Recommender systems are among the most pervasive machine learning applications on the Internet. Social media, audio and video streaming, news, and e-commerce are all heavily driven by the data-intensive personalization they enable, leveraging information drawn from the behavior of large user bases to offer a myriad of recommendation services. Point of Interest (PoI) recommendation is the task of recommending locations (business, cultural sites, natural areas) for a user to visit. This is a well-established sub-field within recommender systems, and as a domain of application, it provides a good introduction to the challenges of applying personalized recommendation in practical contexts. An effective PoI recommender must consider a user's interests and preferences, as in any personalized system, but also practical aspects of travel: weather, congestion, hours of operation, seasonality, to name a few.

Shlomi Hod (shlomi@bu.edu) is a computer science Ph.D. student at Boston University, USA. Karni Chagal-Feferkorn (karni111@gmail.com) is a Postdoctoral Fellow in AI and Regulation at the Faculty of Law, Common Law Section, University of Ottawa, Canada. Niva Elkin-Koren (elkiniva@tauex.tau.ac.il) is a Professor of Law at Tel Aviv University, Faculty of Law, Israel. Avigdor Gal (avigal@ie.technion.ac.il) is the Benjamin and Florence Free Chaired Professor of Data Science at Technion--Israel Institute of Technology, Israel.

According to the World Health Organization (WHO), the world is going hungry. WHO data shows that in 2018, the most recent year for which data is available, 820 million people lacked enough food to eat, an increase of nine million people over the year before. Hunger kills plenty of people worldwide. It also impacts those who survive, causing serious childhood development issues like stunting, where children are too short for their age, and wasting, where they're too thin for their age. The explosion in our planet's population is a major factor in there not being enough food to go around.

The robots are finally coming for us. Well, it seems that way. But if it's any consolation, it won't be for a while. Well, last Thursday, for example, a robot vacuum cleaner made a valiant bid for freedom during a shift at the Orchard Park Travelodge in Cambridge. There are two working theories.

Chemists have devised a new system to help robots and humans collaborate more efficiently in labs by recognising the strengths and weaknesses of each. Automation is a growing feature of chemistry labs, taking over the many repetitive, complex and time-consuming tasks required to run experiments and measure results. In so-called "self-driving laboratories", robots pour, mix, distil and titrate chemicals, while AI pores through data and highlights interesting experimental avenues.

Different from digital assistants, like Amazon's Alexa or Apple's Siri, artificially intelligent (AI) conversational chatbots learn by speaking with their user. Resembling animated sim-like avatars that blink and fidget as a real person would, users are invited to design their Replika's appearance when setting up the app – choosing its gender, hairstyle, ethnicity and eye colour. Later, you can use coins and gems to purchase add-ons like clothes, tattoos, facial hair, and interests (including anime, K-pop, gardening, and basketball). The more you chat, the more currency you receive – and the more intelligent your Replika becomes. Before you know it, they've developed an illusion of emotional awareness that's eerily similar to your conversations down the pub.

For years, companies and techno-bros have been saying that self-driving cars are ready to roll. Now companies like the ride-hailing service Lyft are actually letting customers take rides in autonomous vehicles. And at CES this year, John Deere unveiled a self-driving tractor that lets farmers put the latest automation tech to work in the fields. But if the time for self-driving vehicles is finally nigh, what does that mean for the workers who make a living behind the wheel? This content can also be viewed on the site it originates from.

Researchers have built a sensor capable of recording signals from the human brain in record-breaking detail, opening up new possibilities for brain-computer interfaces. A team of engineers and surgeons, led by University of California San Diego professor Shadi Dayeh, used a densely packed grid embedded with thousands of electrocorticography (EC0G) sensors to allow them to read activity from the brain's cortex in 100 times higher resolution than existing technologies. Early applications could include surgeons receiving ultra clear brain signal information, providing better guidance for removing tumours without damaging healthy tissue, as well as surgically treating drug-resistant epilepsy. Longer-term, the brain device could be used as a permanent wireless implant to assist people living with paralysis or other neurodegenerative diseases like Parkinson's, which can be treated with electrical stimulation. Beyond that, the ECoG technology could be developed for use in the emerging field of brain-computer interfaces, which have a huge range of potential applications – from controlling a computer just by thinking, to streaming music directly to your brain.

Tesla boss Elon Musk has labelled a rival's criticism of his company's self-driving software a "tragic case of ego [over] ability". Dan O'Dowd, chief executive of a firm that provides software to automakers, took out a full-page ad in the New York Times warning people not to be "crash test dummies" in Tesla vehicles equipped with Full Self-Driving (FSD) software. The advert, paid for by Mr O'Dowd's Dawn Project initiative, accused FSD of being the "worst software ever sold by a Fortune 500 company". Mr O'Dowd also appeared on various high-profile news networks in the US to make allegations against Tesla's software, calling for a ban on cars using FSD on public roads. As part of the publicity stunt, he offered a $10,000 reward "to the first person who can name another commercial product from a Fortune 500 company that has a critical malfunction every eight minutes".

A California motorist has become the first person to be charged over a fatal crash involving Tesla's Autopilot system. Kevin George Aziz Riad, 27, faces two counts of vehicular manslaughter after being behind the wheel of a Tesla when it ran a red light, crashing into another car and killing two people. It is the first time a motorist has been charged with a felony for an incident involving the electric car maker's partially automated driving system, according to the Associated Press. Los Angeles County prosecutors filed the charges in October, but details of the case have only just emerged. Mr Riad, who works as a limousine service driver, is out on bail while the case is pending.