Earlier this month, DeepMind presented a new "generalist" AI model called Gato. The model can play the video game Atari, caption images, chat, and stack blocks with a real robot arm, the Alphabet-owned AI lab announced. All in all, Gato can do hundreds of different tasks. But while Gato is undeniably fascinating, in the week since its release some researchers have got a bit carried away. One of DeepMind's top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn't contain his excitement.
The technology consists of sensors that use WiFi signals to help the robot map where it's going. Most systems rely on optical light sensors such as cameras and LiDARs. In this case, the so-called "WiFi sensors" use radio frequency signals rather than light or visual cues to see, so they can work in conditions where cameras and LiDARs struggle -- in low light, changing light, and repetitive environments such as long corridors and warehouses. And by using WiFi, the technology could offer an economical alternative to expensive and power hungry LiDARs, the researchers noted. A team of researchers from the Wireless Communication Sensing and Networking Group, led by UC San Diego electrical and computer engineering professor Dinesh Bharadia, will present their work at the 2022 International Conference on Robotics and Automation (ICRA), which will take place from May 23 to 27 in Philadelphia.
Instagram and Facebook users in Texas lost access to certain augmented reality filters Wednesday, following a lawsuit accusing parent company Meta of violating privacy laws. In February, Texas Attorney General Ken Paxton revealed he would sue Meta for using facial recognition in filters to collect data for commercial purposes without consent. Paxton claimed Meta was "storing millions of biometric identifiers" that included voiceprints, retina or iris scans, and hand and face geometry. Although Meta argued it does not use facial recognition technology, it has disabled its AR filters and avatars on Facebook and Instagram amid the litigation. The AR effects featured on Facebook, Messenger, Messenger Kids, and Portal will also be shut down for Texas users.
The saying "data is the new oil," was reportedly coined by British mathematician and marketing whiz Clive Humby in 2006. Data is the fuel powering modern AI models; without enough of it the performance of these systems will sputter and fail. And like oil, the resource is scarce and controlled by big businesses. What do you do if you're a small computer vision company? You can turn to fake data to train your models, and if you're lucky it might just work.
Virtual sales meetings have made it tougher than ever for salespeople to read the room. So, some well funded tech providers are stepping in with a bold sales pitch of their own: that AI can not only help sellers communicate better, but detect the "emotional state" of a deal -- and the people they're selling to. In fact, while AI researchers have attempted to instill human emotion into otherwise cold and calculating robotic machines for decades, sales and customer service software companies including Uniphore and Sybill are building products that use AI in an attempt to help humans understand and respond to human emotion. Virtual meeting powerhouse Zoom also plans to provide similar features in the future. "It's very hard to build rapport in a relationship in that type of environment," said Tim Harris, director of Product Marketing at Uniphore, regarding virtual meetings.
If you're interested in obscure things, there are two reasons why your searches for items and products are likely to be less related to your interests than those of your'mainstream' peers; either you're a monetization'edge case' whose interests will only be catered to if you're also in the upper categories of economic purchasing power (for example, products and services related to'wealth management'); or the search algorithms that you're using are leveraging collaborative filtering (CF), which favors the interests of the majority. Since collaborative filtering is cheaper and more established than other potentially more capable algorithms and frameworks, it's possible that both these cases apply. CF-based search results will prioritize items that are perceived to be popular among'people like you', as best the host framework can understand what kind of a consumer you are. If you're wary of providing data profiling information to the host system – for instance, not inclined to press the'Like' buttons in Netflix and other video content services – you're likely to be classified quite generically in your earliest interactions with the system, and the recommendations you receive will reflect the most popular trends. On a streaming platform, that could mean being recommended whatever shows and movies are currently'hot', such as reality TV and forensic murder documentaries, irrespective of your interest in these.
This article was written, edited and designed on laptop computers. Such foldable, transportable devices would have astounded computer scientists just a few decades ago, and seemed like sheer magic before that. The machines contain billions of tiny computing elements, running millions of lines of software instructions, collectively written by countless people across the globe. You click or tap or type or speak, and the result seamlessly appears on the screen. Computers were once so large they filled rooms. Now they're everywhere and invisible, embedded in watches, car engines, cameras, televisions and toys. They manage electrical grids, analyze scientific data and predict the weather. The modern world would be impossible without them. Scientists aim to make computers faster and programs more intelligent, while deploying technology in an ethical manner. Their efforts build on more than a century of innovation. In 1833, English mathematician Charles Babbage conceived a programmable machine that presaged today's computing architecture, featuring a "store" for holding numbers, a "mill" for operating on them, an instruction reader and a printer. This Analytical Engine also had logical functions like branching (if X, then Y).
The US national tax authority announced Monday that it will stop using facial recognition software to verify taxpayers' identities when they create online accounts, following a chorus of privacy concerns. Internal Revenue Service officials had put forth the authentication system as a security measure following years of growing fears over online scams and identity theft, but the program ended up also prompting worries. The initiative involved identity verification company ID.me, which won a nearly $90 million contract to make taxpayers' accounts more secure. The IRS said "it will transition away from using a third-party service for facial recognition to help authenticate people creating new online accounts." "The IRS will quickly develop and bring online an additional authentication process that does not involve facial recognition," it said, as the agency faces staffing shortages and significant backlogs.
A Chinese company is selling its surveillance technology to Iran's Revolutionary Guard, police, and military, according to a new report by IPVM, a surveillance research group. The firm, called Tiandy, is one of the world's largest video surveillance companies, reporting almost $700 million in sales in 2020. The company sells cameras and accompanying AI-enabled software, including facial recognition technology, software that it claims can detect someone's race, and "smart" interrogation tables for use alongside "tiger chairs," which have been widely documented as a tool for torture. The report is a rare look into some specifics of China's strategic relationship with Iran and the ways in which the country disperses surveillance technology to other autocracies abroad. Tiandy's "ethnicity tracking" tool, which has been widely challenged by experts as both inaccurate and unethical, is believed to be one of several AI-based systems the Chinese government uses to repress the Uyghur minority group in the country's Xinjiang province, along with Huawei's face recognition software, emotion-detection AI technologies, and a host of others.