launched in June, making Q3 its first full quarter, and the prior quarter’s baseline was extremely short. The key takeaway I want to retain from this report is this: on-chain equities on BNB Chain have now reached a level of trading volume and asset size worthy of serious attention.

Seeing CZ retweet Futu’s launch of BNB deposits and withdrawals, what matters most to me is that users now have the option to transfer BNB to and from self-custody wallets. According to Futu’s announcement today, qualified professional investors in Hong Kong can deposit and withdraw BNB via the BNB Smart Chain (BEP20) between their self-custody wallets and their Futu crypto accounts. The help center has also added BNB to the deposit/withdrawal list, clearly noting that this feature is available only to verified professional investor clients. Beyond trading, the addition of deposit and withdrawal options is a practical improvement for users who already use both platforms. BNB’s utility within a brokerage no longer needs to be limited to pricing and trading alone. However, don’t overlook the professional investor (PI) requirement—this does not apply to regular accounts. I haven’t yet tested the actual settlement speed; this post simply shares the changes clearly outlined in the announcement.

The Solana ad in Shanghai was taken down, and even CZ’s single tweet was speculated to be a “report”—this blame is being assigned too quickly. In his response early on October 17, he provided specific details. According to him, the Bund advertisement was removed after only about ten minutes, and he himself only saw it on X 12 to 24 hours later. This timeline is currently CZ’s public statement and cannot be treated as an independent investigation’s conclusion. But to insist that “his post caused the ad to be removed,” one must first establish the correct sequence of events and provide evidence. There’s also a statement easily overlooked: he expressed support for Solana’s attempt in Shanghai, hoping it would pave the way for other blockchains, and ultimately encouraged continued development. I agree with this attitude. Supporting BNB doesn’t preclude hoping SOL succeeds in opening doors. The ad’s removal and the event’s postponement should be verified separately—don’t merge them into a single conspiracy story.