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.

Parents want the best for their children. While the goal is apparent, figuring out how to do it is challenging. Parents want their kids to be healthy, happy, secure, smart, sociable, smart, athletic, etc. That is a lot to do considering that they have to balance it out based on how quality time they can make for their child, how much resources they can put in to child development, meeting socio-economic needs, etc. With everyone turning to artificial intelligent assistants for help, could there be an AI digital assistant for parents doing one of the most human of things: raising their children?

Graph-based recommender systems (GRSs) analyze the structural information in the graphical representation of data to make better recommendations, especially when the direct user-item relation data is sparse. Ranking-oriented GRSs that form a major class of recommendation systems, mostly use the graphical representation of preference (or rank) data for measuring node similarities, from which they can infer a recommendation list using a neighborhood-based mechanism. In this paper, we propose PGRec, a novel graph-based ranking-oriented recommendation framework. PGRec models the preferences of the users over items, by a novel graph structure called PrefGraph. This graph is then exploited by an improved embedding approach, taking advantage of both factorization and deep learning methods, to extract vectors representing users, items, and preferences. The resulting embedding are then used for predicting users' unknown pairwise preferences from which the final recommendation lists are inferred. We have evaluated the performance of the proposed method against the state of the art model-based and neighborhood-based recommendation methods, and our experiments show that PGRec outperforms the baseline algorithms up to 3.2% in terms of NDCG@10 in different MovieLens datasets.

Google wants to make its smart displays more fun. Today, it's adding a handful of new games that you can play with Google Assistant on smart displays like the Nest Hub Max. If you're a trivia fan, you might choose to play Jeopardy! There are also wordplay games, a drawing game and Google's version of an escape-the-room challenge. Google Assistant was already capable of playing a few voice-based games.

During Alexa Live 2020, Amazon announced a new Alexa Skills Challenge with conversations. The deadline to submit is at 5pm EDT on September 14, 2020 (47 days away). You can submit and find the full details by visiting https://alexaconversations.devpost.com/. Here are some items to get started with. Good luck if you choose to participate.