Remember Skynet, the artificial intelligence that wanted to wipe out humanity in the Terminator movies? Now that is an example of AI gone wrong. Luckily, this will not be the case for us in 2022. AI today is by far not as advanced yet. But the movie does raise a couple of interesting questions.

Artificial intelligence is the capability of a computer system to perform tasks that generally require human intelligence, such as speech recognition, …

It'd be pretty fascinating to see the Democratic Party's latest internal polling on COVID restrictions. We haven't seen it, but it must have been pretty awful, apocalyptic, because something spooked them bad. Over the course of less than a week, the same people who have systematically turned America into a quarantine camp suddenly, out of nowhere, started calling in unison for medical freedom. Suddenly, they sounded like Bobby Kennedy Jr., pretty much all of them. Even the whiny hypochondriacs at The Atlantic Magazine, those neurotic cat owners who've turned COVID hysteria into a religion are now calling for a total abandonment of all Coronavirus restrictions. Believe it or not, that was the headline on The Atlantic's website today.

"Graph algorithms are the driving force behind the next generation of AI and machine learning that will power even more industries and use cases," …

Report Description: Market Strides published report titled Artificial Intelligence In Video Games Market By Type, By Application, Regional Analysis, …

Skydio says the X2D offers up to 35 minutes of flight time, can operate in both day or night, and features artificial intelligence tools that enable …

Cameras that take lens flare-free photos at night, sunlight-readable displays and enhanced durability with tougher and lighter frames: all are …

Art created by artificial intelligence is now being displayed on the outside of the Rotary Centre for the Arts in downtown Kelowna.

Having thrashed mortal champions at poker, chess, Go, and Starcraft, an artificial intelligence program has delivered another humiliation, …

Moderators and automated methods enforce bans on malicious users who engage in disruptive behavior. However, malicious users can easily create a new account to evade such bans. Previous research has focused on other forms of online deception, like the simultaneous operation of multiple accounts by the same entities (sockpuppetry), impersonation of other individuals, and studying the effects of de-platforming individuals and communities. Here we conduct the first data-driven study of ban evasion, i.e., the act of circumventing bans on an online platform, leading to temporally disjoint operation of accounts by the same user. We curate a novel dataset of 8,551 ban evasion pairs (parent, child) identified on Wikipedia and contrast their behavior with benign users and non-evading malicious users. We find that evasion child accounts demonstrate similarities with respect to their banned parent accounts on several behavioral axes - from similarity in usernames and edited pages to similarity in content added to the platform and its psycholinguistic attributes. We reveal key behavioral attributes of accounts that are likely to evade bans. Based on the insights from the analyses, we train logistic regression classifiers to detect and predict ban evasion at three different points in the ban evasion lifecycle. Results demonstrate the effectiveness of our methods in predicting future evaders (AUC = 0.78), early detection of ban evasion (AUC = 0.85), and matching child accounts with parent accounts (MRR = 0.97). Our work can aid moderators by reducing their workload and identifying evasion pairs faster and more efficiently than current manual and heuristic-based approaches. Dataset is available https://github.com/srijankr/ban_evasion.