Science, Technology & Health: June 2010 Archives

Who doesn't love statistics? Ever hear of Benford's Law?

Benford's law, also called the first-digit law, states that in lists of numbers from many (but not all) real-life sources of data, the leading digit is distributed in a specific, non-uniform way. According to this law, the first digit is 1 almost one third of the time, and larger digits occur as the leading digit with lower and lower frequency, to the point where 9 as a first digit occurs less than one time in twenty. This distribution of first digits arises whenever a set of values has logarithms that are distributed uniformly, as is approximately the case with many measurements of real-world values.

One of many techniques for catching statistical cheats. Note to self: don't attempt to fabricate statistical data.

"SHR" outlines that we're now facing the worst case scenario in the Gulf. It's a slow-motion disaster that is only going to get worse over time.

All of these things lead to only one place, a fully wide open well bore directly to the oil deposit...after that, it goes into the realm of "the worst things you can think of" The well may come completely apart as the inner liners fail. There is still a very long drill string in the well, that could literally come flying out...as I said...all the worst things you can think of are a possibility, but the very least damaging outcome as bad as it is, is that we are stuck with a wide open gusher blowing out 150,000 barrels a day of raw oil or more. There isn't any "cap dome" or any other suck fixer device on earth that exists or could be built that will stop it from gushing out and doing more and more damage to the gulf. While at the same time also doing more damage to the well, making the chance of halting it with a kill from the bottom up less and less likely to work, which as it stands now?....is the only real chance we have left to stop it all.

It's a race now...a race to drill the relief wells and take our last chance at killing this monster before the whole weakened, wore out, blown out, leaking and failing system gives up it's last gasp in a horrific crescendo.

We are not even 2 months into it, barely half way by even optimistic estimates. The damage done by the leaked oil now is virtually immeasurable already and it will not get better, it can only get worse. No matter how much they can collect, there will still be thousands and thousands of gallons leaking out every minute, every hour of every day. We have 2 months left before the relief wells are even near in position and set up to take a kill shot and that is being optimistic as I said.

Over the next 2 months the mechanical situation also cannot improve, it can only get worse, getting better is an impossibility. While they may make some gains on collecting the leaked oil, the structural situation cannot heal itself. It will continue to erode and flow out more oil and eventually the inevitable collapse which cannot be stopped will happen. It is only a simple matter of who can "get there first"...us or the well.

We can only hope the race against that eventuality is one we can win, but my assessment I am sad to say is that we will not.

I haven't read of an optimistic scenario presented by anyone knowledgeable. Links welcome.

(HT: Wizbang and Instapundit.)

IBM's Watson artificial intelligence can answer questions posed in natural language.

For the last three years, I.B.M. scientists have been developing what they expect will be the world’s most advanced “question answering” machine, able to understand a question posed in everyday human elocution — “natural language,” as computer scientists call it — and respond with a precise, factual answer. In other words, it must do more than what search engines like Google and Bing do, which is merely point to a document where you might find the answer. It has to pluck out the correct answer itself. Technologists have long regarded this sort of artificial intelligence as a holy grail, because it would allow machines to converse more naturally with people, letting us ask questions instead of typing keywords. Software firms and university scientists have produced question-answering systems for years, but these have mostly been limited to simply phrased questions. Nobody ever tackled “Jeopardy!” because experts assumed that even for the latest artificial intelligence, the game was simply too hard: the clues are too puzzling and allusive, and the breadth of trivia is too wide.

With Watson, I.B.M. claims it has cracked the problem — and aims to prove as much on national TV. The producers of “Jeopardy!” have agreed to pit Watson against some of the game’s best former players as early as this fall. To test Watson’s capabilities against actual humans, I.B.M.’s scientists began holding live matches last winter. They mocked up a conference room to resemble the actual “Jeopardy!” set, including buzzers and stations for the human contestants, brought in former contestants from the show and even hired a host for the occasion: Todd Alan Crain, who plays a newscaster on the satirical Onion News Network.

You can play against Watson yourself if you want. I lost badly.

Read all about the Bathyscaphe Trieste, the only ship to ever dive to the bottom of the Mariana Trench.

For the past few decades artificial intelligence researchers have generally believed that connectionism was the key to building a generalized AI system. Short version of connectionism: symbolic thought is the emergent result of connections between billions of neurons, each of which individually plays only a small, distributed role.

