AI Workbench

Bitwisen.com

About this app

Bitwisen AI Workbench is a hands-on environment for learning, testing, and understanding artificial intelligence methods without setting up a Python environment or cloud notebook.

Explore six connected studios:
• Supervised Learning — regression and classification
• Unsupervised Learning — clustering and anomaly detection
• Semi-Supervised Learning — scarce-label classification
• Reinforcement Learning — planning and control in interactive environments
• Deep Learning Studio — neural-network architectures and training mechanics
• LLM Studio — tokenization, attention, local next-token generation, retrieval, and modern language-model workflows

The Workbench includes 70 classical and tabular algorithms, 20 bundled datasets, 10 reinforcement-learning environments, a transparent teaching transformer, tested examples, and run-specific Model Mechanics. Change parameters, train models, inspect metrics and visualizations, make predictions or replay policies, and save project or result files.

Designed for transparent learning:
• Numerical work runs locally in the application for the bundled models and examples.
• Model Mechanics explains the equations, settings, intermediate values, and limitations behind a run.
• Built-in examples make it easy to compare methods and see how choices affect results.
• Display preferences such as accent color, text size, spacing, contrast, and motion are saved automatically between launches.
• LLM Studio can optionally download browser-compatible pretrained model files when the user explicitly requests them; the bundled teaching model does not require that download.

Bitwisen AI Workbench is intended for education, transparent experimentation, and small-to-medium learning problems. It is not a substitute for production AI infrastructure, regulated analysis, clinical decision support, safety-critical control, or professional review.

Suggested category
Education

Developer / support email
[e-mail]

Suggested website
https://ai-engineer.org/workbench.html

Recommended privacy-policy URL after deployment
https://bitwisen.com/aiworkbench/privacy.html