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惊呆了！我用 Claude Code 直接研究美股/财报 拿刚IPO的 CBRS（Cerebras）当例子，4分钟就出一份完整投研报告，包含： 基本面、财报亮点、DCF详细估值建模、Comps对比、操作建议... 结果Claude说 CBRS的 IPO定价是垃圾价！ 现在 $329 冲进去，DCF显示大概率套3-5年…… 建议等跌回 $200 以下再认真研究... 以后扔一只股票进去，几分钟就让Claude给你输出完整投研报告+明确操作建议，就是不知道准确性如何😂 colbymchenry/codegraph: Pre-indexed code knowledge graph for Claude Code — fewer tokens, fewer tool calls, 100% local Nvidia's annual GTC often sets industry technical benchmarks and prompts competitors to revise roadmaps. The author argues the next structural
AI coding assistants like Claude Code can rapidly produce financial research and valuation models, changing workflows for analysts and developers building fintech tools. Cerebras and AI chip trends affect compute choices and cost structures for running large models used in finance.
Dossier last updated: 2026-05-15 09:56:43
惊呆了！我用 Claude Code 直接研究美股/财报 拿刚IPO的 CBRS（Cerebras）当例子，4分钟就出一份完整投研报告，包含： 基本面、财报亮点、DCF详细估值建模、Comps对比、操作建议... 结果Claude说 CBRS的 IPO定价是垃圾价！ 现在 $329 冲进去，DCF显示大概率套3-5年…… 建议等跌回 $200 以下再认真研究... 以后扔一只股票进去，几分钟就让Claude给你输出完整投研报告+明确操作建议，就是不知道准确性如何😂
colbymchenry/codegraph: Pre-indexed code knowledge graph for Claude Code — fewer tokens, fewer tool calls, 100% local
Nvidia's annual GTC often sets industry technical benchmarks and prompts competitors to revise roadmaps. The author argues the next structural shift in AI chips is heterogeneous inference, where SRAM-first startups like Cerebras are gaining prominence. They analyze generative AI inference workloads in three phases—prefill, decode attention, and decode FFN—each with different compute, memory bandwidth, and capacity needs. Prefill is compute-heavy with moderate memory size needs; decode attention demands very high bandwidth and large memory for KV caches; decode FFN needs high bandwidth and moderate memory for model weights. SRAM-based architectures target these bandwidth-sensitive decode stages, positioning them as a niche for next-wave inference acceleration.
Open Vibe, launched by the Wasp team, is a free open-source, AI-tutored course that helps developers build SaaS apps locally by pairing a terminal-based coding agent with a hands-on curriculum. Users paste a one-line prompt into agents like Claude Code, Codex, or Open Code, which then fetch the curriculum, monitor the learner’s project files, guide real-time pair-programming, quiz concepts, and surface interactive diagrams over the running app. v1.0 is live with initial modules, and new modules arriving soon; the course covers a task-management full-stack app, then scaffolding and deploying your own SaaS. It matters because it blends AI agents and developer tooling to teach practical, debuggable skills rather than passive tutorials or blind prompt-driven builds.