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DEELIG: A Deep Learning Approach to Predict Protein-Ligand Binding Affinity - Docwire News

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Protein-ligand binding prediction has extensive biological significance. Binding affinity helps in understanding the degree of protein-ligand interactions and is a useful measure in drug design. Protein-ligand docking using virtual screening and molecular dynamic simulations are required to predict the binding affinity of a ligand to its cognate receptor. Performing such analyses to cover the entire chemical space of small molecules requires intense computational power. Recent developments using deep learning have enabled us to make sense of massive amounts of complex data sets where the ability of the model to "learn" intrinsic patterns in a complex plane of data is the strength of the approach.


Real-time Interpretation: The next frontier in radiology AI - MedCity News

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In the nine years since AlexNet spawned the age of deep learning, artificial intelligence (AI) has made significant technological progress in medical imaging, with more than 80 deep-learning algorithms approved by the U.S. FDA since 2012 for clinical applications in image detection and measurement. A 2020 survey found that more than 82% of imaging providers believe AI will improve diagnostic imaging over the next 10 years and the market for AI in medical imaging is expected to grow 10-fold in the same period. Despite this optimistic outlook, AI still falls short of widespread clinical adoption in radiology. A 2020 survey by the American College of Radiology (ACR) revealed that only about a third of radiologists use AI, mostly to enhance image detection and interpretation; of the two thirds who did not use AI, the majority said they saw no benefit to it. In fact, most radiologists would say that AI has not transformed image reading or improved their practices.


Researchers demonstrate that malware can be hidden inside AI models

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Researchers Zhi Wang, Chaoge Liu, and Xiang Cui published a paper last Monday demonstrating a new technique for slipping malware past automated detection tools--in this case, by hiding it inside a neural network. The three embedded 36.9MiB of malware into a 178MiB AlexNet model without significantly altering the function of the model itself. The malware-embedded model classified images with near-identical accuracy, within 1% of the malware-free model. Just as importantly, squirreling the malware away into the model broke it up in ways that prevented detection by standard antivirus engines. VirusTotal, a service that "inspects items with over 70 antivirus scanners and URL/domain blocklisting services, in addition to a myriad of tools to extract signals from the studied content," did not raise any suspicions about the malware-embedded model.


Artificial intelligence

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The intelligence demonstrated by machines is known as artificial intelligence. Artificial intelligence makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Using these, machines can be designed to accomplish different tasks in different fields. Email filters, digital calls, data analysis are all examples of NLP. Machines can accurately identify and locate objects then react to what they "see" using digital images from cameras, videos, and deep learning models.


ARTIFICIAL INTELLIGENCE

#artificialintelligence

The intelligence demonstrated by machines is known as artificial intelligence. Artificial intelligence makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Using these, machines can be designed to accomplish different tasks in different fields. Email filters, digital calls, data analysis are all examples of NLP. Machines can accurately identify and locate objects then react to what they "see" using digital images from cameras, videos, and deep learning models.


Listed Funds Trust - TrueShares Technology, AI & Deep Learning ETF (LRNZ) gains 0.84% for July 23

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Listed Funds Trust - TrueShares Technology, AI & Deep Learning ETF (NYSE: LRNZ) shares gained 0.84%, or $0.3862 per share, to close Friday at $46.42. After opening the day at $46.33, shares of Listed Funds - TrueSharesnology, AI & Deep Learning ETF fluctuated between $46.50 and $46.01. Friday's activity brought Listed Funds - TrueSharesnology, AI & Deep Learning ETF's market cap to $30,170,400. The New York Stock Exchange is the world's largest stock exchange by market value at over $26 trillion. It is also the leader for initial public offerings, with $82 billion raised in 2020, including six of the seven largest technology deals.


Getting Industrial About The Hybrid Computing And AI Revolution

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For oil and gas companies looking at drilling wells in a new field, the issue becomes one of return vs. cost. The goal is simple enough: install the fewest number of wells that will draw them the most oil or gas from the underground reservoirs for the longest amount of time. The more wells installed, the higher the cost and the larger the impact on the environment. However, finding the right well placements quickly becomes a highly complex math problem. Too few wells sited in the wrong places leaves a lot of resources in the ground.


Deep Learning

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This article would try to address the basic aspects of deep learning. Deep learning attempts to copy the working mechanism of the human brain by combining data inputs, weights, and biases. The basic mechanism of deep learning is to cluster data and make predictions with a high degree of accuracy. Deep learning involves layers that form a neural network. The layers help in improving accuracy and better prediction.


Algorithm Helps Artificial Intelligence Systems Dodge Adversarial Inputs - ELE Times

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In a perfect world, what you see is what you get. If this were the case, the job of Artificial Intelligence systems would be refreshingly straightforward. Take collision avoidance systems in self-driving cars. If visual input to on-board cameras could be trusted entirely, an AI system could directly map that input to an appropriate action--steer right, steer left, or continue straight--to avoid hitting a pedestrian that its cameras see in the road. But what if there's a glitch in the cameras that slightly shifts an image by a few pixels? If the car blindly trusted so-called'adversarial inputs,' it might take unnecessary and potentially dangerous action.


The Basic Idea of Machine learning, Deep Learning, and Artificial Intelligence

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The basic idea of machine learning, deep learning, and AI is to abstract real-life problems into computerized models, then use mathematical methods, statical analysis, or computer algorithms to solve real-life problems.