As business decision makers take more control over the buying process, technology sellers are struggling to find ways to reach them. However, new technologies are emerging to help Inside Sales teams optimize their reach--transforming the art of selling into more of a science. The science lies behind the creative use of data, and the bigger the data the better. In these technologies, a predictive layer of mathematics is applied to the data resulting in recommendations. This process is the backbone of artificial intelligence or machine learning.

Intel's (NASDAQ:INTC) data-center chief, Diane Bryant, recently presented at an investor conference. During the conference, Bryant went into quite some detail on the company's strategy to participate in the small but fast-growing field of artificial intelligence, or AI for short. Let's take a closer look at what the Intel executive had to say. Analyst Blayne Curtis said that "people don't sort of think of Intel as a play on AI." After giving a brief history of AI, Bryant explained that the whole point of artificial intelligence is to be able to gather "large amounts of data" and then applying "ever-more sophisticated algorithms" to ultimately give computers the ability to "both learn and predict."

Privacy campaigners and open source developers are up in arms over the secret installing of Google software which is capable of listening in on conversations held in front of a computer. First spotted by open source developers, the Chromium browser – the open source basis for Google's Chrome – began remotely installing audio-snooping code that was capable of listening to users. It was designed to support Chrome's new "OK, Google" hotword detection – which makes the computer respond when you talk to it – but was installed, and, some users have claimed, it is activated on computers without their permission. "Without consent, Google's code had downloaded a black box of code that – according to itself – had turned on the microphone and was actively listening to your room," said Rick Falkvinge, the Pirate party founder, in a blog post. "Which means that your computer had been stealth configured to send what was being said in your room to somebody else, to a private company in another country, without your consent or knowledge, an audio transmission triggered by … an unknown and unverifiable set of conditions."

Testing is an often overlooked yet critical component of any software system. In some ways this is more true of models than traditional software. The reason is that computational systems must function correctly at both the system level and the model level. This article provides some guidelines and tips to increase the certainty around the correctness of your models. One of my mantras is that a good tool extends our ability and never gets in our way. I avoid many libraries and applications because the tool gets in my way more than it helps me.

This post is the first in a series I'll be writing for Parallel Forall that aims to provide an intuitive and gentle introduction to deep learning. It covers the most important deep learning concepts and aims to provide an understanding of each concept rather than its mathematical and theoretical details. While the mathematical terminology is sometimes necessary and can further understanding, these posts use analogies and images whenever possible to provide easily digestible bits comprising an intuitive overview of the field of deep learning. I wrote this series in a glossary style so it can also be used as a reference for deep learning concepts. Part 1 focuses on introducing the main concepts of deep learning. Part 2 provides historical background and delves into the training procedures, algorithms and practical tricks that are used in training for deep learning. Part 3 covers sequence learning, including recurrent neural networks, LSTMs, and encoder-decoder systems for neural machine translation.

In co-expression analysis, the correlation between pairs of genes is typically combined into a network model of the correlation structure, which facilitates secondary network analysis such as community structure or centrality [1]. However, the correlation between pairs of genes in a co-expression network typically is assumed to be uniform across all samples (e.g., tissue types, treatment conditions, disease status, etc.). Yet it is often inter-group differences in correlated data that are of biological or clinical interest. For example, a gene co-expression network in microarray data for chronic lymphocytic leukemia using known biomarkers was able to predict treatment outcomes in an independent sample [2]. A differential co-expression network approach that leverages the genetic network information may yield novel biomarkers and improved prediction. Differential expression methods compute the mean difference between groups for each gene but typically do not incorporate conditional variation from other genes in the data that may help explain the between-group variation.

If the business IT market in 2016 was defined by an increased focus on cybersecurity vulnerabilities (including from the Internet of Things), cloud adoption and a shift to hyperconverged infrastructure, what does that augur for 2017? Often, predictions about the year ahead are untethered from the year that was, and do not have much of a connection to underlying trends. The world of enterprise technology likely will not be radically different next year than it was in 2016. However, trends that have been ongoing may accelerate or evolve, as technologies mature and businesses get more acclimated to them. For example, Hardware as a Service may start to take off.

The 2017 Consumer Electronics Show in Las Vegas opens to the public on January 5 but will be preceded by press and preview days on January 3 and 4. This year's show will span across 2.5 million square feet of floor space spread across multiple venues and feature 3,800 exhibitors. "One of the big themes is going to be connectivity," Jeff Joseph, senior vice president for communications and strategic relationships at the Consumer Technology Association, which hosts CES. "For example, Internet of Things, vehicle-to-vehicle communication, voice-activated communication with things like Alexa and Google Home and higher-value content – 4K-produced content that you can move from device to device." In the past few years, more and more car companies and automotive suppliers have used CES to showcase their technological prowess, particularly in the area of self-driving cars.