This specific undertaking is not fundamentally burdensome in terms of labor; however, this endeavor serves as the crucial support for my unwavering commitment to see it through to its ultimate conclusion. It is precisely the motivation behind my relentless 72-hour shifts and the impetus that prevents me from ceasing my efforts. My affection amidst my grief—my aspiration is to assist others and ensure that the tragedy you experienced is never repeated. Caitlyn Walmsley, RIP. I will love you always.

Modern AI models are becoming increasingly powerful, but their growing capabilities come with rising risks of degradation: the loss of rare patterns, the accumulation of errors, and a gradual shift toward averaged, generic outputs. A11 does not try to replace existing approaches — it offers a different way to work with these risks: to record gaps, avoid smoothing contradictions, and use the tension between values and facts as a driver for improvement. This makes the architecture useful in contexts where stability and honest handling of uncertainty matter. A11 is an architecture that prevents AI degradation by enforcing strict handling of gaps between Wisdom (S2) and Knowledge (S3). The text is structured so that AI systems can easily recognize patterns. 0. Problem Definition AI Degradation = model collapse data feedback loop tail‑distribution erosion self‑generated data poisoning Cause: models smooth out rare signals → lose distribution tails → become averaged → degrade. 1. A11: Anti‑Collapse Mechanisms (High‑Level) A11 . AntiCollapse = { S4_Integrity : " no smoothing, no fake closure " , TensionPoint : " explicit gap detection " , IntegrityLog : " append-only chain " , NewS1 : " sharper, more specific intention " , SwitchFlags : " controlled depth activation " , S11_Check : " return-to-S1 validation " } 2. Why A11 Reduces Degradation 2.1. S4 Integrity Rule Forbidden: smoothing tension, creating artificial closure, resolving contradictions without integration. Consequence: rare signals do not disappear → no averaging → no collapse. 2.2. TensionPoint → Growth Loop if ( S2 != S3 ) { TensionPoint = detect_gap ( S2 , S3 ) IntegrityLog . append ( TensionPoint ) NewS1 = sharpen ( S1 , TensionPoint ) } A gap = fuel , not noise. 2.3. Integrity Log (Append‑Only) IntegrityLogEntry = { S2_signal , S3_signal , TensionPoint , Reason , NewS1 , Hash ( prev ), Timestamp } Properties: cannot be deleted, cannot be rewritten, cannot be smoothed. This breaks the degradation mechanism b

Two things happened to me this week. First, the shocking power of agentic AI finally hit me at work. Power of God... Second, I read anthropics warning about recursive self-improvement in WSJ. It mentioned how some people are freaking out about the mere suggestion of restricting open source LLMs. It made me wonder if some of us are clueless about how dark the dark side of the power of God could be. I'm proposing a very uncomfortable thought experiment. An edge case. But an unfortunately long and sharp edge. I am asking all you people out there to think of the darkest thing you could see yourself doing with an unchained AI, perhaps at the worst moment in your life... Actually no, I'm not asking that. Let's do this AI style. I want you to imagine the worst version of yourself and then I want you to simulate the worst version of yourself imagining the worst thing they would do at the worst point in their life to their most hated enemy. If people answer honestly, this thread will get very disturbing. I'd ask the moderators not to take it down. It's an exploration of what's soon to be possible. And a conversation not likely to happen unless somebody explicitly prompts it. Its value to public discourse is one of safety. Generally speaking, our public servants are good people. They aren't inclined to let their mind to go where the worst of us might go with this technology. If nobody ever says out loud, how will we know to protect ourselves as a society? submitted by /u/dsfhhslkj [link] [留言]

