As smart home technology has progressed over the last five years, the interconnectedness of devices has been the central draw. The ability to tie your household lights to your front door, or to connect a security system to sirens throughout the home, appeals to people due to the convenience and peace of mind it can provide. Smart assistants have been the major development, however. The birth and rise of Amazon's Alexa and Google Assistant has played a critical role in the development of smart technology. Despite the controversy these technologies generated, particularly surrounding privacy implications, more and more devices enter the market with built-in voice assistants.

The Bose Home Speaker 300 is one of the most capable speakers you'll find, and it manages to stay around the $200 price point that's reasonable to expect of a midsize smart speaker. Its understated aesthetic will be at home in almost any room, and its 360-degree sound field means you can place it on any counter or table and still get good sound throughout the space. This is a very loud speaker for its size, and clarity does begin to suffer as the volume nears its max, but for most uses, it's not going to be a dealbreaker. Here are the Home Speaker 300's specs: The Bose Home Speaker 300 offers several ways to connect to music sources--even an old-school auxiliary input. Bose's smart speakers really excel when it comes to connectivity.

Artificial intelligence is top of mind for many in the marketing and communications world. Many Marcom departments already use AI to analyze consumer behavior and try to predict future needs. Many brands use algorithms to recommend personalized content, show personalized ads, as well as power customer service chatbots. But what if AI can help brands take their brand voice to the next level? Brands usually spend thousands, if not millions of dollars, fine-tuning their brand voice, which describes a company's personality. Now, AI in digital marketing has a whole new face - literally, as digital avatars and synthetic beings enter the digital marketing world.

With its fourth-generation model, August has one of the best smart locks on the market. It's easy to install, works with most digital assistants and lets you keep using your existing mechanical locks. At $249 it is more expensive than some other smart locks, but starting today you can save $20 by using the code ENGADGETLOCK at checkout. That brings it down to $229, which is the cheapest price we've seen to date. August's latest smart lock is nearly half the size of previous models, comes in silver or black and is invisible from the exterior. It features door-sensing tech that informs you when your door is closed and locked, voice control via Alexa and the Google Assistant (via August Connect), an activity feed to track who comes and goes and the ability to automatically lock itself behind you.

Jennifer Wood-Thompson, an Indianapolis-based office manger, uses both Siri and Alexa for simple tasks such as creating shopping lists, checking the weather and playing music. She said, "My relationship with them has always been a little volatile, because sometimes they're not cooperative. But being home for 2½ months definitely escalated it a little bit." So, she added, "when you ask Alexa to turn on the light and she doesn't do anything, I tend to just yell back at her."

Apple (NASDAQ:AAPL) has acquired Inductiv, a machine-learning (ML) start-up that uses artificial intelligence (AI) to automatically identify and correct errors that may be lurking in data, according to a Bloomberg report. This marks the second such acquisition in as many months aimed at improving the functionality of Siri, the iPhone's voice-activated digital assistant. The company confirmed the deal using its typical boilerplate language, saying that Apple "buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans." ML is a branch of AI that helps computers learn tasks without being specifically programmed for them. The systems use sophisticated algorithms to sift through reams of data, finding patterns that might otherwise be missed, and drawing conclusions based on what it finds.

The Covid-19 pandemic has clearly placed an extraordinary amount of pressure on businesses in practically every sector. Companies have had to pivot and adjust to a new way of working, with a rapid switch to remote teams and virtual workforces - many in a matter of days. The reality is, as we emerge from the current situation, it is inevitable that there will be a lasting impact from the changes that have had to be made. The landscape for business has been altered for good. We have already seen many businesses forced to cease all discretionary spending, pause recruitment plans indefinitely, cut marketing spend while still demonstrating a strong return on investment, and yet still make decisions on how best to drive and generate pipeline.

Complex applications such as big data analytics involve different forms of coupling relationships that reflect interactions between factors related to technical, business (domain-specific) and environmental (including socio-cultural and economic) aspects. There are diverse forms of couplings embedded in poor-structured and ill-structured data. Such couplings are ubiquitous, implicit and/or explicit, objective and/or subjective, heterogeneous and/or homogeneous, presenting complexities to existing learning systems in statistics, mathematics and computer sciences, such as typical dependency, association and correlation relationships. Modeling and learning such couplings thus is fundamental but challenging. This paper discusses the concept of coupling learning, focusing on the involvement of coupling relationships in learning systems. Coupling learning has great potential for building a deep understanding of the essence of business problems and handling challenges that have not been addressed well by existing learning theories and tools. This argument is verified by several case studies on coupling learning, including handling coupling in recommender systems, incorporating couplings into coupled clustering, coupling document clustering, coupled recommender algorithms and coupled behavior analysis for groups.

Alexa is the world's most popular smart assistant and the driving force behind Amazon's beloved Echo smart speaker lineup. These voice-controlled, Alexa-enabled smart speakers can be used to manage your smart home, give you the forecasts for the day ahead, and much more. If you're thinking about inviting Alexa into your home via one of Amazon's Echo speakers, you may be wondering which one to buy. We took a look at two of Amazon's most popular smart speakers, the Echo (third-generation) and the Echo Dot (third-generation) to help you decide which of these handy smart speakers is best for you. The Echo Dot (third-generation) is one of the smallest Amazon Echo smart speakers. The most obvious visual difference between the Echo Dot and the Echo is the size.

Consider the artificially intelligent voices you hear on a regular basis. Are any of them men? Whether it's Apple's Siri, Microsoft's Cortana, Amazon's Alexa, or virtually any GPS system, chances are the computerized personalities in your life are women. This gender imbalance is pervasive in fiction as well as reality. Films like "Her" and "Ex Machina" reflect our anxieties about what intelligent machines mean for humanity.