An international team of scientists, including from the University of Cambridge, have launched a new research collaboration that will leverage the same technology behind ChatGPT to build an AI-powered tool for scientific discovery.
Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.
Researchers are developing a way to incorporate one of the most human of characteristics – uncertainty – into machine learning systems.
The team is exploring the capacity robots have to inspire self-reflection, and support the work of psychologists and clinicians.
Researchers have trained a robotic ‘chef’ to watch and learn from cooking videos, and recreate the dish itself.
Researchers have designed a low-cost, energy-efficient robotic hand that can grasp a range of objects – and not drop them – using just the movement of its wrist and the feeling in its ‘skin’.
A team of student entrepreneurs who see algae as a potential business solution for reducing methane emissions from landfill and waste-water sites won the 2023 Cambridge Zero Climate Challenge after a nail-biting competition.
Researchers have developed a machine learning algorithm that could help reduce charging times and prolong battery life in electric vehicles by predicting how different driving patterns affect battery performance, improving safety and reliability.
Researchers have designed a machine learning method that can predict the structure of new materials with five times the efficiency of the current standard, removing a key roadblock in developing advanced materials for applications such as energy storage and photovoltaics.
Meet Daniel Ives, co-founder of a Cambridge start-up with one big ambition: to put an end to ageing and the diseases that come with it.
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