The hype of AI

A recent article (1) further reinforces what autonomous vehicle industry has been doing. Neural net systems with feedforward and feedback control architectures trained by historical data on specific surfaces and conditions. Remnants of 1960s technologies, ably assisted by zero cost computing, have been percolating across the autonomous landscape. This trajectory is problematic for many reasons.

First, a brain trained on historical data selected by a biased human is a disaster waiting to happen. The situation is no better with hand-coded heuristics as demonstrated by recent aircraft failures. What computer and data scientists have to understand first is that their own brains still remain to be vastly superior to code they write running even on a super-computer. Hence, blind attempts at removing the human from complex decision-making processes are likely to fail.

Second, hype and ignorance have propelled AI to the stratosphere without significant practical use cases. AI is a tool and it is not a panacea. AI still fails when it encounters the unexpected. This is important as it indicates conventional computing and Silicon based architectures, albeit great engineering innovations, have nothing to do with "intelligence." We have not advanced AI much from the 80s, when the "oldies," used to call it expert systems. Granted, simulated voices, believable human faces, and incredible jumping robots are great inventions, but unfortunately, these have nothing to do with AI.

And finally, high human resource intensity in model building often leads to costly failures. For practical AI, two important things need to come together - rapid and flexible prototyping with automation and considering AI to be augmenting the human, not replacing her.

(1) http://robotics.sciencemag.org/content/4/28/eaaw1975

Alzheimer’s - we fail again!

Recent news (1) that high profile experiments, targeting a solution for the famous disease, Alzheimer's, has failed again is sobering. It clearly indicates that life sciences companies are on the wrong track to improve a condition, most dread. It is also a constant reminder that systemic problems cannot be solved by treating symptoms or tactical observations. The engineering view of medicine has run its course and it has been very successful in fighting opponents that can be clearly identified. But now, a system failing because of overuse, cannot be mended by such crude methodologies.

Immortality is prohibited by contemporary Physics. So, the optimization problem narrows to maximizing utility within an afforded time horizon. Humans have been naturally optimistic, an evolutionary advantage. They have been attempting to extend life rather than optimizing within constrains. Therein lies the paradox for healthcare. As artificial intelligence progresses, it is conceivable that a human could have reasonable estimates of life span and disease incidences, at birth. For the first time in history, we may be in a position to focus on optimization of utility rather than extending a highly uncertain horizon.

It is clear that the human hardware deteriorates in predictable ways. Most of it appears to be related to plumbing, an inability to remove waste at an optimum rate. From the brain to the kidneys, waste removal efficiency seems to decline over time, just as in any physical system. We may need to accept this as an unbreakable law and find ways to slow down the deterioration. In this context, research in the direction of cure for auto-immune diseases may be misplaced. What could be more important is predicting the likelihood of disease early and slowing its progression.

Artificial Intelligence could have a significant impact on human utility and happiness. If one can get over the hype and confusion, it will become clear that AI could provide useful guidance for humans to best utilize their limited time in the universe.

(1) https://www.sciencemag.org/news/2019/03/another-major-drug-candidate-targeting-brain-plaques-alzheimer-s-disease-has-failed

F-Theory, Occam's razor and ignorance

Physicists are funny people - they like complexity and large numbers. They recently found F-theory (not sure what "F" stands for except for the obvious possible guesses), that demonstrates a "quadrillion ways, string theory could make the universe." That is impressive and could provide rich fodder for PhD theses and "peer reviewed," publications for a century to come. But does it advance knowledge? It is less clear.

Complexity is a problematic concept. As the true geniuses of the yesteryear correctly emphasized, "God does not play dice," and unless she has a quantum computer in the basement, she will not embark on a journey that has "quadrillion," ways to make the universe. Large numbers could be ego boosting behind the ivy walls but it has no practical use. It is probably time for those attempting to formulate the next exotic "theory of everything," to get out of their windowless offices and smell the roses.

There is no problem that has been solved by increasing complexity. Those who advanced thinking always preferred simplicity. Knowledge is clearly inversely correlated with complexity. Even the money men, who typically do not know much, seem to have gravitated to this universal law. So, why are we here at this point in time? One possible answer is that engineering heavy education has churned out engineers who want to measure "reverberations," not much larger than the size of a proton or mathematicians, enamored by "large numbers." Even the business guys seem to have learned bad habits as most want to use, "big data."

Complexity is utility diminishing. Theories that push in that direction is utterly useless.

(1) https://www.scientificamerican.com/article/found-a-quadrillion-ways-for-string-theory-to-make-our-universe/

The era of bioelectronics

The most complex electromagnetic and chemical system known, the human body, so far has substantially avoided manipulation by electromagnetic means. This may be changing. Recent news (1) about a transistor design that enables integrated, real-time sensing and simulation of signals from living organisms, could lead to better diagnostics and treatment. Low cost Silicon has impeded innovation and applications in non-conventional substrates. There have been few biocompatible designs for the lack of appropriate materials and incentives.

Chemicals have been easier and in the presence of many low hanging fruits, researchers did not spend much time on alternatives. As they solved simpler problems, auto-immune diseases start to dominate the human architecture. The heart-breaking failure of a recent drug for Alzheimer's (2) is symptomatic of the end of the chemical era. The brain likely responds better to electromagnetic stimuli but contemporary pharmaceutical companies are ill-equipped to pursue this line of thought.

Simple diseases such as Hypertension and Type 2 Diabetes, that command over half of the healthcare costs in the log run, could be positively influenced by better monitoring and treatment mechanisms that are integrated into the body. CHF and other Cardiovascular events could be picked up earlier and intervened optimally by the same mechanisms. As the sun gets hotter and nastier, embedded devices in the skin could shield the body from harmful rays. Organ failures could be arrested, nutrition deficiencies could be remedied, better food and treatment regimens could be suggested and humanity could possibly move to a more advanced health regime.

It is exciting. Integrated bioelectronics with embedded artificial intelligence could be a game changer.

(1) http://advances.sciencemag.org/content/5/2/eaau7378
(2) https://www.cnn.com/2019/03/21/health/alzheimers-drug-trial-failure-aducanumab-bn/index.html