Russian President Vladimir Putin warned Friday (Sept. AI development "raises colossal opportunities and threats that are difficult to predict now," Putin said in a lecture to students, warning that "it would be strongly undesirable if someone wins a monopolist position." Future wars will be fought by autonomous drones, Putin suggested, and "when one party's drones are destroyed by drones of another, it will have no other choice but to surrender." U.N. urged to address lethal autonomous weapons AI experts worldwide are also concerned. On August 20, 116 founders of robotics and artificial intelligence companies from 26 countries, including Elon Musk and Google DeepMind's Mustafa Suleyman, signed an open letter asking the United Nations to "urgently address the challenge of lethal autonomous weapons (often called'killer robots') and ban their use internationally."
Two years after originally announcing it, Medtronic and IBM Watson have launched their joint platform the Sugar.IQ, a digital diabetes assistant. "It is designed for people who are currently using Guardian Connect; so made for people on multiple daily injections. It is a personal assistant a little bit like Alexa or Siri," Huzefa Neemuchwala, global head of digital health solutions and AI at Medtronic, said in a Facebook live informational session. "It is an intelligent assistant that keeps track of all of your information and has all of your information in one place. Then through Watson technology we use this information to power insights so we can better manage your diabetes so that you can spend more time in range."
IBM Watson Health has announced a joint initiative with the US Food and Drug Administration to study the use of blockchain technology to share health data to ultimately improve public health. At first, the two-year collaboration will focus on oncology data, pulling together and exchanging data from a variety of sources including that from clinical trials, genomic data, EMRs, and from miscellaneous Internet of Things data from wearables, apps and connected devices. IBM and the FDA will look at how the technology can facilitate information exchange across a spectrum of data types, including clinical trials and real world data. For example, patient-generated data from connected devices could provide clinicians with more insights into population health, potentially offering up research opportunities and ways to leverage large quantities of data into biomedical and healthcare industries. At the core of the collaboration is blockchain technology, which allows secure data sharing between organizations more freely and has been increasingly favored among industry leaders.
The first FDA-approved AI system for diagnosing eye diseases caused by diabetes is completely autonomous, and doesn't require a doctor to interpret the results. Several corporations including Google and DeepMind have been working on building algorithms for diabetic retinography, a leading cause of blindness amongst adults. The first biz to release a device approved by the US Food and Drug Administration (FDA) earlier this year in April, however, is less well-known. IDx LLC, an AI diagnostics company based in Iowa, developed the tool known as IDx-DR. The details about the system were published in a paper in Nature Digital Medicine on Tuesday.
Z Advanced Computing, Inc. (ZAC) of Potomac, MD announced on August 27 that it is funded by the US Air Force, to use ZAC's detailed 3D image recognition technology, based on Explainable-AI, for drones (unmanned aerial vehicle or UAV) for aerial image/object recognition. ZAC is the first to demonstrate Explainable-AI, where various attributes and details of 3D (three dimensional) objects can be recognized from any view or angle. "With our superior approach, complex 3D objects can be recognized from any direction, using only a small number of training samples," said Dr. Saied Tadayon, CTO of ZAC. "For complex tasks, such as drone vision, you need ZAC's superior technology to handle detailed 3D image recognition." "You cannot do this with the other techniques, such as Deep Convolutional Neural Networks, even with an extremely large number of training samples. That's basically hitting the limits of the CNNs," continued Dr. Bijan Tadayon, CEO of ZAC.