In his book Outliers, Malcolm Gladwell repeatedly mentions what has become known as the "10,000-hour rule", which states that to become world-class in any field you must devote 10,000 hours of "deliberate practice". Whether or not you believe the 10,000-hour figure, many would acknowledge that to become an accomplished legal professional requires considerable legal, communicative and, particularly in in-house environments, interpersonal skills that are often acquired after a tremendous amount of effort exerted over many years. There has been much hoopla about AI-based legal systems that, some might have you believe, may soon replace lawyers (no doubt causing a degree of anxiety among some legal professionals). There is some misunderstanding among many lawyers, and much of the public, about what AI systems are presently capable of. Can a legal AI, based on current technology, actually "think" like a lawyer?

"The game isn't going to tell you if you got that right." It's an ominous way to start a game demo, but one I'm not too surprised by after playing 80 Days and Sorcery! Heaven's Vault is Inkle's new game, and I met up with studio co-founders Jon Ingold and Joseph Humfrey recently to get some hands-on time. At first glance it's a huge step away from Inkle's previous games--where 80 Days and Sorcery mostly played out in text, Heaven's Vault features fully navigable 3D environments. Your character Aliya Elasra is 2D though, her movements more suggested by a series of still frames than fully animated.

Artificial Intelligence (AI) is a technology that has seen a profound rise in attention within the last few years. The increase in the technology's media coverage has been the result of consistent progress made in improving its capabilities. The expansion of AI's capabilities has fostered its adaptation into areas such as business, medicine, and automotive. The concept of AI was once the subject of imaginative thinking found in the realm of literature. Stories ranging from Mary Shelley's Frankenstein to 2004's David Mitchell novel Cloud Atlas all address the concept of and questions surrounding AI.

Canan Dagdeviren [JAH-naan DAH-day-vee-ren] is head of the new'Conformable Decoders' research group at MIT. Scientist Canan Dagdeviren is an interpreter for a language without words. She knows they're both saying something important, speaking the unique language of the body. It's a lexicon that's completely different from the Turkish and English that Dagdeviren speaks every day – but it's one she believes we need to start translating in earnest. She wants to count up our brain pulses, watch our temperature change in real time and observe how we breathe. This is different from the health-monitoring tech inside consumer Fitbits and smart watches that can count each step and monitor every heartbeat.

I recently visited China on a business trip. While there, I decided I wanted to get a pedicure. My search turned into quite the adventure -- one that involved cutting edge translation technology, and a key word lost in translation. Google and Baidu (which is often referred to as China's Google) have built voice translation apps, available here and here. You speak into them, they listen and then they translate into the language you choose.

During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge. Nevertheless, several recent results suggest that data-driven approaches are feasible and quite promising. To facilitate research in this area, we have carried out a wide survey of publicly available datasets suitable for data-driven learning of dialogue systems. We discuss important characteristics of these datasets, how they can be used to learn diverse dialogue strategies, and their other potential uses. We also examine methods for transfer learning between datasets and the use of external knowledge. Finally, we discuss appropriate choice of evaluation metrics for the learning objective.

What are the main differences between NLP for Chinese vs NLP for English? Linguistically speaking, Chinese is an isolating language different from English. There are no spaces between words in Chinese written texts, and Chinese grammatical relations are indicated by word order. These factors have multiplied the difficulty of Chinese disambiguation at lexical, syntactic and semantic levels, since modern linguistic concepts and principles are more suitable for English than for Chinese. Currently, most mainstream NLP methods are language-independent.

Android phone users generally have a stock Android keyboard on their phones unless they opt for a third-party one. Google's new Gboard update will add some new features to the stock keyboard and make real-time translation easy, along with adding new Emojis and GIF features. Language translation on a smartphone needed users to use a third-party app or navigate to Google translate. However, with the new integration, users can simply type a phrase and have it translated in the subject box as the keyboard will automatically make suggestions to translate it into the default language chosen in the settings, Google said in its official blog. The new update will give voice-typing a new dimension.

Planning to Netflix and chill this weekend? The movie you choose to watch may be heavily influenced by Netflix's sophisticated algorithms. Similarly, decisions like where you choose to dine and what you choose to wear are increasingly facilitated by predictive technologies powered by deep learning. Here are five ways that popular consumer tech companies Netflix, Yelp, Yahoo, StitchFix, and Google improve your online experience with artificial intelligence. Historically, watching television is a unidirectional communication channel.

Whether an A.I. ought to be granted patent rights is a timely question given the increasing proliferation of A.I. in the workplace. One might argue that Intellectual Property (IP) laws and IP Rights were designed to exclusively benefit human creators and inventors[7] and thus would exclude non-humans from holding IP rights. However, many IP laws were drafted well before the emergence of A.I. and in any case, do not explicitly require that a creator or inventor be'human.' The World Intellectual Property Organization's (WIPOs) definition of Intellectual Property talks about creations of the mind[9] but does not specify whether it must be a human mind. Similarly, provisions in laws promoting innovation and IP rights, such as the so-called Intellectual Property Clause of the U.S. Constitution[10], also do not explicitly mention a'human' requirement.