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Further progress in AI may require learning algorithms to generate their own data rather than assimilate static datasets. A Perspective in this issue proposes that they could do so by interacting with other learning agents in a socially structured way.
AI-generated media are on the rise and are here to stay. Regulation is urgently needed, but in the meantime creators, users and content distributors need to pursue various ways, and adopt various tools, for responsible generation, sharing and detection of AI-generated content.
Advances in DNA nanoengineering promise the development of new computing devices within biological systems, with applications in nanoscale sensing, diagnostics and therapeutics.
Machine learning and quantum computing approaches are converging, fuelling considerable excitement over quantum devices and their capabilities. However, given the current hardware limitations, it is important to push the technology forward while being realistic about what quantum computers can do, now and in the near future.
The development of large language models is mainly a feat of engineering and so far has been largely disconnected from the field of linguistics. Exploring links between the two directions is reopening longstanding debates in the study of language.
Virtual worlds are typically encountered through simulated visual and auditory perceptions. Incorporating touch can create more immersive experiences with a sense of agency.
As many authors are experimenting with using large language models in writing articles, some guidelines are becoming clear, but these will need to evolve as the capabilities and integration of such tools develop further.
In the next phase of space exploration, human crews will be sent on missions beyond the low Earth orbit. Artificial intelligence (AI) is expected to play a main role in autonomous biomonitoring, research and Earth-independent healthcare.
A recent data competition steers clear from leaderboard chasing and promotes the use of a diverse range of metrics to develop rounded, practical algorithms.
