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Datalab Releases lift: A 9B Open-Weights Vision Model That Extracts Structured JSON From PDFs Using Schemas

AI NewsJune 25, 20263Views 0Likes 0Comments

Datalab has released lift, a 9B open-weights vision model for structured extraction. You pass it a JSON schema, and it returns a JSON object that matches. The model reads PDFs and images directly, then decodes against your schema. This is Datalab’s first model built purely for extraction. The team already ships open-source OCR tools: chandra,…

Introducing computer use in Gemini 3.5 Flash

OpenAIJune 25, 20263Views 0Likes 0Comments

Making computer use safe in 3.5 Flash To mitigate some of the prompt injection risks for agents operating in live environments, we use targeted adversarial training for computer use in Gemini 3.5 Flash. We’re also releasing two optional enterprise safeguard systems that enable enterprises to: Require explicit user confirmation for sensitive or irreversible actions. Automatically…

The Best EDB to PST Conversion

IoTJune 20, 20265Views 0Likes 0Comments

If you’ve ever faced the challenge of extracting Exchange mailboxes data from an offline EDB file, you know how painful the process can be. PowerShell cmdlets fail, native tools have limitations, and the risk of data loss is always looming. That’s exactly where Stellar Converter for EDB steps in and after testing it hands-on, I…

Loss Function Explained For Noobs (How Models Know They Are Wrong)

Data AnalyticsJune 20, 20264Views 0Likes 0Comments

# Introduction I know that when beginners start learning machine learning, things seem easy at first. You follow a tutorial that asks you to load a dataset, train a model, and then you see something like this: loss = "mse" or criterion = nn.CrossEntropyLoss(). And just like that, the tutorial starts talking about…

Introducing Gemma 4 12B

OpenAIJune 20, 20266Views 0Likes 0Comments

Today, we are introducing Gemma 4 12B, our latest model designed to bring agentic multimodal intelligence directly to laptops. Bridging the gap between our edge-friendly E4B and our more advanced 26B Mixture of Experts (MoE), Gemma 4 12B packages powerful capabilities inside a reduced memory footprint. It is also our first mid-sized model to feature…

Meet Qwen-RobotSuite: Three Embodied AI Models for VLA Manipulation, Video World Modeling, and Navigation

RoboticsJune 20, 20265Views 0Likes 0Comments

The Qwen team has released three embodied AI models, grouped as Qwen-Robot-Suite. The three are Qwen-RobotManip, Qwen-RobotWorld, and Qwen-RobotNav. Each is built on a Qwen vision-language backbone and targets a different robotics problem. Qwen-RobotManip is a Vision-Language-Action model for manipulation, built on Qwen3.5-4B. Qwen-RobotWorld is a language-conditioned video world model with a 60-layer MMDiT and…

Building Time-Series Machine Learning Models with sktime in Python

Data AnalyticsJune 15, 202616Views 0Likes 0Comments

# Introduction If you work with sensor readings, server metrics, or any data that arrives over time, you already know that standard scikit-learn pipelines don't quite fit. Time series data has structure that tabular models ignore: seasonality, trend, temporal ordering, and the fact that future values depend on past ones. sktime is a…

Zyphra Release Zamba2-VL: Hybrid Mamba2–Transformer Vision-Language Models That Cut Time-to-First-Token by About an Order of Magnitude

AI NewsJune 15, 202613Views 0Likes 0Comments

Zyphra has released Zamba2-VL, a family of open vision-language models. The release covers three sizes: 1.2B, 2.7B, and 7B parameters. Each model is built on the Zamba2 hybrid SSM–Transformer backbone. Vision-language models (VLMs) read images and text together. They answer questions about charts, documents, and photos. Most open VLMs use a dense Transformer as…

Gemini 3.5 Live Translate is here

OpenAIJune 15, 20267Views 0Likes 0Comments

Twenty years ago, translation at Google began as one of our pioneering machine learning experiments to turn the science of language into the magic of human connection. That experiment has come a long way with over a trillion words being translated for billions of users across our products every month. Today, we’re taking our next…

Local Agentic Programming on the Cheap: Claude Code + Ollama + Gemma4

Data AnalyticsJune 10, 20269Views 0Likes 0Comments

# Introduction Visualize this: a multi-agent workflow that reads files, writes patches, runs tests, and iterates across four services, making 400 API calls in a single afternoon. The notification arrives. You have crossed the soft limit again. Every token costs money, every prompt sends your proprietary code to a third-party server, and the…