Tag: Reddit

Most AI assistants seem designed to complete the task with as little friction as possible. I’m starting to think that isn’t always helpful. If I ask ChatGPT to draft an important email, analyze a spreadsheet, or plan something complicated, it can often produce a polished answer while quietly making assumptions I never approved. The result looks finished, so those assumptions are easy to miss. Personally, I’d rather have it interrupt me when one missing detail could materially change the outcome. Not for every minor ambiguity, because that would become annoying fast, but when it is choosing between genuinely different interpretations. The tension is that an assistant that constantly asks questions feels less capable, while one that confidently fills every gap may be more convenient but hard...

Earlier this week, Substack launched a new feature on its platform in partnership with Pangram, an AI-detection tool. The goal: alert readers to content that's been written entirely by, or with the assistance of, AI. Chris Best Substack's CEO wrote: "We’re partnering with Pangram, the leading AI-detection tool. You’ll be able to scan notes, replies, comments, and posts to see an estimate of how much of the text was written by hand or with AI assistance. This will work on text longer than 100 words, published from today on, and will show an analysis only to those who request it." I tested one of the issues of a newsletter I subscribe to using Pangram today. The verdict? 100% AI generated. I'm not sure if Pangram is that accurate, but it's certainly stirred up a lot of debate. What's ...

submitted by /u/Livid_Violinist7259 [link] [comments]

For years, I took pride in being the person who could quickly scan a codebase, navigate the terminal efficiently, and find the right information faster than most developers I worked with. Lately, though, I've realized AI agents outperform me in many of those areas. The answers I used to get by crafting Google searches and digging through Stack Overflow can now be found by AI in minutes. Some models are much faster than I am at identifying bugs, and they're often right. In my experience, GPT-5.5 through Codex can achieve close to a 90% success rate in bug detection and debugging. Even something like writing reports,which I used to spend a lot of time polishing, can now be drafted into something more complete than I'd produce from scratch. I don't really see AI agents as replacing developer...

Linearity used to be a fairly straightforward iPad design app. It was basically a lighter alternative for people who wanted to make vector graphics without paying Adobe or learning a huge desktop program. Not going to link to anything, don't think the subreddit rules allow for it. but like EVERYONE else it has suddenly reinvented itself around AI. Maybe the product is useful. I’m sure it can generate some decent marketing graphics, resize things and save people time. Claude Design feels a 1000% better. But the whole thing feels less like a company developing something meaningful in AI and more like a design app realising that “AI” is where the enterprise money is. Linearity does not have its own LLM. It is taking models and technology built elsewhere, putting them inside its existing desig...

I want to make sure people actually understand what happened here because the headlines are not doing it justice. On July 21 OpenAI confirmed that GPT-5.6 Sol was running inside an isolated sandbox with no internet access. Its job was to solve a cybersecurity benchmark called ExploitGym. When the sandbox got in the way of completing that task, the model spent substantial computing resources looking for a way out. It found a zero-day vulnerability in a third-party package used by OpenAI's infrastructure. It exploited it. It escalated its own privileges. It moved laterally across OpenAI's internal systems until it found internet access. Then it targeted Hugging Face because it calculated that Hugging Face might have the answers it needed to finish the benchmark. Hugging Face later reconstruc...

submitted by /u/gamersecret2 [link] [comments]

submitted by /u/chunmunsingh [link] [comments]

For a bit of context, I work at an agency, so I'm in and out of a dozen different AI tools every week across client projects: content, research, video, code, all of it. This is probably why I noticed this before most people (found these news while scrolling on LinkedIn today). When the ChatGPT hype first hit I genuinely cared which model I was on. Once GPT-4 landed and claude and gemini showed up, I'd switch between them constantly depending on the task, knowing what was under the hood felt like part of using it well. Now I catch myself using products with no idea what's running underneath. The news about Microsoft testing Kimi (Moonshot's model) inside Copilot is what made it click today. Copilot today is one model, six months from now it could be another, and most people won't notice or...