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 Personal Assistant Systems


Deep Reinforcement Learning for List-wise Recommendations

arXiv.org Machine Learning

Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional recommender systems consider the recommendation procedure as a static process and make recommendations following a fixed strategy. In this paper, we propose a novel recommender system with the capability of continuously improving its strategies during the interactions with users. We model the sequential interactions between users and a recommender system as a Markov Decision Process (MDP) and leverage Reinforcement Learning (RL) to automatically learn the optimal strategies via recommending trial-and-error items and receiving reinforcements of these items from users' feedbacks. In particular, we introduce an online user-agent interacting environment simulator, which can pre-train and evaluate model parameters offline before applying the model online. Moreover, we validate the importance of list-wise recommendations during the interactions between users and agent, and develop a novel approach to incorporate them into the proposed framework LIRD for list-wide recommendations. The experimental results based on a real-world e-commerce dataset demonstrate the effectiveness of the proposed framework.


AI and machine learning necessitate a smarter app development and marketing playbook

#artificialintelligence

Build it and they will come. Those were the good ole days. It used to be good enough to design a great app. Add to that an engaging user experience (UX), positive feedback, a high ranking and word of mouth, and your app was ensured continued success. Nowadays however, mobile consumers are simply overwhelmed by choice.


The rise of virtual assistants in the office

#artificialintelligence

It's been six years since Apple added Siri to iOS and voice became a key way users could interact with technology. In the years since, Google Assistant and Alexa have also established strong footholds as central players in the way we manage myriad services and smart-home devices -- and Cortana has become an integral part of the PC. As much as voice-activated virtual assistants have begun to transform the consumer landscape on devices from smartphones and smartwatches to smart speakers, they have yet to truly break through in the enterprise. That isn't to say we don't already accomplish business tasks using these virtual assistants. Many of us rely on them for quick tasks such as getting directions, scheduling appointments and responding to messages.


Amazon Alexa now controls your microwave

Engadget

Alexa's smart home skills aren't just for turning on the lights or locking your door these days -- now, they can help fulfill your culinary ambitions. Amazon has added cooking abilities to its Smart Home Skill framework, letting you control microwaves (and eventually conventional ovens) with your voice. Instead of pressing umpteen buttons, you can simply ask Alexa to "defrost 3lbs of chicken." Suffice it to say this could be helpful if you don't want to start cooking right away, or if you just hate your microwave's interface. Expect to see the cooking features in use very soon.


Microsoft shares pre-order details for the $319 Cortana thermostat

Engadget

Microsoft unveiled its Cortana-powered thermostat, called GLAS, back in July, and now we have more details on it. The software giant partnered with Johnson Controls, the maker of the first in-room thermostat, to create the device, and it's a beauty. It also comes with a hefty price tag: $319, and is available for pre-order now for delivery in March 2018. GLAD is powered by a Windows 10 IoT Core and features a gorgeous translucent touch display. You can control the temperature, check the weather, monitor both indoor and outdoor air quality and more.


I Have to Ask: The A.O. Scott Edition

Slate

A.O. Scott is a film critic at the New York Times. He sits down with Isaac Chotiner to discuss the year in movies, being a film critic in the age of Rotten Tomatoes, and wrestling with Hollywood in a postโ€“Harvey Weinstein world.


Microsoft's Cortana isn't able to identify songs anymore

Engadget

Microsoft didn't have much luck in the digital music realm, from the Zune to its Groove Music service. At the end of 2017, the company switched all of its existing Groove users over to Spotify and shut Groove down. But now it turns out the move came with an unforeseen complication, as reported by Neowin. Cortana, Microsoft's smart assistant, can no longer recognize individual songs. Previously, users could use the song identification feature by pressing Cortana's music icon while a song was playing.


Robo-Caregiving & Why You Might Delegate Your Loved Ones to a Robot

#artificialintelligence

Robotics is already changing how we live, shop, invest, travel, and soon, robo-caregivers will transform how we provide care. Advances in AI will deliver extraordinarily innovative services in support of our loved ones. However, the use of robots to care for our children, elderly and disabled will also give rise to some very human questions. Caregiving is social science jargon for providing unpaid support to a family member or friend who has physical, psychological or development needs. Most caregivers do not know what a caregiver is or even know that they are caregivers.


New LG TVs to Feature Google Assistant

#artificialintelligence

Angela has been a PCMag reporter since January 2012. Prior to joining the team, she worked as a reporter for SC Magazine, covering everything related to hackers and computer security. Angela has also written for The Northern Valley Suburbanite in New Jersey, The Dominion Post in West Virginia, and the Uniontown-Herald Standard in Pennsylvania. She is a graduate of West Virginia University's Perely Isaac Reed School of Journalism.


AI in 2018: Google seeks to turn early focus on AI into cash

#artificialintelligence

This straightforward order to display pictures of delicious fried confections, spoken into a Google Pixel 2 smartphone with the Google Assistant, is the type of command that users have been executing in Alphabet Inc.'s GOOGL, 1.13% GOOG, 1.00% search engine for years. Behind the scenes, however, the response to this type of query now leverages an enormous amount of machine-learning technology that Google has spent years and billions of dollars developing, in hopes of being a leader in artificial intelligence. For that command to function, software produced by Alphabet-owned Google needed to deploy image content analysis systems, voice recognition and a host of other technologies that revolve around machine learning and AI, mostly pumped through high-tech data centers the company has built. It also decided to make the hardware that runs it, with an eye on pushing the abilities of its services to new places in 2018 and beyond. Since 2013, Alphabet has ramped up its infrastructure spending, pouring $57.36 billion into capital expenditures--roughly $10 billion a year.