A legally enforceable AI-user interaction framework that verifies informed consent through multimodal methods, protects user intellectual property via blockchain-based tracking, and ensures lifetime authorship rights with legal safeguards against unauthorized use or AI training reuse.

ADMIT is a research tool within a broader methodological framework combining quantitative and qualitative strategies to identify, analyse, and mitigate social implications associated with automated decision-making systems while enhancing their potential benefits. It supports comprehensive assessments of sociotechnical impacts to inform responsible design, deployment, and governance of automation technologies.

The Code sets out a process to identify, evaluate, and mitigate the known risks of AI to children and prepare for the known unknowns. It requires those who build and deploy AI systems to consider the foreseeable risks to children by design and default.

The GDA leverages aerial imagery, satellite data, and machine learning techniques to evaluate the damage in areas impacted by natural disasters. This tool greatly enhances the efficiency and precision of disaster response operations.

PetaBencana.id leverages AI to provide residents, government agencies, and first responders with a real-time disaster mapping platform for Indonesia.

Croissant is an open-source framework developed by MLCommons to standardise dataset descriptions, enhance data discoverability, and facilitate automated use across machine-learning tasks. Croissant ensures datasets are consistently documented by providing structured metadata schemas, improving interoperability, transparency, and ease of integration.

The Risk Management Profile for Artificial Intelligence and Human Rights serves as a practical guide for organisations—including governments, the private sector, and civil society—to design, develop, deploy, use, and govern AI in a manner consistent with respect for international human rights.

This document introduces the effects of population demographics on biometric functions.

YoloV3 Implemented in Tensorflow 2.0

Wild Me's first product, Wildbook supports researchers by allowing collaboration across the globe and automation of photo ID matching

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

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

Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀

🧙 A web app to generate template code for machine learning

Deep learning library featuring a higher-level API for TensorFlow.

Interpretability Methods for tf.keras models with Tensorflow 2.x

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

This internationally recognised AI Governance framework provides boards and senior leaders with signposts to high level areas of accountability through twelve principles which could be at the heart of any AI governance policy. It is for boards who wish to start their AI journey, or for those who recognise that AI governance is a key enabler for AI success.