Tech News
Auto-research with codex: How I achieved a 232x Faster Kernel
A developer used OpenAI's Codex agent to autonomously optimize a video compression codec kernel, achieving a 232x speedup through a benchmark-profile-verify-research-improve loop, but community comments warn that such...
CORS Chat
Tool: CORS Chat I built this today ( with GPT-5.6-Sol xhigh ) to help test Qwen 3.8 27B running in LM Studio on both my M5 MacBook Pro and an NVIDIA DGX Spark.
Building agentic workflows with SageMaker AI and Bedrock AgentCore
Learn how to combine OpenAI-compatible endpoints on Amazon SageMaker AI with Amazon Bedrock AgentCore runtime to build a multi-agent workflow where each specialized agent uses the model best suited to its job.
The builder’s guide to GPT‑5.6
Learn how startups use GPT-5.6 to build faster, more cost-efficient AI agents with smarter model selection and new Responses API capabilities.
huggingface/transformers Release: v5.15.0
Release v5.15.0 New Model additions Meta Muse Glimmer Muse Glimmer, released today, is Meta’s new multimodal model, especially designed for agentic use cases.
GitHub Repos
koala73/worldmonitor
Real-time global intelligence dashboard.
# TypeScript# agent# aiGraphify-Labs/graphify
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph.
# Python# ai agents# antigravitytrpc-group/trpc-agent-go
A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, evaluation, and observability.
# Go# a2a# a2a protocolResearch Papers
A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization
This paper proposes a hybrid optimization method where an LLM proposes a structural sketch with numeric gaps, and a separate numerical optimizer fills in the gaps, improving efficiency over pure LLM-driven search.
MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning
This paper introduces MOON, a method for multi-task learning that adjusts gradients in a way that respects the matrix structure of neural network parameters, leading to faster and better optimization compared to existing methods.
VALG: An Agentic System for ML Theory Research
This paper introduces VALG, an AI agent that helps researchers do machine learning theory by automatically formulating problems, checking proofs, and organizing them in a structured way.