If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
It is compact and to the point giving you practical "templates" on how to apply different classes of DL algorithms in PyTorch. PyTorch is a Python framework developed by Facebook to develop and deploy Deep Learning models. It is one of the most popular Deep Learning frameworks nowadays. You will learn everything that is needed for developing and applying deep learning models to your own data. All relevant and state of the art model architectures will be covered.
You want to be able to perform your own data analyses with R? You want to learn how to get business-critical insights out of your data? Or you want to get a job in this amazing field? In all of these cases, you found the right course! We will start with the very Basics of R, like data types and -structures, programming of loops and functions, data im- and export. Then we will dive deeper into data analysis: we will learn how to manipulate data by filtering, aggregating results, reshaping data, set operations, and joining datasets.
"The artificial intelligence research community doesn't necessarily have a complete understanding of what neural networks are doing; they give us good results, but we don't know how or why," said Haydn Jones, a researcher in the Advanced Research in Cyber Systems group at Los Alamos. "Our new method does a better job of comparing neural networks, which is a crucial step toward better understanding the mathematics behind AI." Jones is the lead author of the paper "If You've Trained One You've Trained Them All: Inter-Architecture Similarity Increases With Robustness," which was presented recently at the Conference on Uncertainty in Artificial Intelligence. In addition to studying network similarity, the paper is a crucial step toward characterizing the behavior of robust neural networks. Neural networks are high performance, but fragile. For example, self-driving cars use neural networks to detect signs.
A June labor complaint filed to the NLRB claimed that Activision Blizzard discriminated and retaliated against current and former quality assurance testers for their union activity in various ways, including laying off 12 quality assurance testers, reorganizing the studio to remove the quality assurance department, withholding benefits and soliciting grievances. The NLRB also found that the company asked workers to air grievances while they were awaiting a union vote back in May. It is still investigating other parts of the complaint.
Deutsche Bank wants to get in on the trend of banks trying to grab buy now/pay later market share from fintechs, and part of its planning is ensuring bad transactions can get identified as early as possible. "Instant payment needs instant fraud checks," said Kilian Thalhammer, head of merchant solutions for Deutsche Bank. Deutsche Bank has added artificial intelligence from Visa subsidiary Cybersource, which enables merchants to obtain a fraud risk score for transactions. The technology will cover all payments, and will play a role in the bank's pilot of its BNPL product. Banks sense an opportunity in BNPL as nonbank competitors struggle.
With the recent launch of artAIstry, owner Jeff Ganim is on a mission to bring beauty to humanity with his company's captivating AI-produced images. SAN DIEGO, CA – While some critics consider AI-produced images a threat to the traditional creation of art, AI creators like Jeff Ganim hope to demonstrate that this unique, picture-making technique is more friend than foe. "AI art is like a highly advanced paintbrush. It's another tool to add to the artists' toolkit – like when photography was first invented," Ganim said. "Machines are not taking over the human creative process. They are actually enhancing it."
It's the story that has rocked chess and shown no sign of abating. The cheating scandal which has engulfed the sport, involving five-time world champion Magnus Carlsen, is all anyone is talking about. On Monday, Carlsen explicitly accused fellow grandmaster and rival Hans Niemann of cheating for the first time in a lengthy statement on Twitter. The accusation comes weeks after the Norwegian withdrew from the Sinquefield Cup in St. Louis, Missouri, on September 19 following his surprise defeat to the American. "When Niemann was invited last minute to the 2022 Sinquefield Cup, I strongly considered withdrawing prior to the event. I ultimately chose to play," Carlsen wrote.
The University of Illinois Urbana-Champaign (UIUC) is partnering with Amazon, Apple, Google, Meta, Microsoft and non-profit partners in the Speech Accessibility Project. The project's aim is to improve current speech recognition capabilities so that everyone, including people with disabilities and diverse speech patterns, can take advantage of speech recognition systems. "The option to communicate and operate devices with speech is crucial for anyone interacting with technology or the digital economy today," said Mark Hasegawa-Johnson, the UIUC professor of electrical and computer engineering who's leading the project. "Speech interfaces should be available to everybody, and that includes people with disabilities." Currently, many speech recognition systems, such as voice assistants and translation tools, fail to recognize a wide range of speech patterns, including those often associated with disabilities such as Lou Gehrig's disease or Amyotrophic Lateral Sclerosis, Parkinson's disease, cerebral palsy, and Down syndrome Therefore, people who belong to these communities can oftentimes not take advantage of the benefits that speech recognition software can offer. However, through the use of artificial intelligence and machine learning, technology companies can make their voice recognition software more inclusive, and that is the goal of the Speech Accessibility Project.
Elon Musk has been promising the world a humanoid robot called Optimus for more than a year, but the two prototypes unveiled last week did not exactly dazzle with agility. The company's most advanced robot--made with all Tesla components and close to production-ready, according to Musk--waved unsteadily before being shoved across the stage by three human helpers. "This means a future of abundance, a future where there is no poverty, where you can have whatever you want," Musk said of the machine, which was mounted on a stand and cannot yet walk on its own. "It really is a fundamental transformation of civilization." A second humanoid robot, described by Musk as for "rough development" and made from a mixture of Tesla and off-the-shelf parts, was able to walk forward--very unsteadily.
Welcome to the first post in our multi-part series on how Netflix is developing and using machine learning (ML) to help creators make better media -- from TV shows to trailers to movies to promotional art and so much more. Media is at the heart of Netflix. Through each engagement, media is how we bring our members continued joy. This blog series will take you behind the scenes, showing you how we use the power of machine learning to create stunning media at a global scale. At Netflix, we launch thousands of new TV shows and movies every year for our members across the globe.