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Fact-Check, Summarize, Explain Articles with Local AI Tool
Leveraging Local AI Tools for Fact Checking, Summarizing, and Explaining Articles In today's information saturated world, verifying the accuracy of information,…
Local-First AI Tool for Fast Image to Text Conversion
Revolutionize Your Workflow with the Local First AI Tool for Rapid Image to Text Conversion In the digital age, the ability to swiftly convert images to text is…
AI Tool Transcribes YouTube, TikTok, X, Instagram Videos with CPU Only
AI Tool Transcribes YouTube, TikTok, X, Instagram Videos with CPU Only In an era where video content dominates social media, the demand for efficient transcript…
Thinking Machines' Cheap-IM: AI Demo on a CPU Laptop
Exploring Thinking Machines' Cheap IM: AI on a CPU Laptop Thinking Machines has introduced Cheap IM, an innovative AI demo that showcases the impressive capabil…
Auto-Architecture: Karpathy's Loop Targets CPU Efficiency
Auto Architecture: Karpathy's Loop Targets CPU Efficiency Auto architecture, particularly in the context of Karpathy's Loop, represents an innovative approach t…
Arc Sentry: Advanced Prompt Injection Detector for LLMs
Been working on Arc Sentry, a whitebox prompt injection detector for self-hosted LLMs (Mistral, Llama, Qwen). Most detectors pattern-match on known attack phrases. Arc Sentry watches what the prompt does to the model’s internal representation instead, so it catches indirect, hypothetical, and roleplay-framed attacks that get through keyword filters. Benchmark on indirect/roleplay/technical prompts (40 OOD prompts): • Arc Sentry: Recall 0.80, F1 0.84 • OpenAI Moderation API: Recall 0.75, F1 0.86 • LlamaGuard 3 8B: Recall 0.55, F1 0.71 Arc Sentry has the highest recall — it catches more of the hard cases. Blocks before model.generate() is called. The lightweight pre-filter runs on CPU with no model access. pip install arc-sentry GitHub: https://github.com/9hannahnine-jpg/arc-sentry Happy to answer questions about how it works.