
Jasper 🌰@building BBX
16.3K posts

Jasper 🌰@building BBX
@bbxjasper
@bbx_official Co-Founder 🏗️ 🧠 BBX | Crypto × Equity × RWA Connecting crypto intelligence with equity markets — from data to execution. 📊 用数据说话,不猜行情













我倾向于把那个世界叫做: 认知核扩散之后的世界, 更强、更快、更假、更卷、更私人化。





MSX 疑似关联钱包存在将部分用户充值资金转入桥、普通交易所及外部中转网络的行为 由于平台尚未披露完整储备证明、券商账户、交易确认记录及托管/银行流水,这些资金存在被转移且用途不明的重大风险 如果 MSX 实际执行“一股对应一股真实美股”的业务,理论上应存在相对固定、可审计的美元出金、券商入金及证券交易路径 但本次链上追踪结果显示,MSX 疑似关联钱包资金并未主要呈现单一、稳定的美股交易通道,而是分散进入三类路径: A 类:机构、美元通道,约 1,197.3 万美元 包括 FalconX、Circle 等(该路径只能说明具备机构通道可能性,不等于已买美股) B 类:交易所 约 382 万美元 包括 Binance、OKX、Bitget、HashKey 等(进入交易所不等于进入美股体系) C 类:bridges, unknown addresses, proxy contracts、DeFi、OTC 等 高可信核心地址约 667 万美元;含中转/弱关联地址约 779 万美元。 其中 其中 C 类路径金额较大、层级复杂,难以解释为透明的美股购买或储备管理行为 C 类高可信地址:约 667 万美元 0x32008FCB6bbD16532Afc83ca8b6C920DDE22c407 → 0x6C96dE32CEa08842dcc4058c14d3aaAD7Fa41dee USDT0 / OAdapter Proxy 约 3,502,065.89 USDT 0x32008FCB6bbD16532Afc83ca8b6C920DDE22c407 → 0x337685fdaB40D39bd02028545a4FfA7D287cC3E2 Mayan Finance / MayanForwarder2 约 1,480,000 USDT 0x32008FCB6bbD16532Afc83ca8b6C920DDE22c407 → 0x5427FEFA711Eff984124bFBB1AB6fbf5E3DA1820 Celer cBridge V2 约 469,709.27 USDT 0x7282a7229837e13177D01bAb1282aE6E99F1f2e8 → 0xF07E3258395089514200209153a5d25DA97BC22C 高频中转 / OTC 风格枢纽 合计约 1,220,000 USDT/USDC C 类中转/弱关联地址:约 111 万美元 0xDff229AC76474cA7a51D40ea59F27a79e38846C8 → 0xF07E3258395089514200209153a5d25DA97BC22C 300,000 USDT 0xD588731395E9478B10C633fF38cA5C4005c6a443 → 0x684cfed2622E04fa46d40b0D7EbCa38CA1269Ac0 313,123.03 USDT 后续未知。 0x01Ca10E9fFFA1aA68AC27068FFF955E8b1D2b1d1 → 0x4bf12b1cAa6C74A4EdB41Bce85825DD92a0B511F 500,000 USDT 后续未知


ONE CHEAP AI MODEL IS NOT ENOUGH. Fusion lets multiple budget models work together—and the combined answer reportedly lands within 1% of Fable 5. Here’s the setup: → Send one prompt to a panel of up to 8 models → Each model researches and solves the task independently → A judge compares consensus, contradictions, missing details and unique insights Why it matters: ✓ Gemini 3.5 Flash, Kimi K2.6 and DeepSeek V4 Pro formed a budget panel ✓ The panel reportedly beat GPT-5.5 and Opus 4.8 running solo ✓ Opus 4.8 paired with itself improved from 58.8% to 65.5% on the Draco benchmark Roughly 75% of the performance lift came from synthesis—not simply adding different models. The practical lesson: Stop searching for one perfect model. Build a panel, add a judge and fuse the strongest parts into one final answer.




特斯拉监督版 FSD 要来了,这回可以冲了😏














