What are we trying to predict? How are we measuring if we are getting it right? Which departments are a part of this Data Science project? Who is my internal customer? When does this have to be completed?

We've long been fascinated with the idea of smart robots that serve human society. Think about Isaac Asimov's "I, Robot" short stories, Robby in the film "Forbidden Plant," and R2D2 or BB8 in "Star Wars." In these works, robots have some significant advantages over people. They are highly intelligent without being ruled by emotions. They act according to logical if-then processes.

DigitalGenius is announcing its Human AI customer service platform today, along with a 4.1 million seed investment. The work is to augment the process, while still keeping the human element decidedly at the center of things. It's interesting to note that Salesforce was part of the deal, as that could conceivably help the startup scale quickly in this space, thanks to Salesforce's massive distribution network and its suite of automation products ripe for AI. I talked to DigitalGenius chief strategy officer Mikhail Naumov to clarify what AI is and isn't. "It's important to decipher between Hollywood AI and practical AI you can use today," he said.

I like to pick roses on a summer's day and meeting friends. I dearly wish for world peace. I hope to work with children, just as soon as I have completed my doctorate in astrophysics. Not really, but I am in training. I am about to enter a beauty contest.

The Lenny Letter This is a project from Lena Dunham and her partner, Jenni Konner, and is essentially just an email newsletter, but it has become very popular. It offers perspective on politics and society for a mostly female audience and it is attracted over 400,000 subscribers in six months. What's most important about the Lenny Letter is that it has a 65% open rate and advertisers are taking notice. In tech and growth hacking, engagement is still what matters most in marketing. You can check out the Lenny Letter at lennyletter.com.

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.

A patient walks into the emergency department at Rush University Medical Center with a fever and bloodshot eyes. In days of yore, doctors would have to exhaust the obvious possibilities -- like a flu or allergic reaction -- before finally figuring a patient was suffering from Zika virus. But Rush says its predictive software, a system called Guardian, helps alert doctors to a possible diagnosis hours faster than physicians normally would. When dealing with more rare diagnoses, doctors typically think, "it's going to be everything else besides smallpox," said Dr. Dino Rumoro, who's been working on the technology for more than 20 years and is the chairman of Rush's Department of Emergency Medicine. "This gives the clinician a crutch."

In fact, some of Weizenbaum's colleagues and students exhibited very strong emotional connections to the program. As the preceding passage suggests, Weizenbaum discovered something disturbing: people approached the bot as if it were a real, intelligent entity who was genuinely interested in their condition -- even when they knew that it was a computer program. This condition is now referred to as the "Eliza Effect", and although the behaviour of its sufferers isn't always as extreme as the case above (alone time with robots is not consistently requested), it propelled Weizenbaum to become a staunch critic of AI. The Eliza Effect is a prime example of how an object, in this case a typewriter, can form a visceral connection with just a few rudimentary human elements. All it took to elevate a keyboard and screen to a human level was a basic conversational program.

When sailors speak of "blue water," they anticipate taking a boat offshore, out of sight of land, and usually for an extended cruise - an adventure underwritten by a frisson of risk. Much of the chatter about artificial intelligence has the patina of blue-water thinking about it. Its promise is expansive - as broad as an ocean. There are unplumbed depths, certainly treasure and possibly danger. At the risk of overworking the metaphor, today Artificial Intelligence (AI) sits in the matrix of a perfect storm of coincidence.

It's almost a given that you'll ride in an autonomous car at some point in your life, and when you do, the AI controlling it just might have honed its skills playing Minecraft. It sounds crazy, but open-world games like Minecraft are a fantastic tool for teaching learning algorithms--which power the next generation of advanced artificial intelligence--how to understand and navigate three-dimensional spaces. Achieving that is a major stepping stone toward creating AI that can interact with the real world in complex ways. It's easy to consider videogames mindless escapism, but because they generate such vast amounts of information--think of the expansive world players create in Minecraft--they are exceptionally well suited to teaching an AI how to perceive the world and interact with it. "It's hard for a human to teach AI," says Xerox researcher Adrian Gaidon, because they are "worse than the worst toddlers in the world--you have to explain everything."