Check out the "Text, Language, and Speech" sessions at the O'Reilly Artificial Intelligence conference in London, 14-17 October 2019. As companies begin to explore AI technologies, three areas in particular are garnering a lot of attention: computer vision, natural language applications, and speech technologies. A recent report from the World Intellectual Patent Office (WIPO) found that together these three areas accounted for a majority of patents related to AI: computer vision (49% of all patents), natural language processing (NLP) (14%), and speech (13%). Companies are awash with unstructured and semi-structured text, and many organizations already have some experience with NLP and text analytics. While fewer companies have infrastructure for collecting and storing images or video, computer vision is an area that many companies are beginning to explore.

It took senior editor Nicole Lee a bit of time to figure out where the Google Nest Hub (originally the Google Home Hub) fit into her life because it seemed too small to be used like a typical home assistant device. At a mere 7 inches, the smart display is meant to be a personal assistant for any room of the house. Because the Nest Hub lacks a camera, it's even good for the bedroom. Once Nicole started using the Nest Hub like a digital photo frame, albeit one with the smarts to control home automated devices that can also use Google apps, she began to see the strengths of this discreet commected display. In the end, she granted the Nest Hub a commendable score of 87. User reviewers, who always tend to score more harshly, gave the Nest Hub a passable score of 72.

Editor's Note: Updated at 6:34 pm EDT on October 21st to include Google's updated statement about the link between the discovered vulnerabilities and the Great Google Action Disappearance saga. Security Research Labs (SR Labs), "a Berlin-based hacking research collective and consulting think tank," revealed yesterday that it had created and received certification for several Alexa skills and Google Actions that exploited security vulnerabilities in the voice assistants. The firm discussed two specific attacks in a blog post related to phishing and eavesdropping. The former demonstrated how a developer, using the standard Alexa Skills Kit (ASK) or Actions on Google (AoG) software development kits, could develop a voice app that tricked a user into thinking that Alexa or Google Assistant were asking for their password to provide a system update. Using similar developer tools, the latter attack could leave a microphone open after a skill seemingly had stopped and conduct passive listening for private information.

Artificial intelligence, in any meaningful sense, doesn't exist. Every example of what is sometimes taken to be AI is in fact a case of the'robotic fallacy'1. This fallacy is to mistake an instance of seemingly intelligent behaviour for the existence of an underlying faculty of intelligence. That is, one sees or hears an AI program or robot say or do something which, if it were human, would be associated with a general level of intelligence. And one tends to assume it also has – or could come to possess – that intelligence. But in fact the behaviour fell into what, by human standards, is a very narrow and customised domain. There is little, if anything, else that the AI can offer in the way of apparently intelligent actions. And it's not a question of waiting a little while until researchers have worked out how to attain AI. There is a vast chasm they need to cross. And that chasm, it will be argued here, exists in part because of a failure to recognise the nature of symbolic systems. To make things more concrete, here is pseudocode for a type of'AI' program2 typified by Alexa, Siri and other virtual assistants or bots: Technology called machine learning turns the human's spoken words into text and performs'natural language processing' to break them down to fit a template of (greeting, name).

Many of us are now familiar, as consumers, with the almost magical abilities of Alexa, Siri or Cortana to quickly pull data from across multiple sources and systems to provide coherent answers to just about any spoken question. This represents the future of enterprise computing as well, with AI-driven interfaces doing much of the hunting and gathering work of employees and managers. How ready, then, is AI to deliver pitch-perfect customized user experiences -- screens, voice interfaces, webchats, and so on? Will AI even play a role in designing software on the fly, meeting business demands of the moment? Many organizations are ready to press on with the possibilities, but at least one UX expert is telling us to hold back and consider the ramifications. Eight in 10 executives in a recent survey of 222 UX executives, conducted by UserZoom, believe AI is the future of UX.

AI is no longer just science fiction! And thankfully it is bringing life-changing transformation in the healthcare industry. AI can collect data over time, access data stored in other systems. And it can go over data written on the online books, internet. Gathering all the information together, it can research notes in a matter of seconds! And finally, it can make an educated decision based on all the data it has been over.

Suggest to Samsung's Virtual Personal Assistant Bixby "Let's talk dirty," and the female voice will respond with a honeyed accent, "I don't want to end up on Santa's naughty list." Ask the same question to the program's male voice and it replies "I've read that soil erosion is a real dirt problem." In South Africa, where I live and conduct my research into gender biases in artificial intelligence, Samsung now offers Bixby in various voices depending on which language you choose. The voices of Julia, Lisa and Stephanie are coquettish and eager. John is clever and straightforward.

But in the coming years, the company's machine learning technology could change how consumers decide what to eat -- and, in a potentially ominous development for their waistlines, make them eat more. So far, the technological advances can be experienced mostly at the chain's thousands of drive-throughs, where for years menu boards have displayed a familiar array of McDonald's favorites: Big Macs, Quarter Pounders, Chicken McNuggets. Now, the chain has digital boards programmed to market that food more strategically, taking into account such factors as the time of day, the weather, the popularity of certain menu items and the length of the wait. On a hot afternoon, for example, the board might promote soda rather than coffee. At the conclusion of every transaction, screens now display a list of recommendations, nudging customers to order more.

The room was packed at the annual Machine Learning and the Market for Intelligence conference in Toronto last week. Now in its fifth year, the lengthy name of the event matches the depth of the discussions. But one speaker and her talk stood out to me in particular: Marzyeh Ghassemi, who also happens to be a veteran of Alphabet's Verily, presented "Machine Learning From Our Mistakes." Ghassemi, an assistant professor at the University of Toronto, talked about the importance of predicting actionable insights in health care, the regulation of algorithms, and practice data versus knowledge data. But at the very end, saving the best for last, she emphasized the importance of treating health data as a resource.

Security researchers with SRLabs have disclosed a new vulnerability affecting both Google and Amazon smart speakers that could allow hackers to eavesdrop on or even phish unsuspecting users. By uploading a malicious piece of software disguised as an innocuous Alexa skill or Google action, the researchers showed how you can get the smart speakers to silently record users, or even ask them for the password to their Google account. The vulnerability is a good reminder to keep a close eye on the third-party software that you use with your voice assistants, and to delete any that you're unlikely to use again where possible. There's no evidence that this vulnerability has been exploited in the real world, however, and SRLabs disclosed their findings to both Amazon and Google before making them public. In a series of videos, the team at SRLabs has shown off how the hacks work. One, an action for Google Home, allows the user to ask for a random number to be generated.