A massive interconnection of computing cells, also known as neurons, comprises a neural network, which is the heart and soul of all artificial intelligence (AI) algorithms. Almost 80 years ago, in 1943, neurophysiologist Warren McCullough and mathematician Walter Pitts from the University of Illinois at Chicago first proposed the neural network. After a series of evolutions, the deep neural networks (DNNs) -- which are usually those with more than two hidden layers -- are now used for image recognition, image classification, object detection, speech recognition, language translation, natural language processing (NLP), and natural language generation (NLG). The present Refcard first introduces the concept of a neural network by drawing an analogy with the biological neural network and subsequently walks readers through the essential components of neural networks, which are considered the building blocks. Common neural architectures are discussed thereafter, defining the underlying arrangement of the neurons and the specific purposes they serve.

AI has played a role in overcoming COVID especially in drug discovery and other related areas in fighting the pandemic. AI investment in drug design and drug discovery has increased significantly The percentage of graduates undertaking a PhD in AI has increased There is a big uptake in generative AI in the ability to compose text, audio, and images to a sufficiently high standard that humans have a hard time telling the difference between synthetic and non-synthetic outputs for some constrained applications of the technology. AI has a diversity challenge China overtakes the US in AI journal citations After surpassing the US in the total number of journal publications several years ago, China now also leads in journal citations; however, the US has consistently (and significantly) more AI conference papers (which are also more heavily cited) than China over the last decade. Surveillance technologies are fast, cheap, and increasingly ubiquitous The technologies necessary for large-scale surveillance are rapidly maturing, with techniques for image classification, face recognition, video analysis, and voice identification all seeing significant progress in 2020. AI ethics lacks benchmarks and consensus Though a number of groups are producing a range of qualitative or normative outputs in the AI ethics domain, the field generally lacks benchmarks that can be used to measure or assess the relationship between broader societal discussions about technology development and the development of the technology itself.

The CMOS metal layer is used to create an embedded micro-polarizer able to sense polarization information. This polarization information is shown to be useful in applications like real time material classification and autonomous agent navigation. Further the sensor is equipped with in pixel analog and digital memories which allow variation of the dynamic range and in-pixel binarization in real time. The binary output of the pixel tries to replicate the flickering effect of the insect's eye to detect smallest possible motion based on the change in state. An inbuilt counter counts the changes in states for each row to estimate the direction of the motion.

There is increasing awareness that the greatest problems with artificial intelligence are not primarily technical, but rather how to achieve value from the technology. This was a growing problem even in the booming economy of the last several years, but a much more important issue in the current pandemic-driven recessionary economic climate. Older AI technologies like natural language processing, and newer ones like deep learning, work well for the most part and are capable of providing considerable value to organizations that implement them. The challenges are with large-scale implementation and deployment of AI, which are necessary to achieve value. There is substantial evidence of this in surveys.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. Army test-fired Javelin anti-tank missiles at a recent exhibition in Fort Hood, Texas to demonstrate technological advancement in its fighting capabilities. During a series of weapons drills and exercises, soldiers fired Javelins and .50-caliber A Javelin missile fired by soldiers with the 2nd Stryker Brigade Combat Team, separate from the exhibition in Texas.

After NASA's DART spacecraft successfully completed its first planetary defense test last night, the tiny Light Italian Cubesat for Imaging of Asteroids (LICIACube) spacecraft captured the moment in its messy glory. The Italian space agency released a series of images this afternoon that show a before-and-after comparison of the Didymos asteroid system and a bright burst of debris surrounding Dimorphos. LICIACube is tiny, contains two optical cameras and weighs about 31 pounds. The small spacecraft hitched a ride with DART, which deployed the cubesat on Sept. 11, and is operated from a mission control center in Turin, Italy. 'We're really very proud,' Elisabetta Dotto, science team lead at Istituto Nazionale di Astrofisica (INAF), said during a news conference held in Italian on Tuesday.

Almost weekly a friend or an acquaintance asks me, I want to learn to code; which language should I start with? More or less bi-weekly I get a DM on LinkedIn starting with My son should start programming; what is the best language for him? It's not just people who've never coded before. Often I get these messages from people who have several years of coding experience under their belts. I'm not saying this to complain.

Do you understand the impact of AI on a business strategy well enough to take a proactive role in transforming your organization? If you could use some help in this area, instructor Anil Gupta has you covered. In this course, he shows you how deploying AI tools can boost your company's competitive advantage and help you leapfrog over your competition. Anil explains what AI is and how it is deployed in products and services. He goes over the importance of data for developing AI algorithms, as well as machine learning concepts.

This article was published as a part of the Data Science Blogathon. Quantum computing is poised for prominence due to the exponential increase in computing capacity. Complex problems are challenging for traditional computers to solve but simple for quantum computers, making them the perfect tool for this task. A wealth of opportunities are opened up by such a development in nearly every facet of contemporary life. Google recently grabbed attention by announcing that it has achieved quantum supremacy, wherein its computers can carry out tasks that a traditional computer cannot.

Except, possibly, professionals like her who are tasked with reducing it. Ricks has made her career out of caring about traffic patterns. Before her current role as the associate administrator for research, innovation, and demonstration at the FTA, she was the director of mobility and infrastructure for the City of Pittsburgh in Pennsylvania. She has spent countless hours thinking about cars, public transit, roads, and pedestrians--and how to make it all flow more smoothly. "When you're in the peak times for travel, when the system is so full, it only takes a small disruption to cause really big problems," Ricks says.