Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. In 2019, Facebook open-sourced AI Habitat, a simulator that can train AI systems embodying things like a home robot to operate in environments meant to mimic real-world settings, like apartments and offices. Today Facebook announced that it's extended the capabilities of Habitat to make it "orders of magnitude" faster than other 3D simulators available, allowing researchers to perform more complex tasks in simulation, like setting the table and stocking the fridge. Coinciding with this, Facebook collaborated with 3D space capture company Matterport to open-source what it claims is the largest dataset of indoor 3D scans to date.

Apple will no longer send Siri requests to its servers, the company has announced, in a move to substantially speed up the voice assistant's operation and address privacy concerns. The new feature comes two years after the Guardian revealed that Apple staff regularly heard confidential details while carrying out quality control for the feature. Apple's worldwide developers conference (WWDC) was told on Monday that, from this autumn onwards, when new versions of the company's operating systems are released, Siri will process audio "on device" – meaning that, for the majority of queries, no recording will need to be uploaded to Apple's servers. "With on-device speech recognition, the audio of users' requests is processed right on their iPhone or iPad by default," an Apple spokesperson said. "This addresses one of the biggest privacy concerns for voice assistants, which is unwanted audio recording. For many requests, Siri processing is also moving on device, enabling requests to be processed without an internet connection, such as launching apps, setting timers and alarms, changing settings or controlling music."

Amazon's Echo Show devices are among those that will automatically be added to its shared Wi-Fi network scheme, called Amazon Sidewalk. Amazon's Echo Show devices are among those that will automatically be added to its shared Wi-Fi network scheme, called Amazon Sidewalk. Amazon is building a Wi-Fi network – using your Wi-Fi. It's called Amazon Sidewalk, and the company touts it as a way to help its devices work better, by extending the range of low-bandwidth devices to help them stay online. It does that by pooling neighbors' Wi-Fi to help connectivity for devices that are out of range.

In May 1948, women were strikingly prominent in ACM. Founded just months earlier as the "Eastern Association for Computing Machinery," the new professional society boldly aimed to "advance the science, development, construction, and application of the new machinery for computing, reasoning, and other handling of information."36 No fewer than 27 women were ACM members, and many were leaders in the emerging field.a Among them were the pioneer programmers Jean Bartik, Ruth Lichterman, and Frances Snyder of ENIAC fame; the incomparable Grace Murray Hopper who soon energized programming languages; Florence Koons from the National Bureau of Standards and U.S. Census Bureau; and noted mathematician-programmer Ida Rhodes.26 During the war, Gertrude Blanch had organized a massive human computing effort (a mode of computation made visible in the 2016 film Hidden Figures47) and, for her later service to the US Air Force, became "one of the most well-known computer scientists and certainly the most visible woman in the field."24,25 Mina Rees, a mathematics Ph.D. like Hopper and Blanch, notably funded mathematics and computing through the Office of Naval Research (1946–1953), later serving as the first female president of the American Association for the Advancement of Science. In 1949, Rees was among the 33 women (including at least seven ACM women) who participated in an international conference at Harvard University, chairing a heavyweight session on "Recent Developments in Computing Machinery."29

The European Union on Wednesday unveiled strict regulations to govern the use of artificial intelligence, a first-of-its-kind policy that outlines how companies and governments can use a technology seen as one of the most significant, but ethically fraught, scientific breakthroughs in recent memory. Presented at a news briefing in Brussels, the draft rules would set limits around the use of artificial intelligence in a range of activities, from self-driving cars to hiring decisions, school enrollment selections and the scoring of exams. It would also cover the use of artificial intelligence by law enforcement and court systems -- areas considered "high risk" because they could threaten people's safety or fundamental rights. Some uses would be banned altogether, including live facial recognition in public spaces, though there would be some exemptions for national security and other purposes. The rules have far-reaching implications for major technology companies including Amazon, Google, Facebook and Microsoft that have poured resources into developing artificial intelligence, but also scores of other companies that use the technology in health care, insurance and finance.

