Archive for December 4th, 2011
It suddenly occurred to me why cats instantly learn that food is associated with a particular sound—a can opening (and soon the sound of the drawer holding the can opener), a rustle of a kitty-food bag or kitty-treat bag, whatever: they hear the sound, get the food, and by God they know that link, right now.
It’s because cats hunt by hearing: sound is their primary tool in finding food. It’s a very natural and easy link for them to make because they’re primed for it: hear the rustle of a leaf, pounce on it, and lunch—and forever after know that sound means a possible lunch.
I like the part of Sunday when all the chores are done and the rest of the day is mine to have. Since I have only two Sunday chores normally (count out meds and bring up recycling bins), it is generally easy to work them in, but OTOH, I find both sort of boring so I postpone them (always) until after lunch, and then the afternoon starts to slip away. But today, I had them done by 2:00, so lots of time for reading and relaxation.
Hoping you are the same.
20 quadrillion floating-point operations per second: now that’s computing power. The Sister passes along this story by Dan Lyons in the Daily Beast on China’s breaking into the top supercomputing ranks:
Lawrence Livermore National Laboratory is one of the great symbols of America’s scientific and military prowess. For six decades, here on this tranquil campus tucked away in the hill country east of San Francisco, where scientists stroll along leafy paths and zip to meetings on bicycles, huge breakthroughs have been made, like the discovery of a half-dozen elements on the periodic table and the detection of a key component of dark matter.
Livermore’s biggest claim to fame involves designing the world’s most advanced nuclear warheads—this was the mission of the lab when it was created in 1952 by Edward Teller, father of the hydrogen bomb. To do this, Livermore relies on powerful machines called supercomputers, which hum away inside top-secret, heavily guarded buildings. The U.S. has long dominated the industry. Which is what made the news that Bruce Goodwin, head of the lab’s weapons program, received last November all the more momentous: the Chinese had unveiled the world’s most powerful supercomputer, a machine five times more powerful than Livermore’s biggest computer.
To most of us, this might sound like no big deal, akin to Apple coming out with a faster smartphone than Microsoft. But to the scientists, industry titans, and world leaders who understand how delicate America’s position as a global superpower really is, this was a Sputnik moment. Only this time, it wasn’t Russia trouncing the U.S. in the space race, but China surging ahead in one of the most vital areas of national security. By running thousands of processors in parallel, supercomputers not only help design weapons systems, they also model climate change, crack codes, and help develop new and life-changing drugs. Cranking out 500 trillion operations per second, just one of Livermore’s supercomputers throws off so much heat that if the air-conditioning system were to fail, the computer would start to melt within minutes.
Globally, high-performance computing is a $25.6 billion industry, and whoever holds the lead in the field gains huge economic and military advantages. Or put another way, if the U.S. falls behind in supercomputing it could quickly lose its edge in all areas of science, in industries like oil and gas exploration and pharmaceutical research, and in security and military fields. In the race to develop the most powerful computers, both our economic prosperity and our national security are on the line.
When China flipped the switch on the Tianhe-1A, also called the “Milky Way” supercomputer, last fall, it placed itself at the top of the technology world with a stunning demonstration of its newfound engineering prowess. The Chinese grip on the top spot turned out to be short-lived, since six months later, a team in Japan announced an even bigger supercomputer that bumped Tianhe-1A into second place. Nevertheless, . . .
Continue reading. I do wonde how computer-assisted software development (or even computer-directed software development) is progressing.
The US government seems to be a prime enabler to the big drug gangs. The CIA’s involvement in the narcotics underworld during the Vietnam war continues to be rumored, and we know that the BATF send thousands of firearms to Mexican drug cartels, with deadly effective. Though some US officers were killed, none were punished. And now we read about the DEA laundering drug profits for the cartels. (The DEA is the same agency that opposes legal and constructive approaches to drug control, which would undermine the DEA’s size, power, and authority: keep all drugs illegal, and the DEA will always have plenty of money and plenty of work.)
And, of course, the FBI seems to be the go-to agency for initial help in getting a terrorist operation underway—indeed, the FBI seems to take the initiative in that sort of thing fairly often.
As I’ve mentioned, I tend to work in cycles: I have studied Esperanto intensively, for example, 4 or 5 different times, each time learning more and going further, then drifting away and putting it aside. I’ve learned to save the project materials for those kinds of things, because I’m pretty sure the interest will in time revive.
Other such interests: Go, chess (though I believe I’ve permanently abandoned that), letterwriting (pens, papers, and inks), and so on. One reading project is to read one excellent biography of each US president in order of their time in office, the idea being that the time-span overlap of the various biographies will give me multiple takes on significant events and developments, which should reinforce the learning as well as provide diverse perspectives. (I’ll worry about Grover Cleveland if I ever get that far.)
And, of course, there’s the Shakespeare project: to read and ponder the works of The Bard, whoever s/he was. This article makes me think it’s time to get back to that one.
I blogged earlier on the development of increasingly sophisticated pattern recognition and data-linking software as businesses and government agencies begin to dig through the enormous store of on-line information and the continuing flow of on-line activity (that is, looking at the information from the perspective both of content and of links).
I just posted an update:
Three things I noted: First, the articles make no mention of what is undoubtedly heavy government involvement (think DHS and NSA) in the entire enterprise: finding and grooming and recruiting talent, and developing applications to trawl big data looking for patterns.
Second, I would think it would be effective to use big data to find the people who can more effectively use big data: with school records, test scores, social networks, Amazon purchase history, movie-viewing history, and so on now available on-line (with a certain amount of hacking), finding people who can better find more people would be a logical direction of development.
Third, I find it interesting that the volume of digital data is driving development: new things and approaches being developed simply because the data are there.