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'Assassin's Creed Valhalla' DLC will let you lay siege to Paris this summer


When Assassin's Creed Valhalla new expansion comes out this summer, it will allow players to relieve the Siege of Paris, Ubisoft announced at its Forward E3 event on Saturday. Historically, the 845 CE event culminated with the Vikings occupying the city and doing what they did best, plundering it for all it was worth. How the event will unfold in Valhalla, we'll see, but Ubisoft promised the DLC will include new weapons, gear and abilities for players to discover. Additionally, The Siege of Paris will see the return of a fan favorite feature: black box infiltration missions. Leaning into the franchise's sandbox roots, these will give you an objective to complete, but how you go about accomplishing it will be up to you.

E3 2021: Tracking all of Saturday's latest video game announcements

USATODAY - Tech Top Stories

This year's event will be online only and runs Saturday through Tuesday with a slew of briefings from companies including Microsoft and Nintendo. USA TODAY will be following all the E3 announcements and have already been tracking news and updates from the Summer Game Fest, which began Thursday, including the release date for "Elden Ring," a long-teased game by From Software, the studio behind "Dark Souls" and "Bloodborne," and Game of Thrones creator George R.R. Martin. Among the other games many are most anticipating updates about are "Halo Infinite," due later this year for Xbox Series X/S, Xbox One and Windows PCs, and the "Marvel's Avengers" Black Panther downloadable content. Los Angeles Mayor Eric Garretti appeared in a video appearance in the live E3 pre-show to welcome online viewers and to say, "we look forward do seeing you in person in 2022." 'Hardcore tile management':Why Upwords is the superior word game (ahem Scrabble) The extreme sports game features a variety of sports including snowboarding, dirt biking, and other activities.

A survey of machine learning techniques in adversarial image forensics


Image forensic plays a crucial role in both criminal investigations (e.g., dissemination of fake images to spread racial hate or false narratives about specific ethnicity groups or political campaigns) and civil litigation (e.g., defamation). Increasingly, machine learning approaches are also utilized in image forensics. However, there are also a number of limitations and vulnerabilities associated with machine learning-based approaches (e.g., how to detect adversarial (image) examples), and there are associated real-world consequences (e.g., inadmissible evidence, or wrongful conviction). Therefore, with a focus on image forensics, this paper surveys techniques that can be used to enhance the robustness of machine learning-based binary manipulation detectors in various adversarial scenarios.

In defense of statistical modeling


Data science has been hot for many years now, attracting attention and talent. There is a persistent thread of commentary, though, that says data science's core skill of statistical modeling is overhyped and that managers and aspiring data scientists should focus on engineering instead. Vicki Boykis' 2019 blog post was the first article I remember along these lines. Don't do a degree in data science, don't do a bootcamp…It's much easier to come into a data science and tech career through the "back door", i.e. starting out as a junior developer, or in DevOps, project management, and, perhaps most relevant, as a data analyst, information manager, or similar… While tuning models, visualization, and analysis make up some component of your time as a data scientist, data science is and has always been primarily about getting clean data in a single place to be used for interpolation. More recently, Gartner's 2020 AI hype cycle report acknowledges the role of data scientists but says: Gartner foresees developers being the major force in AI.

Global Big Data Conference


Every day, researchers are marking new milestones in the technology sphere. Artificial intelligence is reaching unprecedented heights, taking humankind along with it. Artificial intelligence defines the ability of machines or models to think and learn from experience. Starting from smart home applications and delivery systems to giant robots in factories and robotic surgeon, everything in the digital era is powered by artificial intelligence and its sub-technologies. After the technology got congested with many achievements, researchers divided it into different types of artificial intelligence for their ease.

Advantages and Disadvantages of Artificial Intelligence and What Does the Future Hold? - Big Data Analytics News


Artificial intelligence aims at stimulating human reasoning in machines. There are advantages and disadvantages associated with artificial intelligence that will be listed in this context. AI technology has made it possible to solve complex problems. For instance, AI technology can aid medical practitioners in detecting ailments such as cancer. Also, AI technology can ensure you have access to insider trade news.

Correlation Explained Visually


Every now and then, someone comes and says "I've finally found a replacement for Pearson correlation". The truth is that -- despite its shortcomings -- Pearson correlation (a.k.a. However, the cold hard formula may be a little hard to grasp. So I've tried to find a visual interpretation of Pearson's r, and I hope that it will help you (like it helped me) to understand it in depth. The most interesting part is the numerator: the "codeviance". In fact, the denominator is just a normalization factor that binds the correlation coefficient between -1 and 1 (see here for the mathematical proof).

Top 5 GPT-3 Successors You Should Know in 2021


OpenAI presented GPT-3 in May 2020 in a paper titled Language Models are Few-Shot Learners. In July 2020, the company released a beta API for developers to play and the model became an AI-rockstar overnight. GPT-3 is the third version of a family of Generative Pre-Trained language models. Its main features are multitasking and meta-learning abilities. Being trained in an unsupervised way on 570GB of Internet text data, it's able to learn tasks it hasn't been trained on by seeing a few examples (few-shot). It can also learn from zero- and one-shot settings, but the performance is usually worse.

Implementing ML Systems tutorial: Server-side or Client-side models?


Developing machine learning models is all fun and good, but after developing them you will probably be looking into deploying them into an app to use them. The question is should you put them on the client-side (which is probably the mobile) or should you put the model on a server, send the data to the server and get the results back? In this article, I am going to be discussing the trade-offs and what those 2 methodologies entail. Server-side machine learning models are the most widely-used ML systems simply because the architecture is more simple to implement. For example, you have an application running on the phone (the client) that classifies images.

An 11-Minute Flight To Space Was Just Auctioned For $28 Million

NPR Technology

Participants sit a Blue Origin space simulator during a conference on robotics and artificial intelligence in Las Vegas on June 5, 2019. On Saturday, Blue Origin announced that an unidentified bidder will pay $28 million for a suborbital flight on the company's New Shepard vehicle. Participants sit a Blue Origin space simulator during a conference on robotics and artificial intelligence in Las Vegas on June 5, 2019. On Saturday, Blue Origin announced that an unidentified bidder will pay $28 million for a suborbital flight on the company's New Shepard vehicle. Amazon billionaire Jeff Bezos is going into space on July 20 on a reusable rocket made by his space exploration company, Blue Origin.