We've already explored some ways in which you can make Alexa more companionable during our current stay-at-home existence; naturally, there are plenty of ways to do the same with Google Assistant. If you like, you can change the sound of Google Assistant's voice (a trick that Alexa can't do, aside from celebrity cameos), teach it your nickname, and even engage in some surprisingly authentic back-and-forth with her (or him, depending on which voice you choose). If you've grown tired of the vaguely sterile sound of Google Assistant's default voice, switching to a new one is an easy way to get a fresh start. Ten different voices (including the standard Assistant voice) are available, with both male and female options, plus the voice of American or British accents. You can also pick the voice of Issa Rae (co-creator of HBO's Insecure) to take on a few of Google Assistant's standard duties, including answering questions, giving you weather reports, and telling jokes.

The enterprise digital assistant market has exploded fairly quickly, resulting in some confusion for buyers. Actionable Science, and the company's suite of HR, IT and Customer-facing digital assistants, has brought clarity through its emphasis on cognitive automation. This is what allows the technology to anticipate, understand and auto-resolve, but also calibrate when interactions should be high or low-touch, more personalized or trigger other actions. The company is also executing quite well for an early stage player, a testament to the experience of its founders.

Outreach, a sales engagement platform, unveiled a new Knowledge AI Assistant and platform capabilities at its recent Unleash Virtual Summit 2020 event. The AI Assistant is designed to provide secure sales enablement intelligence, advanced task automation and organization and management capabilities. The new Outreach features are now available, while Outreach Kaia will be released in late 2020. Outreach, a sales engagement platform, unveiled a new Knowledge AI Assistant (Kaia) and platform capabilities at its recent Unleash Virtual Summit 2020 event. The AI Assistant is designed to provide secure sales enablement intelligence, advanced task automation and organization and management capabilities.

Thomas Roszak was working as a maintenance technician at Ocado's giant warehouse in Hatfield when he received a very unusual assignment. His regular job involved repairing and maintaining the online supermarket's automated sorting and packing system, which puts together grocery orders from customers. It can be physically demanding work, manipulating heavy panels and working with other pieces of bulky machinery. In a project designed to ease that burden, Ocado Technology, had been developing a robot that can recognise when a technician might need help and step in with either the right tool or help with lifting. "I grew up on movies like The Terminator, so when I saw that robot I was actually impressed with what it looked like. You can actually imagine it looks like a man."

Artificial intelligence (AI) is the term used to describe the use of computers and technology to simulate intelligent behavior and critical thinking comparable to a human being. John McCarthy first defined the term AI in 1956 as the science and engineering of making intelligent machines. The following article gives a broad overview of AI in medicine, dealing with the terms and concepts as well as the current and future applications of AI. It aims to develop knowledge and familiarity with AI among primary care physicians. AI promises to change the practice of medicine in hitherto unknown ways.

More than 73 million user records have been stolen from a number of online services and are being sold on the dark web for a total of $18,000. The hacker group, named'ShinyHunters', scraped data from at least 10 companies including Zoosk, Chatbooks and the StarTribune. The online dating app, Zoosk, had the largest breach, as the cybercriminals grabbed 30 million user record and Chatbooks came in second with 15 million, according to ZDNet. Chatbooks is the only firm to acknowledge the attack, which said login credentials including names, email address and passwords were taken in the haul, along with some phone numbers and FacebookIDs. More than 73 million user records have been stolen from a number of online services and are being sold on the dark web for a total of $18,000.

In the latest in this series of posts, researchers from the EU-funded COMPRISE project write about privacy issues associated with voice assistants. They propose possible ways to maintain the privacy of users whilst ensuring that manufacturers can still access the quality usage data vital for improving the functionality of their products. "Tell me what you read and I tell you who you are." – Pierre de La Gorce Voice assistants, such as Alexa, Siri, or Google Assistant, are becoming increasingly popular. Some users are, however, worried about their vocal interactions with these devices being stored in the cloud, together with a textual transcript of every spoken word. But is there an actual threat associated with the collection of these data? And if so, could such threats be prevented?

The company says the pandemic has actually given their business a bump, with April being their best month of sales to date as homeowners stuck in their houses look to finally act on long-considered home improvement projects. Directly taking on Google and Amazon generally seems to be an ill-advised strategy for a young startup. It's even more complicated when you're competing on the home assistants front, a technically-complex, capital-intensive future platform that both tech giants have dumped substantial s…

I'm really fascinated by apps like Spotify and Shazam, and would like to pursue a career related to music information retrieval (MIR) and recommender systems. It seems like an esoteric field, especially since deep learning these days seems to primarily be focused on image and text data. Maybe we can connect and form a study group! Maybe we can share interesting papers (e.g. from ISMIR and ACM RecSys conferences), work on projects together, and share study materials.

Intelligent systems designed using machine learning algorithms require a large number of labeled data. Background knowledge provides complementary, real world factual information that can augment the limited labeled data to train a machine learning algorithm. The term Knowledge Graph (KG) is in vogue as for many practical applications, it is convenient and useful to organize this background knowledge in the form of a graph. Recent academic research and implemented industrial intelligent systems have shown promising performance for machine learning algorithms that combine training data with a knowledge graph. In this article, we discuss the use of relevant KGs to enhance input data for two applications that use machine learning -- recommendation and community detection. The KG improves both accuracy and explainability.