Donald Trump knows many words. He has the best words. He's going to find the best people to help him run the country. He knows many smart people. His presidency will be classy, huge, even.

Donald Trump knows many words. He has the best words. He's going to find the best people to help him run the country. He knows many smart people. His presidency will be classy, huge, even.

Every once in a while an innocuous technical term suddenly enters public discourse with a bizarrely negative connotation. I first noticed the phenomenon some years ago, when I saw a Republican politician accusing Hillary Clinton of "parsing." From the disgust with which he said it, he clearly seemed to feel that parsing was morally equivalent to puppy-drowning. It seemed quite odd to me, since I'd only ever heard the word "parse" used to refer to the computer analysis of sentence structures. The most recent word to suddenly find itself stigmatized by Republicans (yes, it does somehow always seem to be Republican politicians who are involved in this particular kind of linguistic bullshittery) is "encryption."

With Congress revisiting how Pentagon units share authority under the 1986 Goldwater-Nichols Act, the intelligence agencies under the next presidential administration should likewise review their own unity of effort to become more agile and able to integrate, the top Defense intelligence official said Thursday. "The integration of intelligence of the past 15 years is a journey that is not finished," said Marcel Lettre, undersecretary of Defense for intelligence, at a banquet for agency and industry professionals in the nonprofit Intelligence and National Security Alliance. "I hope the new administration finds clear progress from the last 15 years and takes it on with a mantle of seriousness, or even sees an opportunity to redouble the effort." Lettre, who was sworn in in December to preside over a 17 billion budget, eight components and 110,000 employees, said he also hopes the next administration will "institutionalize and make irreversible" the intelligence community's digital data sharing modernization effort known as the Intelligence Community Information Technology Enterprise (pronounced "eyesight"). "Key critical data sets are the coin of the realm for the intel community," he said.

I wasn't planning to chip in this time, but I stumbled upon an article so compelling I felt I ought to. Uncanny Valley, published by Anna Weiner on N 1 Magazine, is a short literary piece which lives up to its title. Weiner's nameless narrator is going through most commonplaces of the Valley, both physically and mentally, without really being a part of it. "I learn the bare minimum, code-wise, to be able to do my job well -- to ask questions only when I'm truly in over my head," she confesses. She is going from being the start-up's inaugural customer support rep to become a "success manger", a title so corny for her she can't stand having it on her email signature.

If your mind instantly went to Skynet, I can put your mind at ease; it's not Skynet. That's not, however, to say that this problem isn't just as scary, only without the cool special effects. While Sci-Fi has made the risks of robot takeover well-known, the more immediate concerns are the subtle decisions being made by (sometimes) poorly coded, or designed, algorithms that can drastically alter each of our lives. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. The Obama administration published a report this week that examines problems associated with the shift to an increasingly automated world.

When will the technology arrive that makes you obsolete in your current job? It's no idle question, and one that none other than Microsoft CEO Satya Nadella took up this week in remarks to hundreds of Seattle technology and business leaders. We'll explore his comments, a new offering from Textio, the media's failures in covering the presidential primaries; have some fun with drones, Star Wars, Disney's Frozen, and STEM education; and wash it down with a cold home brew in this edition of Xconomy Seattle's Week in Review: He shared his view of Microsoft's unique culture, and how that gives the company an advantage. One aspect is Microsoft's global mindset, which Nadella, born in Hyderabad, India, talked about in a personal way. "I wouldn't be CEO of Microsoft if it was not for Microsoft's technology being a global force," Nadella said.

Concerns have been raised about the scope of a data-sharing agreement between Google-owned DeepMind and the UK's National Health Service (NHS) after it was revealed the agreement covers access to all patient data from the three London hospitals involved, rather than a more targeted subset of data relating to the specific medical condition the healthcare app in question (Streams) is focused on. Back in February DeepMind announced a collaboration with the NHS to build an app for clinicians treating kidney disease. The company also acquired an existing early stage clinical task management app, called Hark, built by a team from Imperial College London -- evidently with the intention of building on that base tech, but giving it a more specific medical focus in the first instance. The Streams app aims to streamline alerts and access to patient data for doctors and nurses working in the front-line of medical care. But it is not a general medical data alerts or messaging platform.

At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. I would now like to turn the conference over to your host, Jandy Tomy, Vice President of Finance and Investor Relations. With me today on the call are Robert Apatoff, President and Chief Executive Officer; and Becky Sheehan, Executive Vice President and Chief Financial Officer. Before we begin, please remember that, during the course of this call, management may make forward-looking statements within the meaning of the Federal Securities Laws that address the Company's expected future business, financial performance, and financial condition. These forward-looking statements involve risks and uncertainties that could cause actual results to be materially different than those expressed in our forward-looking statements. In addition to the Company's reports filed with the Securities and Exchange Commission, please refer to the text in the Company's press release issued today for a discussion of the risks and uncertainties associated with such forward-looking statements. Also, please note that, on today's call, management will refer to certain non-GAAP financial measures, including adjusted EBITDA, adjusted net income, and free cash flow. The Company believes these non-GAAP financial measures provide useful information for investors. Please refer to today's press release for definitions and calculations of these non-GAAP performance measures, as well as reconciliations of the non-GAAP performance measures to the Company's GAAP financial results. Now, I'd like to turn the call over to Robert Apatoff, President and Chief Executive Officer. Good afternoon, everyone, and thank you for joining us today. I will provide a brief overview of our business highlights, integration efforts, and strategic and operating initiatives. Following my comments, our CFO Becky Sheehan will review our financial results and outlook for 2016 in more detail. Finally, I will provide a few closing remarks, and then we'll open up the call to take your questions.

There's huge progress in AI, or at least huge interest in AI--a bigger interest than there's ever been in my lifetime. I've been interested in AI since I was a little kid trying to program computers to play chess, and do natural language databases, and things like that, though not very well. I've watched the field and there have been ups and downs. There were a couple of AI winters where people stopped paying attention to AI altogether. People who were doing AI stopped saying that they were in the field of AI. They say, "Yes, I do artificial intelligence," where two years ago they would have said, "I do statistics." Even though there's a lot of hype about AI and a lot of money being invested in AI, I feel like the field is headed in the wrong direction. There's been a local maximum where there's a lot of low-hanging fruit right now in a particular direction, which is mainly deep learning and big data. People are very excited about the big data and what it's giving them right now, but I'm not sure it's taking us closer to the deeper questions in artificial intelligence, like how we understand language or how we reason about the world. The big data paradigm is great in certain scenarios. One of the most impressive advances is in speech recognition. You can now dictate into your phone and it will transcribe most of what you say right most of the time. That doesn't mean it understands what you're saying. Each new update of Siri adds a new feature. First, you could ask about movie times, then sports, and so forth. The natural language understanding is coming along slowly. You wouldn't be able to dictate this conversation into Siri and expect it to come out with anything whatsoever. But you could get most of the words right, and that's a big improvement. It turns out that it works best with a lot of brute force data available. When you're doing speech recognition on white males, who are native language speakers, in a quiet room, it works pretty well.