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At the heart of almost every sufficiently massive galaxy there is a black hole whose gravitational field, although very intense, affects only a small region around the center of the galaxy. Even though these objects are thousands of millions of times smaller than their host galaxies, our current view is that the Universe can be understood only if the evolution of galaxies is regulated by the activity of these black holes, because without them the observed properties of the galaxies cannot be explained.

Theoretical predictions suggest that as these black holes grow they generate sufficient energy to heat up and drive out the gas within to great distances. Observing and describing the mechanism by which this energy interacts with galaxies and modifies their is therefore a basic question in present day Astrophysics.

In recent years, roboticists have developed a wide variety of robots with human-like capabilities. This includes robots with bodies that structurally resemble those of humans, also known as humanoid robots.

Testing the performance of can sometimes be challenging, as there are numerous measures to consider when trying to determine their applicability in real-world scenarios. Two features that are particularly important for robots are posture control and , as these robot’s body structures can sometimes make them prone to falling or stumbling, especially in complex environments.

China’s going all in on deep learning. The Beijing Academy of Artificial Intelligence (BAAI) recently released details concerning its “Wu Dao” AI system – and there’s a lot to unpack here.

Up front: Wu Dao is a multi-modal AI system. That means it can do a bunch of different things. It can generate text, audio, and images, and, according to Engadget, it can even “power virtual idols.”

Google has helped create the most detailed map yet of the connections within the human brain. It reveals a staggering amount of detail, including patterns of connections between neurons, as well as what may be a new kind of neuron.

The brain map, which is freely available online, includes 50000 cells, all rendered in three dimensions. They are joined together by hundreds of millions of spidery tendrils, forming 130 million connections called synapses. The data set measures 1.4 petabytes, roughly 700 times the storage capacity of an average modern computer.

Last month, self-driving technology company TuSimple shipped a truckload of watermelons across the state of Texas ten hours faster than normal. They did this by using their automated driving system for over 900 miles of the journey. The test drive was considered a success, and marked the beginning of a partnership between TuSimple and produce distributor Guimarra. This is one of the first such partnerships announced, but TuSimple may soon have some competition from another big player in the driverless vehicles game: Alphabet Inc. subsidiary Waymo.

Yesterday, Waymo announced a partnership with transportation logistics company JB Hunt to move cargo in automated trucks in Texas. The first route they’ll drive is between Houston and Fort Worth, which Waymo claims is “one of the most highly utilized freight corridors in the country.”

He’s got a point. There’s a lot more space in the sky than on the ground, obviously, but flight paths need to be carefully planned and contained within specific areas, particularly in and near big cities. If flying taxis became affordable enough for people to use them the way we use Uber and Lyft today, there would quickly be all sorts of issues with traffic and congestion, both in the sky and with takeoff and landing space on the ground. So why not take a scaled approach from the beginning?

While DNA provides the genetic recipe book for biological form and function, it is the job of the body’s proteins to carry out the complex commands dictated by DNA’s genetic code.

Stuart Lindsay, a researcher at the Biodesign Institute at ASU, has been at the forefront of efforts to improve rapid DNA sequencing and has more recently applied his talents to explore the much thornier problem of sequencing molecules, one molecule at a time.