Scientists have been able to develop artificial intelligence (AI) capable of besting humans at their own games, but a new study suggests that people may have the upper hand when it comes to intuitive thinking. A team of researchers led by Denmark's Aarhus University associate professor Jacob Sherson managed to develop a game based around complex theoretical science in which human players were "able to find solutions to difficult problems associated with the task of quantum computing," whereas computerized numerical optimization failed, according to the scientists' findings published in Nature. "The big surprise we had was that some of the players actually had solutions that were of higher quality and of shorter duration than any computer algorithms could find," Mr. Sherson told the Associated Press. The game, Quantum Moves, is available online for the purpose of helping in the development of quantum computing. While it functions as entertainment, Quantum Moves is built to take quantum physics optimization problems and turn them into a game, the results of which demonstrate fundamental differences between human thought processes and the problem solving of computers.

From the visual input, we get very quickly to a point where we have representations of objects and we can reason about what they do. I think right now, it's still unclear whether deep learning really also has this kind of thing, or whether it just learned something where it can do a good prediction or not.

Artificial consciousness[1] (AC), also known as machine consciousness (MC) or synthetic consciousness (Gamez 2008; Reggia 2013), is a field related to artificial intelligence and cognitive robotics. The aim of the theory of artificial consciousness is to "define that which would have to be synthesized were consciousness to be found in an engineered artifact" (Aleksander 1995). Neuroscience hypothesizes that consciousness is generated by the interoperation of various parts of the brain, called the neural correlates of consciousness or NCC, though there are challenges to that perspective. Proponents of AC believe it is possible to construct systems (e.g., computer systems) that can emulate this NCC interoperation.[2] Artificial consciousness concepts are also pondered in the philosophy of artificial intelligence through questions about mind, consciousness and mental states.[3] As there are many hypothesized types of consciousness, there are many potential implementations of artificial consciousness. In the philosophical literature, perhaps the most common taxonomy of consciousness is into "access" and "phenomenal" variants. Access consciousness concerns those aspects of experience that can be apprehended, while phenomenal consciousness concerns those aspects of experience that seemingly cannot be apprehended, instead being characterized qualitatively in terms of "raw feels", "what it is like" or qualia (Block 1997).

Artificial intelligence (AI), one of 20 core technologies I identified back in 1983 as the drivers of exponential economic value creation, is rapidly working its way into our lives from Amazon's Alexa and Facebook's M, to Google's Now and Apple's Siri. An example of how far AI has come is the recent news that a Google supercomputer, using its advanced AI software, was able to win a stunning 3-0 victory in a man vs. machine face-off against Go grandmaster, one of the game's all-time champions. For those who are not familiar with Go, it is a 3,000-year-old game that is widely considered to be the most complex game ever invented because it is reported to have more possible board configurations than there are atoms in the universe. Until just a few months ago, it was thought that a computer could not defeat a human grandmaster for at least another decade due to the game's complexity. How did Google's AlphaGo program advance so much faster than many expected?

When it comes to human senses, we've found ways to reproduce the look and sound of the real world reasonably accurately. There are even technologies for reproducing the feel of certain experiences, such as flight and car simulators. But the problem of reproducing smell is much more intractable. The 1960 SmelloVision experiment is a case in point. This involved some 30 odors that were released into the cinema at certain times during a movie.

In 2008, Max Yankelevich was in India, visiting the cubicle farms where big banks and insurance companies outsource business processes -- the invoices, memos, and other papers pushed to keep organizations humming. The employees were smart, says Yankelevich, who was running a cloud computing startup at the time. There was good money in doing this sort of back office work -- but it was mind numbing. Companies were trying to figure out the back office work with "the brute force of human power," says Yankelevich, who studied artificial intelligence while getting his MIT computer science degree in the 1990s. "I started thinking ... there's gotta be a way where artificial intelligence can be used generically enough to learn some of these things that these people are doing," he says.

Today I spoke at F8 about how the Applied Machine Learning (AML) team at Facebook is working with dozens of product teams across the company to give people communication superpowers through AI. To do this, we built an AI backbone that powers much of the Facebook experience and is used actively by more than 25 percent of all engineers across the company. Powered by a massive 40 PFLOPS GPU cluster that teams are using to train really large models with billions of parameters on huge data sets of trillions of examples, teams across the company are running 50x more AI experiments per day than a year ago, which means that research is going into production faster than ever. Here are a few of the ways that AI powers various Facebook experiences, with some demos that give a glimpse into what's possible by continuing to research and advance the state of the art in AI. Today, 50 percent of the Facebook community does not speak English, and most people don't speak each other's languages.

Since I started tracking chatbots in mid-2014, I've seen many exciting domain-specific use-cases that are genuinely very useful. Working on Nexmo's Chat App API has also given me a unique perspective on a variety of interesting use-cases explored by businesses. I'm delighted by the tonnes of domain-specific chatbots shipped daily because we are'unconsciously' sharing the task of creating the ultimate chatbot that can handle these diverse tasks. Unsurprisingly in the ongoing chatbots arms race; no chatbot on the market today is based on Artificial General Intelligence i.e. there is currently no chatbot that solves all problems and understands every type of task (Facebook is rumoured to be working on'M' that attempts this). Those available mostly use a variety of Machine Learning (ML) techniques with intricate pattern matching logic to understand user interactions in specific domains.

Chatbots, Live video, and VR technology are all on the docket for Facebook's F8 developer conference, and you can watch the livestream here at 9:30am PST with Mark Zuckerberg's keynote starting at 10am. There'll also be more streamed sessions all day today. While Facebook is tight-lipped about exactly what will be revealed today, we've heard from sources some confirmed launches as well as a few rumors. Here's a few things to watch for: Messenger Chatbot APIs – Facebook will launch tools allowing developers to build automated response agents for Messenger, multiple sources confirm. This follows our scoop from February that Facebook had given some developers a Chat SDK for building bots. These bots could replace 1-800 numbers, providing customer service over chat, and use artificial intelligence to deliver ecommerce, news, content, and other experiences.

In the league of continuous additions to the Unicorn Startup List, China makes the maximum number of entries. Though getting in to the list just before some time was rare, the current scenario is getting different. It all turned around when a recently founded biotech startup Icarbonx announced a Series A round of funding on Monday that now values it at US 1 billion. Icarbonx was founded in late of October, 2015. The company aims to "Manage Your Digital Life", as its name suggests; the name centers around "carbon" – the element of life, while the "i" and "X" indicate the company's plan to fuse the internet and artificial intelligence to create something entirely new.