It's pretty surprising that researchers seem to have found evidence that individual neurons can identify objects as dissimilar as sports cars and dogs because the predominant theories expect that such high-level symbolic recognition would be distributed across a large number of neurons, not concentrated in any recognizable location.

In previous studies, Earl K. Miller, Picower Professor of Neuroscience, found that individual neurons in monkeys' brains can become tuned to the concept of "cat" and others to the concept of "dog."

This time, Miller and colleagues Jason Cromer and Jefferson Roy recorded activity in the monkeys' brains as the animals switched back and forth between distinguishing cats vs. dogs and sports cars vs. sedans. Although they found individual neurons that were more attuned to car images and others to animal images, to their surprise, there were many neurons active in both categories. In fact, these "multitasking" neurons were best at making correct identifications in both categories.

Of course, there are still multiple neurons involved in any of these recognition problems, but it's still striking that such distinct localized behavior can be observed on single neurons.

The New York Times has an interesting article about how sequencing the human genome has led to very few cures.

Ten years after President Bill Clinton announced that the first draft of the human genome was complete, medicine has yet to see any large part of the promised benefits.

For biologists, the genome has yielded one insightful surprise after another. But the primary goal of the $3 billion Human Genome Project — to ferret out the genetic roots of common diseases like cancer and Alzheimer’s and then generate treatments — remains largely elusive. Indeed, after 10 years of effort, geneticists are almost back to square one in knowing where to look for the roots of common disease.

But what the Times and maybe many scientists fail to grasp -- and what Ray Kurzweil would be quick to point out -- is that genetic medicine is still on the flat part of the exponential growth curve. If you examine the green line on the chart below (which represents exponential growth) you will see that it begins very flat. This flatness is an illusion of scale, and as progress is made down the curve the slope steepens eventually and surpasses the linear and quadratic curves.

The benefits of technology follow an exponential curve. It is a mistake to judge the results of the Human Genome Project before we reach the elbow in the curve.

Additionally, I will add that what appears to have been quite a surprise to many medical researchers is no surprise to me at all.

It was far too expensive at that time to think of sequencing patients’ whole genomes. So the National Institutes of Health embraced the idea for a clever shortcut, that of looking just at sites on the genome where many people have a variant DNA unit. But that shortcut appears to have been less than successful.

The theory behind the shortcut was that since the major diseases are common, so too would be the genetic variants that caused them. Natural selection keeps the human genome free of variants that damage health before children are grown, the theory held, but fails against variants that strike later in life, allowing them to become quite common. In 2002 the National Institutes of Health started a $138 million project called the HapMap to catalog the common variants in European, East Asian and African genomes.

With the catalog in hand, the second stage was to see if any of the variants were more common in the patients with a given disease than in healthy people. These studies required large numbers of patients and cost several million dollars apiece. Nearly 400 of them had been completed by 2009. The upshot is that hundreds of common genetic variants have now been statistically linked with various diseases.

But with most diseases, the common variants have turned out to explain just a fraction of the genetic risk. It now seems more likely that each common disease is mostly caused by large numbers of rare variants, ones too rare to have been cataloged by the HapMap.

Old (Wrong) Theory: Most common diseases are caused by a few localized, common, genetic variants. Implication: the human genome is generally in a stable equilibrium that is occasionally disturbed by small numbers of large genetic failures.

New (Right?) Theory: Most common diseases are caused by a large number of small problematic genetic variants. Implication: the human genome is generally unstable and all these genes that we think aren't doing anything are actually quite important. Small variations in these "supporting" genes cause the unstable equilibrium to break down. Human life is like a water tower that collapses if you remove enough cross-beams, even if you don't touch the uprights.

It's no surprise to me at life is an unstable equilibrium, and the only reason I can think of for biologists to assume differently because the theory of evolution completely breaks down if genetic viability isn't inherently stable. (Or so it would seem to me.)

Here's a graph that illustrates how Obama's health care reform bill killed job growth before it even passed.

In case it isn't obvious at first glance, the chart shows that as soon as Obamacare was proposed at the end of October, 2009, companies immediately stopped hiring as many people and unemployment filings decreased at a much reduced rate.

I've been looking around but I can't seem to find an iPed for sale online. Apparently the iPad clone is selling for $105 in China and runs Google's Android OS. If anyone finds a source for these, please let me know.