Category Archives: Science

General Science

Evolution and Innovation

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Apparently I published this before I meant too. Anyway, today in Techdirt, they published a discussion on copying, innovation and evolution. Basically, a biologist argued that we are evolutionarily predisposed to copy and use group learning to develop new tools. What this means is that instead of going out and developing something out of the blue we first have to see what someone else has done and then we copy whatever they did, then in a parasitic way, make marginal improvements on the original. We’re nothing but freeloading copiers that make things a little better.

Techdirt completely disagreed with this point of view. They argued that simply copying something or a part of something doesn’t mean you’re freeloading. You can add a great deal to something to the point that whatever you copied simply becomes a part of a larger whole.

Anyone should know from my writing that I support Techdirt’s perspective. This comes from several several different arguments. The first is from the evolution of technology. If you ignore some of the human motivation behind the changing technology itself and focus on the selection process, you can see that technology changes through incremental adjustments. These changes are selected by the market or in primitive societies by the end result of an improvement. Spears that last longer, less energy expended on making new spears, spears that can be thrown farther, less danger from the animal being killed, or sharper shovels, less energy spent gathering food – more food. This selection process is a very natural process. Additionally, there would be some specialization of skills even at this point in our history. Some people would have been better at making spears and in a collaborative environment, because there were no patents and sharing was for the best of everyone, many people could experiment with new spear designs. This innovation while based on copying is a very real form of innovation that likely lead to gradual improvement over a great deal of time.

The second argument that supports innovation after copying is the argument of Cesar Hidalgo, which argues that looking at what countries are currently producing you can see a relationship with their innovative ability. By looking to see what technologies they import and export you’re able to see how well they have developed scientifically and in the manufacturing world. For example you can expect to see more advanced products come out of a country if they got into producing fertilizer very early in modern times. This typically leads to a general chemical industry which can lead to pharmaceuticals and semiconductors. Why? Well developing a strong base in chemistry with fertilizers can be expanded into drugs and as a base for semiconductors.

How do new countries move into these fields? Essentially, they have a knowledge transfer from a country that is already doing it. This can be done in two ways, one is the easy way: have a multinational company set up a manufacturing then R&D facility in your country. This allows a direct flow of knowledge on how to manufacture the material, which increases the rate of copying. Would allow the country to be a fast follower but will still require significant time for them to eventually innovate on that technology. Having an R&D facility would increase this rate, because local scientists would have already been trained on how to innovate in that field. They would have already been doing research in that industry and would more easily be able to innovate if a spin-off was created (or if the state nationalized that part of the multinational). The second manner is much slower: repatriating of knowledge workers. This is essentially what has happened in Taiwan and India. Educated Indians or Taiwanese returned from the US and created spin-offs and became professors at the local universities. This isn’t always successful.

Saudi Arabia is trying to develop a third way, which is having some success. They are recruiting experts from around the world to develop their own universities and companies. This is having mixed results and education and industry needs to pay attention to these attempts to see how well it plays out in the long run.


Copying is extremely important in education and is required to develop new industries in a country. Technology evolves through copying previous technology, recombining with new learning from other fields and from experimentation within the current field. Without copying there cannot be innovation. The more people participating in an economy where innovation through copying is rewarded, the greater our culture and the greater or technological evolution will be. Biology needs to take a lesson from Evolutionary economics.

Climate change more than melting ice caps

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Yesterday I heard a report on NPR about how climate change is interacting with natural wild fires. I found an article about the paper, which was published originally in Ecosphere, which discusses some of the long term impacts of the climate change on wild fires. To do this, the group used 16 different climate models which ranged from very favorable emission numbers to catastrophic emissions numbers. This allowed for a wide range of different types of human activities and reflective climate changes in the area to be tested. This is important as it gives the article much more validity than if they had simply decided to use the worst case, or best case. Of course, there will be people that will argue that man has nothing to do with the climate and we aren’t impacting it. However, that’s sticking your head in the sand. We know we have impacted the climate in the past (hello Acid Rain) and have actually fixed it though changing our behavior (Acid Rain again).

Just using the climate models isn’t enough to really predict how and where wildfires will occur in the future. The wild fire itself had to be modeled as something where the conditions it could exist in can be tested. The group decided to model wild fire in the same way that movement of animals are modeled. Under certain circumstances it’s likely that an animal group will move into a specific type of environment. This is based on the amount of water, the amount of vegetation and the temperature. Wildfires need the exact same resources to exist. However instead of being lush and moist, the area needs to be dry, but with enough water to have had plant growth to a certain size.

By combing the two techniques the team was able to show that the West is going to be burning a lot more frequently than they are not. This of course creates a serious problem. People like to live in those areas. People don’t like to leave their houses when there are disasters, which means that we’re going to have more people burning, like the one in Colorado.

