Language optimization

Language, a distinct advantage that separated humans from chimps, may become a liability for them in a regime of accelerating information and forced specialization. Early on, language provided efficient communication among clan members with relatively simple objective functions to optimize. Later, as they branched into art, philosophy and literature, language became a construct that may have touched the souls of some, but it also meant that it began to lose the communication efficiency, it was originally designed to do. Presently, conventional languages, with complex semantics and grammar, appear unable to distill and communicate critical technical information.

Computer languages, that stay at a lower level without flowery grammar, are certainly more efficient to program machines. In the human sphere, millennials have been experimenting with a variety of constructs that remove the complexity of grammar and schema, but it is unclear if any of the current methods are efficient in communicating content. In an environment of deep but not broad knowledge per individual, science and engineering may need to invent a modern language that does not constrain them to formats that are designed for different purposes. For example, the abstract of a scientific article, that often limits the format to certain number of words but force the author to utilize inefficient grammar, lose in multiple ways.

It is time to rethink scientific language. Nobody has the time to read through the entire paper and content is not complete in allowed abstract format that conforms to artificial and old constraints.

Gravitational annoyance

A recent paper in the Journal of Science that describes the failure to detect gravitational waves from any source including the merging of two galaxies with possible combination of two black holes, perpetuates the gravitational holdout to otherwise beautiful theories woven up by physicists. Gravitation has spoiled every attempt at Grand Unification of the hypothesized fundamental fields of nature. It is ironic that a field that is obvious at human scale has been the one most difficult to understand and explain with status-quo theories. Ever since an apple fell on Newton’s head, gravity has vexed humankind and it seems like the current situation will continue for a while.

Failure of Grand Unification Theories is a subtle sign that we do not yet have theories that can be unified. Early in the 20th century, a few brilliant minds made inexplicable leaps into emerging knowledge. It is scary to even think of a world in which they did not exist. Newtonian mechanics could have ruled the mediocrity for a few more centuries. However, there were visible cracks in both the theory of relativity and quantum mechanics, and the ones who followed are simply unable to mend them. More importantly, they have taken the hammers given to them and they have been looking for nails all around the universe to put the hammers to good use. None is able to spend a career or even risk a tenured position to ask if the hammers need modifications.

The jumps in the stochastic evolution of knowledge are rare and they are driven by an amazingly few members of billions of humans around the world. The next jump appears too far in a regime mediated by paid research and manufactured education.

Machines do not learn!

Artificial Intelligence is fashionable again, aided by cheap computing and cheaper memory, computer behemoths have been diving head first into the abyss. It has happened before, albeit, with much limited computing power. Just as in the previous iteration in the 80s, the current excitement may die down in a few years. Simulated machine voice and jeopardy are easier problems to solve but finding a cure for cancer is a lot harder. Similarly, churning through limitless text - “search”, is a mechanistic process but “curing death” is not. Soon, hopefully, the “leaders” will realize the naked truth – machines do not learn and that the “singularity” they envision is many centuries away.

Machines have captured the human imagination from the start. When they trained animals to drive farm equipment many thousands of years ago, they understood how machines could be built and powered to enhance productivity. More recently, the silicon chip, a conventional and mechanistic processor, has raised their ambitions to a level that may not be realistic. In the initial going, it was focused on productivity, very similar to farm equipment but now some believe their machines can learn. If so, this is a departure for humans from sustenance to imagination, from mediocrity to advancement, from tactics to strategy. But alas, machines do not learn!

“Machine learning,” a term used too liberally by information technology and consulting firms, may need further definition. One can clearly demonstrate machines do not learn by themselves and if so, we are back to using machines to enhance productivity – a posture humans have been in for ten thousand years.

Real finance

Recent observations by a previous Fed chairman that it is puzzling why one would advocate a reinstatement of Glass-Steagall act because he could not see how the crisis in 2008 would have been avoided had it been in effect, is symptomatic of regulators who are good tacticians but not strategists. From Princeton to Wall street, financial institutions and their regulators still believe intermediation is “God’s work.” Academics, slaves to economics text books from last century, still believe financial intermediation is integral to markets and the economy. If the former chairman is intellectually honest, he may want to revisit the transcripts from Jackson Hole in 2005, before spewing wisdom. The one who came before him, who spewed infinite wisdom for many decades seem to have finally realized, “something was wrong.” He is still selling wisdom at $75K per pop. Meanwhile financial malls, that do everything but intermediation, with a skewed incentive to take risks for their bonuses that depend on the upside potential emanating from their actions and they are generally not accountable for the downside risk, invest into fooling both the academics and the regulators.

Although the chairman may be an expert of the depression era, what he may be missing is that the modern economy needs very little finance as we know it. Any financial activity, that does not have a direct connection to real assets and real investments, adds no value to the economy. Real assets today comprise of only two things – real estate and intellectual property. Financial intermediation in the former can now be done by the internet and it does not require “God’s men,” behind oak desks in the penthouses. And financing needed to develop and nourish IP is not something the mega banks have any clue about. They are dinosaurs with a ridiculous combination of disparate businesses with conflicting incentives that still pose a systemic risk to the entire population.

Glass-Steagall is a necessary condition to eliminate the greed of the ignorant and I am sure “God” will approve.