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兄弟们，又一套顶级 AI 量化打法出来了。 有人拿 Claude Fable 5.1 搭了套 Quant Spline Balance，专门扫 Polymarket 上的加密涨跌盘。日均能稳稳吃 1667 美元左右。 实盘数字挺夸张的。跑了 201 天，总利润 335210。平均每笔大概 60 块。忙的时候每小时能自动成交 70 多笔。BTC、ETH、SOL 的短时涨跌全覆盖。 说白了，不是在赌方向。是靠两个 AI 一块干活，一个负责定价，一个负责对冲，吃的是市场自己搞出来的价差。 定价那边用的是 GAM 非线性模型。它实时抓 BTC 行情，把偏离度、波动率、还剩多少时间、订单流偏了没，这几样丢进公式，算出涨跌该是多少概率。 公式长这样： z = β₀ + s₁(d) + s₂(v) + s₃(τ) + s₄(OFI) 然后转成价格： p_Up = 1 / (1 + e^(−z)) F_Up = 1 × p_Up F_Down = 1 − F_Up 同一波 BTC 波动，时间剩得多少、波动大不大，模型给出的估值就不一样。只要它算出来的公允价比当前买价高，系统就自动进。 另一边是均值方差风控。专门管仓位，别让一边敞口太大。手里有多单的时候，它会盯着空单成本，算一个最合适的残差区间： R* = min(Rmax, max(0, [p_Up − (1 − c_Down)] / [γ × p_Up × (1 − p_Up)])) 一旦一边偏了，马上补反向单，把风险压下来。 核心就一句话。多单成本加空单成本要是低于 1 美元，中间就有差价可以吃。机器人就反复干这件事。 账号实盘： 几笔比较猛的。535 变 2860，净赚 2325。632 变 2896，净赚 2263。685 变 2601，净赚 1916。 简单说，GAM 负责算该值多少钱，均值方差负责别让仓位失控。

BREAKING: Chinese illicit actors laundering funds from the $387M Bitget exploit on behalf of the alleged DPRK attackers are openly asking for support with orders in public Discord servers and Telegram channels of services they use. Notably, Alias 4 (below) was also seen laundering funds from the Kelp DAO $292M exploit earlier this year. I've observed the same pattern after multiple TraderTraitor attributed exploits, and I've closely tracked these groups. I plan to share more of my data on them in coming weeks. Currently, funds are being chain-hopped via bridges and being deposited into mixing services such as Wasabi. Alias 1 - Cc Discord: cc02006 Discord ID: 1351486674386948148 Txn: F08657EFAEAE7B58217CD17A22BF4779582E5D080C2E92E173BC239A5D828363 Alias 2 - jack Discord: jack_34808 Discord ID: 1553705721768714377 Txn: 68583D313A0CCC99F2702D61D05A242A69C86CAE09ED252B65F34B677C377F69 Alias 3 - Melon Discord: under0346 Discord ID: 1394240539108573215 Txn 1: ABE2AEF8B10057E60F8259CA2CA2CD5D71D38D254960FEEE89CB3C95A964873F Txn 2: 7BE290865901DEB1680A6D692A11392D1FDDACA0D31C48F26DCB249F2444BD6B Alias 4 - lolo / Marin TG: pvpcz TGID: 6223514198 Discord: losern Discord ID: 1024415186527985704 Txn: 8E935C19D00F40639B78BF1FD094FE48C92118F3E586AB52DF93851080CCCE15 Alias 5 - HELP ME Discord: helpme031897 Discord ID: 1554035533817188384 Txn: 7C58CAD760EBBED54F2CA4D2146D056910B7B6688B4F524396DC8807353C2379

A data center where compute and memory pool dynamically. Where millions of resources operate as one machine. Where architecture is defined by the needs of the workload, not the limits of connectivity. This vision of all-optical infrastructure points to a future with unprecedented scale, flexibility, and performance. Watch the closing moments from Marvell’s COMPUTEX 2026 keynote to see what’s possible. Watch the full keynote:

