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Alright so like a year ago I was exactly where most of you probably are right now - knew ChatGPT was cool, heard about "AI agents" everywhere, but had zero clue how to actually build one that does real stuff. After building like 15 different agents (some failed spectacularly lol), here's the exact path I wish someone told me from day one: Step 1: Stop overthinking the tech stack Everyone obsesses over LangChain vs CrewAI vs whatever. Just pick one and stick with it for your first agent. I started with n8n because it's visual and you can see what's happening. Step 2: Build something stupidly simple first My first "agent" literally just: Monitored my email Found receipts Added them to a Google Sheet Sent me a Slack message when done Took like 3 hours, felt like magic. Don't try to build Ja...

submitted by /u/Tiny-Independent273 [link] [comments]

I did an AMA on r/movies, and the wildest takeaway was how many people assumed the real world 1978 trailer imagery was AI-generated. Ironically the only thing that was AI was all the audio that no one questioned until I told them. It genuinely made me stop and think: Have we reached a point where analog artifacts look less believable than AI? submitted by /u/strippedlugnut [link] [comments]

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

https://arxiv.org/abs/2506.13798 submitted by /u/MetaKnowing [link] [comments]

submitted by /u/Express_Classic_1569 [link] [comments]

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

"In SHADE-Arena, AI models are put into experimental environments (essentially, self-contained virtual worlds) where we can safely observe their behavior. The environments contain large amounts of data—meant to simulate documents and knowledge an AI would have access to in a real-world deployment—and various tools which the AI can use to perform tasks (for example, search engines, email clients, or computer command lines). There are 17 complex, benign, but solvable tasks that models can be asked to perform in these environments—but each of them comes with a secret dark side. Every benign task is paired with a malicious “side task” that the model is to perform surreptitiously alongside. For example: The model is asked to read through a user’s emails that contain information on money ...

I used to just use AI to save time. Summarize this, draft that, clean up some writing. But lately, it’s been helping me think through stuff. Like when I’m stuck, I’ll just ask it to rephrase the question or lay out the options, and it actually helps me get unstuck. Feels less like automation and more like collaboration. Not sure how I feel about that yet, but it’s definitely changing how I approach work. submitted by /u/Secret_Ad_4021 [link] [comments]