A robot made of Lego can quickly perform an important step for creating machines made of DNA. "This started as a final project in an undergraduate lab course," says Rizal Hariadi at Arizona State University, who tasked his class with building tools using "frugal science". The robot that one group of students built has proved particularly useful and resembles a single arm topped with a holder for cylindrical tubes. It performs a procedure to mix the liquid contents of the tubes, first tilting the tubes from vertical to horizontal, then rapidly spinning them around. This creates a single liquid with a density that uniformly decreases from the bottom to the top.

Machine learning provides powerful tools to researchers to identify and predict patterns and behaviors, as well as learn, optimize, and perform tasks. This ranges from applications like vision systems on autonomous vehicles or social robots to smart thermostats to wearable and mobile devices like smartwatches and apps that can monitor health changes. While these algorithms and their architectures are becoming more powerful and efficient, they typically require tremendous amounts of memory, computation, and data to train and make inferences. At the same time, researchers are working to reduce the size and complexity of the devices that these algorithms can run on, all the way down to a microcontroller unit (MCU) that's found in billions of internet-of-things (IoT) devices. An MCU is memory-limited minicomputer housed in compact integrated circuit that lacks an operating system and runs simple commands.

The new microbot inspired by starfish larva stirs up plastic beads. Among scientists, there is great interest in tiny machines that are set to revolutionise medicine. These microrobots, often only a fraction of the diameter of a hair, are made to swim through the body to deliver medication to specific areas and perform the smallest surgical procedures. The designs of these robots are often inspired by natural microorganisms such as bacteria or algae. Now, for the first time, a research group at ETH Zurich has developed a microrobot design inspired by starfish larva, which use ciliary bands on their surface to swim and feed.

One advantage that the IoT brought to design was the ability for a small local device to access the network's virtually-unlimited computing power. The Amazon Echo is a classic example: a low-cost local device that provided powerful speech recognition AI and an immense application library by way of its Internet connection. Now, some of that AI is moving into the local device to help minimize bandwidth and latency concerns by employing an efficient form of machine learning (ML) for smaller devices. An example of what can be accomplished by placing AI in edge devices can be found in the article AI helps turn gas sensor into electronic nose. In this instance the ML that generates the sensor's algorithms takes place during the design cycle, and the local device simply runs the algorithm.

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The 2016 Nobel Prize in chemistry has been awarded for the design and synthesis of the world's smallest machines. The work has overtones of science fiction, but holds huge promise in fields as diverse as medicine, materials and energy. This is especially true of efforts to develop nano-scale machines (1,000 times smaller than the width of a human hair), which are always destined to remain tiny however big our ambitions for them grow. It's difficult to trace the development of molecular machines to one person or scientific step. But a 1959 lecture by the celebrated physicist Richard Feynman is as good a point as any.