2025 global births by county (top 50): 1. 🇮🇳 India: 23.1M 2. 🇨🇳 China: 8.7M 3. 🇳🇬 Nigeria: 7.6M 4. 🇵🇰 Pakistan: 6.9M 5. 🇨🇩 DR Congo: 4.6M 6. 🇮🇩 Indonesia: 4.4M 7. 🇪🇹 Ethiopia: 4.2M 8. 🇺🇸 United States: 3.7M 9. 🇧🇩 Bangladesh: 3.4M 10. 🇧🇷 Brazil: 2.5M 11. 🇪🇬 Egypt: 2.5M 12. 🇹🇿 Tanzania: 2.4M 13. 🇲🇽 Mexico: 2.0M 14. 🇵🇭 Philippines: 1.8M 15. 🇺🇬 Uganda: 1.7M 16. 🇸🇩 Sudan: 1.7M 17. 🇰🇪 Kenya: 1.5M 18. 🇦🇫 Afghanistan: 1.5M 19. 🇦🇴 Angola: 1.4M 20. 🇾🇪 Yemen: 1.4M 21. 🇻🇳 Vietnam: 1.3M 22. 🇲🇿 Mozambique: 1.3M 23. 🇷🇺 Russia: 1.2M 24. 🇮🇶 Iraq: 1.2M 25. 🇿🇦 South Africa: 1.2M 26. 🇳🇪 Niger: 1.1M 27. 🇮🇷 Iran: 1.1M 28. 🇹🇷 Turkey: 1.1M 29. 🇲🇬 Madagascar: 1.0M 30. 🇨🇮 Côte d’Ivoire: 1.0M 31. 🇲🇱 Mali: 987K 32. 🇨🇲 Cameroon: 981K 33. 🇺🇿 Uzbekistan: 911K 34. 🇹🇩 Chad: 907K 35. 🇬🇭 Ghana: 898K 36. 🇲🇲 Myanmar: 888K 37. 🇩🇿 Algeria: 855K 38. 🇸🇴 Somalia: 822K 39. 🇯🇵 Japan: 748K 40. 🇧🇫 Burkina Faso: 742K 41. 🇿🇲 Zambia: 709K 42. 🇩🇪 Germany: 708K 43. 🇨🇴 Colombia: 693K 44. 🇲🇼 Malawi: 685K 45. 🇬🇧 UK: 680K 46. 🇫🇷 France: 635K 47. 🇲🇦 Morocco: 619K 48. 🇸🇾 Syria: 601K 49. 🇹🇭 Thailand: 572K 50. 🇸🇦 Saudi Arabia: 565K Nigeria alone had 1M more births than the entire Europe

After holding $ETH for 5 months, this guy finally gave up and sold 1,862.3 $ETH ($3.58M) at $1,923, taking a loss of $1.42M(-28%). He bought 1,862.3 $ETH at $2,685 in January when the price of $ETH dropped.

【#THEFIRSTTAKE】# ー No.685 T.M.Revolution / HOT LIMIT ー 白いスタジオに置かれた、一本のマイク。 ここでのルールは、ただ一つ。 一発撮りのパフォーマンスをすること。 ・ @TMR15 ▼Full show on YouTube

Age of each of these countries: USA: 250 years Netherlands: 445 years Sweden: 503 years Spain: 547 years Monaco: 729 years Switzerland: 735 years Thailand: 788 years Mongolia: 820 years Portugal: 883 years Hungary: 1,026 years Poland: 1,060 years Denmark: 1,061 years England: 1,099 years Norway: 1,154 years Russia: 1,164 years France: 1,183 years Morocco: 1,238 years Bulgaria: 1,345 years China: 2,246 years Iran: 2,575 years Japan: 2,685 years Ethiopia: 3,000 years Egypt: 5,125 years

问ai如果把日本韩国美国台湾欧盟的半导体设备龙头股组合成一个etf，取10个股票，如何组合，最好跟存储芯片的扩产路径相关的设备。 设备采购顺序一般是： 前道设备（刻蚀→薄膜沉积→清洗→检测→光刻）→ 后道封装（HBM）→ 测试 因此ETF应该偏重刻蚀、沉积、清洗，而不是EDA或晶圆代工。 1. $LRCX 20% 2. 8035.T 18% 3. AMAT 15% 4. 6525.T 10% 5. 7735.T 10% 6. 8% 7. 6857.T 8% 8. 042700.KS 5% 9.ASML / 4% 10. 8036.T 2% 核心逻辑： 重仓顺序： 刻蚀 > 沉积 > 清洗 > 测试 > HBM封装 > 光刻/检测 最核心三只： LRCX、东京电子、AMAT 最贴近HBM后道： Advantest、Hanmi 最贴近DRAM/NAND前道扩产： LRCX、东京电子、AMAT、Kokusai、SCREEN