Whether they are called manifestos or contracts, the documents published by political parties ahead of an election are rather less substantial than their many pages would suggest. They are full of best-case scenarios, undetailed proposals and dubious costings, and it is hard to picture the impact each party would have on the UK if they followed through with their pitches. So I've been feeding party literature into the political strategy video game Democracy 4, to see how these policies might play out. The results were … well, you'll see. Democracy 4 lets you play out your political fantasies (or nightmares) to see the impact of your choices and, ultimately, if you can get re-elected.

Days after laying off more than a thousand employees from Pixel, Nest, Fitbit, Google Assistant and core engineering divisions, Google is cutting "hundreds of roles" on its advertising sales team, a company spokesperson told Engadget on Tuesday. "Every year we go through a rigorous process to structure our team to provide the best service to our Ads customers," the company said in a statement. "We map customers to the right specialist teams and sales channels to meet their service needs. As part of this, a few hundred roles globally are being eliminated and impacted employees will be able to apply for open roles on the team or elsewhere at Google." The spokesperson declined to share information about the exact number of employees impacted by the cuts or where they were located.

Incumbents like CBA are increasingly looking to A.I. technology to solve their business problems and are eyeing external tech partners to source those A.I. solutions. But these traditional companies have faced challenges nurturing meaningful collaborations that maximize the support they get from A.I. players. Only 1 in 5 incumbents found the right kind of A.I. player, like H20.ai is for CBA, that offers access to custom technology, as well as support for talent, training, and change management, prompting the incumbent to overhaul its processes. We call these A.I. players that provide such support transformers. For industry incumbents that are able to identify and effectively collaborate with a transformer, the value is clear.

On Tuesday, New York City public schools banned ChatGPT from school devices and WiFi networks. The artificial intelligence-powered chatbot, released by OpenAI in November, quickly gained a foothold with the public -- and drew the ire of concerned organizations. In this case, the worry is that students will stunt their learning by cheating on tests and turning in essays they didn't write. ChatGPT (short for "generative pre-trained transformer") is a startlingly impressive application, a sneak preview of the light and dark sides of AI's incredible power. Like a text-producing version of AI art (OpenAI is the same company behind DALL-E 2), it can answer fact-based questions and write essays and articles that are often difficult to discern from human-written content.

Not so long ago, AI was the preserve of the largest organisations, mainly because of its cost and complexity. But this is starting to change. As the technology becomes more affordable, the largest hosting providers, such as Microsoft, Amazon and Google, are opening up access to shared resources and pre-packaged AI systems with offerings aimed at smaller businesses. With AI becoming sophisticated enough to program itself, some leading technology providers are even delving into the world of'citizen developers', as David Shrier, professor of practice, AI and innovation at Imperial College Business School, explains. "This capability is growing closer. Under such a model, a small business owner would rent AI capacity from a large tech company and describe a problem verbally to the AI. The computer would then write a program for itself to solve that problem," he says.

The limitations of automated content moderation tools include accuracy and reliability when the content is extremist or hate speech, due to nuanced variations in speech related to different groups and regions, according to a recent account from New America, a research and policy institute based in Washington, DC. Developing comprehensive datasets for these categories of content was called "challenging" and developing a tool that can be reliably applied across different groups and regions was described as "extremely difficult."

A shimmering Ariana Grande emerges from the starry night sky as she begins to run through her biggest pop hits. Dressed in a glistening sequinned two-piece and rocking a towering ponytail with hints of neon pink, the superstar is both levitating and incandescent. This isn't Grande's latest festival outing, nor is the pop star even physically present. Rather, Grande is seen here in an entirely digital form as part of The Rift Tour, an interactive collaboration with the massively popular online video game Fortnite. Rolling out globally this weekend only, it's a unique partnership the brand is dubbing a "musical journey" with the singer, and marks the latest chapter of an emerging relationship between two disparate cultural behemoths: music and video games.

From the earliest themes of artificial intelligence in Greek mythology, people have long thought about AI and the possibilities it may hold. With the advances in computation and mathematics, Alan Turing's 1950 paper on thinking machines sparked the first real developments of this in practice. The first proof of concept was initialised through Allen Newell, Cliff Shaw, and Herbert Simon's, Logic Theorist, a program designed to mimic the problem-solving skills of humans -- considered by many to be the first artificial intelligence program presented in 1956. AI is 60 years young, we're only at the very beginning. Despite its 60 year history and all of the hype in the last few years, there's a long way to go.

When I was digging deeper into robotic process automation to create this curated guide, I realized that I was confused by RPA, artificial intelligence and AI subset machine learning. In many cases the terms are used interchangeably, and that's not correct. The distinction is really about whether they're process driven (RPA) or data driven (AI, ML). I found the simplest explanation on Silvertouch, which states: "RPA is a software robot that performs repetitive tasks while following strict rules. It is like a clerk who is good at clerical jobs. But AI is an umbrella term that involves the simulation of human intelligence and thought process by machines while dealing with plenty of interrelated information."

The last decade has seen remarkable improvements in the ability of computers to understand the world around them. Photo software automatically recognizes people's faces. Smartphones transcribe spoken words into text. Self-driving cars recognize objects on the road and avoid hitting them. Underlying these breakthroughs is an artificial intelligence technique called deep learning.