Risks and mitigations for developing and deploying generative AI applications.
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This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
A platform for reproducible and scalable machine learning and deep learning on kubernetes.
Open-source tool to simplify the process of creating and managing LLM workflows and prompts as a self-hosted solution.
A Python library for secure and private Deep Learning built on PyTorch and TensorFlow.
Fast and simple framework for building and running distributed applications.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Refinder AI boosts productivity in Slack and Google Chat by automating tasks, managing apps, and providing instant access to knowledge.
An LLM-powered repository agent designed to assist developers and teams in generating documentation and understanding repositories quickly.
Open-source SDK for running LLMs and multimodal models on-device across iOS, Android, and cross-platform apps.
Simple and efficient library to minimize expensive and noisy black-box functions.
An open-source tool for recording screen and audio activity with AI-powered search, automations, and support for local LLMs. opensource.
Explore leaderboards with expert-driven LLM benchmarks and updated AI model rankings across coding, reasoning and more.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Free online machine learning calculators. Input your dataset and watch algorithms like K-Means, Minimax, and KNN get solved step-by-step for CS exams.
Synthetic tabular data generation using GANs, Diffusion Models, and LLMs with adversarial filtering and privacy metrics.
Suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.
Coding agents help developers plan, implement, review, test, and debug software. For independent capability comparisons, see SWE-bench and.
The @testdriverai in any GitHub repo and TestDriver writes UI tests and catches regressions before they merge. AI-powered end-to-end testing.
A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools.
The MIT AI Risk Initiative produces authoritative data and frameworks to help you identify, prioritize, and manage the risks from AI.
A comprehensive testing and evaluation framework for voice agents across language models, prompts, and agent personas.
Open source framework for debugging LLM agents and RAG pipelines with a 16-mode ProblemMap and practical triage checklists.