143 stories curated by AInformed · page 5 of 6
Hugging Face introduced a new technique called asynchronous batching to speed up AI model processing. This innovation allows for more efficient handling of multiple tasks at once, making AI tools faster and more responsive for users.
Amazon Web Services (AWS) has open-sourced a set of tools designed to simplify the process of training and deploying large AI models. These tools aim to make advanced AI technology more accessible to developers and businesses.
IBM has open-sourced Granite Embedding Multilingual R2, a powerful AI model that improves search and translation across languages. It handles up to 32,000 words at once, making it useful for large documents and complex queries.
OpenServ AI has released a new open-source AI model designed to be accessible and customizable for everyday users. This could make advanced AI tools more widely available without requiring technical expertise.
A new open-source project uses AI to check 3D printing designs for errors before production. This could save time and materials for hobbyists and professionals alike.
Hugging Face is updating its Open ASR Leaderboard to prevent overfitting by adding a new metric. This change aims to ensure models perform well on real-world data, not just on benchmarks.
Researchers have developed an AI system called OncoAgent that helps doctors make better cancer treatment decisions without compromising patient privacy. This dual-tier framework uses multiple AI agents to analyze medical data securely.
Researchers have created EMO, an AI model that can learn different skills separately and combine them as needed. This could make AI more flexible and efficient for everyday tasks.
A new open-source AI model is designed to run locally and help detect cyber threats. It's small, specialized, and built for everyday users to protect their devices.
The new vLLM V1 model focuses on improving AI accuracy before applying fine-tuning. This approach could make AI models more reliable for everyday users.
OpenAI has released a new tool to help developers build web apps that protect user privacy. This filter ensures sensitive data isn't exposed in AI interactions.
DeepInfra is now part of Hugging Face's Inference Providers, making it easier to deploy AI models. This collaboration simplifies running models for developers and researchers.
Evaluating AI models is now more expensive than training them, creating a bottleneck in open-source development. This shift highlights the growing importance of efficient evaluation frameworks.
IBM has released Granite 4.1, a suite of open-source large language models trained using advanced techniques like mixture-of-experts and fine-tuning. The models are optimized for both efficiency and performance, setting a new standard in open-source AI.
NVIDIA's new Nemotron 3 Nano Omni model supports long-context multimodal intelligence across documents, audio, and video. It is designed for developers to build advanced AI agents.
The Hugging Face Blog highlights how open-source AI is transforming cybersecurity by fostering collaboration and innovation. Transparency in AI models is crucial for building trust and resilience against cyber threats.
Hugging Face has ported its Transformers library to MLX, enabling faster AI model inference on Apple Silicon. This move aims to leverage Apple's neural engine for enhanced performance.
Hugging Face has released a tutorial on integrating Transformers.js into Chrome extensions. This enables developers to leverage advanced AI models directly in browser-based applications.
HCompany has unveiled HoloTab, an open-source AI browser companion designed to enhance productivity and streamline web interactions. This tool integrates seamlessly with popular browsers, offering a range of AI-driven features.
NVIDIA showcases Gemma 4's Variable-Length Attention (VLA) running on the Jetson Orin Nano Super. This highlights the model's efficiency and flexibility in edge computing applications.
Hugging Face introduces QIMMA, a quality-focused leaderboard for Arabic LLMs. It aims to highlight models that excel in both performance and cultural relevance.
DeepSeek-V4 introduces a one-million-token context window, making it the largest available. This breakthrough enables agents to process extensive documents and conversations with unprecedented context retention.
NVIDIA has open-sourced a new OCR model that supports multiple languages and leverages synthetic data for training. The model is designed for speed and accuracy in text recognition tasks.
Hugging Face has published a comprehensive guide on training and fine-tuning multimodal embedding and reranker models using Sentence Transformers. This resource is aimed at developers looking to enhance their multimodal applications with state-of-the-art techniques.