AI Is the Big Bad New Platform, But It’s Here to Stay and Grow

It’s time to get real in a technology that is accelerating like no other… perhaps because it can “learn” and teach itself. As nations engage in consensus dialog to contain and limit the export of a growing hardware super computing system – plasma-based computers using qubits vs binary calculations – the growth of AI could multiply for so many reasons. But is the United States where this growth will be concentrated? While these facts do not address quality of the patented creations, they do suggest that China has prioritized AI growth well beyond the metrics of American-based research. As the July 4th Forbes points out these “key facts”:

• China has filed more than 38,000 patents for generative AI inventions since 2014, according to the World Intellectual Property Organization (WIPO), the U.N. agency responsible for overseeing international patent recognition and other issues.

• Generative artificial intelligence is AI software capable of generating outputs like text, images, video and sound in response to a prompt, and generative AI inventions include chatbots like OpenAI’s ChatGPT and Anthropic’s Claude, image generators like Adobe’s Firefly and even scientific tools like protein structure AIs from the Massachusetts Institute of Technology, FrameDiff, and Google DeepMind, AlphaFold.

• The figure, which does not account for other forms of AI such as autonomous driving, reveals China has filed more patents for inventions involving generative AI than all other countries combined, accounting for 70% of the more than 50,000 patents filed globally over the last decade.

The U.S., with nearly 6,300 patents filed since 2014, lags in a distant second place, less than one sixth of China’s total, with South Korea (4,155), Japan (3,409) and India (1,350) coming in third, fourth and fifth, respectively, followed by the U.K. (714), Germany (708), Canada (549) and Israel (311).

“But patent data paints only part of the picture, [Van Anh Le, an assistant professor in intellectual property law at Durham University in the U.K.] stressed. ‘To get a more comprehensive understanding, we should also look at other indicators, such as start-up activity, which can signify the health of the innovation ecosystem,’ as well as the rate at which patents are commercialized. Taking this broader view as it applies to AI, Le said the U.S. has a ‘robust innovation environment,’ pointing to the many AI startup companies emerging from there.”

There are serious national security issues in the offing. The ability to combine a full-on plasma computing system with AI probably creates an ability to break through any security barrier system (sorry blockchain) on Earth, yielding not only vital information but perhaps an ability to take over control of another nation’s entire computing systems at will. China gets it. A growing education-averse American electorate, however, is far more focused on austerity and keeping taxes for the rich low than worrying about an incomprehensible, almost futuristic science fiction, computing battle with the People’s Republic of China.

It’s not all bad. Even as we know AI will have a serious impact on the job market, changing entrepreneurial opportunities beyond our imagination, there’s a reason for the image above. AI is already saving lives, showing extraordinary capacities, particularly in increasing the speed and accuracy of diagnostics, robotically enhanced surgery and the creation of new medications and vaccines, as we have recently witnessed in the COVID pandemic.

The ability of aggregating data, discerning even minute patterns often missed by very competent doctors, is what makes AI such a superstar in diagnostics and radiology. What used to be a painstaking human effort accessing limited available data has been transformed, albeit requiring massive new investments in both hardware and software. Writing for the July 9th Associated Press, Gaurav Singal, a computer scientist and physician at Harvard Medical School and former the chief data officer of Foundation Medicine, a cancer diagnostics company, and. Anupam B. Jena, an economist, physician and professor at Harvard Medical School tell us:

“[Humans], of course, err. Sometimes, misdiagnosis occurs because a doctor overlooks something — when the patterns of illness fit the script, but the script is misread. This happens in an estimated 15% to 20% of medical encounters… Artificial intelligence can help solve… two fundamental problems — if it’s given enough financial support and deployed correctly.

“First, AI is less susceptible to common factors that lead doctors to make diagnostic errors: fatigue, lack of time and cognitive bandwidth when treating many patients, gaps of knowledge and reliance on mental shortcuts. Even when illnesses conform to scripts, computers will sometimes be better than humans at identifying details buried within voluminous healthcare data.

“Using AI to improve the accuracy and timeliness with which doctors recognize illness can mean the difference between life and death. Ischemic stroke, for example, is a life-threatening emergency where a blocked artery impedes blood flow to the brain. Brain imaging clinches the diagnosis, but that imaging must be performed and interpreted by a radiologist quickly and accurately. Studies show that AI, through superhuman pattern matching abilities, can identify strokes seconds after imaging is performed — tens of minutes sooner than by often-busy radiologists. Similar capabilities have been demonstrated in diagnosing sepsis, pneumonia, blood clot in the lungs (pulmonary embolism), acute kidney injury and other conditions.

“Second, computers can be useful for illnesses for which we haven’t developed the right scripts. AI can, in fact, diagnose disease using new patterns too subtle for humans to identify. Consider, for example, hypertrophic cardiomyopathy, a rare genetic condition in which the heart’s muscle has grown more than it should, leading to eventual heart failure and sometimes death. Experts estimate that only 20% of those affected are diagnosed, a process that requires consultation with a cardiologist, a heart ultrasound and often genetic testing. What, then, of the remaining 80%?

“Researchers across the country, including at the Mayo Clinic and UC San Francisco, have demonstrated that AI can detect complex, previously unrecognized patterns to identify patients likely to have hypertrophic cardiomyopathy, meaning AI-driven algorithms will be able to screen for the condition in routine EKGs.

“AI was able to recognize these patterns after examining the EKGs of many people with and without the disease. The rapid growth in healthcare data — including detailed electronic health records, imaging, genomic data, biometrics and behavioral data — combined with advancements in artificial intelligence technology has created a major opportunity. Because of its unique ability to identify patterns from the data, AI has helped radiologists to find hidden cancers, pathologists to characterize liver fibrosis and ophthalmologists to detect retinal disease.” We need to embrace AI, not run from it, even as we must set some ground-rules for its use. We need to educate the American public and minimize what I call the “Terminator fear factor.” Or else…

I’m Peter Dekom, but as much as we must address the realities of AI research and development, we must equally address the growing social undercurrents that devalue education and technology – preferring pejorative labels and conspiracy theories to facts – or watch China in the passing lane with a massive smile on its national face.