Tag: tech

The devastating cost of the Big Tech billionaires’ immense wealth

Posted onAuthoradmin

COVID-19 was a boon for the superrich. There are few better examples than the founders, CEOs, and spouses of the five Big Tech giants: Amazon’s Jeff Bezos and Mackenzie Scott, Microsoft’s Bill Gates, Facebook’s Mark Zuckerberg, Google’s Larry Page and Sergey Brin, and Apple’s Tim Cook and Laurene Powell Jobs. I call them the tech barons. The recently released Forbes World’s Billionaires List includes some shocking figures about our tech overlords. At the start of 2020, the tech barons were collectively worth $419 billion. A year later, their wealth had soared to $651 billion—a 56% increase. The hoarding of that wealth harms us all: It distributes resources away from those who need it most and, by allowing the tech barons to influence government policy, corrodes democratic society. Most of us will never grow our wealth by 56% in a year. But wealth begets wealth Read More …

This immersive technology turns hospitals into less stressful places

Posted onAuthoradmin

There is quality sound, and there is noise. Sadly, in our day-to-day lives, we have way too much of the latter. Excessive noise can cause several short- and long-term health problems, such as sleep disturbance, cardiovascular effects, poorer work and school performance, and the most obvious risk: hearing impairment. Noise has emerged as a leading environmental nuisance in the World Health Organization’s European region, and the number of public complaints about excessive noise is growing. Read More …

When broadband monopolies pushed out scrappy local ISPs, we all suffered

Posted onAuthoradmin

Over time, computers have become easier to use and the internet easier to access. It used to be that people needed special training to be able to use software on a machine. Now, small children can do it. Instead of a long, noisy process of connecting through dial-up, our devices can connect to the internet (and each other) instantly, without human intervention or even awareness. Mostly this is a good thing. More intuitive design means getting more people online and bringing more access to powerful tools for self-expression and community. It would be excruciating to try and use sophisticated online tools and platforms using old-school modems and routers. One advantage, though, of older technologies is that they forced us to think about what’s under the hood of the devices we use every day. The clicking, whirring, and beeping of old-school dial-up made it obvious that digital connections don’t just magically appear—they have to be built and maintained. Read More …

AI trained on fake faces could help fix a big annoyance with mask wearing

Posted onAuthoradmin

Last March, when we all started wearing masks, phone makers suddenly had a big problem. The facial recognition systems used to authenticate users on their phones no longer worked. The AI models that powered them couldn’t recognize users’ faces because they’d been trained using images of only unmasked faces. The unique identifiers they’d been trained to look for were suddenly hidden. Phone makers needed to expand their training data to include a wide assortment of images of masked faces, and quickly. But scraping such images from the web comes with privacy issues, and capturing and labeling high numbers of images is cost- and labor-intensive. Enter Synthesis AI , which has made a business of producing synthetic images of nonexistent people to train AI models. The San Francisco-based startup needed only a couple of weeks to develop a large set of masked faces, with variations in the type and position of the mask on the face. It then delivered them to its phone-maker clients—which the company says include three of the five largest handset makers in the world—via an application programming interface (API). With the new images, the AI models could be trained to rely more on facial features outside the borders of the mask when recognizing users’ faces. [Image: courtesy of Synthesis AI] Phone makers aren’t the only ones facing training data challenges. Developing computer-vision AI models requires a large number of images with attached labels that describe what the image is so that the machine can learn what it is looking at. But sourcing or building huge sets of these labeled images in an ethical way is difficult. For example, controversial startup Clearview AI, which works with law enforcement around the country , claims to have scraped billions of images from social networking sites without consent Read More …