A collaboration from UoC Berkeley, Stanford University and Facebook offers a deeper and more granular picture of the actual state of poverty in and across nations, through the use of machine learning. The research, entitled Micro-Estimates of Wealth for all Low-and Middle-Income Countries, is accompanied by a beta website that allows users to interactively explore the absolute and relative economic state of fine-grained areas and pockets of poverty in low and middle-income countries. The framework incorporates data from satellite imagery, topographic maps, mobile phone networks and aggregated anonymized data from Facebook, and is verified against extensive face-to-face surveys, for purposes of reporting relative wealth disparity in a region, rather than absolute estimates of income. A map of global poverty, weighted towards the most affected areas. The system has been adopted by the government of Nigeria as a basis for administering social protection programs, and runs in tandem with the existing framework from the World Bank, the National Social Safety nets Project (NASSP).

The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for inference, autonomy, and decision making purposes. However, due to resource constraints, delay limitations, and privacy challenges, edge devices cannot offload their entire collected datasets to a cloud server for centrally training their ML models or inference purposes. To overcome these challenges, distributed learning and inference techniques have been proposed as a means to enable edge devices to collaboratively train ML models without raw data exchanges, thus reducing the communication overhead and latency as well as improving data privacy. However, deploying distributed learning over wireless networks faces several challenges including the uncertain wireless environment, limited wireless resources (e.g., transmit power and radio spectrum), and hardware resources. This paper provides a comprehensive study of how distributed learning can be efficiently and effectively deployed over wireless edge networks.

When a secretive start-up scraped the internet to build a facial-recognition tool, it tested a legal and ethical limit -- and blew the future of privacy in America wide open. In May 2019, an agent at the Department of Homeland Security received a trove of unsettling images. Found by Yahoo in a Syrian user's account, the photos seemed to document the sexual abuse of a young girl. One showed a man with his head reclined on a pillow, gazing directly at the camera. The man appeared to be white, with brown hair and a goatee, but it was hard to really make him out; the photo was grainy, the angle a bit oblique. The agent sent the man's face to child-crime investigators around the country in the hope that someone might recognize him. When an investigator in New York saw the request, she ran the face through an unusual new facial-recognition app she had just started using, called Clearview AI. The team behind it had scraped the public web -- social media, employment sites, YouTube, Venmo -- to create a database with three billion images of people, along with links to the webpages from which the photos had come. This dwarfed the databases of other such products for law enforcement, which drew only on official photography like mug shots, driver's licenses and passport pictures; with Clearview, it was effortless to go from a face to a Facebook account. The app turned up an odd hit: an Instagram photo of a heavily muscled Asian man and a female fitness model, posing on a red carpet at a bodybuilding expo in Las Vegas. The suspect was neither Asian nor a woman. But upon closer inspection, you could see a white man in the background, at the edge of the photo's frame, standing behind the counter of a booth for a workout-supplements company. On Instagram, his face would appear about half as big as your fingernail. The federal agent was astounded. The agent contacted the supplements company and obtained the booth worker's name: Andres Rafael Viola, who turned out to be an Argentine citizen living in Las Vegas.

MIT researchers have developed a way to produce holograms almost instantly. They say the deep learning-based method is so efficient that it could run on a smartphone. A new method called tensor holography could enable the creation of holograms for virtual reality, 3D printing, medical imaging, and more -- and it can run on a smartphone. Despite years of hype, virtual reality headsets have yet to topple TV or computer screens as the go-to devices for video viewing. One reason: VR can make users feel sick.

Throughout history, society has debated the morality of debt. In ancient times, debt--borrowing from another on the promise of repayment--was viewed in many cultures as sinful, with lending at interest especially repugnant. The concern that borrowers would become overindebted and enslaved to lenders meant that debts were routinely forgiven. These concerns continue to influence perceptions of lending and the regulation of credit markets today. Consider the prohibition against charging interest in Islamic finance and interest rate caps on payday lenders--companies that offer high-cost, short-term loans.