The Future of Technology, the Technology of the Future

This is part four in a five-part series called "The Limits of Accelerating Returns" that focuses on the limitations of Ray Kurzweil's Law of Accelerating Returns when applied to molecular biology and biomedical technology, including longevity treatments. The other articles in the series are "The Limits of Accelerating Returns," "Biology is not Digital," "Garbage In, Garbage Out," and "Implications of Fixed Returns."

In the previous post in this series, I suggested that, in 40 years, we will be able to run complex molecular simulations of the entire human body if the limiting factor is computational power. Unfortunately, that’s just not the case. We can’t generate the requisite data fast enough for the computers to crunch it. Not everything is amenable to accelerating returns.

Read the rest of this entry »

This is part three in a five-part series called "The Limits of Accelerating Returns" that focuses on the limitations of Ray Kurzweil's Law of Accelerating Returns when applied to molecular biology and biomedical technology, including longevity treatments. The other articles in the series are "The Limits of Accelerating Returns," "Biology is not Digital," "Some Rates are Fixed," and "Implications of Fixed Returns."

In his essay called “Making the World a Billion Times Better,” Ray Kurzweil writes, “The approximately 23,000 genes in our cells are basically software programs, and we are making exponential gains in modeling and simulating the information processes that cracking the genome code has unlocked.” The problem is that genes are only roughly analogous to software programs, as I discussed in the previous post in this series, and simulating the information processes of the genome is non-trivial in the extreme.

Let’s take a very simple example of an artificial genome called a “repressilator” that was added to bacteria as a proof-of-concept of synthetic biology and biological simulation. The repressilator’s machinery consists of three genes, each of which turns off one of the other genes. When one of the genes is active, it turns off one of the other genes. Meanwhile, the third gene is in the processing of shutting down the first. When the first gene is turned off, the second one turns on, and stats shutting down the third gene. Thus, there’s a cycle or oscillation to the activation of the genes (the name of the construct is a contraction of “repression” and “oscillation”).

The system also includes a fourth gene that produces a visible signal so that the oscillation can be tracked. This seems like a pretty straightforward system. The scientists who developed it even did a lot of modeling to figure out how to optimize the oscillations before they went to the trouble of building the thing.

But it didn’t work the way they expected.

Read the rest of this entry »

This is part two in a five-part series called "The Limits of Accelerating Returns" that focuses on the limitations of Ray Kurzweil's Law of Accelerating Returns when applied to molecular biology and biomedical technology, including longevity treatments. The other articles in the series are "The Limits of Accelerating Returns," "Garbage In, Garbage Out," "Some Rates are Fixed," and "Implications of Fixed Returns."

A logical way to understand biology as an information technology is to find the commonalities between biology and the everyday computer. Biology has its central dogma, which basically says: DNA stores the instructions for life, RNA carries the instructions, and proteins execute the instructions. If we apply these functions to the components of a computer, we see that DNA is like a hard drive, RNA is the computer’s RAM, and the proteins become the CPU.

Kurzweil appears to regard each gene as its own “program” that is easily turned on or off, just like opening and closing Microsoft Word:

[W]hen the fat insulin receptor gene was turned off in mice, they were able to eat ravenously yet remain slim and obtain the health benefits of being slim. They didn’t get heart disease or diabetes and lived 20 percent longer…

I’m an adviser to a company that removes lung cells, adds a new gene, reproduces the gene-enhanced cell a million-fold and then injects it back into the body where it returns to the lungs. This has cured a fatal disease, pulmonary hypertension, in animals and is now undergoing human trials.

Read the rest of this entry »

This is part one in a five-part series called "The Limits of Accelerating Returns" that focuses on the limitations of Ray Kurzweil's Law of Accelerating Returns when applied to molecular biology and biomedical technology, including longevity treatments. The other articles in the series are "Biology is not Digital," "Garbage In, Garbage Out," "Some Rates are Fixed," and "Implications of Fixed Returns."

Ray Kurzweil is a very smart man who sees the world differently than most of us. We see linear growth, he sees exponential. Kurzweil outlines, for the lay person, what exponential growth means for the future in an opinion piece in the Washington Post called “Making the World a Billion Times Better” [hattip: Siggi Becker via FriendFeed]. Kurzweil says that any information technology is “subject to what I call the ‘law of accelerating returns,’ a continual doubling of capability about every year.” In his use of the term, “information technology” isn’t limited to traditional computer science but also includes nanotechnology and biology.

Kurzweil is absolutely correct that biology is increasingly an information technology. Thanks to high-throughput technologies, research labs are generating incredibly amounts of data, more than anyone really knows how to analyze in any meaningful way. Kurzweil, however, jumps the gun a bit when he says, “The important point is this: Now that we can model, simulate and reprogram biology just like we can a computer, it will be subject to the law of accelerating returns, a doubling of capability in less than a year.” I think he’s right about the amazing things that biomedical technology will achieve—I fully expect to celebrate my 125th birthday in the year 2100—but he misses some important distinctions between biology and computers. These differences place some limits on Kurzweil’s law of accelerating returns. It’s important to understand these limitations so that we have a more accurate idea of what amazing advances we can reasonably expect.