What do you think when you hear the words'artificial intelligence?' Robots? Do images of a world that looks less human flash across your mind? Before you panic, know this. Artificial Intelligence (AI) is much more than the idea of pending doom. Defined as"intelligence displayed by machines, in contrast with the natural intelligence displayed by humans and other animals," AI is simply another means to improve the way that we, as a society, address some of the biggest challenges we face.

New hero Yrel, announced today as part of the Echoes of Alterac release for Heroes of the Storm. Three years ago, Blizzard Entertainment took the heroes from Warcraft and StarCraft and Diablo, dumped them into three lanes, and yelled, "Fight!" Heroes of the Storm marked its third anniversary as Blizzard's massive online battle arena (MOBA) game this weekend, and as part of the festivities, I caught up with game director Alan Dabiri to chat about the state of the Nexus. It hasn't always been a smooth lane (we're looking at you, Hanamura map) and Heroes has sometimes been overshadowed by its bigger brothers in the Blizzard stable of games, but the title has come a long way in three years. For the first time in its history, it recently started launching bits and pieces of its own original story. That's crucial in a company where every game now has its own narrative. In much the same way that Blizzard's Hearthstone started as a digital card game that happened to involve Warcraft characters, then evolved into a game with single-player stories and an impact on intellectual property parent World of Warcraft, Heroes is taking the first step into being a fully-fledged IP in its own right. From map mod to full game: Heroes went from a proof of concept, showing how DOTA could exist as a StarCraft II map, to an actual game. Will the heroes still come from Blizzard's other games? But how did they get here, and why are they fighting? Blizzard's storytelling teams are finally ready to start answering that question, and the game design teams are taking what they learned from Hanamura and other missteps. It's a good time to be a Hero.

Christopher Bouton, PhD, a self-described molecular neurobiologist turned entrepreneur, had such a positive experience starting and running a company that he decided to do it twice. After a five-year stint at pharmaceutical/biotech giant, Pfizer, the Johns Hopkins grad started a company called Entagen, which developed semantic-based analytics for the healthcare sector. After five years running Entagen, Thomson Reuters acquired the company in what Bouton called a "successful exit." Bouton spent a few years under the Thomson Reuters umbrella, but the entrepreneurial itch soon returned. "[In] 2016 while I was sort of contemplating what to do next, I started to take note of all of these deep learning approaches that were starting to be talked about. The reason that they're talking about AI is because of these deep learning algorithms. And so I got interested in what they were and how they worked."

It's an interesting time to be making a case for philosophy in science. On the one hand, some scientists working on ideas such as string theory or the multiverse--ideas that reach far beyond our current means to test them--are forced to make a philosophical defense of research that can't rely on traditional hypothesis testing. On the other hand, some physicists, such as Richard Feynman and Stephen Hawking, were notoriously dismissive of the value of the philosophy of science. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. That value is asserted with gentle but firm assurance by Michela Massimi, the recent recipient of the Wilkins-Bernal-Medawar Medal, an award given annually by the UK's Royal Society. Massimi's prize speech, delivered earlier this week, defended both science and the philosophy of science from accusations of irrelevance.

Privacy advocates have placed an unfair stigma on machine learning. Despite what you may have heard through the mass media, ML is not some fiendish tool for invading people's privacy. Regardless, now that European Union's General Data Protection Regulation has taken effect, there's an even stronger scrutiny of ML uses in target marketing, customer engagement, experience optimization and other use cases that touch personally identifiable information, or PII. But in fact, ML is becoming a key element in how organizations manage compliance with GDPR and other privacy mandates. The core of ML's role in GDPR compliance is in its use as a tool for discovering, organizing, curating and controlling enterprise PII assets across complex, distributed application environments.

What do you think universities should start doing to prepare college grads for a very different labor market ahead? It will depend on the institutions and the individuals involved. Let me offer two guesses. First, we'll need to break down lots of barriers. Take the boundary between work experiences and academic, classroom experiences.

"Ted came up with the breakthrough idea that got rid of the computer so you didn't have to have a computer to make the game work," Allan Alcorn, one of Atari's first employees, said in an interview this week. " It created the industry." Samuel Frederick Dabney, Jr., was born in San Francisco on May 2, 1937. His parents, Irma and Samuel Frederick Dabney, divorced when he was young, and he was raised by his father, an accountant. A brother, Doug, died in 2013.

Silicon Valley has a term for startups that reach the $1 billion valuation mark: unicorns. It suggests not only that hugely successful startups are rare, but also that there's something unreal about them. Founded by a 19-year-old Stanford dropout, Elizabeth Holmes, who went on to become the world's youngest self-made female billionaire, it raised nearly a billion dollars from investors and was valued at $10 billion at its peak. It claimed to have developed technology that dramatically increased the affordability, convenience, and speed of blood testing. It partnered with Safeway and Walgreens, which together spent hundreds of millions of dollars building in-store clinics that were to offer Theranos tests. Tens of thousands of Americans had their blood tested by its proprietary technology. The problem was that Theranos' technology was never close to ready. In a series of devastating articles published in the Wall Street Journal starting in 2015, reporter John Carreyrou reminded us that unicorns are usually found only in fairy tales.

Dan Olley was recently named to the prestigious CIO Hall of Fame by CIO Magazine. In many ways, however, Olley has not been a traditional chief information officer. For one, he has largely held chief technology officer roles. Moreover, he has also had customer-facing, product-centric roles. In his current role as Chief Technology Officer and Executive Vice President of Product Development of Elsevier, his purview is quite broad. Elsevier is a subsidiary of RELX Group, focusing on academic and clinical research. In his role, Olley helps develop solutions to help academics and clinicians train, while enhancing their ability to help patients at the bedside. Olley's focus in recent years has been in machine learning. In fact, he has been immersed in the subject long enough that this insights into its use, the value derived from it, the implications on teams, and the like are unusually deep.

Let me put it this way, Mr. Amor. The 9000 series is the most reliable computer ever made. No 9000 computer has ever made a mistake or distorted information. We are all, by any practical definition of the words, foolproof and incapable of error.