Ed Boyden is a professor of Biological Engineering and Brain and Cognitive Sciences at the MIT Media Lab and the MIT McGovern Institute. He leads the Synthetic Neurobiology Group, which develops tools for analyzing and repairing complex biological systems such as the brain, and applies them systematically to reveal ground truth principles of biological function as well as to repair these systems. These technologies, created often in interdisciplinary collaborations, include expansion microscopy, which enables complex biological systems to be imaged with nanoscale precision, and optogenetic tools, which enable the activation and silencing of neural activity with light. Amongst other recognitions, he has received the Breakthrough Prize in Life Sciences (2016), the Carnegie Prize in Mind and Brain Sciences (2015), the Schuetze Prize (2014), the Jacob Heskel Gabbay Award (2013), the Grete Lundbeck Brain Prize (2013), the NIH Director's Pioneer Award (2013), and the Perl/UNC Neuroscience Prize (2011). Ed received his Ph.D. in neurosciences from Stanford University as a Hertz Fellow, where he discovered that the molecular mechanisms used to store a memory are determined by the content to be learned.

Back when activity based working (ABW) was starting to gain real traction in places like Australia in 2013, we ran some research on which companies were most influential on the organisational leaders that were driving adoption of the work style. For many technology vendors and service providers the results from our more than 50 in-depth interviews with ABW adopters (now more than 250) were somewhat of a shock. The leading influencers were: #1 workpace strategy specialists; #2 interior designers; #3 peers that had adopted ABW; #4 real estate management firms and furniture providers. On the contrary, it was considered critical to get right and pretty much underpinned everything (see our checklist for guidance here). But technology providers simply didn't have a vision or narrative that was resonating with organisational leaders that also had to consider how to best use physical space while changing cultures.

For nearly 30 years, Pedro Domingos has been working within artificial intelligence communities, both as a researcher and a developer. In that time, the University of Washington professor has become an expert on all things machine learning. His new book, The Master Algorithm, traces the beginnings of machine learning, and provides a road-map to where it may be headed in the future. We talked to him by phone about what lies ahead for machine learning, how the master algorithm might change everything, and why he thinks the idea of the singularlity is overstated. Can you give me the elevator pitch on what "The Master Algorithm" is?

John Holden is a journalist specializing in science, tech and innovation. His work has appeared mainly in the Irish Times. Cornered at a party by some bore talking about his unimaginative app that will "change the world." All seemingly convincing excuses to leave have already been used by the rest of the group (who were all there just a second ago). The last refuge of the rude scoundrel -- the smartphone -- is in your jacket pocket in the cloakroom all the way across the room. So you just have to suck it up and simulate enthusiasm for this guy's pitch.

The following interview is one of many included in the report. As part of my ongoing series of interviews surveying the frontiers of machine intelligence, I recently interviewed Yoshua Bengio. Bengio is a professor with the department of computer science and operations research at the University of Montreal, where he is head of the Machine Learning Laboratory (MILA) and serves as the Canada Research Chair in statistical learning algorithms. The goal of his research is to understand the principles of learning that yield intelligence. Yoshua Bengio: I have been researching neural networks since the '80s.

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.

Open AI Gym: What do you think about the Reinforcement Learning toolkit and its evaluation methods? Its been approximately 10 days since the release of Gym. How has your experience with it been so far? Do you think academic/non-academic researchers will embrace it and use it as benchmarks in their publications? Or will it just end up as some highly decorated playground over time? More importantly, do you think it will do anything to accelerate AI research as claimed??

It's always exciting when a new robot arrives in your lab. Usually, the more expensive the robot is, the more exciting it is. With the possible exception of Boston Dynamics' ATLAS, NASA's Valkyrie has got to be one of the most expensive humanoid robots ever made, and last year, NASA promised to give away (or, at least, lend) three of them to universities in the hope that Valkyrie will learn some new skills. Within the last few weeks, the University of Massachusetts Lowell, which teamed up with Northeastern University in Boston, Mass., took delivery of their fancy new robot, as did MIT and the University of Edinburgh in Scotland. We talked to Holly Yanco at UMass Lowell and Taskin Padir at Northeastern, along with Sethu Vijayakumar at Edinburgh and Russ Tedrake at MIT, about what it's like to have a smokin' hot space robot show up on your doorstep in a bunch of pieces.

Harold Cohen, artist and pioneer in the field of computer-generated art, died on April 27, 2016 at the age of 87. Cohen is the author of AARON, perhaps the longest-lived and certainly the most creative artificial intelligence program in daily use. Cohen viewed AARON as his collaborator. At times during their decades-long relationship, AARON was quite autonomous, responsible for the composition, coloring and other aspects of a work; more recently, AARON served Cohen by making drawings that Cohen would develop into paintings. Cohen's death is the end of a lengthy partnership between an artist and an artificial intelligence.

Currently at this time, all participants are in a listen-only mode. Later, we will conduct the question-and-answer session and instructions will follow at that time. Also, as a reminder, this conference call is being recorded. I would now like to turn the call over to your host to Richard Morin. Thank you, and good evening, everyone. Earlier today, we issued a news release announcing Cognex's earnings for the first quarter of 2016, and we've also filed our quarterly report on Form 10-Q. For those of you who have not yet seen these materials, both are available on our website at www.cognex.com. They contain highly detailed information about our financial results. During tonight's call, we may use a non-GAAP financial measure, if we believe it is useful to investors, or if we believe it will help investors better understand our results or business trends. For your reference, you can see a reconciliation of certain items from GAAP to non-GAAP in Exhibit 2 of the earnings release. I'd like to emphasize that any forward-looking statements we made in the earnings release or any that we may make during this call are based upon information that we believe to be true as of today. Things often change and actual results may differ materially from those projected or anticipated. You should refer to the company's SEC filings, including our most recent Form 10-K, for a detailed list of these risk factors. Now, I'll turn the call over to Cognex's Chairman, Dr. Bob Shillman.