We also want several types of topic shifts to Dialogue is at the core of human behaviour and happen. Even though oral face-to-face exchange being able to identify the topic at hand is crucial is the most complete form of dialogue, it is also to take part in conversation. Nevertheless, from a the most complicated to collect due to material and scientific point of view, the notion of topic is somewhat human constraints. Therefore we chose to collect elusive. Mittwoch et al. (2002) and Raymond our corpus through a written messaging tool similar (2004) focus on topic shift markers, while Howe to the one developed by Healey and Mills (2009).

Bi-directional communication between humans and swarm systems begs for efficient languages to communicate information between the humans and the Artificial Intelligence (AI)-enabled agents in a manner that is most appropriate for the context. We discuss the criteria for effective teaming and functional bi-directional communication between humans and AI, and the design choices required to create effective languages. We then present a human-AI-teaming communication language inspired by the Australian Aboriginal language of Jingulu, which we call JSwarm. We present the motivation and structure of the language. An example is used to demonstrate how the language operates for a shepherding swarm guidance task.

Recently, TikTok made a change to its U.S. privacy policy, allowing the company to "automatically" collect new types of biometric data, including what it describes as "faceprints" and "voiceprints." TikTok's unclear intent, the permanence of the biometric data and potential future uses for it have caused concern among experts who say users' security and privacy could be at risk. On June 2, TikTok updated the "Information we collect automatically" portion of its privacy policy to include a new section called "Image and Audio Information," giving itself permission to gather certain physical and behavioral characteristics from its users' content. The increasingly popular video sharing app may now collect biometric information such as "faceprints and voiceprints," but the update doesn't define these terms or what the company plans to do with the data. "Generally speaking, these policy changes are very concerning," Douglas Cuthbertson, a partner in Lieff Cabraser's Privacy & Cybersecurity practice group, tells TIME.

I recently surveyed danish CIO's(Chief information officers) about their relationship with AI and I had some interesting results. One of the results was that one of the biggest barriers to get started on AI projects is that building the business case is difficult. I completely understand the issue and I agree with the CIO's. Building an AI business case is difficult and if you try to build it as a traditionnel IT business case it's down right impossible. Building a business case is all about understanding the cost and revenue drivers well enough to work them into a model that yields a profit with high certainty within an agreed timeline.

Whether to give rights to artificial intelligence (AI) and robots has been a sensitive topic since the European Parliament proposed advanced robots could be granted "electronic personalities." Numerous scholars who favor or disfavor its feasibility have participated in the debate. This paper presents an experiment (N=1270) that 1) collects online users' first impressions of 11 possible rights that could be granted to autonomous electronic agents of the future and 2) examines whether debunking common misconceptions on the proposal modifies one's stance toward the issue. The results indicate that even though online users mainly disfavor AI and robot rights, they are supportive of protecting electronic agents from cruelty (i.e., favor the right against cruel treatment). Furthermore, people's perceptions became more positive when given information about rights-bearing non-human entities or myth-refuting statements. The style used to introduce AI and robot rights significantly affected how the participants perceived the proposal, similar to the way metaphors function in creating laws. For robustness, we repeated the experiment over a more representative sample of U.S. residents (N=164) and found that perceptions gathered from online users and those by the general population are similar.

To the delight of binge-watchers everywhere, it's no longer prohibitively expensive to purchase a giant television. And those devices are also getting smarter, with features like voice commands, personalized recommendations, and built-in apps for Netflix and other streaming services. It's almost impossible to buy a TV without them. The average consumer might ascribe the declining price to a variant of Moore's law. "Right now, you're paying with your data, but you don't know the price," says Casey Oppenheim, CEO of Disconnect, a privacy-focused software company.

While I don't need to convince you on the importance of good information, I often find myself in the position to convince businesses to do more with theirs. In fact, data should be the most important thing on the agenda. That may be more of a stretch for most. After the Scientific Revolution, knowledge was defined by our ability to apply mathematics to empirical data. Intelligence is the ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context.

PyPocketExplore is a CLI-based and web-based API to access Pocket Explore data. It can be used to collect data about the most popular Pocket items for different topics. An example usage would be crawling the data and use it as a training set to predict the number of pocket saves for a web page. The easiest way to install the package is through PyPi. This should get you up-and-running pretty quickly.

Uber is coming closer to its self-driving cars goal. The ride-sharing company announced Monday it launched Uber AI Labs, a new department based in San Francisco which will focus on research in artificial intelligence and machine learning. Uber also revealed it has acquired the AI research startup Geometric Intelligence. The 15 members of the startup will form the primary core of the AI Labs team. With the company's new moves, Uber is betting that artificial intelligence could improve its services.

Apple, like practically every mega-corporation, wants to know as much as possible about its customers. But it's also marketed itself as Silicon Valley's privacy champion, one that--unlike so many of its advertising-driven competitors--wants to know as little as possible about you. So perhaps it's no surprise that the company has now publicly boasted about its work in an obscure branch of mathematics that deals with exactly that paradox. At the keynote address of Apple's Worldwide Developers' Conference in San Francisco on Monday, the company's senior vice president of software engineering Craig Federighi gave his familiar nod to privacy, emphasizing that Apple doesn't assemble user profiles, does end-to-end encrypt iMessage and Facetime and tries to keep as much computation as possible that involves your private information on your personal device rather than on an Apple server. But Federighi also acknowledged the growing reality that collecting user information is crucial to making good software, especially in an age of big data analysis and machine learning.