Running headfirst toward the Denny Limit

Analyzing past records to predict maximum speeds for dogs, thoroughbred horses, and humans. The headline plateau record (the 'Denny Limit', from the paper's author Mark Denny): 9.48s for the 100m sprint, which is both very impressive and -as all explicit limits- bothersome. Why not 9.3s? What do we have to do to make it a cool 9s?

On one hand, we are not the first epoch that attempts to improve physical performance (or any other sort), nor are we the first ones to use then-current science and technology to do it. The appropriate null hypothesis might very well be that increasing scientific resources provide decreasing gains in performance, so while performance will keep improving, it'll do so with an eventually clear lower bound.

Nonetheless, I can't but think that this might not necessarily be the case. Engineering progressed in almost a linear fashion for thousands of years, but eventually knowledge of physics (most importantly, quantitative, mathematical knowledge of physics) opened the doors for a completely different rate of progress. We seem to be getting close to the point where human performance across the board becomes a matter of engineering, which would make models like the one in the article inapplicable.

Most of the time, the null hypothesis of sustained long-term tendencies is the best analytical framework. But 'most of the time' is becoming rarer these days, isn't it?

Researchers from Rice University have created a mathematical model of evolution in viruses and bacteria that takes into account not only mutation rates, but also recombination rates and fitness functions, allowing for a better theoretical understanding of evolutionary processes.

This kind of work at the data-intensive interface between molecular biology, ecology, statistical mathematics and epidemiology will increasingly shape how scientists approach the study of living beings, and in time will change how we interact with the biosphere. At a moment when the planet's biological systems are changing at an incredibly fast rate, knowing how they do so will be necessary if we are to understand how we can live through and with those changes. The treatment of organisms -healing some, attacking some- won't be enough; we'll need to be able to work with entire species or even ecosystems, at enormous scales and dealing with multiple feedback systems.

Plainly speaking, there's no way we are ever going to manage that level of conceptual complexity without advancing our modeling and data-gathering capabilities, and using them as a privileged input to our global decision-making (that is, political) processes.

It's going to be tricky at best.

(An interesting aside: DARPA is partly founding this research, and if you think it has no defense implications, you haven't really thought about what 'defense' will mean a few years from now.)

Alright, alright, so I let the blog fall by the side

Meanwhile, scientists create three-parent embryos. Medical applications aside, in a world of complex sexual and relationship politics, the more tools we have at hand, the better.

Genetics just for you

Plos Bio on individualized genomics. Ten or twenty years for now, a person's genetic sequence will be the first and most basic piece of personal data; I expect babies to be sequenced in utero, for at least some digest of the sequence to be part of IDs, etc. Note that "basic" doesn't mean "private"; I don't really think it will be possible for genetic information to be kept under control, for more or less the same reasons that make DRM schemes impractical.

This, of course, will open a can of worms.