Artificial Intelligence (AI) writers have emerged as a signi ficant force in the realm of content creation. These advanced tools leverage natural language processing techniques to g enerate coherent and logical texts, applicable across vari ous domains such as journalism, advertising, and educational m aterials. This document delves into the capabilities, applications, and implications of AI writers, examining thei r technological underpinnings, market influence, strength s, limitations, future trajectories, and ethical considerat ions. In the rapidly evolving landscape of artificial intelligenc e technologies today, AI models are increasingly being appl ied across various domains, with literary creation being no exc eption.

The Best American Science Fiction and Fantasy 2022, which collects 20 of the best fantasy and science fiction stories of the past year, features a wide range of characters and settings. Guest editor Rebecca Roanhorse made the final selections for this year's volume. "This is not your father's science fiction and fantasy collection," Roanhorse says in Episode 538 of the Geek's Guide to the Galaxy podcast. "I'm excited to see what people are writing, and where the genre is going, and what sort of new voices can be discovered, and how far we can push boundaries and still tell universal stories." P. Djèlí Clark's genre-bending "If the Martians Have Magic" features Haitian priests battling the alien invaders from The War of the Worlds. "I always think my stories are too weird," Clark says.

When my eight-year-old son told me he was making his friends happy and fighting bullies in a video game, I was curious. He told me about Kind Kingdom, a game his school librarian recommended. On his computer, my son walked his character toward a friend whose head was down and handed the other character a heart. The friend picked up his head and smiled. Then my son maneuvered the player along a path and came across a bully who was jumping up and down with his teeth clenched.

Do you have any favorite internal affirmations or mantras you like to offer students to help them feel confident in the face of potential bullies or put-downs? I'm trying to help out my elementary schooler. Right now I'm thinking of sayings along the lines of "I am awesome just as I am," or "I will not let others define me." Additionally, if there are any great all-purpose verbal comebacks or responses that might be applied generally, those would be helpful and welcome as well. Really, I welcome any suggestions you have for helping my child muster up confidence (with kindness). I speak to my students about this all the time.

Welcome to Pushing Buttons, the Guardian's gaming newsletter. If you'd like to receive it in your inbox every week, just pop your email in below – and check your inbox (and spam) for the confirmation email. If you've followed gaming news over the past couple of years, it has been impossible to avoid the many appalling stories about workplace harassment and discrimination that have emerged as part of a long-overdue reckoning in the games industry. As a woman who's worked in the games media for over 15 years, I can only say that I have been grimly unsurprised by the revelations. The consequences that women face for speaking out on these issues has meant that until recently, few were willing to do so publicly.

We already know how powerful techniques such as machine learning and sentiment analyis can be when it comes to deciphering consumer behavior online, and now it seems they can identify bullies, as well. A group of University of Wisconsin researchers have developed a machine learning algorithm that's identifying more than 15,000 tweets per day relating to bullying -- complete with loads of associated sociological insights -- which begs the question of how to act on that data. How do you govern a social web that can be simultaneously a communication platform, a research lab full of unknowing subjects and a boiling-over pot of criminal evidence? In order to train their model, the researchers fed it two sets of tweets -- one they had determined to be about bullying activity and another that was not. Once the model had learned the language identifiers of tweets relating to bullying, it was time to turn it loose on real-world tweets.

Cyberbullying is just as dangerous and huge a problem as regular bullying. Last year, a 12-year-old girl from Florida committed suicide by hanging herself. As the investigation of her demise found out, the reason for her taking her life was cyberstalking and cyberbullying. Two more 12-year-olds were taken into custody after the incident for spreading rumors about the victim online and for inciting her to commit suicide. While bringing many new possibilities to education, technology and Internet accessibility can become a means to harm another person, as seen in this tragic case--and, unfortunately, many others. Part of the problem is that children this young, both bullies and victims, often do not think their actions through and act hastily.

While Americans celebrated a long Labor Day weekend, millions of people in China enrolled in a giant experiment in the future of fake video. An app called Zao that can swap a person's face into movie and TV clips, including from Game of Thrones, went viral on Apple's Chinese app store. The app is popular because making and sharing such clips is fun, but some Western observers' thoughts turned to something more sinister. Zao's viral moment was quickly connected with the idea that US politicians are vulnerable to deepfakes, video or audio fabricated using artificial intelligence to show a person doing or saying something they did not do or say. That threat has been promoted by US lawmakers themselves, including at a recent House Intelligence Committee hearing on deepfakes.

Can machine learning help clean it up? A team of computer scientists spanning the globe think so. They've built a neural network that can seemingly classify tweets into four different categories: normal, aggressor, spam, and bully – aggressor being a deliberately harmful, derogatory, or offensive tweet; and bully being a belittling or hostile message. The aim is to create a system that can filter out aggressive and bullying tweets, delete spam, and allow normal tweets through. The boffins admit it's difficult to draw a line between so-called cyber-aggression and cyber-bullying.

Mutually beneficial behavior in repeated games can be enforced via the threat of punishment, as enshrined in game theory's well-known "folk theorem." There is a cost, however, to a player for generating these disincentives. In this work, we seek to minimize this cost by computing a "Stackelberg punishment," in which the player selects a behavior that sufficiently punishes the other player while maximizing its own score under the assumption that the other player will adopt a best response. This idea generalizes the concept of a Stackelberg equilibrium. Known efficient algorithms for computing a Stackelberg equilibrium can be adapted to efficiently produce a Stackelberg punishment. We demonstrate an application of this idea in an experiment involving a virtual autonomous vehicle and human participants. We find that a self-driving car with a Stackelberg punishment policy discourages human drivers from bullying in a driving scenario requiring social negotiation.