South Park's 27th season return featured a jaw-dropping deepfake of Donald Trump that resulted in an official statement from the White House. South Park's 27th season return featured a jaw-dropping deepfake of Donald Trump that resulted in an official statement from the White House. Deepfakes come with risks that demand urgent regulation. But it is vital their potential as a creative and satirical tool isn't stifled S alman Rushdie believes AI will not be a threat to authors until ChatGPT can write " a funny book ". His faith in human over synthetic creativity may hold some truth in the literary space.

Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. This week, our attention is still turned to Stable Diffusion.

Innovations in artificial intelligence (AI) have fundamentally changed the email security landscape in recent years, but it can often be hard to determine what makes one system different than the next. In reality, under that umbrella term significant differences exist in approaches that may determine whether the technology provides genuine protection or simply a perceived notion of defense. The Rise of Fearware When the global pandemic hit, and governments began enforcing travel bans and imposing stringent restrictions, there was undoubtedly a collective sense of fear and uncertainty. As explained in this blog, cybercriminals were quick to capitalize, taking advantage of people's desire for information to send out topical emails related to COVID-19 containing malware or credential-grabbing links. These emails often spoofed the Centers for Disease Control and Prevention (CDC) and, later on, as the economic impact of the pandemic began to take hold, the Small Business Administration (SBA).

We report a data mining pipeline and subsequent analysis to understand the core periphery power structure created in three national newspapers in Bangladesh, as depicted by statements made by people appearing in news. Statements made by one actor about another actor can be considered a form of public conversation. Named entity recognition techniques can be used to create a temporal actor network from such conversations, which shows some unique structure, and reveals much room for improvement in news reporting and also the top actors' conversation preferences. Our results indicate there is a presence of cliquishness between powerful political leaders when it comes to their appearance in news. We also show how these cohesive cores form through the news articles, and how, over a decade, news cycles change the actors belonging in these groups.

More Human Than Human comes along at a time when perhaps no reminder is necessary: leaving life to bots--whether that means machine learning, artificial intelligence, genuine human-like androids, etc.--might get messy for us humans. Westworld gives us one version of a sentient-machine uprising every Sunday, and news cycles like those involving Cambridge Analytica and Facebook provide gentler reminders that creating increasingly intelligent tech platforms can lead to unwanted manipulation and consequences right now. But the new documentary (which debuted at South by Southwest and plays at the acclaimed Hot Docs Festival in Toronto this week) doesn't set out to paint a picture of some futuristic hellscape. Instead, it wants viewers to pause for a second to consider the forever promise of technology. "We grew up in the shadow of the space program, really believing that tech was going to make our lives better," co-director Tommy Pallotta told Ars. "For five decades, we've seen this promise that tech would create more leisure time for us [and] that it'll make all our lives better. It's kind of insane we're still sold the same promise, but what do we really have to show for it?"

Reinforcement Learning, a key Google DeepMind algorithm, could overhaul news recommendation engines and greatly improve users stickiness. After beating a Go Grand Master, the algorithm could become the engine of choice for true personalization. My interest for DeepMind goes back to its acquisition by Google, in January 2014, for about half a billion dollars. Later in California, I had conversations with Artificial Intelligence and deep learning experts; they said Google had in fact captured about half of the world's best A.I. minds, snatching several years of Stanford A.I. classes, and paying top dollar for talent. Acquiring London startup Deep Mind was a key move in a strategy aimed at cornering the A.I. field.

Reinforcement learning, a key Google DeepMind algorithm, could overhaul news recommendation engines and greatly improve users' stickiness. After beating a Go Grandmaster, the algorithm could become the engine of choice for true personalization. My interest for DeepMind goes back to its acquisition by Google, in Jan. 2014, for about half a billion dollars. Later in California, I had conversations with artificial intelligence and deep learning experts; they said Google had in fact captured about half of the world's best A.I. minds, snatching several years of Stanford A.I. classes, and paying top dollar for talent. Acquiring London startup DeepMind was a key move in a strategy aimed at cornering the A.I. field.