This week's episode focuses on the interface between physics and computing, with deep dives into how artificial intelligence (AI) is contributing to medical physics and how silicon could form the basis of a future quantum computer. First, we hear from Tami Freeman, Physics World's resident expert on medical physics, about a new positron emission tomography (PET) scanner that can image a patient's whole body much more quickly (or at higher resolutions) than is possible with current commercial scanners. We then stick with the medical theme to discuss three recent examples of how AI is being used in medicine: firstly to diagnose skin conditions (but, disturbingly, only if the patient's skin is white); secondly to help radiologists detect lung tumours in X-rays; and thirdly to develop better radiotherapy treatment plans. There are several ways of constructing the qubits, or quantum bits, that make up a quantum computer, and this week we hear from a trio of researchers – Fernando Gonzalez-Zalba, Alessandro Rossi and Tsung-Yeh Yang – who have been developing silicon-based qubits. Their work is part of a Europe-wide collaboration between universities, government laboratories and companies called MOS-Quito, and you can read more about it in their article for the Physics World Focus on Computing.
Artificial intelligence (AI) bots are going to replace our jobs. AI machines will inevitably conspire to kill us all. These are exaggerated versions of three fears commonly associated artificial intelligence (AI). Even the late Stephen Hawking spoke about a potential future in which humans could be superseded by advanced forms of artificial intelligence. But these concerns are not so present in the mind of Nathan Myhrvold, the former chief technology officer at Microsoft who once worked in Hawking's theoretical physics group at the University of Cambridge.
The gems of every World Cup are the impossible goals. Benjamin Pavard bending a cross to pull France over Argentina in the group of 16. Takashi Inui sweeping in a perfectly spin-less goal to bring Japan up over Belgium, if only temporarily. Every spin of the ball moves air across the surface, pushing it into a bend. For a player at this level, bending the ball is an intuitive motion, just a kick to the edge of the ball to arc it in the right direction.
Artificial intelligence is already better than humans at video games, quiz shows and an ancient Chinese board game. Next up, the bots are coming for Jenga. In a newly-published paper, scientists from MIT describe how they taught a robot real-world physics and a practical sense of touch by unleashing it on the tricky tower-building game. Because unlike purely cognitive games that rely on visual cues, such as chess or Go, Jenga "requires mastery of physical skills such as probing, pushing, pulling, placing and aligning pieces," claims MIT's Prof Alberto Rodriguez. The robot (equipped with force sensors and cameras) immediately began prodding and poking the Jenga blocks using its two-pronged arm.