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…
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…
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…
# 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…
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…
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…
# 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…
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.…
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…
# 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…