This raises the question of whether AI — defined as algorithms that mimic human intelligence — can deliver on its potential, and when. The answer is crucial because AI could become the ultimate industry disrupter, threatening tens of millions of jobs in Asia as business processes are automated. In addition, AI is the subject of intense rivalry between the US and China.
Unicorns abound but enthusiasm has dimmed. Will AI fulfil its potential?
Then there is the COVID-19 Open Research Dataset (CORD-19), a multi-institutional initiative that includes The White House Office of Science and Technology Policy, Allen Institute for AI, Chan Zuckerberg Initiative (CZI), Georgetown University’s Center for Security and Emerging Technology (CSET), Microsoft, and the National Library of Medicine (NLM) at the National Institutes of Health (NIH).
The goal of this initiative is to create new natural language processing and machine learning algorithms to scour scientific and medical literature to help researchers prioritize potential therapies to evaluate for further study. AI is also being used to automate screening at checkpoints by evaluating temperature via thermal cameras, as well as modulations in sweat and skin discoloration. What’s more, AI-powered robots have even been used to monitor and treat patients. In Wuhan, the original epicenter of the pandemic, an entire field hospital was transitioned into a “smart hospital” fully staffed by AI robotics.
Any time of great challenge is a time of great change. The waves of technological innovation that are occurring now will echo throughout eternity. Science, technology, engineering and mathematics are experiencing a call to mobilization that will forever alter the fabric of discovery in the fields of bioengineering, biomimicry and artificial intelligence. The promise of tomorrow will be perpetuated by the pangs of today. It is the symbiosis of all these fields that will power future innovations.
In an effort to create first-of-kind microelectronic devices that connect with biological systems, University of Maryland (UMD) researchers are utilizing CRISPR technology in a novel way to electronically turn “on” and “off” several genes simultaneously. Their technique, published in Nature Communications, has the potential to further bridge the gap between the electronic and biological worlds, paving the way for new wearable and “smart” devices.
“Faced with the COVID-19 pandemic, we now have an even deeper understanding of how ‘smart’ devices could benefit the general population,” said William E. Bentley, professor in UMD’s Fischell Department of Bioengineering and Institute for Bioscience and Biotechnology Research (IBBR), and director of the Robert E. Fischell Institute for Biomedical Devices. “Imagine what the world would be like if we could wear a device and access an app on our smartphone capable of detecting whether the wearer has the active virus, generated immunity, or has not been infected. We don’t have this yet, but it is increasingly clear that a suite of technologies enabling rapid transfer of information between biology and electronics is needed to make this a reality.”
With such a device, this information could be used, for example, to dynamically and autonomously conduct effective contact tracing, Bentley said.
Intel’s fifth-generation Loihi chip uses neuromorphic computing to learn faster on less training data than traditional artificial intelligence techniques — including how to smell like a human does and make accurate conclusions based on a tiny dataset of essentially just one sample.
“That’s really one of the main things we’re trying to understand and map into silicon … the brain’s ability to learn with single examples,” Mike Davies, the director of Intel’s Neuromorphic Computing Lab, told me recently on The AI Show podcast. “So with just showing one clean presentation of an odor, we can store that in this high dimensional representation in the chip, and then it allows it to then recognize a variety of noisy, corrupted, occluded odors like you would be faced with in the real world.”
In her new column covering neuromorphic engineering, intelligent robotics, and AI hardware, Sunny Bains looks at attempts to increase connectivity by creating three dimensional systems.
A real-time deep-learning model is proposed to classify the volume of cuttings from a shale shaker on an offshore drilling rig by analyzing the real-time monitoring video stream. As opposed to the traditional, time-consuming video-analytics method, the proposed model can implement a real-time classification and achieve remarkable accuracy. The approach is composed of three modules. Compared with results manually labeled by engineers, the model can achieve highly accurate results in real time without dropping frames.
Introduction
A complete work flow already exists to guide the maintenance and cleaning of the borehole for many oil and gas companies. A well-formulated work flow helps support well integrity and reduce drilling risks and costs. One traditional method needs human observation of cuttings at the shale shaker and a hydraulic and torque-and-drag model; the operation includes a number of cleanup cycles. This continuous manual monitoring of the cuttings volume at the shale shaker becomes the bottleneck of the traditional work flow and is unable to provide a consistent evaluation of the hole-cleaning condition because the human labor cannot be available consistently, and the torque-and-drag operation is discrete, containing a break between two cycles.
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Global neural network software market is set to witness a healthy CAGR of 35.70% in the forecast period of 2019 to 2026.
The new module’s big advantage is that it has its own processor and memory built in, which allows it to analyze video using AI tech like Microsoft’s Azure, but in a self-contained system that’s faster, simpler and more secure to operate than existing methods.
Sony Corp. and Microsoft Corp. have partnered to embed artificial intelligence capabilities into the Japanese company’s latest imaging chip, a big boost for a camera product the electronics giant describes as a world-first for commercial customers.
