I am struggling a bit with docker. The official tensorflow image automatically runs the jupyter notebook upon start. I don't want that, since I'd like to do some additional installs of tools I am using. And when I do Ctrl-C to shut down the notebook, the entire container shuts down...

At the annual NAB (National Association of Broadcasters) show in Las Vegas, Microsoft announced that Azure Media Services will be receiving a host of new features and will even be taking advantage of its machine learning services. Azure Media Services is a collection of cloud-based tools for video workflows and the company intends to make these tools smarter to help users create premium video content more easily. Microsoft will be adding face detection to Media Services through its Face API. The company has decided to go a step further though and will also use the Emotion API from Cognitive Services to detect the emotions of the people who appear in a video. This feature will be useful when it comes to discerning the level of interest of an audience during debates or keynotes.

UCLA researchers have developed a new laser-based technology to rapidly screen blood samples for the presence of cancer cells. The label-free system measures 16 different physical characteristics of each cell and analyzes the data to identify whether the cell is cancerous. Not having to introduce any labeling chemicals and being gentle on the cells, the technique leaves the cells alive and available for further inspection using other means. It relies on a photonic time stretch microscope and a computer that runs deep learning artificial intelligence algorithms. The microscope can take millions of images per second thanks to unusual optics that produce high quality shots even at this speed.

I recently talked about the oncoming internet developments that follow the Internet of Things, from the internet on demand (3D and 4D printing) to the internet of robots. A colleague came up afterwards and said I was daft to talk about robots. "It's science fiction," he claimed. I disagreed, as science fiction is rapidly becoming fact. I was reminded of this while listening to some guy called Brett King talking about his new book Augmented at the Meftech conference this week.

And this opportunity is bigger and more user friendly than any app platform yet. Amazon, Microsoft, Facebook, and Slack are a few of the biggest names leading the way. In the past week, the media has been in a bot frenzy, brought to a peak by Facebook's announcement of a complete platform for building experiences inside Messenger. A flurry of articles have come out proclaiming there to be a new gold rush on bots, with some calling Zuckerberg's announcement "the most consequential event for the tech industry since Apple announced the App Store and iPhone SDK in March 2008." Zuck's was the second top-shelf tech keynote talking about bots this spring.

One of the first key takeaways from Vanderbilt Law School's conference on Thursday about artificial intelligence is that the term doesn't carry much value in the scientific community. "A.I. is whatever we can't do this year," David Lewis, a speaker who holds a PhD in computer science, said in between panel sessions. Lewis estimated we're currently experiencing the second or third wave of "A.I. hype," in which everyone uses the term to describe their technology. That's happened before, he said, and then it went out of style as a marketing buzzword. "By 2020, it'll have a negative connotation again," he predicted.

On Wednesday, a new feature called "Goals" has been added to Google Calendar for its iOS and Android apps. "This is going to be my year. This is the year I will achieve this." Haven't we all uttered those exact words every New Year? Each year, we look ahead with hope and determination.

The subprime financial crisis revealed that our data is only as good as our ability to analyze and understand it. AI will be necessary to helping prevent the next crisis before it happens. In his new film "The Big Short," based on the book by Michael Lewis, Adam McKay attempts the difficult task of explaining exactly how the credit and subprime housing bubble led to the 2008 worldwide economic crash. One of McKay's main points in outlining how Michael Burry, and a handful of other Wall Street outsiders, were able to predict the impending crisis is that they simply investigated the underlying data. As Ryan Gosling's character narrates in the film: "A few did what the rest never thought to do… they looked."

In these situations, it is not always necessary to think about samples and populations, or to think about a model that expresses a scientific idea. It doesn't make sense to me, because if I were to build a regression model I would still need to think about my samples and population. I don't understand why I should just plug my sample data into R and hope for the best without any idea my sample is about. The sentence doesn't add anything, it's confusing and technically incorrect. Instead the goal is to simply find an equation or algorithm that makes reasonably correct predictons sounds doggy to me.

TensorFlow has been at the core of many Google products, and now there's a more versatile version of the open-source machine learning technology.