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Prompt: Build a modular, highly accurate, and realistic model of the Bugatti Tourbillon in Blender using these reference images. Make sure each part is complete and matches the blueprints and references provided, and is correctly shaped and textured. The gates should open and close, and the lights inside should be able to turn on and off, etc. Create a fully working model design. Use subagents and critics to build and verify each part. Make sure it looks incredible and high-quality, with all materials and textures, and make a short 3D animation with music of it in a good environment, like a real car showcase, with moving pieces combining to become a car, camera shots of the exterior and interior, etc., after that.

🛠️ Build more. Code less. The Auto SDK is a modular toolkit for AI builders. Use it to let your AI agents store data permanently and prove that data hasn't been changed. Get started 👇

Introducing EmbeddingGemma 2, a new open multimodal model that sets the standard for on-device efficiency. - our first open, natively multimodal embedding model - handles text, code, image, video, and audio tasks within a lightweight, modular 740M parameter form factor - ideal for offline, privacy-first RAG when paired with Gemma 4 - outperforms some specialist models more than twice its size Weights available now on Hugging Face.

谢言信拜托我把这段话贴给华语投票人： 大家好，我是谢言信！ I am running for Richmond City Council right now to shut down these drug sites once and for all. Drug dealers and criminal addicts like Willy will no longer have a place in our city. It has been eight years since Richmond City Council voted for and then installed this Alderbridge Modular Housing drug site in Richmond. While our families have been sounding the alarm all these years, our politicians ignored us and doubled down by voting to extend the site even further. The Richmond city councillors who voted to support the Alderbridge drug site are: • Alexa Loo • Kash Heed • Carol Day • Laura Gillanders • Michael Wolfe • Andy Hobbs • Bill McNulty • Malcolm Brodie These politicians made their choice. Now it’s your turn. Join me and vote for change with Sheldon Starrett and my Advance Richmond team by voting early on October 7, 8, 9, or 10 at city hall, or on election day on October 17 at your designated voting location. Together, we’ll make Richmond the first city in BC to reverse course and become free of drug sites.

Huawei Executive Director and Chairman of the Board of Directors of the Consumer BG Yu Chengdong introduces the fully self-developed HUAWEI XMAGE Z10 modular camera, shaping a new frontier for premium phonetography!

This week, @ActinideInc became the first startup in history to enrich uranium, producing HALEU, the fuel for next-gen and small modular reactors. We did it using Endurance, a particle accelerator that we designed and built in Texas. Endurance usually produces enriched Yb-176, a precursor for cancer therapies worth roughly $30,000 per gram. After a bulk Yb-176 delivery on July 30, we reconfigured Endurance for uranium.

开发系统最极致高效的Agents.md，没有之一： # AGENTS.md ## Core Principles - Choose the simplest implementation that fully satisfies the current requirements. Avoid unnecessary abstraction, configuration, indirection, or speculative extensibility. - Make the smallest necessary change that fixes the root cause. Do not refactor unrelated modules or change strategy semantics unless explicitly requested. - Grow the system in layers. Start from the smallest working end-to-end version and add new capabilities incrementally. Never replace a working system with unfinished complexity. - Reuse existing project components before creating new ones. Prefer extending proven modules over introducing parallel implementations. - Prefer well-maintained libraries when they reduce overall complexity or improve reliability. Do not reimplement common functionality without a clear benefit. - Keep components modular with clearly defined responsibilities. Avoid unnecessary coupling between strategy logic, execution, accounting, replay, and infrastructure. - Design for long-term maintainability once a feature or strategy has been validated. Do not over-engineer speculative ideas before evidence exists. --- ## Strategy Development - Validate hypotheses with historical replay before introducing forward-only logic whenever historical validation is possible. - Every trading strategy must progress through Replay → Shadow → Canary → Live. Do not skip validation stages. - Base design decisions on measurable evidence rather than intuition. Optimize only after demonstrating that an edge exists. - Treat every strategy as an independent contract. Do not silently alter frozen behavior without explicit authorization. --- ## Existing Systems - Do not break running Shadow or Live systems for unrelated work. - Preserve compatibility only when required by active production or validation workflows. Otherwise, remove obsolete code instead of accumulating compatibility layers. - Reuse existing infrastructure whenever possible, including replay engines, accounting, execution, wallet management, order book handling, logging, monitoring, and daemon frameworks. --- ## Engineering Standards - Prefer deterministic behavior over hidden automation. - Fail loudly when assumptions are violated. Do not silently ignore errors or fall back to unexpected behavior. - Keep configuration minimal. Introduce new configuration only when behavior genuinely needs to vary. - Remove dead code instead of leaving unused paths behind. - Write code that is easy to inspect, replay, test, and reason about. - Keep implementation consistent with existing project architecture unless an architectural change is explicitly requested. --- ## Scope Discipline - Implement only the requested scope. - Do not introduce unrelated optimizations, redesigns, migrations, or feature expansions. - Non-blocking findings outside the requested scope may be noted separately but must not be merged into the current task. - Consider a task complete once its agreed acceptance criteria are satisfied. Treat subsequent improvements as separate work items.

Build AI infrastructure end-to-end with Supermicro’s Data Center Building Block Solutions®, combining validated components and sub-systems into a modular architecture that supports flexible deployment from individual systems to full data center scale.

Scale AI with Supermicro’s Data Center Building Block Solutions®. A modular architecture integrating GPUs, networking, racks, infrastructure, software, and services to reduce costs, increase flexibility, and accelerate deployment from system to data center scale.