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AI 资讯 Dev.to

Day 127 of Learning MERN Stack

Hello Dev Community! 👋 It is officially Day 127 of my software engineering marathon! Today, I leveled up my asynchronous data pipeline in React.js by tackling a critical production-grade performance problem: avoiding memory leaks and managing component unmounting states using the useEffect Cleanup function alongside the native browser AbortController API ! ⚛️🛡️⚡ Additionally, I integrated a fully responsive async loading engine to drastically improve our overall User Experience (UX). 🛠️ Deconstructing the Day 127 Network Boundary Control As shown inside my refactored workspace code layout across "Screenshot (283)_2.png" and "Screenshot (284)_2.png" , the side-effect layer is now safe from ghost background executions: 1. Ingesting the Abort Signal API Inside the lifecycle layer, before initiating the endpoint call, I instantiated an active execution cancellation anchor on Lines 12-13 inside PostContainer.jsx : javascript const controller = new AbortController(); const signal = controller.signal;

Ali Hamza 2026-07-10 20:34 7 原文
AI 资讯 Dev.to

How a Transformer Plays Tic-Tac-Toe

An interactive guide to the architecture behind modern language models. Instead of predicting the next word, this Transformer predicts the next move in a game of fading Tic-Tac-Toe—making every step of the model easy to visualize and understand. Play the game, inspect every matrix multiplication, and watch tokens flow through the network in real time. What's covered Tokenization and embeddings Learned positional encoding Self-attention (Q, K, V) Multi-head attention Causal masking and softmax Residual connections and layer normalization MLP (feed-forward network) Unembedding and sampling Model ablations (no positional encoding, no causal mask, no MLP, no residual stream) Includes interactive visualizations for every stage of the Transformer pipeline - from input tokens to the final prediction. https://sbondaryev.dev/articles/transformer

Sergiy Bondaryev 2026-07-10 20:32 6 原文
AI 资讯 Dev.to

Qualidade aqui!!

Ownership: do "temos um rojão na mão" até "não precisa mais pensar nisso" Daniel Reis Daniel Reis Daniel Reis Follow for He4rt Developers Jul 8 Ownership: do "temos um rojão na mão" até "não precisa mais pensar nisso" # productivity # beginners # braziliandevs # career 159 reactions 6 comments 7 min read

Kevin Wallen 2026-07-10 20:27 3 原文
AI 资讯 Dev.to

Deploy an MCP Server to Edge Compute: Expose Telnyx APIs as Tools for AI Agents

Deploy an MCP Server to Edge Compute: Expose Telnyx APIs as Tools for AI Agents The Model Context Protocol (MCP) has become the standard way for AI agents to call external tools. Claude, Cursor, and a growing ecosystem of agent frameworks speak MCP natively, they discover tools via a tools/list endpoint and call them via tools/call . Any HTTP service that implements that contract becomes a tool provider the agent can use. This walkthrough deploys a working MCP server to Telnyx Edge Compute. The whole server is 167 lines of Python in function/func.py , uses Python's standard library for the HTTP layer, and exposes four Telnyx APIs ( send_sms , search_numbers , run_inference , list_phone_numbers ) as MCP tools. There is no Express, no FastAPI, no SDK, just urllib , json , os , and an ASGI handler. The canonical code example lives in the Telnyx code examples repo: https://github.com/team-telnyx/telnyx-code-examples/tree/main/edge-mcp-server-deploy-python What This Example Builds A single ASGI function deployed to Telnyx Edge Compute that exposes four MCP tools: Tool Telnyx API Purpose send_sms POST /v2/messages Send an SMS message to an E.164 number search_numbers GET /v2/available_phone_numbers Search available phone numbers by country and area code run_inference POST /v2/ai/chat/completions Run LLM inference via Telnyx AI (OpenAI-compatible) list_phone_numbers GET /v2/phone_numbers List phone numbers on the account The function exposes four HTTP endpoints: Method Path Purpose GET , POST /mcp/tools/list Return the tool catalog POST /mcp/tools/call Execute a tool by name with arguments GET /health Health check (tool count, API key presence) GET / Service info (name, tool list, endpoint paths) Once deployed, an AI agent that supports MCP can be pointed at the deployed URL and immediately call Telnyx APIs as part of its reasoning loop. Why Edge Compute Edge Compute runs serverless functions co-located with the Telnyx private network, the same network that handles voice,

Harpreet Singh Seehra 2026-07-10 20:23 3 原文
AI 资讯 Dev.to

Day 125 of Learning MERN Stack

Hello Dev Community! 👋 It is officially Day 125 of my software engineering marathon! Today, I crossed an elite milestone in frontend data architecture: moving completely away from local hardcoded mock lists by connecting my centralized state management infrastructure to live third-party servers using the Fetch API alongside Async/Await ! ⚛️🌐⚡ Now, the social media feed dynamically handles server-side data models, passes payloads to an active state reducer, and broadcasts states down to presentation layers via a custom Context portal! 🛠️ Deconstructing the Day 125 Async Network Lifecycle As shown inside my development setup across "Screenshot (279).png" , "Screenshot (280).png" , and "Screenshot (281).png" , the application state engine is clean and modular: 1. Extensible Central State Reducers ( PostList.jsx ) Engineered explicit structural actions inside the reducer core to seamlessly support both user generation and full-scale network array overriding: javascript } else if (action.type === "NEW_INITIAL_POSTS") { NewPostValue = action.payload.posts; }

Ali Hamza 2026-07-10 20:21 7 原文
AI 资讯 MIT Technology Review

The Download: Claude’s inner workings and OpenAI’s “super app”

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Anthropic found a hidden space where Claude puzzles over concepts The AI firm Anthropic has got the clearest glimpse yet at what’s really going on inside large language models as they…

Thomas Macaulay 2026-07-10 20:10 4 原文
开发者 The Verge AI

Doom’s new expansion shows just what makes id Software special

This week should have been a celebration for Doom developer id Software. The studio just launched Revelations, a meaty expansion for Doom: The Dark Ages that adds a powerful new weapon and more demonic levels to blast through. Even though I hadn't picked up The Dark Ages for more than a year, it only took […]

Jay Peters 2026-07-10 20:00 10 原文
AI 资讯 HackerNews

Show HN: Microcosm Industries – Simulation toys and software microcosms

I’ve been obsessed with simulation toys (software that allows you to play with a complex miniature world) ever since I was young and playing with SimCity and cellular automata. This kind of software exists at the delightful and weird intersection of simulation, complexity science, education, and gaming. And I want more of it! I created Microcosm Industries to initially act as a clearinghouse for simulation toys that are being built, ones that allow the user to playfully grapple with complex syst

arbesman 2026-07-10 19:56 2 原文