One of the tropes of science fiction is the uncanny valley -- the phenomenon of a robot looking eerily human-like but not quite right in some intangible way. Another is the breakdown in the distinction between human and machine. And a third is artificial intelligence becoming so complex and sophisticated that humans are no longer able to understand or control it. Well, not to be the bearer of bad news, but all of those tropes from the movies are already happening. The good news is that some of these advances have the potential to make our lives a lot better.

Drone maker DJI's latest release, the Phantom 4, makes it easier than ever to capture beautiful aerial photos and videos. But the Chinese firm is working on ways to make the process simpler still. The company is currently building a set of automatic camera maneuvers that could allow Phantom 4 owners to nail complex shots by just pushing a button. "A lot of people, what they'll do is they'll fly around and their first shots aren't that great because they're getting used to it," says Pan. The feature would allow Phantom 4 owners to choose from a selection of camera maneuvers that the drone would be able to execute on its own.

In 2012, a year which feels a lot like the very early years of the era of data, Wired published this article on Narrative Science, an organization based in Chicago that uses Machine Learning algorithms to write news articles. Its founder and CEO, Kris Hammond, is a man whose enthusiasm for algorithmic possibilities is unparalleled. When asked whether an algorithm would win a Pulitzer in the next 20 years he goes further, claiming that it could happen in the next 5 years. Hammond's excitement at what his organization is doing is not unwarranted. But his optimism certainly is. Unless 2017 is a particularly poor year for journalism and literary nonfiction, a Pulitzer for one of Narrative Science's algorithms looks unlikely to say the least.

Ali Kheyrollahi is a solution architect building web scale solutions, trying to marry scalability with performance. He loves HTTP, API design and business-modelling DDD-style. An Open Source author and blogger, he tries to give back to the community what he has gratefully taken from it. He is a blogger and has co-authored a book. "BUILD STUFF" is a Software Development Conference for people who actually build stuff.

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Data scientists must always remember that data sets are not objective - they are selected, collected, filtered, structured and analyzed by human design. Naked and hidden biases in selecting, collecting, structuring and analyzing data present serious risks. For example, a recent Wall Street Journal article entitled "Tweets Provide New Way to Gauge TV Audiences" provides evidence of a disconnect between mainstream viewers and folks who use Twitter. The chart above shows the disconnect between the most popular and most tweeted shows - the most tweeted show is not a top ten show. While Twitter data can be useful for detecting trends and sentiments for certain areas (e.g., disease surveillance, natural disaster surveillance, product sentiments, financial trading, politics) in limited circumstances using scientific methods, it can also mislead and present a false view of reality.

"What is the relationship like between your team and the data scientists?" This is, without a doubt, the question I'm most frequently asked when conducting interviews for data platform engineers. It's a fine question – one that, given the state of engineering jobs in the data space, is essential to ask as part of doing due diligence in evaluating new opportunities. I'm always happy to answer. But I wish I didn't have to, because this a question that is motivated by skepticism and fear. If you read the recruiting propaganda of data science and algorithm development departments in the valley, you might be convinced that the relationship between data scientists and engineers is highly collaborative, organic, and creative. However, it's not a well kept secret that this is seldom the case. Most shops foster a relationship between engineers and scientists that lies somewhere in the spectrum between non-existent1 and highly dysfunctional. Data scientists: the folks who are "better engineers than statisticians and better statisticians than engineers".

Vivek Wadhwa is an academic, entrepreneur, and author who holds appointments at Stanford, Duke, and Singularity University. For the past century, the price and performance of computing has been on an exponential curve. And, as futurist Ray Kurzweil observed, once any technology becomes an information technology, its development follows the same curve, so we are seeing exponential advances in technologies such as sensors, networks, artificial intelligence, and robotics. The convergence of these technologies is making amazing things possible. Yes, with every good there is a bad; wonderful things will become possible, but with them we will also create new problems for mankind. Here are six of the technologies that will make this happen, and the good they will do.

A "rock star" (New York Times) of the computing world provides a radical new work on the meaning of human consciousness. The holy grail of psychologists and scientists for nearly a century has been to understand and replicate both human thought and the human mind. In fact, it's what attracted the now-legendary computer scientist and AI authority David Gelernter to the discipline in the first place. As a student and young researcher in the 1980s, Gelernter hoped to build a program with a dial marked "focus." At maximum "focus," the program would "think" rationally, formally, reasonably.

Most discussions of "robot rights" play out in a seemingly distant, science-fictional future. While skeptics roll their eyes, advocates argue that technology will advance to the point where robots deserve moral consideration because they are "just like us," sometimes referencing the movie Blade Runner. Blade Runner depicts a world where androids have human-like emotions and develop human-like relationships to the point of being indistinguishable from people. But Do Androids Dream of Electric Sheep, the novel on which the film is based, contains a small, significant difference in storyline. In the book, the main character falls in love with an android that only pretends to requite his feelings.