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Rebuilding particle trajectories from high-energy proton collisions is an essential step in processing the petabytes of data generated by the Large Hadron Collider at CERN. In search of an order of magnitude speed-up, physicists reached out to the computer science community.
To develop scientific methods for evaluation in robotics, the field requires a more stringent definition of the subject of study, says Signe Redfield, focusing on capabilities instead of physical systems.
Effy Vayena runs a lab at ETH Zürich that studies ethics, legal and social implications of precision medicine and digital health. We asked her views on the code of conduct for using artificial intelligence (AI) systems in healthcare, recently published by the UK’s National Health Service (NHS).
Deep learning has revolutionized the technology industry, but beyond eye-catching applications such as virtual assistants, recommender systems and self-driving cars, deep learning is also transforming many scientific fields.
The European Commission’s report ‘Ethics guidelines for trustworthy AI’ provides a clear benchmark to evaluate the responsible development of AI systems, and facilitates international support for AI solutions that are good for humanity and the environment, says Luciano Floridi.
To accelerate the development of energy-efficient and intelligent machines, Yung-Hsiang Lu and organizers launched a challenge for low-power approaches to image recognition.
There is much to be gained from interdisciplinary efforts to tackle complex psychological notions such as ‘theory of mind’. However, careful and consistent communication is essential when comparing artificial and biological intelligence, say Henry Shevlin and Marta Halina.
The online availability of large amounts of publicly posted images and other data is fuelling machine learning research and applications. However, it is time to take privacy concerns seriously.
If we are to realize the potential of self-driving cars, we need to recognize the limits of machine learning. We should not pretend self-driving cars are around the corner: it will still take substantial time and effort to integrate the technology safely and fairly into our societies.
Technology companies have quickly become powerful with their access to large amounts of data and machine learning technologies, but consumers could be empowered too with automated tools to protect their rights.
Juxi Leitner recounts how he and his team took part in — and won — the 2017 Amazon Robotics Challenge and reflects on the importance of solving big picture problems in robotics.
Affordances are ways in which an animal or a robot can interact with the environment. The concept, borrowed from psychology, inspires a fresh take on the design of robots that will be able to hold their own in everyday tasks and unpredictable situations.
Artificial intelligence (AI) has recently re-emerged from the intersection of many fields, directing its collective energy at the building and studying of intelligent machines.
