Applying Deep Learning to Extreme Weather
Dan deftly moves us on to the main topic of this show, how researchers are using supercomputers to apply deep learning to extreme weather. A research team from Rice University utilized three supercomputers (TACC’s Stampede 2, Wrangler, and Pittsburg Supercomputing Center’s Bridges system) to see if data on heat waves and cold spells could be predicted by analysis of atmospheric circulation and prior surface temperature. The results of these tests indicated that this deep learning approach is more accurate at predicting extreme weather.In the call, we discuss the computational difficulty of weather forecasting and the use case that the Rice researchers are testing. This promising research can pay great dividends in terms of giving early warning to hazardous weather, saving crops and perhaps saving lives in the process. As promised in the podcast, here’s a link to the paper. We also have a short discussion of what motivates Dan to read a particular paper and what turns him off. Jessi’s main standard in papers is that it has to be able to be printed in black and white and remain legible and understandable. So if you want to attract Jessi’s attention for your paper, make sure your charts don’t use color.
Things You Think You Know, But Maybe Don't.
The question this week is why Cray computers were horseshoe shaped. One of the reasons was wire length and this shape puts the components closely together to reduce the length of the wires needed to connect them. It also gave them enough room for a person to get their hands inside to weave the wires. So the key was minimal, uniform, and accessible wire length. There are also a couple of other explanations, one is that it gave room for the liquid cooling pipes necessary to cool the box, another is that the system forms a capital “C” shape, which stands for, of course, Cray.Catch of the Week
Henry: is away this week. (We know some of you don't read this all and come straight here!)
Jessi: Tells us that the US might want to take a close look at Estonia as a model to overcome cybersecurity. The country has put together a civilian cybersecurity force and instituted mandatory cyber classes in schools. This is a response to massive cyberattacks launched against Estonia in 2007 that took down much of their digital infrastructure for weeks.
Shahin: Discusses how Justine Haupt came up with a way to keep her cell phone from distracting her – she built a rotary dial interface for it. Along with helping save her from using the most time-wasting features on her phone, it will also confound an entire generation of folks who have never seen a rotary phone dialer. Justine also is working in robotics and has a page of her inventions and thoughts.
Dan: Brings up a story about a man convicted of murder mainly on the basis of DNA evidence, although that evidence was shaky, mainly saying that they couldn’t exclude him. His case was reopened by the Innocence Project who reached out to a company called Cybergenetics for further analysis. Cybergenetics ran samples through their 170,000 line AI algorithm and found that there was zero chance that the convicted man’s DNA was present in the sample. So the man will be released, which is great. The problem is that the Cbyergenetics code is a black box and the company, citing competitive advantage, will not release the code. How should we deal with situations like this in the future?
Listen in to hear the full conversation
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