Mobile maps route us through traffic, algorithms can now pilot automobiles, virtual assistants help us smoothly toggle between work and life, and smart code is adept at surfacing our next our new favorite song. But AI could prove dangerous, too. Tesla CEO Elon Musk once warned that biased, unmonitored and unregulated AI could be the "greatest risk we face as a civilization." Instead, AI experts are concerned that automated systems are likely to absorb bias from human programmers. And when bias is coded into the algorithms that power AI it will be nearly impossible to remove.

Google has unveiled updates for its artificially intelligent voice assistant and new privacy tools to give people more control over how they're being tracked on the go or at home. The company also unveiled a new Pixel phone and smart home display. Google just made ordering pizza, pad thai and fried chicken from your favorite restaurants even easier. The search giant announced on Thursday that it updated apps like Google Maps, Google Search and the Google Assistant to make ordering food online more convenient, so you don't have to download as many third-party apps. "When I was pregnant with my son last year, my cravings were completely overpowering," said Google's senior product manager of food ordering, Anantica Singh, in a blog post.

When we program morality into robots, are we doomed to disappoint them with our very human ethical inconsistency? In his newest novel, Machines Like Me, the British writer Ian McEwan takes on the rise of artificial intelligence, exploring how humans would react to the creation of perfectly human-like robots. But he does it in his particularly McEwan-esque fashion. Rather than creating a work of speculative fiction set in a near future where general artificial intelligence has become a reality, McEwan sets Machines Like Me in an alternate past, a 1980s London where the internet already exists and the English A.I. pioneer Alan Turing -- who in our world was effectively hounded to death by government authorities in 1954 because of his homosexuality -- instead lived and went on to create the first true A.I.: a collection of androids for purchase called Adams and Eves. Why paranoia about digital voice assistants is overblown.

Are you interested in machine learning and its applications? If you're looking to learn something new and great, how about a machine learning recommendation system? Well, don't be scared or blown away with those massive terms and words, they just tell someone what exactly some code does. Machine learning has always been in the news, whether for taking away jobs or making a robot understand and reply to a human. But what exactly can we do with machine learning?

Are you interested in machine learning and its applications? If you're looking to learn something new and great, how about a machine learning recommendation system? Well, don't be scared or blown away with those massive terms and words, they just tell someone what exactly some code does. Machine learning has always been in the news, whether for taking away jobs or making a robot understand and reply to a human. But what exactly can we do with machine learning?

"While such phrasings may be natural for a user, current speech processing systems are not configured to handle commands that are not preceded by a wakeword," wrote the patent application's authors, Kurt Wesley Piersol and Gabriel Beddingfield. "Offered is a system to correct this problem." In a statement, an Amazon spokesperson told BuzzFeed News, "The technology in this patent is not in use, and referring to the potential use of patents is highly speculative." The spokesperson added that Amazon files many patent applications that are not ultimately implemented into consumer-facing products, and that patents do not necessarily reflect "current or near-future states of products and services." According to the patent application, after a wake word is detected, Alexa may "look backwards" to determine if the command came before the wake word, and use pauses in speech to identify the beginning of the command.

Content-based news recommendation systems need to recommend news articles based on the topics and content of articles without using user specific information. Many news articles describe the occurrence of specific events and named entities including people, places or objects. In this paper, we propose a graph traversal algorithm as well as a novel weighting scheme for cold-start content based news recommendation utilizing these named entities. Seeking to create a higher degree of user-specific relevance, our algorithm computes the shortest distance between named entities, across news articles, over a large knowledge graph. Moreover, we have created a new human annotated data set for evaluating content based news recommendation systems. Experimental results show our method is suitable to tackle the hard cold-start problem and it produces stronger Pearson correlation to human similarity scores than other cold-start methods. Our method is also complementary and a combination with the conventional cold-start recommendation methods may yield significant performance gains. The dataset, CNRec, is available at: https://github.com/kevinj22/CNRec

With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to recommendation systems to video/audio surveillance. More recently, with the proliferation of mobile computing and Internet-of-Things (IoT), billions of mobile and IoT devices are connected to the Internet, generating zillions Bytes of data at the network edge. Driving by this trend, there is an urgent need to push the AI frontiers to the network edge so as to fully unleash the potential of the edge big data. To meet this demand, edge computing, an emerging paradigm that pushes computing tasks and services from the network core to the network edge, has been widely recognized as a promising solution. The resulted new inter-discipline, edge AI or edge intelligence, is beginning to receive a tremendous amount of interest. However, research on edge intelligence is still in its infancy stage, and a dedicated venue for exchanging the recent advances of edge intelligence is highly desired by both the computer system and artificial intelligence communities. To this end, we conduct a comprehensive survey of the recent research efforts on edge intelligence. Specifically, we first review the background and motivation for artificial intelligence running at the network edge. We then provide an overview of the overarching architectures, frameworks and emerging key technologies for deep learning model towards training/inference at the network edge. Finally, we discuss future research opportunities on edge intelligence. We believe that this survey will elicit escalating attentions, stimulate fruitful discussions and inspire further research ideas on edge intelligence.

Corporate payments technology firm Bill.com is rolling out a new platform designed to deploy artificial intelligence (AI) for automated workflows. In an announcement on Wednesday (May 22), Bill.com said it has launched the Intelligent Business Payments Platform for small and medium-sized businesses that need a more efficient business payments solution. Bill.com pointed to its own research, which found the payments platform saves SMB users an average of 5.5 hours every week, or 35 business days a year, by automating processes that professionals had previously completed manually. The platform includes an Intelligent Virtual Assistant, which automates invoice processing and approval, and uses machine learning to automatically capture data from those invoices and identify potential errors. It can also recognize bill approval routing and payment thresholds.

The Echo Wall Clock looks classic but acts futuristic. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. If you own an Amazon Echo smart speaker, you need to keep reading. Last last year, Amazon started teasing the Echo Wall Clock, an Alexa-connected device that syncs with your Echo to display visual timers and alarms.