Our editor rounds up the best presents you can play. I'll start with a caveat: the games in this guide are mostly screenless. Video games are a rich cultural medium, I'm told, but one in which I have zero expertise; for my twelve-year-old nephew, the main video gamer in my life, I usually just buy a Nintendo gift card and call it a day. The suggestions below focus, instead, on puzzle books, brainteasers, and the sort of party games that require no higher tech than a couple of AA batteries. Such analog games are staples of holiday gift-giving, and for good reason.

The game of Jenga represents an inspiring benchmark for developing innovative manipulation solutions for complex tasks. Indeed, it encouraged the study of novel robotics methods to successfully extract blocks from the tower. A Jenga game round undoubtedly embeds many traits of complex industrial or surgical manipulation tasks, requiring a multi-step strategy, the combination of visual and tactile data, and the highly precise motion of the robotic arm to perform a single block extraction. In this work, we propose a novel, cost-effective architecture for playing Jenga with e.Do, a 6-DOF anthropomorphic manipulator manufactured by Comau, a standard depth camera, and an inexpensive monodirectional force sensor. Our solution focuses on a visual-based control strategy to accurately align the end-effector with the desired block, enabling block extraction by pushing. To this aim, we train an instance segmentation deep learning model on a synthetic custom dataset to segment each piece of the Jenga tower, allowing visual tracking of the desired block's pose during the motion of the manipulator. We integrate the visual-based strategy with a 1D force sensor to detect whether the block can be safely removed by identifying a force threshold value. Our experimentation shows that our low-cost solution allows e.DO to precisely reach removable blocks and perform up to 14 consecutive extractions in a row.

Welcome to Signals & Threads, in-depth conversations about every layer of the tech stack, from Jane Street. Today, I'm going to have a conversation with Andrey Mokhov about build systems. Build systems are an important but I think poorly understood and often unloved part of programming. Developers often end up with only a hazy understanding of what's going on with their build system learning just enough to figure out what arcane invocation they need to get the damn thing working and then stop thinking about it at that point, and that's a shame because build systems matter a lot to our experience as developers. A lot of what underlies a good developer experience really comes out of the build system that you use and also there's a lot of beautiful ideas and structure inside of build systems. Sadly, a lot of that beauty is obscured by a complex thicket of messy systems of different kinds and a complicated ecosystem of different build systems for different purposes, and I'm hoping that ...

For several decades, various types of artificial intelligence have been facing off with people in highly competitive games and then quickly destroying their human competition. AI long ago mastered chess, the Chinese board game Go and even the Rubik's cube, which it managed to solve in just 0.38 seconds. Now machines have a new game that will allow them to humiliate humans: Jenga, the popular game ---- and source of melodramatic 1980s commercials ---- in which players strategically remove pieces from an increasingly unstable tower of 54 blocks, placing each one on top until the entire structure collapses. A newly released video from MIT shows a robot developed by the school's engineers playing the game with surprising precision. The machine is quipped with a soft-pronged gripper, a force-sensing wrist cuff and an external camera, allowing the robot to perceive the tower's vulnerabilities the way a human might, according to Alberto Rodriguez, the Walter Henry Gale career development assistant professor in the Department of Mechanical Engineering at MIT. "Unlike in more purely cognitive tasks or games such as chess or Go, playing the game of Jenga also requires mastery of physical skills such as probing, pushing, pulling, placing, and aligning pieces," Rodriguez said in a statement released by the school.

Jenga is one of the most popular indoor games. The slow-moving game truly tests your patience and focus. Soon, humans will have to compete with robots in the game of Jenga. Researchers at MIT have developed a robotic arm that knows when to keep moving or switch to a new block without letting the tower fall. The arm is essentially a customised version of ABB IRB 120 robotic arm.

After strategy games such as chess and Go, robots are now also learning to play skill games. To tackle of the game Jenga, a tower of wooden blocks needs to be modified, provided scientists a robot arm with the sensitive touch sensors. "to conclude through buttons in the animal Kingdom is ubiquitous, but in the robot handling under-developed," write the researchers. This information conveyed by the tactile sense could be, in the industry. "In a production line for mobile phones come in almost every step of the impression of a snap closure or a screw with more power and touch than by sight," explains co-author Alberto Rodriguez.

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.

The humble game of Jenga has become the latest human pursuit to fall to machines, scientists have announced. In what marks significant progress for robotic manipulation of real-world objects, a Jenga-playing machine can learn the complex physics involved in withdrawing wooden blocks from a tower through physical trial and error. This differentiates it from robots that have mastered purely cognitive games such as chess and Go through visual cues. "Playing the game of Jenga also requires mastery of physical skills such as probing, pushing, pulling, placing and aligning pieces," said Prof Alberto Rodriguez from the department of mechanical engineering at Massachusetts Institute of Technology. Combining interactive perception and manipulation – whereby the robot would touch the tower to learn how and when to move blocks – is extremely difficult to simulate and therefore the robot has to learn in the real world, he added.

You probably remember the rules of Jenga: You tap at a wooden block in the tower, try to remove it, and then hopefully place the piece back on top of the increasingly unstable creation. The first person to knock the tower over loses. Jenga's physical nature makes it different from classic coffee table games like chess, or Go, which are contests at which artificial intelligence already excels. As complex as those games are, Jenga poses its own unique challenges for a robot. Mechanical engineers at the Massachusetts Institute of Technology have been working on a two-fingered bot that uses AI and sensors to figure out the physics of that game and play it.

Despite dazzling advances in AI, robots are still horribly ham-fisted. Increasingly, researchers and companies are turning to machine learning to make them more adaptive and dexterous. This typically means feeding the robot a video of what's in front of it and asking it to work out how it should move in order to manipulate that object. For instance, researchers at OpenAI, a nonprofit in San Francisco, taught a robotic hand to manipulate a child's block in this way. By signing up you agree to receive email newsletters and notifications from MIT Technology Review.