Machine learning (ML) has received a lot of attention recently, and not without good reason. It has already revolutionized fields from image recognition to healthcare to transportation.

How do you know if you've made the right decision for a hire? Often, employers go off gut instinct and make a decision retrospectively, but it turns out AI might be able to help out in human resource management through shedding light on the best hiring decisions. In this episode, Pasha Roberts, Chief Scientist at Talent Analytics, Corp. tells us about how his company is working on helping companies make better decisions before they hire by applying machine learning and artificial intelligence to various data points on a given applicant, including information from aptitude tests that may help predict not only performance but retention.

It's hard to bet against the continued rise of automation, robots, and artificial intelligence (AI), all of which are already having major impacts on how we work, learn, shop, and play. But being able to predict that robotics and AI will change our lives is a lot easier than predicting how they will change our lives. In a recent forecast for 2017 and beyond, for instance, analyst firm IDC said we can expect to continue seeing robotic and AI technologies keep growing more affordable, more capable, and easier to use. The Obama White House said it expects the same, but also warns in a new report that "growth will not be costless" and could harm workers lacking the skills to compete in an AI-driven economy. How the incoming administration plans to address such issues is also uncertain. While President-elect Donald Trump's campaign promised to revive U.S. manufacturing and spend $1 trillion on the nation's infrastructure, he has also tapped Hardee's/Carl's Jr. chief Andrew Puzder -- who supports the use of automation to save on employment costs -- as secretary of the U.S. Department of Labor.

GPU technology has been around for decades, but only recently has it gained traction among enterprises. It was traditionally used to enhance computer graphics, as the name suggests. But as deep learning and artificial intelligence have grown in prominence, the need for fast, parallel computation to train models has increased. "A couple years ago, we wouldn't be looking at special hardware for this," said Adrian Bowles, founder of analyst firm STORM Insights Inc. in Boston. "But with [deep learning], you have a lot of parallel activities going on, and GPU-based tools are going to give you more cores."

Many believe Artificial intelligence is a new concept. But in reality it is something that businesses have been trying to implement in key areas. The role of artificial intelligence is to organize operations and improve automation. Some of the biggest international tech giants such as Google, Apple and Microsoft have made announcements related to artificial intelligence this year. In September, a number of companies, including Amazon, Facebook, Google, IBM and Microsoft, also launched a Partnership on Artificial Intelligence to Benefit People and Society to address opportunities with AI technology .

This ended up being more of a blog than a comment lengthwise. I really believe that the intense discussion of'data scientist' vs. 'statistician' is one that's driven by quite a number of factors. And I think it is inappropriate, presumptuous at best to say that there is a'death' of any one particular discipline in this area. The quantitative and computational arena, both in the theoretical and applied arena is evolving, but nevertheless much is grounded in the disciplines of statistical practitioners. Here are some simple armchair thoughts about how and why I believe that'data scientist' and'statistician' are at their core nearly synonymous.

Google's Embedding Projector web applications will give developers a way to visualize how well their machine learning systems are interpreting data.

Chatbots are programs that mimic conversation with people using artificial intelligence. With recent advances in AI these have become much more accurate, especially when focused on a specific domain. Combine these advances with the consumer trend towards messaging -- people are now spending more time in messaging apps than in social media -- and it seems we might be about to enter the age of the chatbot. We decided to take a closer look at the top emerging chatbot start-ups in text chat, across a range of industries, and pick out the most promising. You can find out more about the 25 companies below, or discover more chatbot startups on our search engine.

Last March, Google's computers roundly beat the world-class Go champion Lee Sedol, marking a milestone in artificial intelligence. The winning computer program, created by researchers at Google DeepMind in London, used an artificial neural network that took advantage of what's known as deep learning, a strategy by which neural networks involving many layers of processing are configured in an automated fashion to solve the problem at hand. Unknown to the public at the time was that Google had an ace up its sleeve. You see, the computers Google used to defeat Sedol contained special-purpose hardware--a computer card Google calls its Tensor Processing Unit. Norm Jouppi, a hardware engineer at Google, announced the existence of the Tensor Processing Unit two months after the Go match, explaining in a blog post that Google had been outfitting its data centers with these new accelerator cards for more than a year.

It's been a year of change in the enterprise software market. SaaS providers are fighting to compete with one another, machine learning is becoming a reality for businesses at a larger scale, and containers are growing in popularity. Here are some of the top trends from 2016 that we'll likely still be talking about next year. As more and more companies adopt software-as-a-service products like Office 365, Slack, and Box, there is increasing pressure to collaborate for companies that compete with each another. After all, nobody wants to be stuck using a service that doesn't work with the other critical systems they have.