If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
NEWPORT NEWS, Va., Jan. 30, 2020 – More than 1,600 nuclear physicists worldwide depend on the Continuous Electron Beam Accelerator Facility for their research. Located at the Department of Energy's Thomas Jefferson National Accelerator Facility in Newport News, Va., CEBAF is a DOE User Facility that is scheduled to conduct research for limited periods each year, so it must perform at its best during each scheduled run. But glitches in any one of CEBAF's tens of thousands of components can cause the particle accelerator to temporarily fault and interrupt beam delivery, sometimes by mere seconds but other times by many hours. Now, accelerator scientists are turning to machine learning in hopes that they can more quickly recover CEBAF from faults and one day even prevent them. Anna Shabalina is a Jefferson Lab staff member and principal investigator on the project, which has been funded by the Laboratory Directed Research & Development program for the fiscal year 2020.
Most MRI images datasets are more or less 1000 images where it is divided into two classes of almost equal numbers. Also, I plan on using Deep Convolutional Autoencoders on MRI images on that size. Is there an autoencoder architecture that is able to get good results on small datasets? Any more techniques to do on this kind of problem?
At HIMSS20 next month, two machine learning experts will show how machine learning algorithms are evolving to handle complex physiological data and drive more detailed clinical insights. During surgery and other critical care procedures, continuous monitoring of blood pressure to detect and avoid the onset of arterial hypotension is crucial. New machine learning technology developed by Edwards Lifesciences has proven to be an effective means of doing this. In the prodromal stage of hemodynamic instability, which is characterized by subtle, complex changes in different physiologic variables unique dynamic arterial waveform "signatures" are formed, which require machine learning and complex feature extraction techniques to be utilized. Feras Hatib, director of research and development for algorithms and signal processing at Edwards Lifesciences, explained his team developed a technology that could predict, in real-time and continuously, upcoming hypotension in acute-care patients, using an arterial pressure waveforms.
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Artificial intelligence and machine learning are increasingly embraced by U.S. carriers as they seek to remain competitive and modernize their operations, a new LexisNexis Risk Solutions study has found. Struggles remain, however, in terms of figuring out staffing and proper use of the technology to optimize its benefits. LexisNexis' look at how the top 100 U.S. carriers are using and benefiting from artificial intelligence and machine learning found a robust adoption of the technology and a strong belief in the benefits it will bring. Approximately 62 percent of respondents said they worked for insurance carriers that have already adopted artificial intelligence (AI) and machine learning (ML) initiatives. About 75 percent said they believe AI and ML can provide carriers with a competitive advantage through better decision-making.
National guidance is urgently needed to oversee the police's use of data-driven technology amid concerns it could lead to discrimination, a report has said. The study, published by the Royal United Services Institute (Rusi) on Sunday, said guidelines were required to ensure the use of data analytics, artificial intelligence (AI) and computer algorithms developed "legally and ethically". Forces' expanding use of digital technology to tackle crime was in part driven by funding cuts, the report said. Officers are battling against "information overload" as the volume of data around their work grows, while there is also a perceived need to take a "preventative" rather than "reactive" stance to policing. Such pressures have led forces to develop tools to forecast demand in control centres, "triage" investigations according to their "solvability" and to assess the risks posed by known offenders.
Image classification is the Hello World of deep learning. For me, that project was Pneumonia Detection using Chest X-rays. Since this was a relatively small dataset, I could train my model in about 50 minutes. The dataset I worked with, involved around 4,500 images. And the only reason it took 50 minutes was because the images were high definition.
Microsoft launched on Tuesday, February 18, the first artificial intelligence laboratory at the Bucharest Academy of Economic Studies (ASE), one of the largest economic higher education institutes in Romania. In the new lab, which required an investment of EUR 50,000, the students can find more about machine learning, create and test AI algorithms, store and manage huge volumes of data, or develop applications and platforms themselves, local Republica.ro As of March 3, 11 cloud engineers from Microsoft Romania will hold courses aimed at helping students develop both technical and business innovation skills. The first course to be held in the new cloud lab will focus on the latest innovations in information technology using Azure, Microsoft's cloud computing platform. The next courses will focus on artificial intelligence, and the ASE students will be encouraged to develop their own projects.