Results for “fluid-intelligence”

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

Integrates on-device and cloud machine learning into Flutter apps with TensorFlow Lite and Firebase ML Kit, covering image classification, object detection, OCR, face detection, and barcode scanning.

Run computational fluid dynamics simulations using Python, including Navier-Stokes equations, shallow water, and stratified flows with pseudospectral methods and HPC support.

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

当需要进入并维持高效、专注的心流状态，以提升学习、工作或技能获取效率时

多阶段研究 idea 生成管道：景观扫描 → 双模型脑暴 → 初筛 → 深度验证 → 写入 wiki

当需要在日常任务或长期目标中创造高度专注、高效且愉悦的“心流”体验时

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

当需要进入高度专注、高效且愉悦的心流状态以完成创造性或学习性任务时

A complete tour of the intelli-verse-x 5-layer stack — Leantime/GitHub at the top, Beads/Bernstein/Claude-Squad in the middle, Gas Town as the multi-project fabric, and LiteLLM/Infisical/Langfuse/n8n/GH-Actions underneath. Use whenever the user asks "what does X service do", "where does Y data live", "how do I get to Z", or you need to understand which tool to reach for. This is the architecture map.

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

Build or review SwiftUI features using the iOS 26+ Liquid Glass API with native modifiers, container patterns, and performance-aware guidance.

Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns.

Build, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API, with guidance on availability, composition, and performance.

Generate image captions, answer visual questions, and perform image-text retrieval using BLIP-2's Q-Former architecture with frozen vision encoders and LLMs.

当需要在学习或成长过程中，通过设定合适难度的挑战来进入专注和高效的心流状态，从而将失败转化为积极的学习体验时

当面临信息过载或想法过多，需要筛选出值得投入资源（时间、精力）去执行的高价值想法时

当需要进入高度专注、高效且愉悦的工作或学习状态时

Memory (abaf-memory)