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Machine Learning


Real-time Analytics News for Week Ending January 22 – RTInsights

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… an AI/Machine Learning (ML) platform designed to address the needs of … gap between the quantum computing and machine learning communities.


Machine-learned, light-field camera detects 3D facial expressions – News Medical

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The facial expressions in the acquired 3D images were distinguished through machine learning with an average of 85% accuracy – a statistically …


how-artificial-intelligence-will-power-the-next-wave-of-healthcare-innovation-in-future

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Data is certain to revolutionize healthcare in the same way it transformed other industries. But it will need help. Today, healthcare providers are collecting exabytes of patient data from hospitals, clinics, imaging and pathology labs, and more. These data provide a wealth of information about human health but are difficult to understand due to their lack of structure and sheer volume. Fortunately, sophisticated AI and machine learning solutions can carry the torch of innovation.


COVID-19 detection in CT and CXR images using deep learning models

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Infectious diseases pose a threat to human life and could affect the whole world in a very short time. Corona-2019 virus disease (COVID-19) is an example of such harmful diseases. COVID-19 is a pandemic of an emerging infectious disease, called coronavirus disease 2019 or COVID-19, caused by the coronavirus SARS-CoV-2, which first appeared in December 2019 in Wuhan, China, before spreading around the world on a very large scale. The continued rise in the number of positive COVID-19 cases has disrupted the health care system in many countries, creating a lot of stress for governing bodies around the world, hence the need for a rapid way to identify cases of this disease. Medical imaging is a widely accepted technique for early detection and diagnosis of the disease which includes different techniques such as Chest X-ray (CXR), Computed Tomography (CT) scan, etc.


Low-code and no-code AI tools pose new risks

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This is the promise made by enterprise AI company C3 AI in splashy web ads for its Ex Machina software. Its competitor Dataiku says its own low-code and no-code software "elevates" business experts to use AI. DataRobot calls customers using its no-code software to make AI-based apps "AI heroes." They're among a growing group of tech companies declaring that the days of elitist AI are over. They say with software that requires little to no coding at all, even the lowly marketing associate -- now the "citizen data scientist" -- has the power to create and use data-fueled machine-learning algorithms.


Senior Machine Learning Engineer (Matching)

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Beat is the fastest growing ride hailing app in Latin America and a part of the international FreeNow Group, the multi-service mobility joint venture backed by BMW Group and Daimler AG. One city at a time, we are on a mission to develop seamless mobility for a safe and sustainable urban life. We are proud to say we have launched Beat Tesla / Loonshot, the first and largest private all-electric vehicle service in Latin America. As an organization, we are committed to our drivers with ethical practices and a safe working environment. To our customers, we differentiate ourselves from other ride-hailing apps with our super user-friendly app and excellent customer service.


TinyML is bringing deep learning models to microcontrollers

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This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Deep learning models owe their initial success to large servers with large amounts of memory and clusters of GPUs. The promises of deep learning gave rise to an entire industry of cloud computing services for deep neural networks. Consequently, very large neural networks running on virtually unlimited cloud resources became very popular, especially among wealthy tech companies that can foot the bill. But at the same time, recent years have also seen a reverse trend, a concerted effort to create machine learning models for edge devices.


Amazon says first clothing store will be a fashion and technological revelation – RetailWire

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The new concept is built upon machine learning algorithms, according to the retailer, that "produce tailored, real-time recommendations for each …


IT Leaders Consider Security Tech a Part of Business Transformation

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With new threats disrupting business operations and an increasingly strict regulatory environment, security is no longer a risk mitigation activity or a growth inhibitor. Rather, information security is increasingly being viewed as strategic business enabler for the enterprise. That is evident in IDG's 2022 State of the CIO Survey, where IT leaders and line of business (LOB) executives were asked which technologies they expected to have the greatest effect on how their company functions over the next few years. While the respondents list the usual suspects – big data/analytics, AI/machine learning, and cloud infrastructure – in the top 3, 19% say identity and access management has the most potential to significantly impact business operations. In a distributed world, identity and access management (IAM) is instrumental in managing security in a cloud-based world, which makes its placement between cloud infrastructure and cloud databases (picked by 17% of respondents) appropriate.


The importance of invariance in AI 🤖

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Compared to computers, humans and most other vertebrates (including some invertebrates), can learn internal representations of things, such as objects, or concepts, unbelievably fast. Instead of requiring millions of labeled data points, a toddler will understand the concept of a chair with only a handful of examples. How? Do most organisms have a large set of hard-coded procedures encoded in their neural circuitry, that were created and accumulated overtime through evolutionary forces? Considering the evidence, this seems to be very unlikely. We know that organisms do have some hard-coded memories that influence their behaviors and actions, but the number of such procedures is limited.