Recently, neural networks have been widely used in e-commerce recommender systems, owing to the rapid development of deep learning. We formalize the recommender system as a sequential recommendation problem, intending to predict the next items that the user might be interacted with. Recent works usually give an overall embedding from a user's behavior sequence. However, a unified user embedding cannot reflect the user's multiple interests during a period. In this paper, we propose a novel controllable multi-interest framework for the sequential recommendation, called ComiRec. Our multi-interest module captures multiple interests from user behavior sequences, which can be exploited for retrieving candidate items from the large-scale item pool. These items are then fed into an aggregation module to obtain the overall recommendation. The aggregation module leverages a controllable factor to balance the recommendation accuracy and diversity. We conduct experiments for the sequential recommendation on two real-world datasets, Amazon and Taobao. Experimental results demonstrate that our framework achieves significant improvements over state-of-the-art models. Our framework has also been successfully deployed on the offline Alibaba distributed cloud platform.

After almost six years on the market, smart speakers now come in a variety of sizes, shapes, capabilities and prices. Whether you want a cheap speaker to keep the kids entertained, one that doubles as a digital photo frame or one that sounds so good you'll want to yell "turn it up to 11", here's a quick guide to the best on the market. Google's Assistant is the best voice system on the market. It has better understanding than rivals, an enormous range of knowledge and – importantly – the ability to choose between male and female voices, even on a user-by-user basis as Google can distinguish between the individuals giving instructions. The Nest Mini is the second generation of Google's smallest and cheapest smart speaker.

We already knew Cortana's days as a consumer-facing digital assistant were numbered after Microsoft said earlier this year it would remove the AI from its Android launcher app. But the company has now detailed additional cuts that users are likely to feel more keenly. The changes won't happen all at once. To start, Microsoft will end support for third-party Cortana skills on September 7th, 2020. In early 2021, Microsoft then plans to discontinue the Cortana apps on iOS and Android, as well as remove the current Cortana functionality the first-generation Surface Headphones feature.

In February, Microsoft revealed that it would be slowly phasing out Cortana functionality in mobile and other devices, implying that the third-party Harman Kardon Invoke would be among them. On Friday, Microsoft clarified that these changes will occur in early 2021, including the Invoke--but the company will offer gift cards of up to $50 to sweeten the deal. Microsoft said Friday that it is eliminating the third-party Cortana skills--Cortana plug-ins that could be used to ask for a Fitbit activity summary, for example--by September 7. In January, 2021, the mobile Cortana app for iOS and Android will stop working. And in "early 2021," Microsoft says, the Cortana functionality for the Invoke will also cease to exist.

Abhi is the Co-founder & Chief of Product, Tech @ Zylotech with rich experience across AI and customer data management led revenue-ops. Consumers have high expectations when engaging with brands, whether those brands are B2C or B2B. They expect companies they engage with to be omnichannel, engaging with them on multiple devices and all channels, with quality and consistent experiences across all channels. They expect immediacy for nearly everything from answers to questions with relevant content to personalized recommendations and contextualized offers. And they expect interactions with brands to be personalized based on their needs at the moment, not just on their broader needs.

In 2012 we started a project to allow our Home Control System to support natural language processing. This allows it to understand basic commands in English via the spoken voice or via a text interface (e.g. Our thinking back then and still is that a voice only interface is severely limiting. This approach also fits better with our user interface research and strategy. Since then we have been extending this to essentially be a narrow Artificial Intelligence (AI) capability.

Motorized window treatments that can open and close on command, on a schedule, or even based on room occupancy are the ultimate finishing touch for any smart home. Like smart lighting, smart window treatments offer a host of benefits in terms of convenience, security, and energy conservation. There's a safety angle, too: There are no pull cords that pose a strangulation risk to children and pets. But the wow factor they deliver also renders them a luxury item--even deploying them one room at a time can cost thousands of dollars if each room has a lot of windows. Shades are a soft window covering, typically made of fabric.

Google Play Music is currently the best streaming music service for people who have their own music collections. The service lets users upload 50,000 of their own music files, then access the audio on a wide range of streaming devices. It's a great way to access your own music files from anywhere, and it doesn't cost a dime. Unfortunately, the free ride is just about over. At the end of this year, Google will discontinue Google Play Music and push users over to YouTube Music as a replacement.

Artificial intelligence (AI) has reached new heights. The mix of the innovation, information, and talent that make intelligent frameworks possible has arrived at a critical stage, driving phenomenal development in AI investment. The time of AI has arrived. Established organizations are now moving past experimentation. Money is flowing into AI advances and applications at large organizations.

You must have heard about machine learning as it has become a buzzword. Machine learning is an innovative method of analyzing data that has the capability to automate analytical model building. It is a field of computer science and an important branch of artificial intelligence. Machine learning is based on the revolutionary idea that computer systems could learn from data, just like humans. As a result, they can identify patterns and make informed decisions without resorting to much human intervention. Machine learning is now a keyword in the world of technology.