March 17, 2023

"A client of mine had suffered from periodic seizures", by Howard Rankin, PhD

"Where is the need for AI predictions the greatest?", by Michael Hentschel

"IntualityAI-on-a-Chip", by Grant Renier

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TRADING PERFORMANCE RESULTS OF THE INTUALITYAI SYSTEM HAVE MANY INHERENT LIMITATIONS.  NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN REPORTED PERFORMANCE RESULTS AND RESULTS SUBSEQUENTLY ACHIEVED BY THE SYSTEM OR PORTFOLIO. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF THE SYSTEM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF REPORTED PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.

A client of mine had suffered from periodic seizures

 He didn’t want for this condition to seriously impact his life, so he would carefully plan his activities and ensure he was never alone when he was outside the home. He also had some devices that monitored various health metrics. For the most part these were passive measurements of individual systems. Passive measurement is critical because research shows that as soon as the end user has to actively operate the equipment, reliability goes down, sometimes way down, especially in an older or impaired population.

One day this client was out shopping: with his wife, and had a severe seizure. He fell heavily, hitting his head hard on the floor. He never recovered and died just a few weeks later.

The main reason we measure metrics: like health variables,

 is to attempt to predict when a critical event may happen so preventive measures can be taken. Knowing that my friend had his blood pressure on the rise just before the event isn’t terribly helpful. Its prevention we are after, and prevention is about prediction. In addition, a systemic approach that looks at a variety of measures, not just one on its own, is also like to show more meaningful effects.

It is ironic, and perhaps illuminating: in the light of the above story, that when I first met Grant Renier, he told me about IntualityAI’s enhanced prediction of epileptic seizures. Using Intuality in combination with relevant passive and systemic health measurement, Intuality was able to significantly increase the alert time for a seizure from just under a minute to almost four minutes. Four minutes gives the patient and any caregiver, plenty of time to prepare for a seizure, including sitting the patient down and securing him or her in a safe position so that they don’t fall during the seizure, a major problem, arguably the biggest problem, for those who suffer with the problem.

Measurement is good but accurate prediction: based on passive measurement of systems is essential. There’s not much point in measuring anything but especially health metrics, if it doesn’t help make critical predictions that prevent adverse outcomes.

by Howard Rankin PhD, psychology and cognitive neuroscience

Where is the need for AI predictions the greatest?

-True value in computing: comes from better understanding and optimizing every next action we take.
-It’s not present data that matters: It’s sensing and predicting small and large changes. Our future matters most.
If our future matters most: then it will be of great value to improve our fact-based and intuitive predictions of what will happen.
With more accurate prediction: we can act and react more confidently.
With continual real-time prediction: we can make better continual decisions.

We humans aren’t perfect: Neither are machines, though we can help each other get better.
Machines weigh past and present: facts and calculate probabilities, not predict.
Machines assist humans in making decisions, to replicate human behaviors and our ways to decide.
Humans make instant probability-laden decisions intuitively: right or wrong, because we have to, for success and survival.
Sometimes we fail: to make any decision at all, uncomfortably procrastinating until we have emergencies resulting from inaction.
Our computer tools: are even more uncomfortable making and acting on predictions than we are: evaluating probabilities is hard enough. Figuring out how the probable scenarios have future results that themselves require informed decisions is harder still.
Even AI still has trouble: with a vast swamp of human probability analysis and uncertainty.
But now comes humanize AI. To better comprehend human behavioral predictions and actions.
IntualityAI predicts actionable events: as a dedicated prediction engine, while some other AI’s just calculate probabilities.
Where is the need for AI predictions the greatest? It will undoubtedly involve the largest arenas of human behavior and human needs.
It would involve some of the biggest global unit markets:

Is NeuraLink “a bridge too far” ? …
… or is it merely the logical endpoint of monitoring our bodies as one giant sensor sensing everything?
… and when we finally have all the data that the human body collects to activate its immune system, what then?
We need an AI that is humanized: to recognize human events and instantly interpret the precise information we need.
In the Matrix Movie, humans were slave biological robots, a pre-designed ideal breed of livestock bioreactor, manufacturing energy for the machines. If we do not humanize the machines before they automate us, slavery is our future. 

by Michael Hentschel, anthropologist, economist, venture capitalist

IntualityAI-on-a-Chip

The derailment of a Norfolk Southern train: that spilled toxic chemicals and led to a controlled burn of the substances in East Palestine was a disaster. If each train car truck had been fitted with a smart sensing chip that predicted bearing and wheel failure, on the axle-end cover, the event might have been prevented.

Our prior experience: in manufacturing an older version of IntualityAI into a mobile chip with Texas Instrument brought its predictive powers to various applications in the petroleum and other industries.

More recently: a chip-form of IntualityAI was commercialized for predicting the failure of heavy-duty and automobile components. The current version of the system is more efficient and compact for a new upgraded version of IntualityAI-on-a-Chip.

The device has advantageous features: for bringing preventive predictions to a wide range of mobile applications:

The future of medicine: lies in incorporating wearable monitoring technology into the healthcare system. Although the wearable monitoring market has been primarily dominated by the fitness/tracking consumer sector, significant advancements are taking place in the healthcare industry. Recently, companies have expanded their focus and intensified their efforts in developing more intricate applications for monitoring critical parameters like ECG, EEG, EMG, blood pressure, and blood glucose levels to aid in timely and precise diagnoses. New smart-watches are now sensing and reporting all of these parameters and more. 

None are predicting future health issues: for user as preventive warnings, nor reporting overall future health status.  IntualityAI-on-a-Chip would initially be for personal use by the general public as an extension of the current status-reporting software.  (IntualityAI has successful trials in predicting epileptic seizures, heart arrhythmia, and hypoglycemic events.)

We will be presenting our human behavior simulation and prediction technology to the International Ai4 Conference in Las Vegas, in August (https://ai4.io/usa/full-agenda/). While the Conference covers all AI subjects and technologies, this year it attendance will have a 50% focus on health applications.  

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by Grant Renier, engineering, mathematics, behavioral science, economics

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