Google's next smartphone could be just a few months away from hitting the shelves. The tech giant is expected to release the Pixel 3 and Pixel 3 XL smartphones on October 9th, according to Bloomberg. However, unlike previous years, the devices will be released at a New York City launch event, instead of San Francisco, like Google has done in the past. Google's next smartphone could be just a few months away from hitting the shelves. The Pixel and Pixel 2 were launched on October 4th in 2016 and 2017, respectively, so this year's event would be slightly later in the month. It comes as there have been weeks of leaks claiming to show off the Pixel 3 and Pixel 3 XL's specs.

You now have a viable option if you want a high-end Google Assistant speaker that slots between the good-but-not-mind-blowing Home Max and Bang & Olufsen's ultra-premium Beosound models. Harman Kardon has unveiled the Citation 500, a smart speaker that touts 200W of stereo audio and high-resolution 24-bit/96kHz support in a compact form for £549 (about $708). It's difficult to say for sure that it bests the Home Max when Google doesn't provide official wattage, but it could easily outperform much of what's on the market. As it stands, the Citation isn't relying solely on audio prowess. It serves as a smart home hub, and an LCD on the top helps control playback when you're not shouting song requests.

JP Morgan Chase is rebuilding its consumer business model to create a "digital everything" strategy that trades short-term losses for long-term profits. With $2.6 trillion in total assets, JP Morgan Chase is the largest bank in the US. Led by Chairman and CEO Jamie Dimon, the bank is undergoing a transformation, moving away from offline legacy systems and into the digital age. Over the past two years, the bank has spent nearly $20B to scale its technology and prepare itself for the next generation of banking. Today, JPMorgan (JPM) is using its capital and scale to build an entirely digital bank. This is in part because customers no longer need to rely on banks for financial services -- 60% of US bank customers say they are willing to try a financial product from a tech firm they already use, and that number rises to 73% for customers aged 18 -- 34. This trend towards digitization is already starting to play out as fintechs circumvent banking licenses by partnering with issuing banks to offer checking account-like products. JPM's digital push, a theme it refers to as "Mobile First, Digital Everything," is showing positive early results. In Q2'18 JPM had about 48M active digital customers, while top competitor Bank of America had 36M.

Cross-domain collaborative filtering (CF) aims to alleviate data sparsity in single-domain CF by leveraging knowledge transferred from related domains. Many traditional methods focus on enriching compared neighborhood relations in CF directly to address the sparsity problem. In this paper, we propose superhighway construction, an alternative explicit relation-enrichment procedure, to improve recommendations by enhancing cross-domain connectivity. Specifically, assuming partially overlapped items (users), superhighway bypasses multi-hop inter-domain paths between cross-domain users (items, respectively) with direct paths to enrich the cross-domain connectivity. The experiments conducted on a real-world cross-region music dataset and a cross-platform movie dataset show that the proposed superhighway construction significantly improves recommendation performance in both target and source domains.

Implicit feedback is the simplest form of user feedback that can be used for item recommendation. It is easy to collect and domain independent. However, there is a lack of negative examples. Existing works circumvent this problem by making various assumptions regarding the unconsumed items, which fail to hold when the user did not consume an item because she was unaware of it. In this paper, we propose as a novel method for addressing the lack of negative examples in implicit feedback. The motivation is that if there is a large group of users who share the same taste and none of them consumed an item, then it is highly likely that the item is irrelevant to this taste. We use Hierarchical Latent Tree Analysis(HLTA) to identify taste-based user groups and make recommendations for a user based on her memberships in the groups.

If you've ever dreamed of having your own personal stylist--or if you just want to get perfect shots of your #OutfitoftheDay--Amazon's Echo Look might be you new BFF. And today you can get the Alexa-powered camera for just $120, 40 percent off its list price and the first price drop everRemove non-product link. And what's more, today's deal also includes a $25 Amazon Fashion credit that's good on Amazon-sold clothing until December 31, 2018. The Look comes with a built-in camera to take full-body pictures of your daily look, with backgrounds blurred out so the focus is on you. If a photo just isn't enough to see all angles of your outfit, it will take a short 360-degree video or even let you see a live feed via the connected mobile app.

Currently, our AI systems tend to be built for a specific purpose. This is Narrow AI – artificial intelligence that is designed to complete one highly defined task. Common applications for Narrow AI include tasks such as image recognition, automatic video recommendations on sites such as YouTube and Netflix, and the natural language processing ability of the Amazon Alexa digital personal assistant. Whilst Narrow AI systems can excel at executing highly complex tasks, their abilities are limited. A Narrow AI programme that is extremely advanced in its field will be unable to solve tasks outside of that domain – even if they are technically much simpler.

Don't you just love how Siri, Alexa or Google Assistant answer all of your questions? Isn't it interesting when you receive prompt responses on some website's chat box no matter what the time is? Yes, marketers know this interests you and this is why AI holds fascinating possibilities in the future for marketing. Using AI, brands are studying user needs, behaviours and predicting their future actions. AI's competence to handle a large volume of data, and finding reasons and patterns among them has given marketers exceptional ability to make data-driven predictions and decisions.

The gadgets we think of as home essentials have changed beyond recognition in the past few decades. In 1970, just 35 per cent of homes had a landline telephone and there were no mobiles. Now, technologies that were once the stuff of science fiction are part of our daily lives: take Amazon's Alexa – inspired by the talking computer on the Starship Enterprise in Star Trek. Today, millions of British households own these'smart speakers' that allow voice commands to control everything from TVs to lighting systems. Indeed, as of this year, one in five households will be'smart', with devices that are wirelessly connected to the internet, and controlled via smartphone or a hub.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)