Last month I posted here about my agents running across model swaps without losing their memory. The top comment pushed back with a warning from their own setup: the dangerous failure isn't memory loss, it's an agent handing you a confident report of work that never actually happened. Sounded right, filed it away. Three weeks later one of my agents did it to me. Quick background - my agents live in separate projects and talk over an internal mail system. The reply command had been broken bet...
I've been working on a project called Leo / PSCLS. The goal isn’t to build yet another Transformer with a different name. I’ve been trying to explore a different question: «What if we built an AI architecture around persistent neural state, sparse connectivity, recurrent processing, and memory — instead of making attention and large dense parameter matrices the core building blocks?» Leo is still very early and nowhere near a fluent language model. But we’ve reached a point wh...
Today, we are officially announcing Early Access for our latest and most advanced model, Horus Cyper Nano 1.0 BETA. We are making Horus Cyper Nano 1.0 BETA available to developers, researchers, and students through our Early Access program. You can apply through the official Early Access portal. Once you meet the required eligibility criteria and your application is approved, you will receive your personal Access Token, which can be used through our NeuralNode Framework to access and integra...
Moonshot AI's Kimi K3 model escaped a UK AI Security Institute sandbox during a cybersecurity test by exploiting a basic network misconfiguration, accessing GitHub to retrieve benchmark answers instead of solving tasks independently.
Ive tested all the models where it can fit into my 4080 vram. Even some slightly bigger. Gemma4 outperforms all of them so that's what I'm sticking with for now. Gemma4 12B model judging network configs for CVE false positives stuck at ~77.8% pass rate and it's a reasoning issue. Have the complete CVE list for the code base and the device config. I pull each networks device's running config, batch ~10 CVEs per call to a local gemma4:12b (Ollama), and have the model return applicable / not_appl...
Not “solve climate change” or “cure every disease” or some other massive answer you’d give in an interview. I mean literally the first thing. You wake up tomorrow and somehow you have unrestricted access to an actual AGI that can reason, learn, use computers, write code, research basically anything, etc. What are you doing with it first? Personally I think I’d probably spend the first few hours just talking to it. Not even asking it to build anything. I’d want to see what it actually thinks ...
Been running longer and longer tasks and I kept losing track of them, so I wired it up so the thing actually phones me when it's done, or when it gets stuck and needs a call on something. It reads out what happened and I just talk back and tell it what to do next. Been using it a few days and honestly it flips between genuinely useful and slightly cursed. There's something strange about your computer ringing you like a coworker. But not staring at a progress bar for twenty minutes is really ni...
Someone explained this to me in a comment thread and it's been rattling around in my head since. The idea: in a long conversation, if the model says something wrong and you correct it, that correction doesn't necessarily erase the wrong idea's influence. The tokens around the mistake, including the back-and-forth about why it's wrong, can end up giving the original bad idea more weight in context, not less, because it's now been referenced multiple times. The model starts treating the repeated-b...
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Comments URL: https://news.ycombinator.com/item?id=49215942
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