The authors, in the NPR interview, argued that this means we need to learn how to live with wildfire in the same way that we’ve learned how to live with floods and earthquakes. How can we do that though? It is likely to be more difficult than flooding because you can’t just build a mound of dirt as a ridge to prevent fire from moving further. With water you can do this with varying success. With fire, that mound of dirt will eventually grow grass on the mound and would just as easily catch fire. Even stone walls would be passable as a strong wind could blow embers over the wall or heat the wall to the point of material catching on the other side.

These are issues that we will have to resolve in the next 10-30 years. This seems like a long way off, but time has a habit of sneaking up on you and before you know it we’ll be having wildfires like we had in Texas last year and are having in Colorado and New Mexico now. I’m glad we’re aware of the extent of the risk now though.

Is Scientism the problem?

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I just finished reading an article in The New Republic which argues that history and the humanities are knowledge too. At times it felt like the author was yelling at his brother begging to be noticed. Personally, I feel that in general the author is correct, that history and humanities do plan an important role and can be considered as knowledge. However, the author makes one glaring mistake, he is equating the unified theories of everything in physics with everything, where it typically means a combination of all physical laws within physics both particle and cosmic, which would then move into chemistry and likely into biology. However, this type of theory of everything would stop there. It couldn’t really combine natural selection as functions of chemicals in a specific manager do not necessarily mean a truer understanding of evolution. It would be able to explain how phenotypes are changed with genotypes, but not why one genotype/phenotype pair was selected over another without an understanding of the specifics of the environments at a time. A true theory of everything at that level would essentially be a simulation of the universe. It would be impossible to model in a series of equations beyond the fundamental laws of physics.

For the evolution of biological systems you have to understand the natural history of the world that the organisms develop and evolve. This is why when you read Sagan, Dawkins or any other biologists or cosmologist they argue that if you rewound the tape of history you’d get a different present day. Some things may have happened just slightly different enough and you’d have no humans. The understanding of the history of our world allows us to understand where the future of it is going.

In the same way, history does matter. There are branches of economics, such as evolutionary economics that use complexity models and work to ensure that the history of events are included in their models. What the major difference between typical theories of history and psychology and newer models of economics and complex systems of physics, is that we’re able to test them using simulations. It is likely that in the future we’ll be able to do the same thing with history. This will give us a deeper understanding of why our societies have developed as they have. One heavily contested aspect of evolution, which is mentioned in the article, is cultural inheritance, which is where the theory of memes came from. This approach doesn’t suggest one type of people is better than another or one lifestyle is better than another, it simply says that in the environment that the culture resides it’s more capable of surviving than others. This can go down deeper to smaller niches within the culture and how well they adapt to their environment.

Other aspects the author argues discusses is the differences in the acceptability (or perhaps the perception) of radical paradigm shifts in science compared to the humanities and history. He mentioned specifically Freud in psychology and Galileo in physics. He argues that Galileo was able to make changes in physics because he tackled an “easy” problem that had minimal level of complexity. He went after the theory of gravity and how objects fall at the same rate while Freud went after the entirety of the human psyche. I agree there is a difference of complexity, however the key differences between Galileo and Freud is that he was better able to explain the state of the world and when new scientific theories were produced they continued to explain what Galileo found but with more accuracy and expanded on them. When Freud was discredited it was more like discrediting Alchemy than going from Newtonian physics to Relativistic physics.

The key difference between many theories in humanities and in the rest of science is the lack of continuum between two major theories. Yes, Relativistic physics completely obliterated the value of Newtonian physics and created a new world (universe) view, but it solved the same problems or proved that many of the old problems were only problems because the theory wasn’t complete enough.

The key that needs to be remembered in either science or humanities is that all models are wrong, but some are useful. Freud was wrong in how he looked at the human psyche, but his models allowed other theories to be tested and used and likely spawned Neuroscience and the bridging between neuroscience and many of psychological problems.

Evolution and Synthetics

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An amazing scientific announcement has recently occurred, we have been able to show that synthetic DNA, XNA, is capable of evolving. This is interesting for several reasons. First, it’s just more evidence of evolution, which should be a rather no brainer at this point. Second, it shows that there are other materials that can function similarly to DNA and RNA. Finally, we can make these structures and they will behave in a similar fashion to DNA and RNA.

If we can create something that evolves under stress, it indicates that evolution is still extremely robust. If this type of material did not evolve, it would have made scientists look at both that material itself and check a few things. First, would we expect this material to evolve. Second, if yes, why doesn’t it evolve. If we are developing a material that is expected to mimic DNA/RNA, it is likely that we would expect it to evolve in a similar fashion. If it doesn’t evolve, then this could have serious consequences. This would not disprove evolution, as DNA/RNA both evolve, it would indicate that either we have the wrong material or that only DNA/RNA can evolve. It would explain why only DNA/RNA have been found on earth and not any other type of xNA material.

