Author Simon Stålenhag has a new work out this month. December is traditionally a quieter month for new releases from publishers and that's definitely true this year, with a sparser than usual science-fiction offering to chew over. That said, there are some intriguing titles out this month, and I'm looking forward to the new book from artist and author Simon Stålenhag, another illustrated dystopia, as well as a mysterious-sounding Russian novel, and the conclusion of Bethany Jacobs's excellent space opera trilogy. Jacobs has written a piece for the New Scientist Book Club about how the late Iain M. Banks inspired her own world-building. The Book Club is currently reading Banks's classic Culture novel - do join us .

When fed a sufficient amount of training data, artificial intelligence techniques can be used to generate new ideas in several different ways. Is that creativity?

Researchers make progress toward groups of robots that could build almost anything, including buildings, vehicles, and even bigger robots. Researchers at MIT have made significant steps toward creating robots that could practically and economically assemble nearly anything, including things much larger than themselves, from vehicles to buildings to larger robots. The new work, from MIT's Center for Bits and Atoms (CBA), builds on years of research, including recent studies demonstrating that objects such as a deformable airplane wing and a functional racing car could be assembled from tiny identical lightweight pieces -- and that robotic devices could be built to carry out some of this assembly work. Now, the team has shown that both the assembler bots and the components of the structure being built can all be made of the same subunits, and the robots can move independently in large numbers to accomplish large-scale assemblies quickly. The new work is reported in the journal Nature Communications Engineering, in a paper by CBA doctoral student Amira Abdel-Rahman, Professor and CBA Director Neil Gershenfeld, and three others.

The researchers accurately reconstructed the behavior of quantum systems using neural networks and "ghost" electrons. Physicists are (temporarily) augmenting reality in order to crack the code of quantum systems. Calculating the collective behavior of a molecule's electrons is necessary to predict a material's properties. Such predictions could one day help scientists create novel drugs or create materials with desirable qualities like superconductivity. The issue is that electrons may become'quantum mechanically' entangled with one another, which means they can no longer be treated individually.

"Much harder are tasks that require situational awareness, involving almost instantaneous adaptations to changing circumstances in the environment," explains Theodoros Stouraitis, a visiting scientist in the Interactive Robotics Group at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). "Things become even more complicated when a robot has to interact with a human and work together to safely and successfully complete a task," adds Shen Li, a Ph.D. candidate in the MIT Department of Aeronautics and Astronautics. In a new work, described in a paper that appears in an April 2022 issue of IEEE Robotics and Automation, Li, Stouraitis, Gienger, Vijayakumar, and Shah explain the headway they've made on a more demanding problem--robot-assisted dressing with sleeved clothes. While other researchers have made state estimation predictions of this sort, what distinguishes this new work is that the MIT investigators and their partners can set a clear upper limit on the uncertainty and guarantee that the elbow will be somewhere within a prescribed box. Such an algorithm could, for instance, guide a robot to recognize the intentions of its human partner as it works collaboratively to move blocks around in an orderly manner or set a dinner table.

Robots are already adept at certain things, such as lifting objects that are too heavy or cumbersome for people to manage. Another application they're well suited for is the precision assembly of items like watches that have large numbers of tiny parts--some so small they can barely be seen with the naked eye. "Much harder are tasks that require situational awareness, involving almost instantaneous adaptations to changing circumstances in the environment," explains Theodoros Stouraitis, a visiting scientist in the Interactive Robotics Group at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). "Things become even more complicated when a robot has to interact with a human and work together to safely and successfully complete a task," adds Shen Li, a Ph.D. candidate in the MIT Department of Aeronautics and Astronautics. Li and Stouraitis--along with Michael Gienger of the Honda Research Institute Europe, Professor Sethu Vijayakumar of the University of Edinburgh, and Professor Julie A. Shah of MIT, who directs the Interactive Robotics Group--have selected a problem that offers, quite literally, an armful of challenges: designing a robot that can help people get dressed. Last year, Li and Shah and two other MIT researchers completed a project involving robot-assisted dressing without sleeves.

Most of us have a music, movie or video-game library – possibly all three – but few have an art collection or even know what their favourite works of art are. Next year, that will change as art moves from the inaccessible to the everyday, thanks to AI. Art hasn't felt accessible to many for a long time. Our main experience of it involves visiting galleries and museums or feeling out our depth in art history classes. At a gallery, we spend a couple of hours looking at a lot of seemingly important pieces, but then we leave and the artworks stay where they are. They don't draw us in, like a favourite album, movie or video game, and we know we can't afford to take them home with us.

People tend to rejoice in the disclosure of a secret. Or, at the very least, media outlets have come to realize that news of "mysteries solved" and "hidden treasures revealed" generate traffic and clicks. So I'm never surprised when I see AI-assisted revelations about famous masters' works of art go viral. Over the past year alone, I've come across articles highlighting how artificial intelligence recovered a "secret" painting of a "lost lover" of Italian painter Modigliani, "brought to life" a "hidden Picasso nude", "resurrected" Austrian painter Gustav Klimt's destroyed works and "restored" portions of Rembrandt's 1642 painting "The Night Watch."The As an art historian, I've become increasingly concerned about the coverage and circulation of these projects.

People tend to rejoice in the disclosure of a secret. Or, at the very least, media outlets have come to realize that news of "mysteries solved" and "hidden treasures revealed" generate traffic and clicks. So I'm never surprised when I see AI-assisted revelations about famous masters' works of art go viral. Over the past year alone, I've come across articles highlighting how artificial intelligence recovered a "secret" painting of a "lost lover" of Italian painter Modigliani, "brought to life" a "hidden Picasso nude", "resurrected" Austrian painter Gustav Klimt's destroyed works and "restored" portions of Rembrandt's 1642 painting "The Night Watch." As an art historian, I've become increasingly concerned about the coverage and circulation of these projects.

Note to readers: Hello world is a program developers run to check if a newly installed programming language is working alright. Startups and tech companies are continuously launching new software to run the real world. This column will attempt to be the "Hello World" for the real world. At the Emami Art gallery, Harshit Agrawal, 29, will exhibit his work titled'EXO-Stential – AI Musings on the Posthuman.' At first look, you'd think the vivid imagery is solely the artist's imagination.