Daniel Lemire's blog

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Science and Technology links (July 21st, 2018)

  1. It seems that something called “Cartesian Genetic Programming” could be a match for Deep Learning.
  2. If you look at the best paid individuals in most fields, most of them are men. Why is that? There are many possible explanations. One of them is that men take more risks. If you hope to ever get larger rewards, it helps to take large risks.It is undeniable, I think, that boys take more physical risks than girls. But do men really take more risks than women in their careers?

Biologists tend to tell us that females are more risk adverse. The usual story is that a female’s ability to reproduce is mostly limited by the availability of food and shelter, whereas a male’s ability to reproduce has far more to do with its ability to impress females, or to impose its will. We can test it out by entering animals in games. For example, Orsini et al. investigated the issue in rats:

Consistent with findings in human subjects, females were more risk averse, choosing the large, risky reward significantly less than males. This effect was not due to differences in shock reactivity or body weight, and risk-taking in females was not modulated by estrous phase. Systemic amphetamine administration decreased risk-taking in both males and females; however, females exhibited greater sensitivity to amphetamine, suggesting that dopaminergic signaling may partially account for sex differences in risk-taking.

Social scientists have another, different take. For example, Nelson, an economist, finds the whole question metaphysical:

The statement “women are more risk averse than men” is fundamentally a metaphysical assertion about unobservable essences or characteristics, and therefore cannot be empirically proven or disproven. A review of the empirical literature, with attention paid to the misleading nature of generic beliefs and statements, the proper interpretation of statistical results, and the quantitative magnitudes of detectable differences and similarities, sheds doubt on whether statements such as these should have any place in an empirical science that aspires to objectivity. The widespread acceptance of such statements appears to perhaps be rooted more in confirmation bias than in reality.

  1. A honey bee has about one million neurons and a billion synapses. The best smartphones have many more transistors than honey bees have synapses.
  2. Do human beings have “general” intelligence? Kevin Kelly, a well-respected writer, does not think so:

We like to call our human intelligence general purpose, because compared with other kinds of minds we have met, it can solve more types of problems, but as we build more and more synthetic minds we’ll come to realize that human thinking is not general at all. It is only one species of thinking.

  1. Our cells are powered by mitochondria (tiny cells living inside our cells). If your mitochondria cease to function well enough, your cells are as good as dead. But could they be revived? It seems so, at least as far as the heart of babies is concerned: fresh mitochondria can revive flagging cells and enable them to quickly recover.
  2. Each time your cells divide, the end of your chromosomes (the telomeres) shortens. Thus a given human cell can only divide so many time. This sounds terrible, but it is less terrible because cells have ways to elongated their telomeres when needed (telomerase)… however, most cells will just divide a fixed number of times. At that point, the cell either dies (apoptosis) or, rarely, becomes senescent. However, the cells don’t literally run out of telomeres. So what happens? According to Ly et al. the problem is structural: the telomeres loop around, hiding the end of the chromosome. When the telomeres are too short to effectively hide the end of the chromosome, it is treated as defective by our biochemistry.
  3. Will we continue to get faster computers? Denning and Lewis think so:

These analyses show that the conditions exist at all three levels of the computing ecosystem to sustain exponential growth. They support the optimism of many engineers that many additional years of exponential growth are likely. Moore’s Law was sustained for five decades. Exponential growth is likely to be sustained for many more.

  1. There is a huge garbage patch in the Pacific ocean. It is huge: about the size of the state of Texas. A large fraction, nearly half of it, is made of fishing gear.
  2. We making progress against cancer, but it is not enough. In 2018, an estimated 1,735,350 new cases of cancer will be diagnosed in the United States and 609,640 people will die from the disease.
  3. Bill Gates wants to help diagnose Alzheimer’s early. It is believed that by the time you have symptoms of Alzheimer’s, you have already extensive damages. Many researchers believe it could be far easier to prevent these damages than to reverse them.
  4. It is believed that Alzheimer’s might be caused by protein aggregation in the brain. But it is not entirely clear how these proteins causes problems. New research suggests that their proteins induce cellular senescence in the brain. So cell senescence could be a key factor in the emergence of Alzheimers’.