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World Of Warcraft's 'Shadowlands' expansion arrives on November 23rd

Engadget

November 23rd marks the 16th anniversary of World of Warcraft, and Blizzard plans to celebrate the occasion by giving you plenty more to do in the game. It'll start rolling out the long-awaited Shadowlands update at 6 PM ET on that day. That's four weeks after Blizzard originally planned to release the expansion. The studio delayed the rollout of Shadowlands from October 26th to improve the endgame and polish up the expansion as a whole. To whet your appetite a bit more, a pre-launch warm-up event starts on November 10th, in which you can take on "a flood of the Scourge."


Target's Black Friday has started: Here are early deals to shop

Mashable

Target unveiled its Black Friday 2020 ad on Oct. 29, and some deals are beginning Nov. 1 through Nov. 7, with several already available as of Oct. 29. Here are our top picks from the ad scan. BEST TV DEAL: LG 65-inch NanoCell 81 Series 4K UHD smart TV -- save $300 (available as of Oct. 29) BEST SMART HOME DEAL: Ring Video Doorbell 3 -- save $60 (available as of Oct. 29) In case you haven't heard, even though it's still October, Black Friday has already started. Best Buy, Walmart, and Dell already dropped their Black Friday ads and some early deals have already begun. Target also released its Black Friday ad with some deals running Nov. 1 through Nov. 7, and some already up.


Army improves Abrams tank gun system with upgraded fire control

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Army has been upgrading and augmenting the attack system for its Abrams tank to ensure a clearer view for gunners looking to find, engage and destroy targets. The effort involves upgrading and modifying Kongsberg's Common Remotely Operated Weapons Station, a combat-tested technology that lets soldiers control and fire a vehicle weapon from beneath the protection of armor by virtue of looking at a video screen and leveraging advanced fire-control technology. Kongsberg took 300 systems and manufactured the smaller, lower profile systems the Army wanted to change as a way to help modify the weapons system for more efficient use.


Detecting Alzheimer's Earlier with the Help of Machine-Learning Algorithm

#artificialintelligence

Functional magnetic resonance imaging (fMRI) is a noninvasive diagnostic technique for brain disorders, such as Alzheimer's disease (AD). It measures minute changes in blood oxygen levels within the brain over time, giving insight into the local activity of neurons; however, fMRI has not been widely used in clinical diagnosis. Their limited use is due to the fact fMRI data are highly susceptible to noise, and the fMRI data structure is very complicated compared to a traditional x-ray or MRI scan. Scientists from Texas Tech University now report they developed a type of deep-learning algorithm known as a convolutional neural network (CNN) that can differentiate among the fMRI signals of healthy people, people with mild cognitive impairment, and people with AD. Their findings, "Spatiotemporal feature extraction and classification of Alzheimer's disease using deep learning 3D-CNN for fMRI data," is published in the Journal of Medical Imaging and led by Harshit Parmar, doctoral student at Texas Tech University.


Challenges in operationalizing a machine learning system

#artificialintelligence

The goal of this blog is to cover the key topics to consider in operationalizing machine learning and to provide a practical guide for navigating the modern tools available along the way. To that end, the subsequent blogs will include further detailed architecture concepts and help you apply them to your own model pipelines. This blog series will not explain machine learning concepts but rather to tackle the auxiliary challenges like dealing with large data sets, computational requirements and optimizations, and the deployment of models and data to large software systems. Most classical software applications are deterministic where the developer writes explicit lines of code that encapsulate the logic for the desired behavior. Whereas, the ML software applications are probabilistic where the developer writes a more abstract code and lets the computer write the code in a human unfriendly language i.e. the weights or parameters required for the ML model.


Intel to Acquire SigOpt to Scale AI Productivity and Performance

#artificialintelligence

What's New: Today, Intel announced it will acquire SigOpt, a San Francisco-based provider of a leading platform for the optimization of artificial intelligence (AI) software models at scale. SigOpt's AI software technologies deliver productivity and performance gains across hardware and software parameters, use cases and workloads in deep learning, machine learning and data analytics. Intel plans to use SigOpt's software technologies across Intel's AI hardware products to help accelerate, amplify and scale Intel's AI software solution offerings to developers. "In the new intelligence era, AI is driving the compute needs of the future. It is even more important for software to automatically extract the best compute performance while scaling AI models. SigOpt's AI software platform and data science talent will augment Intel software, architecture, product offerings and teams, and provide us with valuable customer insights. We welcome the SigOpt team and its customers to the Intel family."


How to Use AI for High Volume Recruiting

#artificialintelligence

The job market is governed by one constant--change. Sometimes that change can be anticipated, like seasonal recruitment cycles. In many countries across the world, lockdown restrictions are slowly being relaxed and economies are beginning to reawaken. Consequently, companies can expect to receive a high volume of job applications from candidates eager to return to work. To effectively handle this surge in hiring, talent teams should incorporate AI recruitment tools into their workflows as much as possible.


Growing inequality in AI research

#artificialintelligence

The 2020 presidential election presents two stark paths for the direction of future-focused scientific research, I write with my Axios colleague Alison Snyder. Why it matters: Science is a long game, with today's breakthroughs often stemming from research carried out decades ago, often with government help. That means the person who occupies the White House over the next four years will help shape the state of technology for decades into the future. Where it stands: The Trump administration's record on science is criticized by experts in nearly every field, from climate change to biotechnology to health, who sense that science as a practice has been deprioritized and politicized. Yes, but: Two research areas prioritized under the Trump administration -- AI and quantum information sciences (QIS) -- are at the heart of technonationalism and the global science race, particularly between the U.S. and China.


How Artificial Intelligence Powers B2B Companies - ONPASSIVE

#artificialintelligence

AI and Machine learning concepts are gaining a lot of traction, and these hot trends in technology can transform the way businesses work, mainly in the B2C landscape. It's no surprise that AI is getting the entire spotlight regarding B2C companies than B2B business, mostly because of the significantly larger consumer base. Through AI's profound impact on enhancing customer experience, these technologies transform the digital era's shopping landscape. However, B2B business isn't exempt from the AI revolution; many B2B business operations have their set of challenges which can be nullified or optimized with this latest technology. One of the many ways AI transforms business is by working to establish higher merchandise.


PowerTransformer uses AI to rewrite text to correct gender biases in character portrayals

#artificialintelligence

Unconscious biases are pervasive in text and media. For example, female characters in stories are often portrayed as passive and powerless while men are portrayed as more proactive and powerful. According to a McKinsey study of 120 movies across ten markets, the ratio of male to female characters was 3:1 in 2016, the same it's been since 1946. Motivated by this, researchers at the Allen Institute for Artificial Intelligence and the University of Washington created PowerTransformer, a tool that aims to rewrite text to correct implicit and potentially undesirable bias in character portrayals. They claim that PowerTransformer is a major a step toward mitigating well-documented gender bias in movie scripts, as well as other scripts in other forms of media.