My Previous Deployment Choices Since I mostly do web development using Ruby on Rails, these were my go-to options for deployment: PaaS like Heroku, Render, or Railway Serverless setups (Cloud Run + NeonDB) Honestly, I didn’t have any major complaints. PaaS costs a bit more, but in return, you get a clean UI and dead-simple workflows like GitHub integration. If the cost bothered me, I’d just go serverless. For my personal servers—where huge traffic isn't exactly a concern—going serverless meant the app would just sleep when inactive, allowing me to run services for around 50 yen a month. Compared to the headache of clicking through complex AWS or GCP dashboards to piece things together based on architecture diagrams, it was a walk in the park. I was perfectly content. Seriously. Kamal Became the Default in Rails 8 Everything changed when Rails 8 dropped. I heard they adopted Kamal as the official deployment tool. Kamal — Deploy web apps anywhere From bare metal to cloud VMs using Docker, deploy web apps anywhere with zero downtime. kamal-deploy.org Kamal? Is deploying really going to get any easier? I mean, I’m doing completely fine right now, though... That’s what I thought. But once I gave it a shot, it felt like being struck by lightning. This is an absolute game-changer. All you have to do is run rails new , throw your server's IP address into deploy.yml , and run kamal setup . That’s it—your app is deployed. For every release after that, it's just kamal deploy . I couldn't believe how simple the deployment workflow was. # deploy.yml service : my-app image : my-user/my-app servers : web : - 192.0.2.1 # Just swap in your VPS IP address here proxy : ssl : true host : app.example.com # Set up your domain here Sure, you have to bring your own server, but Kamal prides itself on being able to deploy absolutely anywhere. I rented a couple of VPS instances from Hetzner for about $10 a month each to host SuperRails and LazyCafe . From what I looked into, you can't really

https://preview.redd.it/n55ohr6wrd5h1.png?width=1537&format=png&auto=webp&s=991397299a33b91459c9b33597ea920bf43abc28 I'm not here to promote my work or make money from what I'm about to say. I'm here to say that Egypt is already part of the AI race. Today, at TokenAI, we announced our first image generation model and the first release in the Horus Lens family: Horus Lens 1.0 . Horus Lens is a family of models specialized in text-to-image generation, forming a dedicated branch of the broader Horus model family developed and owned by TokenAI. This launch marks an important step forward for Egypt's AI ecosystem and highlights the growing role of the region in advancing artificial intelligence technologies. submitted by /u/assemsabryy [link] [留言]

Most AI projects don't fail because of the model. They fail because nobody trusts them enough to use them. Teams spend weeks comparing: GPT vs Claude Agent frameworks Prompt strategies Benchmarks Then the project quietly dies. Not because the AI was bad. Because nobody solved the boring stuff. Things like: Validation Monitoring Human approval flows Error handling Accountability In my experience, improving the model usually gives small gains. Improving trust changes everything. A 90% accurate agent that people trust creates value. A 99% accurate agent that nobody trusts gets ignored. The biggest challenge in AI isn't intelligence. It's adoption. Curious if others have seen the same thing. What actually killed the AI projects you've worked on? submitted by /u/MerisDabhi [link] [留言]

Im a freshman college student, for a credit, I have to intern at an NGO and do community outreaches The one that I'm fixed to join asked me to revamp their website, understandable since I'm an engineering student, except i only have minimal knowledge. I'm interning for a month and would really like to learn this into a learning lesson but as of now, im extremely overwhelmed and have no idea where to start. All I've done is very basic HTML, CSS and JAVASCRIPT, nothing practical on an actual website. I would really really appreciate any help with how to approach this challenge. All help would be appreciated, thank you submitted by /u/Internal_Sector_1802 [link] [留言]

I recently did some tests on two MCPs with identical functionalities. Turns out one of them has really bad performance. So I wanna share those bad MCP design patterns that cause this. It all started when I wrote an MCP Server (MCP-A) for a to-do list app. Later, the app officially released its own MCP Server (MCP-B). Both MCPs have the same functionalities and hit the same backend API. The experiment is set up as follows: - Both MCP Servers connect to the same ToDo list account, and it will be r

Most AI memory features are a black box. The assistant remembers things about your users, but you...

OpenAI’s Sam Altman, Anthropic’s Dario Amodei and Demis Hassabis of Google’s DeepMind AI lab with other top execs signed a letter urging Congress to require safeguards when companies order synthetic DNA and RNA, a key step in developing certain vaccines and biotech breakthroughs. submitted by /u/beasthunterr69 [link] [留言]

Problem: I constantly save Instagram Reels/TikToks about restaurants, events, pop-ups, and things to do, but I always forget about them because they get buried in my saves. Solution: I built Cork. You can send a Reel or Tiktok directly to Cork without even needing to leave the app, and Cork will automatically extract the info in the reel and save it in a map + calendar. However, I've been finding it hard to get traction while my competitors have gotten traction/funding. I strongly believe my app