Search Results for "visualize"

openv0 is a generative UI component framework designed to help developers create interface elements using AI-assisted workflows. It enables users to generate, iterate, and refine UI components with a live preview system, making it easier to visualize results during development. openv0 is built around a modular architecture, allowing different parts of the generation process to be extended or replaced through plugins. A key aspect of openv0 is its multipass pipeline, where each stage of component generation operates independently, enabling more complex and flexible transformations. ...

While coding with AI assist, I noticed bigger projects need something more rigid as context so the AI coder doesn't stray away when I try to add new features. You know, to keeps its memory fresh and not change the stuff that already works. The trick is to ask the AI to write a diagram in Mermaid.js format that solidifies the structure of the project and then use that as context to keep the AI reminded at all times what the project is as a whole. This will prevent it from changing things...

...Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks.

...TensorSpace is a neural network 3D visualization framework designed for not only showing the basic model structure but also presenting the processes of internal feature abstractions, intermediate data manipulations and final inference generations. By applying TensorSpace API, it is more intuitive to visualize and understand any pre-trained models built by TensorFlow, Keras, TensorFlow.js, etc.

Bottery is a prototyping environment and mini-language for designing conversational agents as explicit state machines rather than opaque bundles of code. It encourages authors to model intents, dialog turns, and transitions in a compact, declarative form that’s easy to visualize and simulate. A built-in simulator lets you “play” the conversation, test edge cases, and tweak flows without wiring up back-end services first. Because behavior is defined in a DSL, teams can version the conversation design alongside code and keep product, research, and engineering aligned. The repo includes examples of slots, branching, and side effects, showing how to express common patterns like confirmations, fallbacks, and small talk. ...