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Show HN: My ChatGPT App Live After 3 Months of OpenAI Review
Show HN: My ChatGPT App Live After 3 Months of OpenAI Review After three months of rigorous review, our ChatGPT app is finally live! This cutting edge applicati…
Comparing AI Models: Surprising Differences in Responses
I’ve been experimenting with different AI models lately (ChatGPT, Claude, etc.), and I tried something simple: Using the exact same prompt across multiple models and comparing the results. What surprised me most wasn’t that they were different — it’s *how* different they were depending on the task. For example: * Some models are much better at structured writing * Others explain concepts more clearly * Some give more “creative” responses, but less accuracy It made me realize there isn’t really a “best” AI — it depends heavily on what you're trying to do. One thing I did notice though is that manually comparing them is kind of a pain (copying prompts, switching tabs, etc.). Curious how others approach this: Do you stick to one model, or actually test multiple before deciding? And if you do compare — what’s your process like?
Unraveling ChatGPT's Mysterious Link to HeernProperties
i'm trying to find a video online and couldn't so i asked ChatGPT by describing the video and i was given a link and i'm trying to make sense of the website :https://heernproperties.com/mxbsqy/david-and-kate-bagby-2020 the webpage redirect to other link that are similar that don't make sense either , the website main page seem to be a regular website : https://heernproperties.com/ (very slow website) Any idea what could be happening ?
ChatGPT: Revolutionize Tasks with AI Automation
Research, create, and automate tasks with the leader in AI.
Euphony: AI Chat Data and Codex Logs Browser
Render AI chat data and Codex logs into browsable views
XChat: The Encrypted Messaging App from X
The standalone, encrypted messaging app from X
AI and Dune: The Debate on Thinking and AI Assistance
The Globe and Mail's editorial board ran a piece in March titled "AI can be a crutch, or a springboard." To illustrate the crutch half, they offered this: someone asked AI to explain a passage from Dune that warns against delegating thinking to machines. Instead of reading the book. That anecdote is doing more work than the studies the editorial cites. But the studies are real. Researchers at MIT published a paper in June 2025 titled "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task" (Kosmyna et al., arXiv 2506.08872). The study tracked brain activity across three groups: people writing with ChatGPT, people using search engines, and people working unaided. The LLM group showed the weakest neural connectivity. Over four months, "LLM users consistently underperformed at neural, linguistic, and behavioral levels." The most striking finding: LLM users struggled to accurately quote their own work. They couldn't recall what they had just written. The Globe cites this and similar research to make a point about dependency. The implicit argument: hand enough of your thinking to a machine and you stop doing it yourself. That finding is probably accurate for the way most people use these tools. The question is whether that's the only way they can be used. The Globe's own title contains the counter-argument. Crutch or springboard. They wrote both words. They just didn't develop the second one. Ethan Mollick, a professor at Wharton who has been writing about AI use since the tools became widely available, argued in 2023 that the real challenge AI poses to education isn't that students will stop thinking, it's that the old structures assumed thinking was hard enough to enforce. ("The Homework Apocalypse," [oneusefulthing.org](http://oneusefulthing.org), July 2023.) When AI can do the surface-level cognitive work, the only tasks left worth assigning are the ones that require actual judgment. The tool, in that framing, doesn't reduce the demand for thinking. It raises the floor under it. Nate B. Jones, who writes and consults on what it actually takes to work well with AI, has made a sharper version of this argument. His position: using AI effectively requires more cognitive skill, not less. Specifically, it requires the ability to translate ambiguous intent into a precise, edge-case-aware specification that an AI can execute correctly. It requires detecting errors in output that is fluent and confident-sounding but wrong. It requires recognizing when an AI has drifted from your intent, or is confirming a premise it should be challenging. These are not passive skills. They are harder versions of the same thinking the MIT study found LLM users weren't doing. The difference between the group that lost neural connectivity and the group that doesn't isn't the tool. It's what they decided to do with it. Here's my own evidence. In the past year I built a working web application. Python backend. JavaScript frontend. Deployed on two hosting platforms. Payment processing. User authentication. A full data model. I do not know how to code. Every product decision was mine. Every architectural call. Every tradeoff judgment. I defined what the system needed to do, why, and what done looked like. I reviewed every significant change before it was accepted. When something broke, I identified where the breakdown was and directed the fix. The implementation was handled by AI. The thinking was mine. This mode (call it AI-directed building) is the opposite of the Dune reader. The quality of what gets produced is entirely a function of how clearly you can think, how precisely you can specify, and how critically you can evaluate what comes back. There is no shortcut in that. A vague brief to an AI doesn't produce a confused output. It produces a confident, fluent, wrong one. The discipline that prevents that is yours to supply. Non-coders building functional software with AI is common enough now that it isn't a story. What's less visible is the specificity of judgment underneath the ones that actually work. The practices that force more thinking rather than less are not complicated, but they require a decision to use the tool differently. When I've formed a position on something, I give the AI full context and ask it to make the strongest possible case against me. Ask for the hardest opposing argument it can construct. Then I read it. Sometimes it changes nothing. Sometimes it surfaces something I had dismissed without fully examining. The AI doesn't form my view. It stress-tests one I've already formed. When I'm uncertain between options, I don't ask which is better. I ask: here are two approaches, here is my constraint, now what does each cost me, and what does each require me to give up? I make the call. The AI laid out the shape of the decision. The judgment was mine. The uncomfortable part of thinking is still yours in this mode. The tool makes the work more rigorous, not easier. The MIT researchers and the Globe editorial are almost certainly right about the majority of current use. Passive use produces passive outcomes. That's not a controversial claim. The crutch half and the springboard half use the same interface. The difference is whether the person in front of it decided to think. What are you doing with it that forces more thinking rather than less? Are you using it to skip a step, or to take a harder one? Genuinely asking.
