Redact PII before your model searches the web
Build a loop where Rampart redacts personal details on your machine, Tabstack researches the redacted question, and your own model writes the reply. Four short Python files.
Tabstack Blog13 min read
ONNX Runtime
13 stories
Compressed a RoBERTa AI-text detector from ~500 MB to ~97 MB so it runs client-side in the browser, plus a 26 MB image detector [P]
I wanted an AI text and image detector that doesn't need you to upload anything, so I took two existing open detectors and got them running fully client-side with ONNX Runtime Web.
Reddit - r/ML2 min read
Local-First Semantic Search on Windows: Running SigLIP2 and DINOv3 with Tauri 2 and ONNX
I built PixaFind for the search you do when you remember a file's contents but have forgotten its name. You might remember a cat sitting in sunlight, a whiteboard from a meeting, or a paragraph about a budget. None of those memories give you a path to type into Explorer.
Dev.to AI10 min read
AI Resume Screeners Ignore Gender. They Don’t Ignore ChatGPT
Four AI screeners did not hire by gender on frozen resumes. They hired Gemini-written CVs at 98% and GPT-written CVs at 86%. Name-swap study. The post AI Resume Screeners Ignore Gender. They Don’t Ignore ChatGPT appeared first on i10X Blog.
i10x Blog13 min read
Build Local AI Apps with C++ and NVIDIA TensorRT RTX Samples
Adding AI models to local applications requires a portable model format, a reliable runtime, and acceleration that works across target systems. Do Inference Now...
NVIDIA Developer Blog3 min read
Setting up vector search for github starred repos
Ask the starred-repo corpus questions in natural language: embed the query on-device, rank the stored vectors, and show the matching repos in the TanStack Start UI. This is where the earlier chapters pay off.
Dev.to AI9 min read
Oxidizing Cross-Encoders
We rewrote cross-encoder inference in Rust, benchmarked it against Python, and on a small reranking model it came out only 1.1x faster at the median. That is not a sign of a slow Rust implementation.
Qdrant7 min readCrowdStrike Accelerates Real-Time Data Classification with On-Device AI
CrowdStrike worked closely with Intel to introduce a new capability in Falcon Data Security that classifies sensitive data using language models that run on-device using dedicated hardware for AI. Learn more!
CrowdStrike Charlotte AI Blog6 min read
Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Hugging Face Blog9 min read
FastEmbed: Qdrant's Efficient Python Library for Embedding Generation
Data Science and Machine Learning practitioners often find themselves navigating through a labyrinth of models, libraries, and frameworks. Which model to choose, what embedding size, and how to approach tokenizing, are just some questions you are faced with when starting your work.
Qdrant10 min read
Release v5.13.0
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release v5.13.0 · huggingface/transformers
Transformers19 min read
Running PII detection locally with the Rampart NER model
How Arcjet added an optional on-device model backend for sensitive information detection: a pluggable rule interface, deterministic recognizers for structured data, offset reconstruction for token-classification output, and local ONNX inference in the request path.
Arcjet Blog11 min read
Back to school: the best AI programming languages to learn first
AI isn’t a specialty anymore, it’s the foundation of modern software. In this guide, Ali breaks down the best programming languages for AI in 2025 and how your choice can make or break speed, workflow, and realworld result
Pieces Blog8 min read
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