NOVA: The Fabric of the Cosmos

NOVA's "The Fabric of the Cosmos" premieres tonight, November 2, at 9pm ET/PT on most PBS stations. Recommended for: families who aren't quite sure what relativity is, but want to find out.

Starting tonight, enjoy the four-hour series The Fabric of the Cosmos, based on physicist Brian Greene's breakthrough book. I've previewed the first episode of the show, and found it a worthy companion to the book, especially for those who aren't particularly up on physics in general: do you know what Einstein's theory of relativity really is? How about the Higgs Field (and that elusive Higgs boson) -- do you know what that actually is? How about dark energy, or the notion that the universe might be a holographic projection of a 2D version of itself? All of these are discussed in the first episode (airing tonight), which deals with the nature of "space" -- what is space, when you remove all the "stuff" (atoms and such), and how does it work? In a sense, the show is sort of "Physics for Dummies" in that it presents easily understandable metaphors for all of these questions (except the hologram thing, which still seems bonkers), and helps you to understand how physicists have thought about space over hundreds of years.

The only downside to the show is Brian Greene himself, as a host -- he doesn't quite have the spark of a Carl Sagan or a Neil deGrasse Tyson. He's good at explaining what he's talking about (and indeed he is accessible to a fault -- he often repeats simple concepts), but somehow the first hour seems a little flat -- at times I found myself wondering who the audience was supposed to be, because the show mixed extremely simple ideas (like "is space empty or not") with mind-blowingly complex ones (the universe is a hologram, projected from a 2D version of itself). In the middle there is a very easy-to-follow discussion of what Einstein really contributed to physics, and a good discussion of why space, time, and the speed of light are fundamentally kind of weird. The trick is, at times the material appears pointed at middle school students, at others it's very heady stuff.

Gather the Family Around

Because of this mixed-audience issue, I think this series makes sense for families. I can see some elementary school kids engaging with this material, though middle and high school ages seem more appropriate. There is nothing risque or dangerous in the material, and it's presented in a very friendly, engaging format. The production value is insanely high (lots of computer graphics and 3D modeling, even in static interview shots), which should make even the boring bits (or stuff that's over young kids' heads) fun to watch. And you might walk away saying, "Huh, I kinda actually do get why Einstein was a big deal." Seems worth your time, eh? Here's another video of Brian Greene introducing the series:

The first episode airs tonight, and subsequent episodes air weekly. There's more information on the Fabric of Cosmos website.

Blogger disclosure: I wasn't specially compensated to do this review. I'm a lifelong fan of NOVA, though!

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Land Cover CCI, ESA
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European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]


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