Whilst recent times have seen tremendous progress, AI is still far from 'solved'. Machines have only a shallow understanding of the world around them and, to advance to the next stage, they need access to the vast knowledge that humans have about our physical world, culture and emotional behaviour.
To make a machine capable of operating in the world and interacting in a natural manner with us is an exciting grand challenge that will require a range of collaborative advances.
The Centre aims to make next-generation AI systems that have enhanced capabilities in Computer Vision, Natural Language Processing and Machine Reasoning and Machine Interaction.
To do this we bring world-leading research talent together and work on joint projects that drive progress. Beyond a pure engineering view, we take a principled approach to understanding how to efficiently train machines and interpret their capabilities and performance.
The Centre's approach to creating efficient, effective and responsible AI is inclusive, taking input from computer science, statistical learning theory, probabilistic modelling, engineering, cognitive neuroscience and the social sciences
Our research groups & networks
Natural Language Processing
The principal goal is to build machines that can read and "understand" unstructured textual information, converting it into interpretable structured knowledge to be leveraged by humans/other machines.
Computer Vision Group
Computer vision and image processing aim to extract useful information from images and movies.
Statistical Machine Learning group
This group focuses on data-efficient machine learning, probabilistic modelling, and autonomous decision making.
ELLIS @UCL
ELLIS is a European AI network of excellence comprising Units within 30 research institutions. It focuses on fundamental science, technical innovation and societal impact.
UCL Deciding, Acting, and Reasoning with Knowledge (DARK) Lab
(DARK) Lab is a Reinforcement Learning research group, focused on research in complex open-ended environments that provide a constant stream of novel observations without reliable reward functions.
Robot Perception and Learning Lab
RPL focuses on perception and learning for robotics, and in particular, on new estimation and planning algorithms for robots that locomote and manipulate in uncertain natural environments.
Web Intelligence
The WI group interests lie in the areas of information retrieval, data mining, and machine learning. The group also focus on user engagement, personalisation, inferring interests, and recommendations.
Contact us
Centre for Artificial Intelligence
Click to email. ai@cs.ucl.ac.uk
Claire Hudson
UKRI Centre for Doctoral Training in Foundational AI Manager
Click to email. claire.hudson@ucl.ac.ukMedia requests/enquiries: Please contact the UCL Media Relations Team, or find an expert on the UCL Experts Data.
