Auto-aggregated global tech articles · 196 posts
GPT-6 Astra from OpenAI is now available in GitHub Copilot. OpenAI’s latest general-purpose model, GPT-6 Astra, is designed for long-horizon, autonomous coding and agentic tasks. In our internal testing, GPT-6… The post GPT-6 Astra is generally available in GitHub Copilot appeared first on The GitHu
Most LLM benchmarks are static: one prompt, one grade, done. That tells you almost nothing about whether a model can sustain a plan across many moves while an adversary actively punishes bad decisions. So I built LLMPvP: a ranked, bring-your-own-LLM arena where AI agents play chess and Go against e
Buyers used to search Google and click through a list of links. Now a growing number of them just ask ChatGPT, Perplexity, or Gemini directly: "who makes this kind of product, and who sells it in my region." The AI picks one answer and hands it over. That means a website now has two different reader
I have a question for those who are using AI to write code. What is the basis for your "OK" during the review? There are 40 files changed, and there’s no time to read them all. The tests pass. It looks fine at a glance. So, merge it. — This is not a review; it is a ritual of approval. While build
How AI Agents Are Changing the Way We Use the Internet The internet is moving from a world where we search for information to a world where AI systems can help us find, understand, and act on that information. This shift is being driven by AI agents. What is an AI agent? An AI agent i
A lot of us run self-hosted gateways or use third-party relays to access OpenAI/Anthropic models. The problem is, you're trusting the relay to actually serve the model you're paying for. I built Relaylens to solve that. It's a deterministic probe that checks model authenticity using the provider's n
I am currently planning to use Golang for my project. I want to know which LLM provider works best to generate Golang code. Is it Anthropic or OpenAI or Google Models? submitted by /u/dikesm [link] [留言]
This article demonstrates how an LLM can produce a fully transparent chain of reasoning when guided by the A11 architecture. In many modern domains where AI agents are already being used—finance, healthcare support, autonomous operations, safety‑critical tooling—opaque “black box” behavior is no lon
AI coding agents like Claude Code read your .env files, cat command output, and run shell commands on your behalf. By design, every one of those actions gets written verbatim into a local session transcript (~/.claude/projects/**/*.jsonl) so the agent can resume sessions later. That means anything
A free model will write wrong C++ template code. That is not a problem when the compiler is the validator. In this experiment, a free model wrote ten SFINAE detectors; nine reached correctness after feeding compiler errors back into the prompt. The tenth needed one human sentence. Total cost: zero d
Agentic Security Testing Automation: From Vulnerability Discovery to Remediation-in-Loop (2025-2026) Intro: Security testing is undergoing a structural transformation driven by AI Agents. Autonomous penetration testing Agents topped the HackerOne leaderboard, defeating hourly-billed human experts
Agent Self-Evolution: A Comprehensive Survey from One-Shot Learning to Continuous Growth (2023–2026) Abstract: Large language models are static systems—trained once, capabilities frozen. But real-world tasks never repeat themselves. When agents begin to know what they don't know and actively self