On May 26, 2017, Cool Technologies signed a Strategic Alliance Agreement with Veteran Technology Group (Vet Tech), creators of artificial intelligence software and services. Under the agreement, we will package Vet Tech software with our MG systems where applicable.

First a bit of background: Artificial Intelligence enables machines to sense, comprehend, act and learn.


With its self-learning capabilities, AI becomes an ever progressing, ever refining, ever enhancing feedback loop. It gains years of experience in weeks of operation, improves productivity and lowers costs. Unlike traditional assets that depreciate over time, AI assets increase in value. Perhaps best of all, the fact that AI can learn and adapt means that more benefits and applications for Cool Tech’s patents may be uncovered.

The Benefits of Vet Tech’s AI

Vet Tech software leverages operations research and machine learning to rapidly and effectively diagnose problems in vehicles or other equipment.

Machine learning enables computers to make decisions based on sample data by extracting and codifying system expertise. For instance, to create predictive tools, the AI analyzes massive amounts of data on a vehicle including specs, operation, troubleshooting and repairs. The machine learning algorithms search for patterns and build their own rules and guidelines. Then they continually test their diagnosis using unexamined data, new problems input and the results obtained.

So, when inexperienced operators access the software, they receive expert guidance on how to diagnose and resolve problems without consulting a manual or calling in to the shop.

To enhance productivity even more, the software tracks the actions the operator makes during the repair. It notes what works, what didn’t and the time spent. By comparing the time spent with repairs of similar problems, it learns which repairs were the fastest and most efficient and applies those next time.

Equally, as problems arise, it reviews the conditions that led up to the problems to further improve its abilities at predicting breakdowns, anticipating maintenance and even parts replacement.

The more points monitored, the more data received, the faster and better the system becomes. And the sooner it’s engaged, the more the benefits compound.

The benefits for CoolTech:

  • Faster problem resolution which reduces time spent on troubleshooting and increases productivity
  • Dependable fault detection which decreases repair and replacement costs
  • Remote data gathering through telematics combined with analytics may reveal faulty service processes and components.

The benefits for our customers:

  • Increased employee availability as problems are fixed faster
  • Times savings as problems are fixed remotely without dispatching a repairman or bringing the vehicle into the shop
  • Cost reductions as fewer spare parts are used and fewer service dispatches are needed
  • Reduction in training time for new staff
  • Improved knowledge sharing raises skill level of operators and maintenance personnel

This is just the beginning. There are a couple of new developments on the horizon which should magnify the AI’s benefits for CoolTech even more.

AI Is Learning to Write Code and to Build Its Own, More Intelligent AI

Researchers at Microsoft and the University of Cambridge have created a machine learning system that can write its own code. This could enable non-coders to simply describe an idea for a program and let the system build it.

The system creates new programs by piecing together lines of code taken from existing software – just like a programmer — except AI can search much faster and more thoroughly than a human coder. It scours vast databases of source code and sorts the fragments according by their probable usefulness.

Older systems take minutes to experiment with different combinations of code before piecing together a functional program. The Microsoft system created working programs in fractions of a second. And because it learns which combinations of code work and which don’t, it improves every time it faces a new problem.

Google’s new approach to machine learning relies on neural networks that mimic the way the brain learns. It enables AI technology to create new networks that are more powerful, efficient, and easy to use. The company expects this to inspire new types of networks to handle new types of computing and within five years to make it possible for non-experts to create neural nets tailored to their particular needs.

So, customized computer programs and customized AI are on the horizon.

Embracing AI can be a powerful competitive advantage

Consider the Internet of Things a precursor to the seamless integration of intelligent systems. Currently, it enables physical devices to connect and communicate with digital systems. The telematics incorporated in the MG system is a good example. Now add AI with its ability to learn, adapt and evolve over time. Billions of data points can get incorporated in a database, sorted, analyzed and used to eliminate faults, refine processes, improve outcomes and create new methods of achieving a desired goal.

That portends a consistently rising rate of return. And not just on the conceptual or application ends, but on production as well. AI can be used for rapid prototyping or resource allocation to reduce time-to-market. For instance, Autodesk’s new computer-aided design system draws on the power of the cloud to create thousands of virtual prototypes and compare their function, cost and material against specified criteria. According an article by Accenture, Berg Health used AI to halve the development cost of a single drug from $2.6 billion to $1.3 billion.

Imagine the potential when you have patents already in place — a foundation for AI to analyze and build from. Patents that address a problem common to electronics, processes involving friction or all moving machines: heat. We firmly believe that AI will lead to the faster and fuller realization of the applications for our technology in the marketplace.

Cool Technologies currently has seven patents and another seven pending or applied for.