Evaluating massive language fashions (LLMs) is each scientifically and economically pricey. As the sphere races towards ever-larger fashions, the methodology for evaluating and evaluating them turns into more and more crucial—not only for benchmark scores, however for knowledgeable improvement selections. Latest analysis from the Allen Institute for Synthetic Intelligence (Ai2) introduces a strong framework centered…
On this tutorial, we implement a totally useful Ollama atmosphere inside Google Colab to duplicate a self-hosted LLM workflow. We start by putting in Ollama immediately on the Colab VM utilizing the official Linux installer after which launch the Ollama server within the background to show the HTTP API on localhost:11434. After verifying the service,…
In the domain of multimodal AI, instruction-based image editing models are transforming how users interact with visual content. Just released in August 2025 by Alibaba’s Qwen Team, Qwen-Image-Edit builds on the 20B-parameter Qwen-Image foundation to deliver advanced editing capabilities. This model excels in semantic editing (e.g., style transfer and novel view synthesis) and appearance editing…
Artificial Intelligence (AI) has evolved rapidly—especially in how models are deployed and operated in real-world systems. The core function that connects model training to practical applications is “inference”. This article offers a technical deep dive into AI inference as of 2025, covering its distinction from training, latency challenges for modern models, and optimization strategies such…
Hugging Face has just released AI Sheets, a free, open-source, and local-first no-code tool designed to radically simplify dataset creation and enrichment with AI. AI Sheets aims to democratize access to AI-powered data handling by merging the intuitive spreadsheet interface with direct access to leading open-source Large Language Models (LLMs) like Qwen, Kimi, Llama 3,…
In this tutorial, we implement an advanced data pipeline using Dagster. We set up a custom CSV-based IOManager to persist assets, define partitioned daily data generation, and process synthetic sales data through cleaning, feature engineering, and model training. Along the way, we add a data-quality asset check to validate nulls, ranges, and categorical values, and…
dots.ocr is an open-source vision-language transformer model developed for multilingual document layout parsing and optical character recognition (OCR). It performs both layout detection and content recognition within a single architecture, supporting over 100 languages and a wide variety of structured and unstructured document types. Architecture Unified Model: dots.ocr combines layout detection and content recognition into…
Nvidia has taken a major leap in the development of multilingual speech AI, unveiling Granary, the largest open-source speech dataset for European languages, and two state-of-the-art models: Canary-1b-v2 and Parakeet-tdt-0.6b-v3. This release sets a new standard for accessible, high-quality resources in automatic speech recognition (ASR) and speech translation (AST), especially for underrepresented European languages. Granary:…
Large Language Models (LLMs) have revolutionized fields from natural language understanding to reasoning and code generation. However, pushing their reasoning ability to truly superhuman levels has been limited by the need for massive, high-quality, human-annotated datasets. A team of researchers from Tencent AI Seattle Lab, Washington University, the University of Maryland, and the University of…
Salesforce AI Research has unveiled Moirai 2.0, the latest advancement in the world of time series foundation models. Built atop a decoder-only transformer architecture, Moirai 2.0 sets a new bar for performance and efficiency, claiming the #1 spot on the GIFT-Eval benchmark-the gold standard for time-series forecasting model evaluation. Not only is it 44% faster…