90% Of Faculty Say AI Is Weakening Student Learning: How Higher Ed Can Reverse It
New research shows learning erosion is real—but evidence-anchored design, governance, and assessment can turn AI into an asset rather than a liability.
New research shows learning erosion is real—but evidence-anchored design, governance, and assessment can turn AI into an asset rather than a liability.
As part of this update, Google is also pushing AI Mode even harder by creating a bridge between it and . Google says that ...
Of the countless AI tools available today, NotebookLM remains virtually one-of-a-kind. As a Google app that uses AI to help ...
Students are taking new measures, such as dumbing down their work, spying on themselves and using AI “humanizer” programs, to ...
Claude AI XRP prediction targets $2.15 by month-end. Here's how this Anthropic AI XRP price forecast 2026 compares to ChatGPT ...
We ran a 500-cycle benchmark to test long-horizon reasoning stability in large language models — not just output quality, but whether a model can maintain coherent identity and logic across hundreds of recursive reasoning steps.This is part of our SIGMA Runtime project — a cognitive control layer that runs on top of any LLM and tracks drift, coherence, and identity persistence in real time.---Why we did thisMost LLM evals measure short reasoning spans — 1-10 turns. But when a model is asked to
The ChatGPT Apps SDK has a steep learning curve, specially OAuth, where you're the provider and ChatGPT is the client (not the other way around). This can trip you up easily.This skill teaches Claude Code how to build ChatGPT apps correctly: - MCP server setup (Node.js/Python) - OAuth with PKCE and Dynamic Client Registration - Widget development with window.openai API - 20+ gotchas with fixes How to install it:npx skills add https://github.com/vdel26/skills
Good afternoon everyone, spent like 2 weeks straight doom-scrolling Anthropic docs, Arxiv rabbit holes, and Claude blog posts till my eyes bled. Instead of shipping yet another wrapper that "reinvents" the wheel, I just vibe engineered this thing to max out Claude Code's native features. Klaus Baudelaire (https://github.com/blas0/klaus-baudelaire) basically: Routes agents (in parallel/sequence) with through keyword based scoring + prompt length (no fancy e
I've been lurking on HN for years. You know the drill: interesting headline, 200+ comments, you dive in thinking "I'll just skim for 5 minutes"... and an hour later you're 36 chambers deep in a thread about memory allocation patterns in Postgres and you've completely forgotten what the original article was about.I don't just want a "summary" (which usually just shortens the noise). I want the meta-consensus: "What is the actual trade-off being de
It is now common to have multiple people using their smartphones to video the same event. I'm thinking Pretti and Good's killings. I've heard of Gaussian Splattering, which constructs a 3D scene from multiple cameras. Is it useful for these analyzing these events? And, if so, can someone build an easy-to-use open source tool?My speculation is that it would be useful to: (1) synchronize video, (2) get more detail than a single camera can get, (3) track objects (like Pretti'
My wife recently re-entered the job market and we noticed a frustrating trend: many of the roles are shared as regular status updates by recruiters rather than official listings in the Jobs tab.I don't know why this became a practice, but they are very easy to miss, unlike the job listings with alerts and all kinds of search.So I built this Chrome extension over a weekend to solve that problem. It tracks specific people or companies and captures those hidden opportunities from the feed.## T
Investing.com -- OpenAI CEO Sam Altman revealed that the company plans to release several Codex-related products in the coming month, with the first launch scheduled for next week.
OpenAI Codex has arrived in JetBrains IDEs with free promotional credits. The GPT-5.2-Codex agent can autonomously debug, refactor, and build features.
On Friday, OpenAI engineer Michael Bolin published a detailed technical breakdown of how the company’s Codex CLI coding agent ...
Lately i've been experimenting with this template in Claude's default prompt ``` When I ask a question, give me at least two plausible but contrasting perspectives, even if one seems dominant. Make me aware of assumptions behind each. ```<p>I find it annoying coz A) it compromises brevity B) sometimes the plausible answers are so good, it forces me to think<p>What have you tried so far?
... to get an interesting glimpse into what they know about you already.At least, I did.I then followed up with: "That’s fascinating, thank you. Please tell me more things that you know about me." and, in a new thread: "I want to tell you about myself so that you can help me better, but I first need to know everything you already know about me." It felt a bit like asking an ad targeting platform to tell me how it targets me.I also asked it to speculate about me: "Ba
Hi HN, it seemed like there was broad interest in the previous Erdos problem that GPT 5.2 Pro solved: https://news.ycombinator.com/item?id=46664631I recruited a team of smart undergraduates to construct a dataset of ChatGPT responses to every open Erdos problem and verify the output.They found:- 3 problems with new proofs (though in 2 cases, historical partial results were found that could be extended to solve the same problem)- 4 problems where 5.2 Pro or Deep Research found an e
I built an open-source GitHub Action that translates i18n files using LLMs, designed as a drop-in replacement for Lokalise, Phrase, and Crowdin.The problem: TMS platforms charge per-word and per-seat, and their machine translation lacks product context. A typical SaaS with 500 strings across 9 languages costs $200-500/month.How it works: - Extracts strings from your codebase (XLIFF, JSON, PO, YAML) - Diffs against previous translations (only translates what changed) - Sends to any LLM (Clau
I have a medium sized database of around 150 entries each with 10-15 parameters. It was put together by Claude. But the amount of hallucinated data is extraordinary! Trying to fix it using another llm like chat gpt or gemini hasn’t worked since they balk at looking for data for >50 data points. Gemini actually deleted 100 entries from the database while analysing it! So the question is- Is there a suitable way to analyze the database for inaccuracies/hallucinations and fix them, apart
I have a mass of AI subscriptions. ChatGPT, Claude, Perplexity, Gemini. My workflow became: ask Claude, then paste the same question into ChatGPT to sanity-check, then maybe ask Perplexity if I need sources. Five tabs, constant copy-pasting.Council just runs your prompt against multiple models at once and shows responses side-by-side. That's it.A few things I noticed while building this:1. Models disagree with each other way more than I expected. Ask anything slightly subjective or recent,