Summary; The paper studies the classical problem of estimating the probability mass function (pmf) of a discrete random variable given iid samples, but distributed among different nodes. The key quantity of interest is how much communication must be expended by each node (in a broadcast, but perhaps interactive, setting) to a central observer which then outputs the estimate of the underlying pmf. The main results of the paper areclearly stated and are easy to follow. The results mostly point out that in the worst case (i.e., no assumptions on the underlying pmf) there is nothing better for each node to do than to communicate its sample to the central observer. The paper addresses a central topic of a long line of recent works on distributed parameter estimation.

One day after California green-lighted a massive expansion of driverless robotaxis in San Francisco, the implications became clear. At about 11 p.m. Friday, as many as 10 Cruise driverless taxis blocked two narrow streets in the center of the city's lively North Beach bar and restaurant district. All traffic came to a standstill up Vallejo Street and around two corners on Grant. Human-driven cars sat stuck behind and in between the robotaxis, which might as well have been boulders: no one knew how to move them. The cars sat motionless with parking lights flashing for 15 minutes, then woke up and moved on, witnesses said.

ARLINGTON, VIRGINIA - OCTOBER 31: A voter walks out of a polling station during early voting for the ... [ ] U.S. Presidential election on October 31, 2020 in Arlington, United States. With predictions of record turnout of 150 million people, representing 65% of eligible voters, we have to ask ourselves why we continue to rely on antiquated systems, paper ballots and inadequate machines to handle the most important day of our democracy. There is technology available today that can make every election day going forward safe, efficient, and most importantly, secure. If we look to AI and innovation, we can see the future of election day. No long lines, no waiting on ballots to be dumped and counted.

In today's day, customer service is incredibly essential. Customers want to resolve their problems as quickly as possible regarding their products and services, but that's not always possible. Emails, phone calls and chats all things take employees to man as well as operate. It means that long lines can leave and stack up customers waiting for their turn for hours to be served. But the good news is Artificial Intelligence can solve it. Artificial Intelligence run Chatbot can help customers with their queries 24*7 and 365-day since they need no human employees to function.

WASHINGTON – Immigration desk computers at various airports went down for about two hours on Monday, causing long lines for travelers entering the United States after year-end holidays, according to Customs and Border Protection and posts on social media. The processing system outage began at about 7:30 p.m. EST and was resolved about 9:30, the customs agency said in a statement. All airports were back on line after wait times for travelers that were longer than usual, it said. "At this time, there is no indication the service disruption was malicious in nature," the agency said. It gave no explanation for the disruption and said travelers were processed using alternative procedures.

Engineers participating in a hackathon last weekend demonstrated an artificial intelligence that they say could someday detect cancerous moles, TechCrunch reports. Although the program is currently in its infancy, the team hopes that enough user submissions could allow Doctor Hazel to predict skin cancer with at least 90 percent accuracy. After one day and thousands of image downloads, the AI is identifying cancer at an 85 percent success rate, the team said during a presentation at TechCrunch Disrupt's San Francisco 2017 hackathon. However, the team has launched a beta and is inviting users to submit their own photos to improve Doctor Hazel's performance. "There's a huge problem in getting AI data for medicine … no one wants to share," Mike Borozdin, developer of Doctor Hazel, told TechCrunch.

Thousands of angry British Airways passengers on Sunday confronted long lines, confusion and canceled flights at London's Heathrow and Gatwick airports as the airline worked to fix computer systems crippled by a massive global IT failure. British Airways said Sunday that it was still working on the massive problem, which caused the airline to cancel all flights from the two London airports. "Work continues to restore all of our IT systems, but we expect some further disruption today," the airline said. The airline said that it hoped to operate a "near normal schedule" at Gatwick and the "majority of services" from Heathrow on Sunday. The airline offered to refund or rebook customers affected by the problem.

For a previous generation in the US, the only places where one might worry about the possibility of a mass casualty were "high-value targets," like airports and government offices, places that have body scanners and bag inspections, security guards and long lines to get in today. But attackers increasingly strike at public places like nightclubs, stadiums, clinics, malls, places of worship and schools. A startup called Evolv Technology Inc., has raised $18 million to help venues with even a limited budget use advanced technology rather than pat downs to detect and prevent mass casualties. Investors in Evolv's new round of funding included General Catalyst, Lux Capital, Gates Ventures, and Data Collective. The Waltham, Mass.-based startup has created both hardware and software for physical security.

"When I go to a Broadway show, I'm not very happy that scalpers have bought up all the tickets," says Andrew Ng, chief scientist of Baidu Research, the Silicon Valley branch of the tech company often described as the Google of China. Baidu has proposed a new artificial intelligence solution not only to thwart scalpers but to speed up the wait at any place where checking tickets or IDs leads to long lines. Today the tech giant announced new face recognition technology that it says is up to 99.77% accurate--able to distinguish people even better than a human can. Baidu published two peer-reviewed research papers and tested the technology using popular methodologies, so it's making more than empty claims. But beyond questions over how and how well these technologies work are questions of how they will be used.