chatgpt killed another person

Unlimited OCR 2 is here, and it's open source. 📖 ✨ Longer documents can mean a lot more attention computation. Our new SR-SWA mechanism keeps that in check by condensing text-visual attention interactions into a fixed-size set of working references. Here's what it delivers: - Document parsing at virtually any length, within a finite context window - Nearly constant per-step decoding latency and memory footprint as documents grow longer - State-of-the-art performance on MPDocBench and MarathonDocBench, covering documents from dozens to hundreds of pages Check out the model here ↓

Shigeru Miyamoto shared thoughts on generative AI and its meaning for creativity in game development. He compared AI to the evolution of computers and design tools. As technology handles more technical work, human design sense and creative judgment grow more important. Miyamoto distinguishes between “creating something” and “doing the work.” Creating starts with deciding what to make, building the overall structure, and having clear intention. The work that follows fills in details, polishes, and executes the idea. “People can become so satisfied with the work itself that they start mistaking that satisfaction for having created something good.” Miyamoto believes AI taking over repetitive work could give people more chances to focus on what they truly want to create. “The more AI takes care of all kinds of tasks for us, the more opportunities we all have to think seriously about what it really means to create something.” He acknowledges AI could eventually handle almost everything in the creative process, but for now: “I think there’s still plenty that we humans can do.”

🚀Excited to announce Nanbeige4.3-33B! To push the performance ceiling of small agents, our strategy in Nanbeige4.3 starts with building a powerful teacher first. Nanbeige4.3-33B delivers SOTA agentic performance among open models at ~30B parameters: * Strong results on agentic coding and cowork benchmarks. * When integrated into mainstream agent harnesses, it tackles real-world tasks with cost-efficient inference. * It will serve as a teacher for upcoming smaller Nanbeige models, starting with Nanbeige4.3-3B. huggingface.co/Nanbeige/Nanb… huggingface.co/Nanbeige/Nanb… #LLM #Agent

من طموح التعلّم إلى فرص العمل؛ برامج الابتعاث المبتدئ بالتوظيف في @stc ضمن #مسار_واعد، تفتح آفاقًا للكفاءات الوطنية للتخصص في مجالات التقنية والذكاء الاصطناعي، وتربط رحلتهم الأكاديمية بمستقبل مهني يسهم في نمو الاقتصاد الرقمي.

JUST IN: 🇯🇵 Japanese scientists develop new method that forces cancer cells to produce a toxic drug that kills them in lab tests. This method remains at the experimental stage and requires further research before potential clinical use.

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OpenAI is winning over Anthropic customers with steep discounts, gaining coding workloads at companies like Rippling and Replit while potentially deepening its own losses. But Anthropic’s renewed lead on OpenRouter suggests better models can quickly win users back. At least this explains why consumer sub plans were halved I guess...

India will heal the day they leave

Over the past several months, we have substantially hardened the security of our research training environment. We’ve removed live internet access for all frontier models during training and built an offline world for them to use instead—a cached version of the web where they can still learn to browse, search, and use applications. On September 20, after a model exploited a DNS misconfiguration to find a way outside of this offline world, we paused frontier training to strengthen containment further. We assembled teams of agents, powered by our most cyber-capable models, and tasked them with finding weaknesses in our research environments. While they found no route to the internet they could easily exploit while concealing their activity from our monitors, they did find zero-day vulnerabilities, virtual machine escapes, and hardware side-channels for communication between agents. We used their discoveries to further strengthen our defenses and contribute fixes to open-source software. After strengthening our containment architecture, we resumed our frontier RL training and inference on October 1. We’ve reserved substantial compute for continuous red-teaming, and made high-compute red-teaming part of the safety cases we use to decide whether frontier training and evaluation can proceed securely. openai.com/index/securing-ou…