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Category: robotics/AI – Page 1179

Gas turbines are widely used for power generation and aircraft propulsion. According to the laws of thermodynamics, the higher the temperature of an engine, the higher the efficiency. Because of these laws, there is an emerging interest in increasing turbines’ operating temperature.

A team of researchers from the Department of Materials Science and Engineering at Texas A&M University, in conjunction with researchers from Ames National Laboratory, have developed an artificial intelligence framework capable of predicting (HEAs) that can withstand extremely high temperature, oxidizing environments. This method could significantly reduce the time and costs of finding alloys by decreasing the number of experimental analyses required.

This research was recently published in Material Horizons.

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I have a question for you that seems to be garnering a lot of handwringing and heated debates these days. Are you ready? Will humans outlive AI? Mull that one over. I am going to unpack the question and examine closely the answers and how the answers have been elucidated. My primary intent is to highlight how the question itself and the surrounding discourse are inevitably and inexorably rooted in AI Ethics.

A worthy question is whether humans will outlive AI, though the worthiness of the question is perhaps different than what you think it is. All in all, important AI Ethics ramifications arise.

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Facebook (now Meta) popularized the Silicon Valley ethos with the saying “Move fast and break things”. This approach might have worked when disrupting the social media business, but it’s causing all sorts of problems for them as well as other major AI players. Breaking things and moving fast might be the reason why so many AI projects are failing. According to an MIT study, over 85% of AI projects fail to deliver their stated objectives, and 70% of data science projects never make it to fruition. Clearly moving fast and breaking things doesn’t work if you’re not getting closer to success.

There’s a difference between Iterating to Success and Breaking Things.

Early AI winners align organizational and business strategies to build value and manage risk.

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The tool can identify symptoms of dengue, malaria, leptospirosis, and scrub typhus.

The study investigates both statistical and machine learning approaches. WHO has categorized dengue as a “neglected tropical disease.”

A prediction tool based on multi-nominal regression analysis and a machine learning algorithm was developed.

Accurate diagnosis is essential for the proper treatment and ensuring the well-being of patients. However, some diseases present with similar clinical symptoms and laboratory results, making diagnosing them more challenging.

Continue reading “AI could revolutionize healthcare but can we trust it?” | >

This video will address the hypothesis that advances in artificial intelligence (AI) and neurotechnology could trigger a technological singularity. The singularity could involve the development of artificial intelligence (AI) that is superior to human intelligence, effectively blurring or perhaps removing the distinction between humans and machines.

There is no agreement on when artificial superintelligence will be achieved. Still, one thing is sure: we need to think about our collective goals before the alarming trend of technological singularity makes them irrelevant. Whether powered by AI or some other technical method, the singularity will result in a technological tsunami that will pose unprecedented challenges to human civilization and the physical world on all scales.

Subscribe for the latest news on technology, innovation, megaprojects, robots, military technology, aviation, Elon Musk, Tesla, and SpaceX. Inspired by Tech Vision, Simply Tech, Tech Division, Destiny, Ridddle, Future Unity, Tech Space, Pro Robots, Futurity, Elon Musk Evolution, Motech, Top Luxury, Military News & Daily Aviation.

Inspired by Technological Singularity: Will A.I. Take Over?

Continue reading “The Technological Singularity is Near” | >

How expensive and difficult does hyperscale-class AI training have to be for a maker of self-driving electric cars to take a side excursion to spend how many hundreds of millions of dollars to go off and create its own AI supercomputer from scratch? And how egotistical and sure would the company’s founder have to be to put together a team that could do it?

Like many questions, when you ask these precisely, they tend to answer themselves. And what is clear is that Elon Musk, founder of both SpaceX and Tesla as well as a co-founder of the OpenAI consortium, doesn’t have time – or money – to waste on science projects.

Just like the superpowers of the world underestimated the amount of computing power it would take to fully simulate a nuclear missile and its explosion, perhaps the makers of self-driving cars are coming to the realization that teaching a car to drive itself in a complex world that is always changing is going to take a lot more supercomputing. And once you reconcile yourself to that, then you start from scratch and build the right machine to do this specific job.

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Summary: A newly developed artificial intelligence model can detect Parkinson’s disease by reading a person’s breathing patterns. The algorithm can also discern the severity of Parkinson’s disease and track progression over time.

Source: MIT

Parkinson’s disease is notoriously difficult to diagnose as it relies primarily on the appearance of motor symptoms such as tremors, stiffness, and slowness, but these symptoms often appear several years after the disease onset.

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