Since this material can evolve it leads to interesting questions itself. Did evolution occur  between DNA/RNA and other xNA’s? Did the RNA/DNA combination beat out every other stain of xNA’s? This would be interesting to understand. If RNA/DNA did evolve because it was better suited to Earth’s early environment does that mean that our current environment still suits it best? Could we evolve completely new life forms based on these structures? Only time and more research will allow us to answer these questions. But we do know that these new strains could allow us to develop treatments and other solutions to biological problems.

One way we could answer these questions is if we discover alien life that is based off of non-RNA/DNA combination. This could be in the form of anything from bacteria to full blown organisms. At this point, it is more likely we’ll find a bacteria life form based on another XNA than anything else as they are capable of surviving exposed space transportation, such as on an asteroid.

The fact that we’re able to create XNA is an amazing accomplishment. It indicates that we understand biochemicals required for life to an extent that we are able to create new enzymes that mimic RNA/DNA. We also understand that the most important metric for this experiment is not the fact that we could make a stable XNA, but that it must evolve. A stable or static XNA would not be interesting as it would have no ability to adapt in an environment where there is competition. The ability to change as the conditions change is what separates RNA/DNA from other proteins and enzymes. Only the best combinations are able to change and develop over time.

I’m excited to see how these changes will impact us. I think there are some significant long term implications for this, but at this time I’m not sure what they are. The fact that we’re capable of doing this is an incredible step.

Book Review: Idea Factory, the history of Bell Labs

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Yea, I know I’ve just been doing book reviews.

This book was amazing. I had no idea of all the different things that Bell Labs produced from the mid 1920’s until the 1970’s and later. The book focused on the high point of Bell Labs innovation run. It followed the career of several, at the time, famous and prominent scientists that were employed at Bell Labs. Please such as Mervin Kelley (vastly improve the vacuum tube and was a long running director, VP and President of the Labs), William Shockley (inventor of the transistor) Brattian (inventor of a different kind of transistor), Claude Shannon (inventor of the field of Information Science), John Pierce (inventor of passive and active satellite). These there were many others, however, they each had significant impacts on how our modern society works.

The book does an excellent job in explaining some of the basics of how the research was conducted, what work needed to be done to make it work on an experimental level, the method of transferring the invention into innovation or a full product and the goal of each of these inventions. Mervin Kelley was famous for saying that to implement a change in AT&T’s network the new technology must be “better or cheaper or both.” This prevented a great deal of frivolous technologies from being implemented into the telephone network. Additionally, this was required to ensure that AT&T was always able to work towards reducing rates for subscribers as they were a “natural” monopoly.

This was a time when research was done to ensure that the network would be operational for 30 years without malfunction. This required huge investments in quality control and required that additional costs were built into the network for redundancies and protection. In fact Statistical Process Control was invented at Bell Labs to ensure proper quality.

How did all of this work? Well, there were two factors going on here. First, Bell Labs was able to hire the best and brightest to work on interesting problems. Second, the scientists had a continually evolving project that always needed more innovation. These two combined with a freedom to explore allowed the scientists to delve into basic and applied research. In some cases they did not know how or why something would work, but felt that it would improve the quality of the telephone network.

One of the goals of AT&T was to create a coast to coast network with universal service. This required the company to figure out how to address signal decay due to distances over several miles. To address this the company developed the vacuum tube repeater, which significantly increased the distance a voice call could travel. The manufacturing of a tube was extremely difficult and expensive. Bell Labs felt that there had to be a different way to create a repeater. Over the next 20 years they investigated off and on (with a break for WWII) how to make semiconductors work as a repeater. Bell Labs was capable of making this sort of investment because it had a guaranteed revenue stream and a mandate to continually improve the network. These two together allowed the Labs to do work that they otherwise would not have been able to investigate.

This is a very different model for innovation than we currently have in any organization. Universities come close, but they fall short in the fact that the professors are continually required to apply for more money and seek permission from someone to pursue their work. Bell Labs was much more relaxed about this.

This innovation method is also very different than some of the historic events in the US, such as the Manhattan Project or the Moon Landing. Those were single goals which allowed the focus of a great group of minds.There was never any intention of keeping those minds together for the next big project. Bell Labs had the ability to do this.

There are some organizations that should be able to do something like this. The National Labs are one, but there’s no direct business need so even this doesn’t exactly work. An organization like TNO in the Netherlands, which focuses more on practical matters could increase the amount of basic research they conduct in various different areas. TNO is structured differently than the National Labs in the US, because they are expected to work closely with both industry and universities. This gives each of the groups a strong business focus and could serve as a pipeline from basic research into business activities for the companies that work with TNO. However, at this point TNO does not perform these activities.

I give this book a 4.5/5. It was extremely well written, well organized and dealt with some amazing subject matters.