AI tools for Data Scientists

Minutes, not hours

A training API that hands control of model fine-tuning to researchers while someone else deals with the servers and scaling headaches

GPU instances spin up in seconds with Medjed AI

Open Source GenAI powered tool

Data annotation costs serious money

Model evaluation meets active learning in Encord, a system built to guide AI applications from initial data work through production deployment

Vertex AI Model Garden is Google Cloud's catalog for finding, customizing and deploying machine learning models in one place.

ModelScope is an open-source model community and hosting hub founded in June 2022 by the Institute for Intelligent Computing together with the CCF Open Source Development Committee.

HuggingChat is the chat app from Hugging Face, powered by open source AI models.

LLaMA-Factory is an open-source framework for fine-tuning more than 100 large language models and vision-language models.

Lambda is a GPU cloud built for training and serving AI models.

Vast.ai is a GPU rental marketplace where developers and AI teams rent compute for training, fine-tuning, inference and rendering.

Axolotl is a free, open-source tool for fine-tuning large language models.

V7 Darwin is a data labeling and training data platform for machine learning teams.

pgvector is an open-source extension that adds vector similarity search to Postgres.

Scale AI supplies the data and evaluation services behind many of the world's leading AI models, and it also builds applied AI systems for enterprises and governments.

Surge AI positions itself as a source of human intelligence for training advanced AI.

Visual Studio Code is a free, open source code editor that runs on Windows, macOS and Linux and now includes built-in AI agents.

Text Analytics for Health is a capability within Microsoft's Azure Language service that reads unstructured medical text and labels the clinical information in it.

European AI with open-source roots

Framework for building with large language models

Open-source models without infrastructure

Production AI infrastructure

Cheap AI inference