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The Walden Pond – How Artificial Intelligence Libraries are Accelerating Investigation and …

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Jay was previously the Chief Strategy Officer at kCura before he founded NexLP, a pioneering AI company in Chicago acquired by Reveal.


AI study reveals the secret of an artistic 'hot streak'

Daily Mail - Science & tech

Whether an artist, scientist, or film director, trailblazers in particular fields often have a critically-acclaimed'hot streak' where they produce a series of outstanding work in short succession. Now, scientists at Northwestern University in Illinois claim to have pinpointed the secret formula that often triggers a pioneer's best work. Using a form of artificial intelligence (AI) called deep learning, they mined data related to thousands of artists, film directors and scientists to identify a magical formula for success. Hot streaks directly result from years of'exploration' (studying diverse styles or topics), immediately followed by years of'exploitation' (focusing on a narrow area to develop deep expertise), they claim. They define a hot streak as a burst of high-impact works clustered together in close succession – as achieved by artists such as Vincent Van Gogh and Jackson Pollock, or film directors like Peter Jackson or Alfred Hitchcock.


Motorola Solutions Launches the First In-Car Video System Enabled by Artificial Intelligence

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The M500, Motorola Solutions' AI-enabled in-car video system for law enforcement, introduces advanced analytics to drive operational efficiency, safety and transparency for law enforcement and citizens. The M500, Motorola Solutions' AI-enabled in-car video system for law enforcement, introduces advanced analytics to drive operational efficiency, safety and transparency for law enforcement and citizens. CHICAGO--(BUSINESS WIRE)--Motorola Solutions today introduced the first AI-enabled in-car video system for law enforcement, the M500. The solution is bringing more powerful capabilities to the police vehicle to enhance awareness and safety while building trust and transparency throughout communities. The M500 features new backseat passenger analytics which automatically start the in-car camera recording as soon as an individual enters the back of a police car.


Artificial cell can be used to destroy germs such as E. coli and clean up pollution in water

Daily Mail - Science & tech

Scientists have developed an artificial cell that can eat bacteria – just like the hungry video game character Pac-Man. The cells are the size of a red blood cell and can be used to'eat' bad bacteria such as E coli, deliver drugs to sites in the body and clean up pollution in water. The Pac-Man cell was created by researchers at New York and Chicago universities by piercing a microscopic hole in a sphere made from a polymer to allow matter to enter or exit. The cell can be made to pump or'eat' by shining a light on it. The research was published in Nature.


An interaction regression model for crop yield prediction - Scientific Reports

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Crop yield prediction is crucial for global food security yet notoriously challenging due to multitudinous factors that jointly determine the yield, including genotype, environment, management, and their complex interactions. Integrating the power of optimization, machine learning, and agronomic insight, we present a new predictive model (referred to as the interaction regression model) for crop yield prediction, which has three salient properties. First, it achieved a relative root mean square error of 8% or less in three Midwest states (Illinois, Indiana, and Iowa) in the US for both corn and soybean yield prediction, outperforming state-of-the-art machine learning algorithms. Second, it identified about a dozen environment by management interactions for corn and soybean yield, some of which are consistent with conventional agronomic knowledge whereas some others interactions require additional analysis or experiment to prove or disprove. Third, it quantitatively dissected crop yield into contributions from weather, soil, management, and their interactions, allowing agronomists to pinpoint the factors that favorably or unfavorably affect the yield of a given location under a given weather and management scenario. The most significant contribution of the new prediction model is its capability to produce accurate prediction and explainable insights simultaneously. This was achieved by training the algorithm to select features and interactions that are spatially and temporally robust to balance prediction accuracy for the training data and generalizability to the test data.


