Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Type

Privacy & data governance

Clear all

Origin

Scope

SUBMIT A TOOL

If you have a tool that you think should be featured in the Catalogue of AI Tools & Metrics, we would love to hear from you!

SUBMIT
Objective Privacy & data governance

Uploaded on Apr 23, 2024
This Recommendation specifies use cases and requirements for multimedia communication enabled vehicle systems using artificial intelligence, including overview, use cases, high-layer architecture, service and network requirements, functional requirements, and non-functional requirements.

TechnicalUnited StatesUploaded on Apr 22, 2024
Data platform for LLMs - Load, index, retrieve and sync any unstructured data

Related lifecycle stage(s)

Build & interpret model

TechnicalUploaded on Apr 22, 2024
A flexible framework of neural networks for deep learning

Related lifecycle stage(s)

Build & interpret model

TechnicalUnited StatesUploaded on Apr 22, 2024
XLNet: Generalized Autoregressive Pretraining for Language Understanding

TechnicalUnited KingdomUploaded on Apr 22, 2024
Tutorials, assignments, and competitions for MIT Deep Learning related courses.

TechnicalFinlandUploaded on Apr 22, 2024
Jupyter notebooks for teaching/learning Python 3

Related lifecycle stage(s)

Build & interpret model

TechnicalUnited StatesUploaded on Apr 22, 2024
Turi Create simplifies the development of custom machine learning models.

TechnicalSpainUploaded on Apr 22, 2024
Classical equations and diagrams in machine learning

TechnicalGreeceUploaded on Apr 22, 2024
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

TechnicalUnited StatesUploaded on Apr 22, 2024
NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applications.

TechnicalUnited StatesUploaded on Apr 18, 2024
An end-to-end model risk management platform that automates model documentation and dramatically simplifies AI model validation.

TechnicalUploaded on Apr 2, 2024
A Python package for identifying 42 kinds of animals, training custom models, and estimating distance from camera trap videos

Related lifecycle stage(s)

Build & interpret model

TechnicalUnited StatesUploaded on Apr 2, 2024
Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle

Related lifecycle stage(s)

Build & interpret model

TechnicalUnited StatesUploaded on Apr 2, 2024
YoloV3 Implemented in Tensorflow 2.0

Related lifecycle stage(s)

Build & interpret model

TechnicalChinaUploaded on Apr 2, 2024
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

TechnicalUnited StatesUploaded on Apr 2, 2024
Wild Me's first product, Wildbook supports researchers by allowing collaboration across the globe and automation of photo ID matching

Related lifecycle stage(s)

Collect & process data

TechnicalIsraelUploaded on Apr 2, 2024
Explainability for Vision Transformers

Related lifecycle stage(s)

DeployPlan & design

TechnicalUploaded on Apr 2, 2024
The open big data serving engine. https://vespa.ai

TechnicalUnited StatesUploaded on Apr 2, 2024
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

TechnicalUploaded on Apr 2, 2024
trustworthy AI related projects

catalogue Logos

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.