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说的真好 《AI-Generated Images Discourage Me From Reading Your Blog》AI 生成图让我放弃阅读很多博客文章 看到一个文章使用非常夸张的标题和各种 skills 生成的图片，我都会略过。博客应该呈现的是真实人类的思考，而非某个 AI 的产物。

Welcome to ClickHouse, @andy_pavlo 👋 We're launching ClickHouse Labs, a new research group advancing foundational database technology, led by Andy as VP of Database Research. Andy is an award-winning database researcher, professor at Carnegie Mellon University’s Computer Science Department and longtime leader of the CMU Database Research Group. At ClickHouse Labs, he'll build a team to take on the hardest problems in database systems, testing their work on real workloads and publishing it in the open, across both ClickHouse and PostgreSQL. Read Andy’s blog:

📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub： - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀 📖 Blog: ✅ Qwen Studio: ⚡ API:

Is Ethereum finally taking the driver's seat from Bitcoin? 📉➡️📈 The $ETH / $BTC ratio just surged to a 3-month high of 0.030, driven by a massive +16% monthly performance spread in favor of Ethereum (+24% vs. +8%). The latest KuCoin blog breaks down the fundamental forces behind the momentum shift: 📊 Reclaiming the 200-Day SMA: The cross-rate has officially reclaimed its 200-day Simple Moving Average for the first time since January, signaling a technical trend reversal. 🌊 ETF Flow Flippening: U.S. Spot Ethereum ETFs recorded $103.9M in weekly net inflows—outpacing Spot Bitcoin ETF inflows by a factor of 3-to-1. 🔒 The Supply Vortex: Public treasury accumulation (Bitmine holding ~4.8% of circulating supply), a zero validator exit queue, and 2.5M ETH waiting in the staking entry queue have squeezed spot liquidity. ⚙️ "Glamsterdam" Horizon: Institutional RWA dominance exceeds $17B on Ethereum, with the H2 2026 "Glamsterdam" upgrade set to introduce parallel processing and slash L1 fees by over 70%. Is this just a short-term liquidity rebound or the start of a full-scale market rotation? Read the full technical breakdown here:

Is the AI boom facing its first major credit market warning sign? ⚠️📉 NVIDIA’s 5-year Credit Default Swaps (CDS) surged to a record high of 82 basis points as market concerns mount over massive $750B+ AI infrastructure commitments and vendor financing loops. The latest KuCoin blog breaks down what this credit risk spike means for tech equities and the crypto market: 📉 Credit Default Swaps Surge: Five-year CDS on NVIDIA debt hit a record high of 82 bps—its largest single-day jump—as credit markets aggressively reprice contingent liabilities. 💼 The $750B AI Web: Massive deals including a $500B+ partnership with SK Group and a potential $250B financing backstop for OpenAI are raising concerns over balance sheet complexity. 🔄 Circular Financing Fears: Credit markets are questioning vendor financing feedback loops, where chip demand is partially supported by the supplier's own capital commitments. ⚡ Crypto Market Spillover: As high-beta risk assets, digital assets continue to show tight correlation with technology risk sentiment, reacting directly to credit market signals from the AI complex. Are we seeing the early warning signs of an AI capital bubble, or is this just near-term noise? Read the full analysis here:

Releasing the model weights and technical report of Kimi K3. Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window. New model architecture: 2.5x the intelligence per unit of compute, not just more params. Alongside Kimi K3, we're opening up more of the stack behind it — high-performance attention kernels, MoE communication library, and infrastructure for running agent environments at scale. Model weights: Tech report: Tech blog: