Picture a virtual assistant that helps find directions, schedules appointments or plays music, and the soothing yet robotic sound of a female voice likely comes to mind. From Apple's Siri to Amazon's Alexa, a majority of the world's most popular virtual assistants have female personas. But that's starting to change as a growing number of consumers -- and companies -- turn to digital assistants. Some developers are going against the grain, creating chatbots and messaging apps that no longer conform to one gender and challenging a tradition of female digital assistants that some say display submissive personalities. Making virtual assistants female by default can be bad for business and perpetuate stereotypes, these chatbot developers say, so they're offering more options to consumers.

BY PATRICK WATSON: The news headlines after last week's jobs report proved it again: Life is hard (and getting harder) for low-skilled workers. Illegal immigrants take their service industry jobs. Robots take their manufacturing industry jobs. According to the media, many low-skilled workers have simply given up. Their lives are terrible, and everyone wants to help.

Machine Learning, somehow, emerged from Artificial Intelligence.

Artificial intelligence (AI) on its own isn t enough to compete -- companies need industry-specific solutions to business problems. So said Martin Schroeter, IBM Corp. (NYSE: IBM) s company senior vice president and chief financial officer, on the company s quarterly earnings call Thursday afternoon. Cognitive computing technology (IBM s term for AI) is just "table stakes," said Schroeter, claiming that his company is going the extra mile. IBM is building datasets for Watson to serve specific industries, including healthcare and finance. "You need more than public data or algorithms to solve real-world problems," Schroeter said.

The exponential progress in the field of robotics has already been feared to take so many production jobs away from humans, and the latest edition to those victims might be the programmers. Researchers at the Google Brain artificial intelligence have designed a machine learning system that can develop machine learning software. Interestingly, when compared, it exceeded the results from the ones designed by humans. According to Jeff Dean, who leads the Google Brain research group, such exertion could supplant some of the work from the workers and enhance the pace of the implementation of the AI software in different fields of economy. "Currently the way you solve problems is you have expertise and data and computation," said Dean, at the AI Frontiers conference in Santa Clara, California.

NEW YORK - As soon as you approach Pepper, a 4-foot-tall robot, she starts sizing you up. Thanks to facial recognition capabilities, Pepper can determine your gender and age bracket. And as you begin asking her questions, she can draw from a vast volume of cloud-based information to give what she thinks are relevant answers. If you smile, she can tell the conversation is going well and that you're finding her answers helpful. If you don't, she might ask you if she's misunderstanding your requests.

Kristen Stewart is quickly becoming one of my favorite people. She's gone from Twilight to indie darling, picking some amazing films that show us she has way more talent than Bella Swan gave her credit for. Stewart is gearing up to debut her directorial debut, a 17-minute short film called Come Swim, which was inspired by a painting Stewart had previously completed. The film integrates the painting using a technique called "style transfer," which uses convolutional neural networks to have an algorithm change a video in real time. If we saw this on an airplane we'd probably throw up.

As AI enters our homes through smart home devices or tries to conquer our streets through self-driving cars, one need not be a Luddite to contemplate the potentially heavy implications of AI upon our daily lives and livelihood. The key to answering the question and indeed to understand the ultimate limits of AI is to ask if machines can really think. In this article, I list three tests drawn from three different disciplines to address that query.

Microsoft CEO Satya Nadella: "The fundamental need of every person is to be able to use their time more effectively, not to say, 'Let us replace you'." Microsoft is striving to give technology human intelligence and capabilities, but CEO Satya Nadella says it and its rivals should divert efforts away from AI that replaces people. Nadella will join a chorus of tech leaders at this year's World Economic Forum meeting in Davos, addressing concerns that the current war for AI talent being waged by Google, Microsoft, Amazon, Apple, and Facebook will lead to machines that replace, rather than help humans. Don't worry, robots and AI won't take your job: Well, at least not all of it Automation probably won't lead to massive unemployment, but governments will still need to prepare for major upheaval, according to a new study. Nadella says he's warned Microsoft and its rivals to steer clear of "parlor tricks" that show AI's power without preserving workers' dignity.

The insurance sector is one of the most old-fashioned and resistant to change -- so artificial intelligence will have an even greater effect. The insurance sector is one of the most old-fashioned and resistant-to-change space, and this is why AI will have a greater impact on that with respect to more receptive industries. The collection of data of new types (i.e., unstructured data such as reports, images, contracts, etc.) and the use of new algorithms are disrupting the sector in several ways. This is a really simplistic representation of the insurance business in the last fifty years, and I am aware that insurance experts might disagree with me in many different ways. There are a couple of further features to be pointed out: first of all, insurance has historically been sold not bought, which means that brokers and agents were essential to tracking new customers and to even retain old ones. In addition, it is an industry which is by definition rich of data because they collected anything they could, but is also one of the less advanced because either many of those data are unstructured or semi-structured, or the model used are quite old and simple.