Counter-terrorism authorities have, for years, characterized keeping up with terrorist organizations and their use of digital tools and social media apps as a game of Whac-a-Mole. Jihadist terrorist groups such as Islamic State and its predecessor al-Qaida, or even the neo-Nazi group the Base, have leveraged digital tools to recruit, covertly finance via crypto, download weapons for 3D printing and spread tradecraft to its followers, all while leaving law enforcement and intelligence agencies playing catch up. Over time, thwarting attacks and maintaining the technological advantage over these types of terror groups has evolved, as more and more open source resources become available. Now, with artificial intelligence – both on the horizon as a rapidly developing technology and in the here and now as free, accessible apps – agencies are scrambling. Sources familiar with the US government's counterterrorism efforts told the Guardian that multiple security agencies are very concerned about how AI is making hostile groups more efficient in their planning and operations.

If you had "leaking classified US military documents for the lulz" on your 2023 Bingo card, congratulations. The fast-paced drama surrounding the online disclosure of top-secret material ripped through this week's news. We'll dive into the details below, but there's one key takeaway: This bizarre kind of leak may be only the beginning. Anyone worried about chaos agents of a different variety now have a new way to protect their online identities. LinkedIn this week began to roll out new tools that allow you to verify your identity and your job.

Over the weekend, experimenters discovered that OpenAI's new chatbot, ChatGPT, can hallucinate simulations of Linux shells and role-play dialing into a bulletin board system (BBS). The chatbot, based on a deep-learning AI model, uses its stored knowledge to simulate Linux with surprising results, including executing Python code and browsing virtual websites. Last week, OpenAI made ChatGPT freely available during a testing phase, which has led to people probing its capabilities and weaknesses in novel ways. I want you to act as a Linux terminal. I will type commands and you will reply with what the terminal should show.

The world of mobile apps is changing, and it's all thanks to artificial intelligence (AI). An increasing number of companies are investing in AI technology that can be used to improve their products and services. But why should you care? What types of impacts could this have on your business? Let's explore some ways that AI will impact the development process for mobile apps: AI-powered personal assistants are becoming increasingly popular, and they can help with a range of tasks.

In my previous column, I looked at the problem of artificial intelligences forcing hardware to consume too much power, which could lead to an unsustainable spike in demand at data centers in this country by 2025. To test out their appetites for more power, I employed several advanced artificial intelligences, and also their close cousins machine learning, cognitive computing, deep learning and advanced expert system technology. For that column, I only measured how much power they consumed, but my original intention was to actually test them out to show some innovative things the technology was accomplishing. I am circling back to that effort now. For many years we have been reporting on the technology of artificial intelligence, about how it's being built out and made more efficient, or how it can be paired with other technologies like quantum computing to become even more accurate.

Through the pixel fuzz of a sputtering Zoom connection, it's hard to be sure if the eyes staring out from the laptop screen are human. Lars Buttler is a real person, but he is the CEO of AI Foundation, a company that makes fake ones: trainable, artificially intelligent agents that might one day take the place of a human personal assistant, a customer service representative, or you yourself (if you aspire to omnipresence or digital deathlessness). When Buttler appeared in a Zoom call last week, there was something strange about the light hitting his shaved head, and the stark white office behind him definitely wasn't part of the material world. His speech was awkward, with overlong pauses and canned jokes that fell on a silent audience, but video calls are like that, at least for now, while people adjust to working lives forced into the ether. His eyes seemed awake and alive in a way that the faces of the other participants in the Zoom call--venture capitalist, a tech founder, and an activist, all of them puppeted by artificial intelligence--were not.

Ai News page, brings together the best news on AI topics from reliable sources and platforms. We've curated and vetted the content, so you don't have to worry about its veracity and usefulness. We understand that your time is limited. That's why we only include those articles that will benefit you the most. For ease of use, we've divided Ai News page into three distinct sections -- News, Social Media Engagement and Chat.

AiNews.page, brings together the best news on AI topics from reliable sources and platforms. We've curated and vetted the content, so you don't have to worry about its veracity and usefulness. We understand that your time is limited. That's why we only include those articles that will benefit you the most. Below is a brief description on what you can expect from each section.

Given a certain complexity level, humanized agents may select from a wide range of possible tasks, with each activity corresponding to a transient goal. In general there will be no overarching credit assignment scheme allowing to compare available options with respect to expected utilities. For this situation we propose a task selection framework that is based on time allocation via emotional stationarity (TAES). Emotions are argued to correspond to abstract criteria, such as satisfaction, challenge and boredom, along which activities that have been carried out can be evaluated. The resulting timeline of experienced emotions is then compared with the `character' of the agent, which is defined in terms of a preferred distribution of emotional states. The long-term goal of the agent, to align experience with character, is achieved by optimizing the frequency for selecting the individual tasks. Upon optimization, the statistics of emotion experience becomes stationary.

I like to keep regular tabs on the state of data science education in America. As one of the hottest fields in the economy, I find that the quality of data science courses is a leading indicator of the state of online education innovation. So, when I see significant new develops in online education technology, I'll dedicate some time to taking the course (and, selfishly, I like to learn new data skills). One website that I've used before, Udacity, recently launched several new courses on artificial intelligence, machine learning and statistics. I've had mixed experiences with Udacity in the past.