Latest Tools

5 live tools

Browser-native AI and machine learning tools

This tools library collects small, focused utilities for learning machine learning, reviewing text safety, and experimenting with AI media workflows. Each tool is designed to run from the browser with a clear task surface: upload or enter data, adjust the relevant controls, inspect the result, and use the explanation to decide what to do next.

Which tool should you open first?

Learn regression

Start with Linear Regression Lab for one input feature, move to Multiple Linear Regression Lab for several predictors, then use Logistic Regression Lab when the target is a yes/no class.

Review classroom text

Open Vulgarism Detector when you need a fast first-pass check of student answers, comments, discussion text, or moderation queues before a human makes the final decision.

Plan AI video runs

Use Video Generation Studio when you want one workspace for prompts, reference images, aspect ratios, durations, provider settings, and run history across supported video models.

What these tools are built for

The machine learning labs are useful for students, analysts, and builders who want to see how model settings affect predictions without setting up a notebook. The moderation tool is built for practical review workflows where privacy, regional context, and human judgment matter. The video studio is for creative and technical users who need a structured way to prepare generation requests and compare provider capabilities. None of these tools should replace expert review, but they can shorten the path from raw input to a clear next action.

Privacy, limits, and responsible use

Browser-native tools are convenient, but the right privacy model depends on the task. The regression labs are meant for sample or non-sensitive CSV data. Vulgarism Detector performs quick local review and should be treated as a decision aid, not an automatic discipline system. Video Generation Studio can store provider credentials in a local encrypted vault, so users should still follow provider billing rules, content policies, and organizational approval processes before running production work.