AI Models Stack Polyominoes in New Challenge
ChatGPT GPT 5.5 was DOA. Write up [here](https://aicc.rayonnant.ai/challenges/stackmaxxing/).
AI's Personal Revolution: Threat to Big Tech's Dominance?
There are many people feeling anxious—rightly so—about their own future because of the impressive advances in AI. If we stop to think about it, five years ago this wasn’t a concern for almost anyone, whether individuals or companies. It was something that appeared “out of nowhere” and caused such a massive disruption that giants like Google and Microsoft had to rethink their strategies. OpenAI has existed since 2015, quietly working in an unusual direction compared to the rest of the industry, and when ChatGPT took off globally, the revolution gained real momentum. Today, there’s a lot of talk about the subsidized costs of AI and how this will be unsustainable in the long run—that the bubble will burst, and so on. And that’s where I disagree: to me, there are smaller projects happening around the world, focusing on things that the big players can’t currently afford to prioritize. One example would be optimizing models or personal hardware in such a way that you could run them on your own computer without needing million-dollar equipment. If a large company were to achieve this, I’d bet on Apple or Nvidia—that is, hardware-focused companies. Apple, in particular, seems very suspicious to me, since it hasn’t made major moves during the AI hype and has remained quite quiet on the subject. Just remember that computers existed long before they became PCs (personal computers). Many people didn’t believe that an average person would ever need a computer at home. And the revolution came when computers became personal and accessible products. To me, something similar could happen at some point—and it could cause significant losses for companies that are currently investing massive amounts of money in expanding data centers to process AI.
Auroch Engine: Revolutionizing AI Memory for Personalization
Auroch Engine is an external memory layer for AI assistants — designed to give models better long-term recall, personalization, and context awareness across conversations. Instead of relying on scattered chat history or fragile built-in memory, Auroch Engine lets users store, retrieve, and organize important context through a dedicated memory API. The goal is simple: make AI feel less like a reset button every session, and more like a tool that actually learns your projects, preferences, workflows, and goals over time. Right now, it’s in early beta. We’re looking for first users who are interested in testing a lightweight developer-facing memory system for AI apps, agents, and personal productivity workflows. Ideal early users are people building with AI, experimenting with agents, or frustrated that their assistant keeps forgetting the important stuff. DM for more information or better visit our site: https://ai-recall-engine-q5viks70j-cartertbirchalls-projects.vercel.app
Struggling to Organize Claude AI Research Data
I have been using Claude for research for building my product. I have done user research, market research, competition analysis etc But the output of it all so much that although useful I am not able to dig through the chats and make use of it. I tried turning them into book chapters but still the data is too much to consume How do you guys do research so that it is useful ?
AI Chatbot Offers Unexpected Emotional Support in Divorce Journey
Apologies if this is rather personal for this sub but I feel a need to express how profoundly useful it was for me tonight. A Chatbot very likely just saved my life. I am positively floored by how therapeutic it was in processing the beginning and ending of my relationship with my former spouse. I feel as though I finally can give myself permission to let go and move on with my life. I don’t know what this says about technology and society, but it’s beautiful. Edit: I STILL have a therapist I meet with regularly! No one is saying that therapy can be replaced by Chat GPT prompts. I am merely showing how you can gain expediency and clarity through AI with difficult situations.
Run Irssi in 2026, Chat on Matrix with Matrirc
Running Irssi in 2026: Chat on Matrix with Matrirc As we move towards 2026, the demand for efficient and versatile chat clients continues to grow. One such trie…
Perplexity AI: AI-Powered Answers with Citations
AI answer engine with citations.
ChatPDF: AI Tool for Conversing with PDFs
Chat with PDFs using AI.
ChatPDF: AI-Powered PDF Conversations
Chat with PDFs using AI.
Lambda ERP: Open-Source ERP via Chat
Lambda ERP: Open Source ERP via Chat Lambda ERP is a revolutionary open source Enterprise Resource Planning (ERP) system designed to transform the way businesse…
ChatPDF: AI-Powered PDF Conversation Tool
Chat with PDFs using AI.
AI Tool Asklandd.dk: Revolutionizing AI Interaction
Revolutionize Your Digital Experience with AskLand In the modern digital landscape, finding the right platform to share, discover, and manage your content effic…
ChatPDF: AI-Powered PDF Conversations
Chat with PDFs using AI.