Like Google and Amazon before it, Apple has been caught sending voice assistant recordings to contractors, who listen to snippets of your requests and conversations, without telling anyone. In response to the privacy concerns that raises, Apple says it will eventually give users control over whether their Siri data gets sent to third-party eavesdroppers, but it's unclear whether that consent will be opt-in or opt-out. Letting people opt out of data collection is better than not giving them any choice at all. But for decades, that's been the extent of the conversation. It gives too many giant tech companies plausible deniability for the rampant hoovering of your personal information, and allows them to implicitly blame the victim when they overreach: Don't get angry at us, you could have opted out this whole time.

Apple has suspended its practice of having human contractors listen to users' Siri recordings to "grade" them, following a Guardian report revealing the practice. The company said it would not restart the programme until it had conducted a thorough review of the practice. It has also committed to adding the ability for users to opt out of the quality assurance scheme altogether in a future software update. Apple said: "We are committed to delivering a great Siri experience while protecting user privacy. While we conduct a thorough review, we are suspending Siri grading globally. Additionally, as part of a future software update, users will have the ability to choose to participate in grading."

My family and I continue to have more and more conversations with Alexa, Siri and Google Assistant lately. Having three AI based sources within speaking range of each other, we have a tendency to fact check them against one another - especially when someone doesn't quite trust or agree with the answer they get. For example, is Australia considered a continent or is it Oceania? Is a hot dog a sandwich? Who is the best NBA player of all time ever?

Are they relevant, or just a fad like the Nintendo Wii? There seem to be personal assistants being added to everything, from smartphones, to watches, to speakers. And now, a Personal Assistant is coming to Microsoft Azure. Microsoft is reviving Clippy to be the Cloud Assistant you need for helping work with and maintaining your Microsoft Azure cloud resources. Personal Assistants are great at helping with very specific tasks like setting reminders and using voice commands to get stuff done.

Technology changes so fast that our lives are radically different from even a decade ago, yet slowly enough that sometimes we don't even notice the changes. We live in the future, in other words, and sometimes it takes a moment to realise what an odd, and perhaps unsettling, future it is. So I'm going to try laying it out for you in plain English. Not one, but two, controversial billionaires have created projects aimed at reading minds. Elon Musk, the South African co-founder of PayPal, unveiled the latest step in his plan to build mind-reading implants two weeks ago.

--Collaborative filtering is one of the most popular techniques in designing recommendation systems, and its most representative model, matrix factorization, has been wildly used by researchers and the industry. However, this model suffers from the lack of interpretability and the item cold-start problem, which limit its reliability and practicability. In this paper, we propose an interpretable recommendation model called Multi-Matrix F actorization (MMF), which addresses these two limitations and achieves the state-of-the-art prediction accuracy by exploiting common attributes that are present in different items. In the model, predicted item ratings are regarded as weighted aggregations of attribute ratings generated by the inner product of the user latent vectors and the attribute latent vectors. MMF provides more fine grained analyses than matrix factorization in the following ways: attribute ratings with weights allow the understanding of how much each attribute contributes to the recommendation and hence provide interpretability; the common attributes can act as a link between existing and new items, which solves the item cold-start problem when no rating exists on an item. We evaluate the interpretability of MMF comprehensively, and conduct extensive experiments on real datasets to show that MMF outperforms state-of-the-art baselines in terms of accuracy. I NTRODUCTION In recent years, recommendation systems gain increasing interest by both researchers and the industry [1], [2]. The most popular recommendation systems are based on collaborative filtering (CF) technique, which provides recommendations based on other similar users' choice [3]. Matrix factorization (MF) is one of the most common collaborative filtering models, whose main idea is to learn user latent vectors and item latent vectors, so that the inner product of the two vectors can approximate the original matrix with the minimal approximation error. MF has advantages of simplicity and performing well in many domains, such as recommendation systems, computer vision and document clustering [4]-[7]. However, it suffers from two limitations.

For years, the Sonos Wi-Fi speakers have been beloved by music fans for the ease of listening to streaming music at home with great sound. Also, add the ability to add multiple speakers for even better sound without having to resort to stringing speaker wire all over. The one drawback: Sonos speakers can be pricey, topping off at $499 per speaker and even higher for the $699 TV Playbar. So good news consumers: The most affordable way to get into the Sonos system goes on sale Thursday. But you won't find the speakers at Best Buy, Amazon or any of the other retailers which usually stock Sonos products.

Artificial intelligence-based property management platform Askporter has won a further £1.5 million in funding from half a dozen venture capitalists. One of the backers, Woking-based Henley Investments, has used the announcement to claim that the property management sector is'inefficient and ripe for disruption'. Askporter, which still calls itself a start-up despite being three years old, is a proptech company that uses a digital platform including a'virtual assistant' app to help property management teams run buildings more efficiently. It claims to help "cut costs and reduce the time spent on tedious tasks, all the while providing first-class support to occupants". "Our success raising £1.5 million investment reflects wider changes sweeping the property industry," says AskPorter CEO Tom Shrive (pictured, left).

If you ever get the creepy feeling you're being monitored when you use your computer, smartphone or smart speaker, our guest Geoffrey Fowler is here to tell you you are. Fowler writes a consumer-oriented technology column for The Washington Post. He's been investigating the ways our browsers and phone apps harvest personal information about us even while we're sleeping. And he discovered that Amazon had kept four years' worth of recorded audio from his home, captured by his Alexa smart speaker, including family conversations about medications and a friend doing a business transaction. Geoffrey Fowler joined the Post in 2017 after 16 years with the Wall Street Journal, writing about consumer technology, Silicon Valley, national affairs and China. He writes his technology column from San Francisco. He spoke with FRESH AIR's Dave Davies. You have a recent column. The headline is "I Found Your Data. It's For Sale." What kind of personal data did you find available for sale on the Internet? GEOFFREY FOWLER: I found all kinds of things that normal people would consider secrets and that corporations spend a lot of money - millions and millions of dollars - to try to keep out of the hands of their competitors and criminals. I found people's flight records. I found people's records from their doctors prescribing them medications. I found people's tax documents that they were - thought they were only sharing with their tax preparer. And they were available with one click. I could have opened them up and downloaded them. And where did this data come from?

Difficult co-workers who defy authority are more likely to cheat on their partners, a new study suggests. Researchers at the University of Texas discovered the correlation after studying the records of police officers, financial advisers, white-collar criminals and senior executives who used the Ashley Madison marital infidelity website. The data suggests a strong connection between people's actions in their personal and professional lives. They found that Ashley Madison were more than twice as likely to engage in corporate misconduct. Researchers investigated four study groups totalling 11,235 individuals.