A former Apple contractor who pulled the curtain on the tech giant last summer, exposing an inside program that listens to user's Siri recordings, has made himself known to the world. Thomas le Bonniec worked under a Siri'grading project' that gathered snippets of audio in order to improve the smart assistant's accuracy. Last year, le Bonniec revealed to The Guardian that while working for Apple he heard private and sometimes intimate recordings including medical discussions, criminal activity, sex and official business talks. The whistleblower had initially remained anonymous, but has revealed himself in protest against the lack of action taken against Apple for'violating fundamental human rights' - and he has done so with an open letter to European privacy regulators stating his concerns. Former Apple contractor, Thomas le Bonniec, who pulled the curtain on the tech giant last summer, exposing an inside program that listens to user's Siri recordings, has made himself known to the world'There's not much vetting of who works there, and the amount of data that we're free to look through seems quite broad,' le Bonniec told the Guardian in July.

Facebook is launching what it's calling a "universal product recognition model" that uses artificial intelligence to identify consumer goods, from furniture to fast fashion to fast cars. It's the first step toward a future where the products in every image on its site can be identified and potentially shopped for. "We want to make anything and everything on the platform shoppable, whenever the experience feels right," Manohar Paluri, head of Applied Computer Vision at Facebook, told The Verge. Product recognition is the first in a slew of AI-powered updates coming to its e-commerce platforms in the near future, says the company. Eventually, these will combine AI, augmented reality, and even digital assistants to create what it calls a "social-first" shopping experience.

Don't worry if you missed out on the last time the HomePod was on sale -- the deal is back. Best Buy is once again selling Apple's smart speaker for $200, or a full $100 off the usual price. At that cost, it could easily make sense if you're in an Apple-centric household and want a speaker to lift your mood or control your smart home. The HomePod has long been one of our top picks for sound quality, punching well above its weight (or rather, size) -- especially now that you can create stereo pairs and groups. And while the initial feature set was underwhelming, to put it mildly, Apple has gone some length to improve things with multi-user support, audio handoffs, live radio and Spotify voice control.

Robotic process automation is spreading across banking and financial services. The origins of automation extend back to 1745, when English blacksmith Edmund Lee patented the rotating fantail that keeps a windmill's sails pointed into the wind. The first completely automated industrial process emerged toward the end of the 1700s, when American inventor Oliver Evans developed the automatic flour mill. Fast-forward to the 2000s and the era of Digital Disruption 2.0: The world today is experiencing the impact of another monumental breakthrough – the emergence of robotic process automation (RPA). RPA uses software to automate repetitive processes that humans would otherwise do, freeing these people for higher value work.

Of all the smart displays on the market right now, many of you went for the Echo Show 5. Amazon's mid-sized model features a sunrise alarm, quality sound and of course, the Alexa assistant. When senior editor Nicole Lee reviewed the Echo Show 5, she was impressed with the small device's ability to compete with larger options like the Lenovo Smart Clock or Google's Nest Hub. We asked Echo Show owners why they went with the 5-inch version from Amazon, what their favorite features were and what it was like to watch videos on the device. Here's what they had to say. Our reviewer Nicole pointed out that the smaller screen on the Echo Show 5 makes it ideal for the kitchen and the bedroom, and that is indeed where most of our users placed the device.

If you're just starting out with smart speakers or want multiple tech-savvy clocks around the house, this might be the deal you're looking for. You can buy two Echo Show 5 smart displays for the price of one at Amazon for $90 if you enter the code SHOW52PK at checkout. Best Buy is offering a similar deal if you add two of the screens to your cart. This is a daily deal at Best Buy, so you'll likely need to act quickly at both sites if you want to take advantage of the sale. A previous deal dropped the price of an individual unit down to $50, but this is a steeper overall discount if you're in the market for two.

When California issued a stay-at-home order back in March to curb the spread of the coronavirus, Dana Angelo, a 33-year-old copywriter at an ad agency in Los Angeles, found herself with more free time. So, out of boredom, she turned to a social activity she could still do from home: She got back on the dating app, Bumble. Angelo said she's been rotating through online dating apps -- she's also tried Tinder and Hinge -- with minimal luck since getting out of a long-term relationship about a year ago, and had recently been taking a break. "You just see the same people on all of them and then it gets kind of depressing," Angelo said. But something surprising happened this time around: She actually met someone she genuinely likes.

When California issued a stay-at-home order back in March to curb the spread of the coronavirus, Dana Angelo, a 33-year-old copywriter at an ad agency in Los Angeles, found herself with more free time. So, out of boredom, she turned to a social activity she could still do from home: She got back on the dating app, Bumble. Angelo said she's been rotating through online dating apps -- she's also tried Tinder and Hinge -- with minimal luck since getting out of a long-term relationship about a year ago, and had recently been taking a break. "You just see the same people on all of them and then it gets kind of depressing," Angelo said. But something surprising happened this time around: She actually met someone she genuinely likes.

Recommender systems are widely developed to learn user preferences from their past history and make predictions on the unseen items a user may like. User preferences in the form of absolute preferences, such as user ratings or clicks are commonly used to model a user’s interest and generate recommendations. However, rating items is not the most natural mechanism that users use for making decisions in daily life. For instance, we do not rate t-shirts when we want to buy one. It is more likely that we will compare them one to one, and purchase the preferred one. In this work, we focus on relative feedback, which generates pairwise preferences as an alternative way to model user preferences and compute recommendations. In our scenario, each user is shown a set of item pairs and asked to compare them to indicate which item in the pair is more preferred. We propose a recommendation algorithm to predict a user’s relative preference for a given pairs of items and compute a personalised ranking of items. We demonstrate the effectiveness of our proposed algorithm in comparison with state-of-the-art relative feedback based recommendation approaches. Our experimental results reveal that the proposed algorithm is able to outperform the baseline algorithms on popular ranking-oriented evaluation metrics.

The proliferation of personalized recommendation technologies has raised concerns about discrepancies in their recommendation performance across different genders, age groups, and racial or ethnic populations. This varying degree of performance could impact users’ trust in the system and may pose legal and ethical issues in domains where fairness and equity are critical concerns, like job recommendation. In this paper, we investigate several potential factors that could be associated with discriminatory performance of a recommendation algorithm for women versus men. We specifically study several characteristics of user profiles and analyze their possible associations with disparate behavior of the system towards different genders. These characteristics include the anomaly in rating behavior, the entropy of users’ profiles, and the users’ profile size. Our experimental results on a public dataset using four recommendation algorithms show that, based on all the three mentioned factors, women get less accurate recommendations than men indicating an unfair nature of recommendation algorithms across genders.