Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. Google is making a high-profile push into AI, with the internet titan's chief referring to it as a force for change as powerful as powerful as smartphones. Google Assistant software is being built into new Pixel handsets - aiming to outdo Apple's Siri - enabling users to organize and use information on the devices and in the cloud - to check emails, stay up to date on calendar appointments, news or ask for traffic and weather data. Google also offers AI through its Allo messaging application which can be installed on smartphones, and its Google Home hub, a stand-alone device similar to Amazon's Echo which responds to voice commands to manage tasks and fetch information where people live.

Aritifical intelligence is rapidly becoming one of the most prevalent topics in technology and today's titans are not ignoring the trend. All of the major companies, it seems, are now investing in machine learning one way or another. Who will win the AI arms race? Impossible to say this early, but consumers stand to benefit regardless. The permeation of AI through daily services and products will simply mean a superior experience for end users.

The AI 100 recognizes the teams and technologies that are successfully using AI to solve big challenges. The award winners will be announced on January 10th at The Innovation Summit being hosted at the Bacara Resort in Santa Barbara, CA. Companies will be selected on the basis of their Mosaic scores and their responses to interviews/questions posed by CB Insights' industry analysts. Companies can be located anywhere and must be privately-held. There is no cost to nominate a company or win the AI 100.

An artificial intelligence chatbot designed by a 19-year-old Stanford student appealed over 4,000,000 in parking fines in just twenty-one months, The Guardian reported. The AI is at the heart of a free service called DoNotPay that was designed by London native Joshua Browder to help users contest parking fines. After racking up 30 parking tickets in and around London when he was 18, the self-taught coder decided to help his fellow parking-challenged motorists with a program that would help them navigate the ticket appeals process. "I think the people getting parking tickets are the most vulnerable in society," Browder told The Guardian. "These people aren't looking to break the law. I think they're being exploited as a revenue source by the local government."

New research provides a Rosetta Stone that translates the language of reinforcement learning to the quantum realm. It tackles sticky questions like what it means for a quantum agent to learn and how the history of a quantum agent's interaction with its environment can be captured in a meaningful way. It also shows how a standard algorithm in the quantum toolkit can help agents learn faster in settings where an early stroke of luck can make a big difference--like when learning how to navigate a maze. Future research could investigate whether a quantum computer, with the added help of a quantum agent, could learn about its own noisy environment fast enough to change the way it reacts to errors. The work may also shed light on one of the deepest questions in physics: How does the everyday world arise from interactions that are, at the microscopic level, described by quantum mechanics?

Personalized, relevant, and timely marketing interactions are undoubtedly the most effective. In the past, marketers sent out blanket campaigns to their users irrespective of their behavior while interacting with their product, the stage they were at in the product lifecycle, or their customer LTV. Of course, if you send out a blanket campaign to your whole user base then the message will not resonate with each user equally, some will be engaged and others will disregard the interaction. This raises an issue for marketers – how can they ensure that they do not annoy their loyal users whilst communicating on a personal level with their users? Instead of trying to find one marketing campaign that will please you full user base, it is better to create multiple different campaigns for segments of users with different interests or preferences.

Microsoft's artificial intelligence (AI) technology can now recognize conversational speech slightly better than humans who do so professionally, according to recently-released research from the company. Microsoft recently got its AI's error rate in understanding speech down to about 5.9% from 6.3%, which puts it slightly below the human error rate, which is also close to 5.9% "We [improved] on our recently reported conversational speech recognition system by about 0.4%, and now exceed human performance by a small margin," the report stated. This news comes a mere month after Microsoft announced that it had reached an error rate of 6.3%, at the time setting a record among its peers. However, Microsoft's research also noted that error rates of human transcribers can vary between 4.1% to 9.6%, depending on how carefully they perform the transcription. SEE: AI experts weigh in on Microsoft CEO's 10 new rules for artificial intelligence Still, the closeness in quality to human transcription is impressive.

One of the major trends I have been researching recently, has been the shift in interest towards Artificial Intelligence (AI) in its multiple forms and guises, and the potential it has to analyse vast quantities of data and quickly derive actionable insights. As we all know, AI, Machine Learning and Deep Learning are not new. However, there has been huge investment in the space in recent years and the ability to automatically apply complex mathematical calculations to Big Data – over and over, faster and faster – is a recent development. With steady advances in digitisation and cheap computing power, no wonder people are excited about the possibilities. One of the areas of AI that gets the most attention is Deep Learning.

Welcome to the very first edition of The Morning After, Engadget's revamped newsletter. First, I'd like to congratulate you for subscribing to what is undoubtedly the greatest newsletter you'll ever read. Thanks are also in order for giving us some of your precious inbox real estate each day. You're hearing from me, Editor in Chief Michael Gorman, because this is the Weekend Edition -- in which I'll be putting context around the most interesting and important stories we published over the past week. Come Monday at 6 AM ET, and every weekday after, the daily version will hit your inbox with summaries of the biggest stories from the previous day, delivered with Engadget's trademark wit and insight.

We have lots of cutting-edge projects for you being discussed in the Gitter channels, ranging from mapping brain activity at scale, computer vision, neural networks, data visualization to natural language processing. Check out the list below and don't hesitate to join the conversation. Did we miss a particular community in this category, or do you want us to feature your channel? Drop us a line in the Gitter HQ and we will add it to the list.