The chatbot craze began in 2016 with Facebook's announcement of a developer-friendly platform to build chatbots on Facebook messenger. Soon, chatbots were heralded as the next stage of the conversational revolution. Toolkits that helped you build a bot in five minutes grew popular, companies raced to the market with new bot announcements and technology conferences headlined buzzword-driven keynotes about how bots would take over human jobs.

Japanese car maker Toyota unveils a new humanoid robot that mirrors the movements of its remote operator, as Stuart McDill reports. A link has been posted to your Facebook feed. Japanese car maker Toyota unveils a new humanoid robot that mirrors the movements of its remote operator, as Stuart McDill reports.

The International Telecommunications Union (ITU), the United Nations specialised agency for information and communication technologies (ICTs), has launched a new ITU Focus Group to establish a basis for ITU standardisation to assist machine learning (ML) in bringing more automation and intelligence to ICT network design and management.

Target's higher minimum wage aims to attract and retain good staffers. See how much other big retailers are paying. This May 3, 2017, photo shows the Target logo on a store in Upper Saint Clair, Pa. Target is jumping into voice-activated shopping as it deepens its relationship with Google, offering thousands of items found in the store except for perishables like fruit and milk. The move is happening as Google says shopping will be available later in 2017 through Google Assistant on iPhone and Android phones, joining its Google Home device and Android TV.

Knowing how to write high quality software -- the days of one team writing throwaway models and another team implementing them in production are slowly coming to an end. With programming languages like Python and R and their packages making it easy to work with data and models, it is reasonable to expect a data scientist or machine learning engineer to attain a high level of programming proficiency and understand the basics of system design. While "big data" is a term used way too often, it is true that the cost of data storage is on a dramatic downward trend. This means that there are more and more data sets from different domains to work with and apply models to. And yes, knowing something about at least one of the popular areas of the field that have gotten traction lately -- deep learning for computer vision and perception, recommendation engines, NLP -- would be a great thing once you have the fundamental understanding and technical proficiency.

AUCKLAND, NEW ZEALAND - AUGUST 03: Isuru Fernando of IBM speaks during the TILT / Fresh Directions In Healthcare Marketing seminar on August 3, 2017 in Auckland, New Zealand. TILT is an interactive seminar designed to inspire healthcare marketers to use digital tools to communicate with their customers. In May 2014, IBM announced the acquisition of an AI startup, Cognea, that developed a cognitive computing and conversational artificial intelligence platform. IBM aimed to integrate it with Watson, the company's question-answering supercomputer, for more real conversations with users. Since then, it's been a wave of sorts with technology companies like Facebook, Microsoft, Google, Amazon and others investing in their own AI efforts while acquiring several startups in the space.

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.

A new $240 million center at MIT may help advance the field of artificial intelligence by developing novel devices and materials to power the latest machine-learning algorithms. It could, perhaps, also help IBM reclaim its reputation for doing cutting-edge AI. The project, announced by IBM and MIT today, will research new approaches in deep learning, a technique in AI that has led to big advances in areas such as machine vision and voice recognition. But it will also explore completely new computing devices, materials, and physical phenomena, including efforts to harness quantum computers--exotic but potentially very powerful new machines--to make AI even more capable. "It's an area no one is touching, and it has the potential for orders-of-magnitude improvements."

There has never been a better time to be a politician. But it's an even better time to be a machine learning engineer working for a politician. Throughout modern history, political candidates have had only a limited number of tools to take the temperature of the electorate. More often than not, they've had to rely on instinct rather than insight when running for office. Now big data can be used to maximise the effectiveness of a campaign.

In the mid-1990s, Douglas Eck worked as a database programmer in Albuquerque while moonlighting as a musician. After a day spent writing computer code inside a lab run by the Department of Energy, he would take the stage at a local juke joint, playing what he calls "punk-influenced bluegrass" -- "Johnny Rotten crossed with Johnny Cash." But what he really wanted to do was combine his days and nights, and build machines that could make their own songs. "My only goal in life was to mix A.I. and music," Mr. Eck said. It was a naïve ambition.