Lifeboat Foundation

“Today, simple warning systems are the most common means for aiding a rotorcraft aircrew, such as auditory alerts to increase altitude. These warning systems are limiting and can induce unanticipated cognitive burdens on pilots”, says Northrop Grumman. “Studies have shown that inattentional blindness to such warnings can occur, often making them ineffective for the aircrew.”

To help keep the AI assistant in sync with its human users, the software program will use sensors, worn by the pilots, to gauge what each human perceives and knows. The types of sensors were not disclosed, though eye-tracking technologies have been used for similar purposes in the past.

Here’s an interesting thought experiment. Pretend that you took all words at their literal interpretation, all of the time, wherever you went, and acted upon those words strictly and accordingly. For example, suppose you are driving in your car and perchance see a billboard that is touting the message that you should eat at Joe’s Pizzeria, accessible at the next exit up ahead. The normal course of events would be that you would consult your stomach to ascertain whether you are hungry. Furthermore, if you were hungry, the next question is whether you want pizza. Upon deciding that maybe you do want pizza, the next aspect would be whether you want to take the upcoming exit and eat at Joe’s Pizzeria since you might have in mind some other pizza eatery instead. But, none of those sensible and reasonable ideas rattle around in your noggin. We have agreed that you are going to take everything in a meticulously literal way. By gosh, the billboard instructed you to go eat at Joe’s Pizzeria, so that’s what you are going to do. Come heck or high water, you will take the next exit and you will drive straight to that pizzeria and you will order yourself a juicy hot pizza. This might work out okay and you’ll be happy that you obediently abided by the wording of the billboard. Perhaps though this side trip has made you late for work. Your boss won’t especially appreciate that you opted to be tardy because you just had to get a slice of pizza. Ouch, your boss fires you the moment you proffer such a lame excuse.

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Existing AI and Machine Learning is stuck at doing literal interpretation and lacks any common-sense, which bodes for great concerns and especially when it comes to the advent of self-driving cars.

Continue reading “Strict Literal Interpretation Is A Hardheaded Drawback Of Machine Learning And Likewise Bad For AI Self-Driving Cars” »

Over the years, much has been said about artificial intelligence (AI) and the healthcare industry. Much of it has been focused on two extremes. On one hand, there’s the fairly mature use of neural networks for radiological analysis. On the other, there’s the focus on fraud management. Those have become “must have’s” in my perspective. It’s filling the middle ground that interests me. Medical insurance is, as patients, providers, and payors all can agree, is often convoluted and complex. There’s a business problem in making processes more efficient, and the foolishly named robotic process automation (RPA) is only a step in the right direction. More robust AI can help all three stakeholder groups address their needs in managing medical insurance. The general medical insurance industry does deal with radiology and images. However, that’s typically in specialties. In the dental industry, radiology is a regular tool, using x-rays to understand tooth and gum conditions and then to document work that has been done. The basics of AI and radiology have been covered, in this column and many other places, so this article isn’t going to cover the concepts, it’s important to realize how important that analysis is in dental care.

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In this case, it’s increasing the accuracy and speed of dental insurance processing, resulting in better medical control, improved financial outcomes for providers and payors, and improved care and customer service for the patient.

Continue reading “Artificial Intelligence And Dental Insurance — It Is More Than A Focus On Radiology And Fraud” »

Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together.

Elon Musk: Tesla could play a role in Artificial General Intelligence, decentralize Tesla Bot to avoid Terminator scenario.

Quantum computing is still rare enough that merely installing a system in a country is a breakthrough, and IBM is taking advantage of that novelty. The company has forged a partnership with the Canadian province of Quebec to install what it says is Canada’s first universal quantum computer. The five-year deal will see IBM install a Quantum System One as part of a Quebec-IBM Discovery Accelerator project tackling scientific and commercial challenges.

The team-up will see IBM and the Quebec government foster microelectronics work, including progress in chip packaging thanks to an existing IBM facility in the province. The two also plan to show how quantum and classical computers can work together to address scientific challenges, and expect quantum-powered AI to help discover new medicines and materials.

IBM didn’t say exactly when it would install the quantum computer. However, it will be just the fifth Quantum One installation planned by 2023 following similar partnerships in Germany, Japan, South Korea and the US. Canada is joining a relatively exclusive club, then.