Wallbox is looking to make inroads in North America with its first home electric vehicle charger for the region. It created a new version of the Pulsar Plus, which the company has been selling in Europe, for the market. Wallbox says the charger works with all EVs. The features include Amazon Alexa and Google Assistant voice control, Bluetooth and Wi-Fi connectivity, charge scheduling and flexible amperage setting. The device is available in two configurations.

In online advertising, recommender systems try to propose items from a list of products to potential customers according to their interests. Such systems have been increasingly deployed in E-commerce due to the rapid growth of information technology and availability of large datasets. The ever-increasing progress in the field of artificial intelligence has provided powerful tools for dealing with such real-life problems. Deep reinforcement learning (RL) that deploys deep neural networks as universal function approximators can be viewed as a valid approach for design and implementation of recommender systems. This paper provides a comparative study between value-based and policy-based deep RL algorithms for designing recommender systems for online advertising. The RecoGym environment is adopted for training these RL-based recommender systems, where the long short term memory (LSTM) is deployed to build value and policy networks in these two approaches, respectively. LSTM is used to take account of the key role that order plays in the sequence of item observations by users. The designed recommender systems aim at maximising the click-through rate (CTR) for the recommended items. Finally, guidelines are provided for choosing proper RL algorithms for different scenarios that the recommender system is expected to handle.

Amazon's new Echo Show 10 (third-generation), the first Alexa device with a motorized swiveling display, is now available for preorder for delivery starting on February 25. The new model, which was announced in September 2020, retails for $249.99 and is available in two colors: charcoal and glacier white. With the Echo Show 10, you can stream your favorite shows, follow along with recipes, call your friends and family, and more. The main draw for the Echo Show 10 is its smart motion. The touch-enabled display and embedded camera rotates atop a round base, which allows the built-in smart technology to keep the camera and screen in your line of sight automatically.

When motion is detected, the Kangaroo Doorbell Camera captures images, creating a two-second GIF-style clip that's delivered quickly to your phone. Instead of capturing videos, the doorbell stitches together GIF-like images when motion is detected or the doorbell is pressed. While Kanagroo's doorbell comes with basic features like motion detection, smart alerts, and night vision it lacks two very common smart doorbell functions: two-way talk and live video. For those reasons, comparing Kangaroo's doorbell to other smart doorbells is a bit like comparing apples to oranges, as it's designed to be a simple smart doorbell with limited features. It's still worth noting that the 70-degree field of view is narrow when compared to the 160-degree angles of other top doorbells we've tested from Nest and Eufy.

Google's latest Chromecast streaming media dongle is a bit different. With a full interface and a remote, the new Chromecast with Google TV costs £59.99 and sits above the basic £30 Chromecast. You can still Google Cast to the new device, but the new flat plastic dongle is more than just a simple receiver, running the full Android TV software similar to the Nvidia Shield or smart TVs from Sony and others. Once plugged in, the new Chromecast is set up using the Google Home app on an Android, iPhone or iPad in about five minutes. Scan the QR code on your TV, log in with the required Google account, and choose some apps to install.

With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedback. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game(GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods.

In the last few years, three major topics received increased interest: deep learning, NLP and conversational agents. Bringing these three topics together to create an amazing digital customer experience and indeed deploy in production and solve real-world problems is something innovative and disruptive. We introduce a new Portuguese financial domain language representation model called BERTa\'u. BERTa\'u is an uncased BERT-base trained from scratch with data from the Ita\'u virtual assistant chatbot solution. Our novel contribution is that BERTa\'u pretrained language model requires less data, reached state-of-the-art performance in three NLP tasks, and generates a smaller and lighter model that makes the deployment feasible. We developed three tasks to validate our model: information retrieval with Frequently Asked Questions (FAQ) from Ita\'u bank, sentiment analysis from our virtual assistant data, and a NER solution. All proposed tasks are real-world solutions in production on our environment and the usage of a specialist model proved to be effective when compared to Google BERT multilingual and the DPRQuestionEncoder from Facebook, available at Hugging Face. The BERTa\'u improves the performance in 22% of FAQ Retrieval MRR metric, 2.1% in Sentiment Analysis F1 score, 4.4% in NER F1 score and can also represent the same sequence in up to 66% fewer tokens when compared to "shelf models".

With the emergence of personality computing as a new research field related to artificial intelligence and personality psychology, we have witnessed an unprecedented proliferation of personality-aware recommendation systems. Unlike conventional recommendation systems, these new systems solve traditional problems such as the cold start and data sparsity problems. This survey aims to study and systematically classify personality-aware recommendation systems. To the best of our knowledge, this survey is the first that focuses on personality-aware recommendation systems. We explore the different design choices of personality-aware recommendation systems, by comparing their personality modeling methods, as well as their recommendation techniques. Furthermore, we present the commonly used datasets and point out some of the challenges of personality-aware recommendation systems.

Back at its fall hardware event last year, Amazon announced the Echo Show 10. And now it finally has a release date. You'll be able to pick the company's latest smart display on February 25th for $250. In case you need a refresher, the Echo Show 10 is one of Amazon's strangest devices to date. It features a rotating base and a computer vision algorithm that allows its 10-inch screen to reposition itself and face you head-on wherever you are in a room.

People have long used Tasker to take care of repetitive tasks on their Android device, or to customize its features based on things like whether they're at home or at the office. Now the app's features are a little easier to use since you can trigger them via Google Assistant. XDA points out a post by the developer on Reddit where he points out the currently available triggers, which you can use to run your favorite automations by name. Tasker is an incredibly powerful utility, but it can be a bit complex and intimidating, and voice control could be the difference in making it usable on a regular basis around your home. If you have the Google Play Pass subscription then access is free, and there's also a seven day trial available, otherwise it costs $3.49 in the Play Store.