Executive Interview: Chuck Brooks, Cybersecurity Expert - AI Trends

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Chuck Brooks, president of Brooks Consulting, globally recognized as a subject-matter expert on Cybersecurity and Emerging Technologies, sees the coming proliferation of IoT devices as expanding the threat landscape. His experience helps to put it in perspective. In government, he has received two Presidential appointments, by George W. Bush to a legislative position at the Department of Homeland Security, and by Ronald Reagan as an assistant to the director of Voice of America. In industry, Chuck has served in executive roles for General Dynamics, Xerox, Rapiscan Systems, and SRA. Today, Chuck is on the Adjunct Faculty at Georgetown University's Graduate Applied Intelligence Program and the Graduate Cybersecurity Program, where he teaches courses on risk management, homeland security, and cybersecurity. He has an MA in International relations from the University of Chicago, a BA in Political Science from DePauw University, and a Certificate in International Law from The Hague Academy of International Law. He recently spent a few minutes with AI Trends Editor John P. Desmond to discuss the state of cybersecurity today.


#IROS2020 Plenary and Keynote talks focus series #4: Steve LaValle & Sarah Bergbreiter

Robohub

In this new release of our series showcasing the plenary and keynote talks from the IEEE/RSJ IROS2020 (International Conference on Intelligent Robots and Systems) you'll meet Steve LaValle (University of Oulu) talking about the area of perception, action and control, and Sarah Bergbreiter (Carnegie Mellon University) talking about bio-inspired microrobotics. Bio: Steve LaValle is Professor of Computer Science and Engineering, in Particular Robotics and Virtual Reality, at the University of Oulu. From 2001 to 2018, he was a professor in the Department of Computer Science at the University of Illinois. He has also held positions at Stanford University and Iowa State University. His research interests include robotics, virtual and augmented reality, sensing, planning algorithms, computational geometry, and control theory.


Real Talk: Intersectionality and AI

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In 1989, Kimberlé Crenshaw, now a law professor at UCLA and the Columbia School of Law, first proposed the concept of intersectionality. In an article published in the University of Chicago Legal Forum, she critiqued the inability of the law to protect working Black women against discrimination. She discussed three cases, including one against General Motors, in which the court rejected discrimination claims with the argument that anti-discrimination law only protected single-identity categories. Black women, the court said, could not be discriminated against based on the combination of identities, in this case race and gender. Intersectionality, at its core, represents the interconnected nature of our identity.


Machine learning predicts behavior of stainless steel at the microstructural level

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To the naked eye, a sheet of stainless steel presents a smooth, polished, homogenous surface. The same material when viewed at 400 times magnification reveals its true jumbled structure--different crystal shapes, joined at wildly different angles. Researchers at the University of Illinois Urbana-Champaign used data from high-resolution images of stainless-steel samples to train neural networks that make predictions about how the material will behave at places where the crystals meet, when strained. John Lambros explained, when studying the properties of a material such as stainless steel, it is impossible to conduct separate experiments at such high magnifications that subject it to every conceivable parameter--every temperature, every loading angle, every amount of pressure. So we often rely on models.


Surgalign Announces Issuance of U.S. Patent Covering the Use of Artificial Intelligence in Medical Image Segmentation - Surgalign

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The machine learning system is part of HOLO AITM, Surgalign's core technology in artificial intelligence and augmented reality. DEERFIELD, Ill., Aug. 19, 2021 – Surgalign Holdings, Inc., (NASDAQ: SRGA) a global medical technology company focused on elevating the standard of care by driving the evolution of digital surgery, today announced that the United States Patent and Trademark Office (USPTO) recently issued a patent covering a machine learning system for automated segmentation of a three-dimensional bony structure in a medical image. The granted patent expands and further strengthens the company's HOLO AI technology portfolio. "This patent is a foundational element of how we harness technology and data to power our digital surgery platform," said Terry Rich, Surgalign's president and chief executive officer. "While'artificial intelligence' and'machine learning' have become buzzwords that are often misused, misrepresented, and misunderstood, at Surgalign AI is a core competency and a key element of our efficient and highly valuable approach to improving patient's lives."