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India AI Impact Summit 2026: How to use AI to learn coding? Try these methods and you'll be able to make your life easier.

At this event held at Bharat Mandapam, the government, companies, and startups highlighted that AI is now opening up the ...
GitHub

Supercharge your Claude Code — Kill loops, save tokens, remember everything.

"Claude tried the same failing approach 15 times in a row. I watched it burn through my tokens doing the exact same thing over and over while I wasn't looking." Claude Code sometimes enters loops — ...
GitHub

Persistent memory for AI coding agents.

floop captures corrections you make to AI agents, extracts reusable behaviors, and activates them in the right context — so your agents learn from mistakes and stay consistent across sessions. It uses ...
IEEE

Human-In-The-Loop Oracle Learning for Simulation-Based Testing

Abstract: Ensuring safety and providing rigorous behavioral guarantees are critical for robotic systems operating in high-stakes environments such as autonomous driving. Field testing is common, but ...
Hacker

This 40B “Loop” Coder Model Tries Twice So Your Code Doesn’t Have To

Among other things, launching AIModels.fyi ... Find the right AI model for your project - https://aimodels.fyi ...
WTVD

Popular Chapel Hill eatery The Loop reopens after extensive storm damage from tropical depression

CHAPEL HILL, N.C. (WTVD) -- The Loop is back and officially open for business. The popular restaurant within Chapel Hill's Eastgate Crossing had been shuttered since July as a result of flooding ...
IEEE

Neural Network Coding Layer (NNCL): Enhancing Deep Learning Robustness Against Feature Erasure

Abstract: This paper proposes a novel Neural Network Coding Layer (NNCL) that applies network coding theory to provide structured redundancy and enable reconstruction of lost features, thereby ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...