High-throughput Screening for Energy

The battle for innovation will be won at the intersection of materials and information. The field has been lagging for nearly a century as scientists focused on incremental improvements to established media. Now, there appears to be hope for progress at an accelerated pace (1). Well established techniques in fields such as life sciences could boost productivity in other areas.

Humans have gotten used to relying on nature for materials for half a million years. In the modern world, that substantially curtails their ability to move further. They have been given a matrix of simple molecules and the capability to combine them at will to create new properties and applications. They have been misguided for ever, trying to make gold from charcoal and attempting to fuse hydrogen in a cold test-tube. Industries such as pharmaceuticals that claim to have found "new agents," largely relied on tree barks and soil. It was nature that made the humans tick, albeit at a very uninteresting level.

The ability to custom develop materials to fit desired properties will be an indication of human advancement. It is not the ability to code, to send mechanical toys to nearby planets, to keep the weak and the weary on life support systems, to devise theories of nothing, to postulate the growth and decline of countries, markets and cryptic currencies, to create humanoids without consciousness, to make vehicles that move at the speed of sound or to inject poison to the political swamps.

Next generation materials will redefine the energy and the future of the "tiny blue dot."


(1) https://www.sciencemag.org/news/2018/12/megalibraries-nanomaterials-could-speed-clean-energy-and-other-grand-challenge-targets

It is all in your mind

An experiment at Stanford (1) appears to demonstrate the power of the placebo effect. Most pharmaceutical research clearly points to the effects of believing and as suggested in the study, it has implications for how information is captured and disseminated through tests. Humans are susceptible to suggestion and can completely rewire the infrastructure of their body from their brain. This should have had survival benefits early as the village elder may have segregated people into random groups and reinforced one side positively and the other not. Those who where lucky enough to be in the right group started believing and ultimately succeeded, proving the point.

An over-tested and over-treated contemporary population is not only suffering from ineffective treatment regimens but also the negative effects imparted on their bodies by their brains. As medical schools get more technical in their educational stance, they have to remember that the weakest link in the chain remains to be the patient, who could easily fight technology. In this context, it may be time to redesign education bottoms up with more focus on how patients internalize information. Ultimately, it is the content of revealed information that drives outcomes. As technology advances we are likely to be exposed to more information and the effects of such exposure could completely negate any positive impact of advanced treatments.

For a variety of reasons, humanity is at crossroads. On one hand, we have accelerating technologies that boasts to make everything better and on the other, it conflicts with the psyche of ordinary human beings. With a harsh timing constraint, once an individual is sliding down the slope, it is nearly impossible to reverse the trend.

Everything appears to come back to how society manages and uses information.


(1) https://www.sciencemag.org/news/2018/12/just-thinking-you-have-poor-endurance-genes-changes-your-body

GammaGo

News (1) that AlphaGo can successfully learn Chess, Shogi and Go through self-play is interesting. It is symptomatic of trends in AI largely relying on raw computing power. Typically, innovation lags when resources become infinite and we have early signs of trouble here. Reinforcement learning through self-play is not a new concept - it has been here from the advent of computers. It is just that not many have access to computing resources necessary to create demonstrable prototypes.

More importantly, this approach is unlikely to culminate in cognition and consciousness, the possible end game. It is clearly the case that computers can create usable heuristics by repeated experiments, just as humans do. However, those heuristics are generated within a framework of rules that were specified ex. ante. The "deep mind," enthusiasts had argued a few years ago that their computer found a "new way," to play an ancient game. It is quite possible that given a large number of experiments, computers can learn from cases that are outside the norm. But to label this "creativity," is a stretch. It is more an accident than invention. One could argue that humans have benefitted handsomely from accidents in the past and so why not computers. This is true and so the general question is whether computing resources running amuck with an infinite number of repeated experiments can provide learnings from accidents at a faster rate than humans are capable of.

It is tantalizing. What the AI leaders need to understand, however, is that we have been here before. A critical look at the approach may be beneficial. We knew that we could predict from historical data ever since math was invented and we knew that repeated search of the design space could yield usable results since the advent of computers. The question is whether we have done anything new except pouring money into scaling conventional technologies. Stacking countless "computers," in the "cloud" on the promise of AI has many drawbacks.

It is time to go back to the drawing board. A field replete with engineers seems to be going in the wrong direction. As innovation lags in materials and quantum processing, they are creating mountains of Silicon to show heuristics generation is possible. The mathematicians locked up in low productivity areas such as finance, may be well advised to go back and think.

Thinking has a low premium currently and that is problematic.


(1) http://science.sciencemag.org/content/362/6419/1140