The folks over at x.ai – creators of Amy, the artificial intelligence answer to scheduling meetings – have had a shot at showing exactly what it looks like inside their bot's brain, using AI, of course. The team used a powerful deep-learning model, a Recurrent Neural Network (RNN), to trawl 500,000 words in its database, looking at their sequence in a sentence to understand what they mean, then predicting how to categorize them. This year's edition of TNW Conference in Amsterdam includes some of the biggest names in tech. Without a human ever telling the RNN the definitions of different word groups, it has managed to understand that Stanford is different from Instagram, and that Jesse, Luke and Jason are names. This data was cut to down to the 3,500 most frequently used words and has then been projected into a 2D shape in order to show the relationships the AI has made between different words.

For decades robots have won the affection of humans in pop culture -- whether it was R2-D2 in Star Wars or Rosie the Robot in the Jetsons. But as popular as these machines have been on screen, we haven't seen similar robots enter our everyday lives. Now that appears on the verge of changing as the technology sector increasingly invests in robotics. Funding to private robotics companies doubled in 2015 to reach a record high of 587 million, according to CB Insights. And robots were the dominant theme at a conference Amazon held earlier this week to encourage inspiration and creativity in tech's hottest fields.

When Ray Kurzweil met with Google CEO Larry Page last July, he wasn't looking for a job. A respected inventor who's become a machine-intelligence futurist, Kurzweil wanted to discuss his upcoming book How to Create a Mind. He told Page, who had read an early draft, that he wanted to start a company to develop his ideas about how to build a truly intelligent computer: one that could understand language and then make inferences and decisions on its own. It quickly became obvious that such an effort would require nothing less than Google-scale data and computing power. "I could try to give you some access to it," Page told Kurzweil.

All the stuff early Google mastered. With that mission accomplished Google has moved on to the next challenge. I haven't yet seen the talk by Jeff Dean - but it is interesting that I tweeted out the exact same thing a few days ago on Twitter: "IMO Google's long term goal is not just to "Organize the world's information" but to "Understand" it using #AI:

Computing was some pretty exciting stuff for those of us back in the 80s who still remember the first time we booted up our 386DX. While nobody could really say what the advantages of the "DX" were, better at math or something, we still ponied up the extra 200 USD to pick up that 386DX 16Mhz along with a Super VGA graphics card, then hooked that bad boy up to CompuServe via our lightning fast 14,400 baud U.S. Robotics "Sportster" modem. That was well before Al Gore created the Internet, and a lot has changed since then. So are we, so let's go through and define some of these terms and what they mean for investors. "The Cloud" – The idea here is that instead of purchasing applications then installing them onto a computer, you lease the applications on demand and access them over the internet.

Reinforcement learning, a key Google DeepMind algorithm, could overhaul news recommendation engines and greatly improve users' stickiness. After beating a Go Grandmaster, the algorithm could become the engine of choice for true personalization. My interest for DeepMind goes back to its acquisition by Google, in Jan. 2014, for about half a billion dollars. Later in California, I had conversations with artificial intelligence and deep learning experts; they said Google had in fact captured about half of the world's best A.I. minds, snatching several years of Stanford A.I. classes, and paying top dollar for talent. Acquiring London startup DeepMind was a key move in a strategy aimed at cornering the A.I. field.

It's Friday September 14, 2046, and you are at the airport getting an alert from your car that your 10,000 mile service is due, but something peculiar comes with your alert. It's a question: your car asks you if you wish to have the service taken care of within the next 10 days, or after. Your car's smart system contacts the car dealer's smart system and arranges everything, but first it checks your calendar and figures out if you are out of town on any particular day. It discovers you will be traveling for the day on Monday the 24th, so it books your car service to the airport from the service department, your airline and hotel reservations, and your dinner reservations with your client. It also updates your social profiles for you while sending you relevant information about where you are going, whom you know there, whom you have not been in touch with for a while that may be in the area, and a plethora of other intelligence useful for you.

We all have those friends or colleagues who are the "go to" person for tough problems, whether it's car repairs or career advice. The difference between the "go to" person and everyone else is experience and a kind of raw talent. In fact, the very best – the experts – leverage those qualities to innovate. In Malcolm Gladwell's Blink, he recites example after example of experts at the top of their field making genius decisions in an instant. Despite constant advances in technology, the idea that a machine could ever achieve that expert level seems unfathomable. Even technologists, who are accustomed to accepting everything new, find themselves doubting the ultimate potential of artificial intelligence (AI).

Jia Jia (innovation consultant; New York): Reading about Google's AlphaGo crushing world champion Lee Se-dol made me unexpectedly afraid. I'd not given much thought to AI and had assumed that warnings from the likes of Elon Musk, Stephen Hawking and Bill Gates was cautionary but no cause for alarm. But knowing how the computer plays is unnerving. After his defeat in the first game, Lee commented of AlphaGo that "It did not play like a human at all." In fact, AlphaGo had made an early mistake but didn't lose its cool as a human would.

This week, a short novel written by an AI program did well in a Japanese literary contest, scientists spotted traces of a possible new particle that could shake the foundations of physics and a team of researchers discovered in the human genome a "nearly intact" genetic blueprint for a 700,000-year-old stowaway virus. A short novel written by a Japanese artificial intelligence software program passed the first screening round for the Nikkei Hoshi Shinichi Literary Award. "The day a computer wrote a novel," the program wrote near the end of the piece, "the computer, placing priority on the pursuit of its own joy, stopped working for humans." A team of scientists from Tufts University and the University of Michigan Health System has found a "nearly intact" genetic copy of an ancient virus that spliced itself into our DNA. The team doesn't rule out the possibility that it could come alive again.