Apple has developed a new Siri voice, now available in the beta versions of its iOS 15.4 software, that doesn't sound obviously male or female. The decision to introduce a gender-neutral voice is one that sees the tech giant taking yet another step away from the criticism that, historically, digital assistants have reinforced unfair gender stereotypes. Over the years, industry observers and experts argued how the creation of voice assistants with female-sounding names -- like Alexa, Siri and Cortana -- which also speak with female-sounding voices, implied that women should be the ones to do your bidding at any time and even take your abuse. A U.N. study additionally called out the female voiced-assistants and their submissive and sometimes even flirty and coy styles. More problematically, the decision to make so many of the virtual assistants female by default was likely driven by a lack of diversity in the teams responsible for building our everyday technology.

Rotten Tomatoes recently shared a list of DC Extended Universe (DCEU) movies to explain the timeline. However, they mistakenly featured the Marvel Cinematic Universe (MCU) movie, "Guardians of the Galaxy" title in that list. This mistake has not gone down well with director James Gunn, who was quick to take a dig at the list. Gunn reposted Rotten Tomatoes's tweet on Wednesday, and wrote, "I'm surprised Guardians is after Birds of Prey in the DCEU timeline." The comment came after the DCEU timeline featured a poster of Gunn's recently released TV series, "Peacemaker," but the title was written "Guardians of the Galaxy."

While Siri is best known for its original, female voice, users will soon be able to opt for a new'gender-neutral' voice, called Quinn. Apple is launching the new voice in its next iOS update, which was released to developers this week. The tech giant has confirmed that the new voice was recorded by a member of the LGBTQ community, but did not offer any further details. 'We're excited to introduce a new Siri voice for English speakers, giving users more options to choose a voice that speaks to them,' Apple told Axios. While Siri is best known for its original, female voice, users will soon be able to opt for a new'gender-neutral' voice, called Quinn. While the new voice is simply called'Voice 5' on the iPhone, its filename refers to the voice as Quinn, according to iOS developer Steve Moser.

The Internet is a constantly evolving technology that continues to innovate. So far, we've experienced Web 1.0 and 2.0, and there's much discussion of what to expect from Web 3.0. Web 1.0 provided a static experience for users without the ability to create the content-rich sites we have today. Web 2.0 brought us together with social media and dynamic websites, but at the cost of centralization. Web 3.0 looks to give us control of our online information and also create a semantic web.

A woman said she lost $390,000 after falling for an online crypto dating scam and wants to warn others. Nicole Hutchinson, of Tennessee, told CBS News not only did she lose her own money, but her father's, too while attempting to make friends before moving to California. Hutchinson inherited her mother's house after she died and decided to sell the property. She split the profit with her father and inherited $280,000 that was supposed to be used to help her family build a life in California. The 24-year-old decided to try the online dating site Hinge and matched with a man named "Hao" while visiting a friend in the state, the New York Times reported.

Apple's iOS 15.4 will bring more than AirTag anti-stalking messages and direct iPhone contactless payments. Axios has confirmed the latest iOS 15.4 beta includes a less gendered Siri voice option for English speakers. The voice, recorded by a member of the LGBTQ community, was meant to increase the diversity of Apple's assistant. This should give users more choices for a "voice that speaks to them," Apple said in a statement. It's not certain if or when the voice will be available in other languages.

One of the most compelling InfoQ features are our topic graphs, which synthesizes our understanding of how different topics stack up in the technology adoption curve. They are immensely useful as a guide to prioritize different and competing interests when it's time to decide what we want to cover from an editorial perspective, but we also believe that sharing them can help our readers to better understand the current and future tech landscape and help inform their decision process. Topic graphs build upon the well-known framework Geoffrey Moore developed in his book "Crossing the Chasm." Moore's framework describes five stages that describe how technology adoption evolves in time, through the "innovators", "early adopters", "early majority", "late majority", and "laggard" stages. InfoQ has a leaning towards identifying those ideas and technologies that belong to the innovators, early adopters, and early majority stages. We also strive to acknowledge topics that we consider as having already crossed into late majority. You will generally find plenty of content on InfoQ about the late majority and laggards phases, as artifacts of our previous coverage.

Originally posted on The Horizons Tracker. Recommender systems are pervasive on most websites today, with their influence on our buying behavior considerable as they guide us towards products that our past buying behavior indicates we might like. Netflix, for instance, famously tapped into the wisdom of the crowd to improve its recommendation engine, with the end result being a system that the company suggests generates around $1 billion per year for them. Research1 from China's Jiangxi University of Finance and Economics explores whether such systems are positive for end-users, however. The researchers analyzed previous studies on the topic before building a model that shows how our preferences influence our purchase decisions, and also the role AI recommendation systems play.

Massive efforts are made to reduce biases in both data and algorithms in order to render AI applications fair. These efforts are propelled by various high-profile cases where biased algorithmic decision-making caused harm to women, people of color, minorities, etc. However, the AI fairness field still succumbs to a blind spot, namely its insensitivity to discrimination against animals. This paper is the first to describe the 'speciesist bias' and investigate it in several different AI systems. Speciesist biases are learned and solidified by AI applications when they are trained on datasets in which speciesist patterns prevail. These patterns can be found in image recognition systems, large language models, and recommender systems. Therefore, AI technologies currently play a significant role in perpetuating and normalizing violence against animals. This can only be changed when AI fairness frameworks widen their scope and include mitigation measures for speciesist biases. This paper addresses the AI community in this regard and stresses the influence AI systems can have on either increasing or reducing the violence that is inflicted on animals, and especially on farmed animals.

When users are watching videos on Youtube, a list of recommended videos are displayed on the side which the user might like in a certain order. As the adoption grew across Youtube, this meant that the more people spend time on Youtube, the more Ads they were served which in turn meant more revenue for Youtube. However, this has to be balanced with providing them with useful content which they would like to watch.