AI has become an integral part of every tech company's pitch to consumers. Fail to hype up machine learning or neural networks when unveiling a new product, and you might as well be hawking hand-cranked calculators. This can lead to overpromising. But judging by its recent WWDC performance, Apple has adopted a smarter and quieter approach. Sprinkled throughout Apple's announcements about iOS, iPadOS, and macOS were a number of features and updates that have machine learning at their heart.

The updated Amazon Alexa Plus is seen above. When it comes to making your home smart, you need the right gear. Amazon's Alexa resides in millions of households and make sure you get the most out of yours. Tap or click for 13 Alexa skills you'll use over and over again. While you're adjusting settings, it's not just snooping Big Tech companies you need to guard against.

Virtual assistants turn 16 this year and you don't have to look too hard - or speak too loudly - to find them. In fact, there will be around 8 billion voice-based devices by 2023 - more than the world's population today. From Amazon's Echo and Google's Assistant to Apple's Siri, Samsung's Bixby and Microsoft's Cortana, billions of people around the world are using their voices every day to schedule appointments, get directions, play music or get answers quickly-- all things that once required us to tediously type or write. Even Twitter recently announced that users can now audio tweet their inner musings. And yet, despite widespread adoption of voice-based devices in our personal lives, applications based on voice are nowhere as pervasive in our professional lives as they are in our homes. One could argue that consumer technology leads the way in changing human behavior and that the consumerization of the enterprise is always driven first by an expectation that work tools should be equally as convenient as personal technology solutions.

For example, NCF [8] takes user-item implicit feedback data as inputs for the rating prediction task; and DeepFM [6] leverages both numerical and categorical data for the CTR prediction task. However, high degree of specialization comes at the expense of model adaptability and tuning complexity. As recommendation tasks evolve over time and additional types of data are collected, the originally apt model can either become obsolete or require tremendous tuning efforts. So far, several pipelines for recommender systems, e.g., OpenRec [16] and SMORe [4], tried to address the adaptability issue via providing modular base blocks that can be selected according to the context of recommendation. Nevertheless, both determining the blocks to use and tuning the model parameters are not straightforward when facing new data and changing tasks. In order to bridge the gap, we present AutoRec, which aims to provide an end-to-end solution to automate model selection and hyperparameter tuning. While many AutoML libraries, such as Auto-Sklearn [5] and TPOT [12] have shown promising results in general-purpose machine learning tasks (e.g., regression and hyperparameter tuning) and

They might apply to one of these futuristic job ads one day. Fifteen years ago, people would have looked at you sideways if you told them you were a data scientist, driverless car engineer, or drone operator. It's hard to believe, but in 2006 those industries didn't really exist. By 2030, automation is expected to hit a midpoint, "something like 16 percent of occupations would have been automated--and there would be impact and dislocation as a result of these technologies." Artificial Intelligence, spatial computing (augmented and virtual reality), brain-computer interfaces, are all set to substitute labor or complement it in some way.

The digital revolution has been increasingly enhancing the impact of marketing on management. Digital marketing is quite a broad term encompassing social media marketing, e-mail marketing, internet marketing, and search engine marketing, among others. While e-mails, social media, websites, and e-commerce, are tools that marketers use to promote services and products to their target audience, Artificial Intelligence (AI) is now intrinsically being used for digital marketing to map the right kind of promotional tools for specific market offerings. AI and Customer Value A combination of AI and digital marketing has been adopted extensively across sectors such as healthcare, financial services, retail, automobiles, education, and entertainment. As a case in point, the ability to track data makes it possible for retailers to develop strategies for a better understanding of consumer behaviour by keeping the user's purchase life-cycle at the center.

Technology has made it easier for bright ideas to come into fruition, what with the available online tools and software that you can download and use even in the comfort of home. Selling that idea, however, is not as easy, and this is where some startups fall short. There are many considerations after transforming a great idea into something tangible for your target market. Not least of which is how a business can deliver the right product or service to the right market at the right time. This is where a go-to-market strategy comes into play.

Google is making it easier to connect with more people in video calls and meetings using its Nest Hub Max video display device. The Nest Hub Max ($229), released about 10 months ago, served as Google's entry in the smart video display competition with Amazon's Echo Show and Facebook's Portal. An update, out now, lets you make group calls of up to 32 with the Google Duo app – and up to 100 in the Google Meet app. Previously, Nest Hub Max get-togethers maxed out at person to person calls using Google Duo. You create your groups in the Google Duo app (available for Android and iOS) and then tell the Hub Max, "Hey, Google, make a group call."

Minsky and McCarthy, in the 1950s, described artificial intelligence as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task. The AI systems typically demonstrate behaviors associated with human intelligence like planning, learning, reasoning, problem-solving, knowledge representation, perception, motion, manipulation, and to a lesser extent, social intelligence, and creativity. Nowadays, artificial intelligence is all around us in computers, speech and language recognition of the Siri virtual assistant on the Apple iPhone, in the vision-recognition systems on self-driving cars, in the recommendation engines that suggest products you might like based on what you bought in the past, interpreting video feeds from drones carrying out visual inspections of infrastructure such as oil pipelines, organizing personal and business calendars, responding to simple customer-service queries, coordinating with other intelligent systems to carry out tasks like booking a hotel at a suitable time and location, helping radiologists to spot potential tumors in X-rays, flagging inappropriate content online, detecting wear and tear in elevators from data gathered by IoT devices, the list goes on and on. There is a flood of virtual assistants, such as Apple's Siri, Amazon's Alexa, Google Assistant, and Microsoft Cortana, etc. The AI is capable of executing vastly different tasks, anything from giving you a haircut to building complex robots as commonly seen in movies, the likes of HAL in 2001, or Skynet in The Terminator, though doesn't exist today certainly a reality of tomorrow. What is machine learning: Machine learning is where a computer system is fed large amounts of data which it then uses to learn how to carry out a specific task such as understanding speech or captioning a photograph.

When it comes to smart assistants, we like Google Assistant over Amazon's Alexa here at WIRED. It's easier to set up and is just better at answering voice questions, hands-free. A growing number of smart speakers and smart displays support it, too. It was $574 and dropped down to $300 around March. Now it's the lowest we've seen, and the Amazon price is about $150 cheaper than other major retailers like B&H.