The comparison revealed that people who are lying are less likely to use personal pronouns - such as "I", "me", "mine" - and tend to use more adjectives, such as "brilliant" and "sublime". Reasons for this language use could be that liars try to dissociate themselves from the content of a message, while clouding its meaning in unnecessary description. Other clues that someone is lying include linking sentences to each other so that thoughts appear to be connected, and mirroring the sentence structure of the person they're communicating with. The algorithm is better at detecting lies than the average human. People manage to spot a lie 54 per cent of the time, according to the researchers, whereas the computer lie detector detects it 70 per cent of the time.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

Forget your smartphones and other accessories: voice communication underpinned by artificial intelligence (AI) is going to be the basis for our connected day-to-day lives. And the shift has already begun! Some pointers: a recent survey, which polled a representative sample of 500 US residents, revealed that only 2% of iPhone users have never used the virtual assistant Siri. Meanwhile Google revealed during the Google IO developer festival held in Mountain View in May just how much emphasis the Internet giant is now placing on voice technology. In the very near future, voice might well be used to direct Google searches, a prospect which could explain the firm's massive investment in Google Assistant. Another pointer: we can count on seeing increasingly high-performance and lower-cost artificial intelligence tools.

Artificial intelligence (AI) will soon transform the way we work With recent developments like the launch of Facebook's chatbot store, Apple's acquisition of Emotient, and the release of Viv, a virtual assistant from the founders of Siri, there's no doubt that artificial intelligence (AI) has started to quickly proliferate across consumer applications. Nonetheless, many of these new applications are still more novelty than necessity as their functionality is rudimentary at best, though we've come to rely on them daily – from Amazon product recommendations to Facebook facial recognition (auto tagging). Until consumer-facing AI can usher in new technological advancements that provide deeper and more human-like interaction, it still has a long way to go before it reaches its tipping point.

Artificially intelligent beings, once portrayed in celluloid as gigantic machines inside mammoth control rooms, are now a part of every smartphone (virtual assistants). And as I write this post, technology bigwigs and startups alike are tirelessly engaging in the effort to build the perfect virtual assistant for everyone. In their powerful endeavor, they have been strongly aided by the power of inexpensive, computing platforms in the form of the smartphones. Significant advancements in speech recognition algorithms have also contributed to the optimism. Those who understand technology will also appreciate the fact that access to data through web APIs has also boosted the research and outcome in the domain.

Among all the AI helpers from major tech companies, Google Assistant is the most mysterious. Google has billed Assistant as one component in "the next evolution of Google." Others, such as Danny Sullivan at Search Engine Land, have gone a step further, imploring us to think of Assistant as "Google 2.0." Backchannel's Steven Levy has documented how Google is rebuilding its entire company around the type of machine learning that Assistant will showcase. Yet despite all of Assistant's potential, we know very little about how it'll operate.

Artificial intelligence is either the bright shining future of technology or an insidious threat that could endanger all of mankind, depending on your point of view. Now Google, one of the companies leading the development of AI systems, has set out five key challenges that need to be overcome with the technology - but they are somewhat more mundane than robots rising up to take over the world. Instead, the company sees one of the key problems as being how to stop negative side effects, such as a cleaning robot that knocks over a precious vase to get its job done faster. Google has published a new research paper highlight five challenges it sees as needing to be overcome to prevent AI and robots causing unintended harm. It also says robots need to be programmed in a way so they do not'game the system' – such as simply covering mess in a room with a sheet it cannot see through rather than tidying up. Avoiding Negative Side Effects: How can we ensure that an AI system will not disturb its environment in negative ways while pursuing its goals, e.g. a cleaning robot knocking over a vase because it can clean faster by doing so?

You can hardly talk to a technology executive or developer today without talking about artificial intelligence, machine learning or bots. While everyone agrees on the importance of machine learning to their company and industry, few companies have adequate expertise to do what they wanted the technology to do. Here are some insights into what we can expect in the coming years around ML and AI. If your company isn't using machine learning to detect anomalies, recommend products or predict churn, you will start doing it soon. Because of the rapid generation of new data, availability of massive amounts of compute power and ease of use of new ML platforms (whether it is from large technology companies like Amazon, Google and Microsoft or from startups like Dato), we expect to see more and more applications that generate real-time predictions and continuously get better over time.

With recent developments like the launch of Facebook's chatbot store, Apple's acquisition of Emotient, and the release of Viv, a virtual assistant from the founders of Siri, there's no doubt that artificial intelligence (AI) has started to quickly proliferate across consumer applications. Nonetheless, many of these new applications are still more novelty than necessity as their functionality is rudimentary at best, though we've come to rely on them daily – from Amazon product recommendations to Facebook facial recognition (auto tagging). Until consumer-facing AI can usher in new technological advancements that provide deeper and more human-like interaction, it still has a long way to go before it reaches its tipping point. Enterprise AI, however, offers immediate applications that help solve problems that many companies and workers face today, such as data overload. Companies across a wide range of industries have already taken advantage of AI capabilities in order to help improve both internal and external processes.

Artificial intelligence that can understand and answer any work-related question it is asked has been made available in the UK for the first time. The computer software, called Starmind, uses machine learning to understand queries, then source answers from previous staff conversations on a subject or track down experts within the company who are able to help. Its creators refer to it as'brain technology', adding its aim is to become a central knowledge bank within any company, an instant database of information that can be accessed by anyone. AI software which understands and answers work-related questions has been made available in the UK. Starmind is an artificial intelligence software for the workplace, designed in Switzerland.