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

Origin

Scope

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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

TechnicalUnited StatesUploaded on Apr 22, 2024
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

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

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


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

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


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.

TechnicalEducationalUploaded on Apr 25, 2024
The AI Incident Database is a free and open-source project dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment of artificial intelligence systems.

Objective(s)

Related lifecycle stage(s)

Operate & monitor

TechnicalProceduralUnited StatesJapanUploaded on Apr 19, 2024
Diagnose bias in LLMs (Large Language Models) from various points of views, allowing users to choose the most appropriate LLM.

Related lifecycle stage(s)

Plan & design

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 18, 2024
Tool to scrape local business data from Google Maps

Objective(s)


TechnicalProceduralIsraelUploaded on Apr 11, 2024
Citrusx offers a multifaceted solution to connect all stakeholders in the company through an SDK, user-friendly UI, and automated reporting system.

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

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

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

TechnicalUnited StatesUploaded on Apr 2, 2024
Visual analysis and diagnostic tools to facilitate machine learning model selection.

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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.