7 LLM generation parameters, explained visually: https://t.co/z4uPYyooc5 ...

RT Avi Chawla (@_avichawla)- Google Maps uses graph ML to predict ETA- Netflix uses graph ML in recommendation- Spotify uses graph ML in recommendation- Pinterest uses graph ML in recommendationHere are 6 must-know ways for graph feature engineering (with code): ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/djM0vgEJOuAvi Chawla (@_avichawla):- Google Maps uses graph ML to predict ETA- Netflix uses graph ML in recommendation- Spotify uses graph ML in recommendation- Pinterest uses graph ML in recommendationHere are 6 must-know ways for graph feature engineering (with code): ...

PyTorch Geometric is a PyTorch extension specifically developed for building graph-based neural networks.It has an intuitive API that facilitates inspecting and analyzing graphs and building ML models on graph-based datasets.Open-source with 22k+ stars! https://t.co/A1ojZGubhG ...

6) Eigenvector centralityIf a node is connected to other influential nodes, it amplifies its own influence.It helps identify nodes that are influential not only due to their direct ties but also due to their connections with other influential nodes.Here's the code👇 https://t.co/zgMirjdzoo ...

- Google Maps uses graph ML to predict ETA- Netflix uses graph ML in recommendation- Spotify uses graph ML in recommendation- Pinterest uses graph ML in recommendationHere are 6 must-know ways for graph feature engineering (with code): ...

Technology & Development - React 获得了一种与 agents 交互的原生方式 [1] - 构建 agentic UIs 仍然非常困难 [1] - 需要将 agent 的输出流式传输到前端 [1] - 需要保持状态 [1]

GitHub repo: https://t.co/hCC5vtadZn(don't forget to star it ⭐ ) ...

Core Functionality & Features - CopilotKit v1.50 解决了构建 Agentic UIs 的难题，提供了一种原生的 React 方式与 agents 交互 [1] - `useAgent()` React hook 管理前端的完整 agent 生命周期，简化了 input → agent → streamed results → UI 的流程 [2] - 该 hook 将所有 agent 事件流式传输到 UI，自动同步对话状态，并处理重新连接 [4] - CopilotKit 支持线程（可恢复的对话）、自动流式重连、新的设计系统和更严格的类型安全 [3] Technical Aspects & Implementation - CopilotKit 通过 AG-UI 事件包装发送用户输入，并与所有主流框架兼容 [4] - 该方案旨在减少自定义粘合代码，例如 WebSockets、状态管理和手动事件解析 [1] - CopilotKit 是完全开源的，可以在 GitHub 上查看完整的实现 [3] Industry Impact & Benefits - CopilotKit 使构建 copilots、助手或任何 agentic 工作流程的前端部分变得更加容易 [3] - 通过实时、长时间运行的 agent，CopilotKit 提升了用户体验 [2][3]

Performance Improvement - The challenge is to accelerate the token generation speed of a GPT model from 100 tokens in 42 seconds, aiming for a 5x improvement [1] Interview Scenario - The scenario involves an AI Engineer interview at OpenAI, highlighting the importance of understanding optimization techniques beyond simply allocating more GPUs [1]