Goto

Collaborating Authors

 AAAI AI-Alert for Jun 19, 2018


Why Won't Facebook Talk About How Often Its Algorithms Are Wrong?

Forbes - Tech

Two weeks ago Facebook released yet another glossy marketing infographic site and video touting how its state of the art technology, top engineers and teams of experts have made massive strides in conquering yet another scourge of the online world through the power of advanced algorithms. This past week its EMEA counterterrorism lead announced that its algorithms were now deleting 99% of all ISIS and al-Qaida terrorism content across the site. As with all of Facebook's announcements to date, neither of these proclamations made any mention of how often the algorithms that increasingly control its platform are wrong and whether they are actually right more often than they are wrong. After initially promising to provide a response, the company once again declined to comment on the false positive rates of its algorithms or why despite repeated requests it continues to refuse to release those numbers. Why is the company so afraid to talk about whether its algorithms are actually accurate?


A machine has figured out Rubik's Cube all by itself

#artificialintelligence

The Rubik's Cube is a three-dimensional puzzle developed in 1974 by the Hungarian inventor Erno Rubik, the object being to align all squares of the same color on the same face of the cube. It became an international best-selling toy and sold over 350 million units. The puzzle has also attracted considerable interest from computer scientists and mathematicians. One question that has intrigued them is the smallest number of moves needed to solve it from any position. The answer, proved in 2014, turns out to be 26.


DeepMind's AI can 'imagine' a world based on a single picture

#artificialintelligence

Artificial intelligence can now put itself in someone else's shoes. DeepMind has developed a neural network that taught itself to'imagine' a scene from different viewpoints, based on just a single image. Given a 2D picture of a scene – say, a room with a brick wall, and a brightly coloured sphere and cube on the floor – the neural network can generate a 3D view from a different vantage point, rendering the opposite sides of the objects and altering where shadows fall to maintain the same light source. The system, called the Generative Query Network (GQN), can tease out details from the static images to guess at spatial relationships, including the camera's position. "Imagine you're looking at Mt. Everest, and you move a metre – the mountain doesn't change size, which tells you something about its distance from you,"says Ali Eslami who led the project at Deepmind. "But if you look at a mug, it would change position.


Teaching Robots How to Move Objects

#artificialintelligence

MIT doctoral student Maria Bauza is exploring providing tactile feedback to robots. With the push of a button, months of hard work were about to be put to the test. Sixteen teams of engineers convened in a cavernous exhibit hall in Nagoya, Japan, for the 2017 Amazon Robotics Challenge. The robotic systems they built were tasked with removing items from bins and placing them into boxes. For MIT graduate student Maria Bauza, who served as task-planning lead for the MIT-Princeton Team, the moment was particularly nerve-wracking.

  AI-Alerts: 2018 > 2018-06 > AAAI AI-Alert for Jun 19, 2018 (1.00)
  Country:
  Industry: Education (0.56)

Senators Demand Answers From Amazon on Echo's Snooping Habits

WIRED

A Portland woman recently told a local news outlet that her Amazon Echo device had gone rogue, sending a recording of a private conversation to a random person in her contact list. On Thursday, two senators tasked with investigating consumer privacy sent a letter to Amazon CEO Jeff Bezos demanding answers. In the letter, Republican senator Jeff Flake and Democratic senator Chris Coons, who serve respectively as chairman and ranking member of the Judiciary Subcommittee on Privacy, Technology and the Law, ask Bezos to explain how exactly the Amazon Echo device listens to and stores users' voices. The senators also seek answers about what the company is doing to protect users from having that sensitive information misused. The letter, which was reviewed by WIRED, comes in the midst of what Flake calls a "post-Facebook" world, referring to the data privacy scandal in which Facebook says the data of as many as 87 million Americans may have been misappropriated by a political consulting firm called Cambridge Analytica.


Police face legal action over use of facial recognition cameras

The Guardian

Two legal challenges have been launched against police forces in south Wales and London over their use of automated facial recognition (AFR) technology on the grounds the surveillance is unregulated and violates privacy. The claims are backed by the human rights organisations Liberty and Big Brother Watch following complaints about biometric checks at the Notting Hill carnival, on Remembrance Sunday, at demonstrations and in high streets. Liberty is supporting Ed Bridges, a Cardiff resident, who has written to the chief constable of South Wales police alleging he was tracked at a peaceful anti-arms protest and while out shopping. Big Brother Watch is working with the Green party peer Jenny Jones who has written to the home secretary, Sajid Javid, and the Metropolitan police commissioner, Cressida Dick, urging them to halt deployment of the "dangerously authoritarian" technology. If the forces do not stop using AFR systems then legal action will follow in the high court, the letters said.


Israel's Netanyahu Says Drone Deal With Germany Will Strengthen Ties

U.S. News

JERUSALEM/BERLIN (Reuters) - Israeli Prime Minister Benjamin Netanyahu said on Thursday that a roughly one-billion-euro ($1.18 billion) drone deal with Germany would strengthen bilateral security relations and give a boost to Israel's defense industry.

  AI-Alerts: 2018 > 2018-06 > AAAI AI-Alert for Jun 19, 2018 (1.00)
  Country:
  Industry: Government (1.00)

Artificial Intelligence: The Clever Ways Video Games Are Used To Train AIs

Forbes - Tech

Who says you can't get smart playing video games? Although the idea of spending hours playing video games isn't usually recommended for humans to increase their intelligence, the realistic 3-D graphics and environments of many video games just might make video games the perfect learning tool for artificial intelligence. AI algorithms get smarter and learn to perform tasks by being fed enormous amounts of data. When you're on Facebook, this doesn't present a huge obstacle. Facebook creates huge data sets daily and also has the financial capability to close any gaps.


Byton's K-Byte Electric Concept Makes Self-Driving Look Good

WIRED

While Tesla has spent the past six months struggling to ramp up production of the Model 3 and fielding criticism over its Autopilot tech and safety protocols, one of its most intriguing wannabe rivals, Byton, has spent the first half of 2018 positioning itself to swipe Elon Musk's electric innovation crown. The coup d'EV started in January at CES, with the reveal of a screen-stuffed concept SUV. In February, Byton announced a partnership with star-studded Aurora to bring self-driving smarts to its vehicles. And today, at CES Asia in Shanghai, it unveiled a second concept car, a small sedan that can't help but make you think of a certain car rolling off the assembly line in Silicon Valley. Byton's new ride is the K-Byte, a three-box sedan with the front wheels pushed as far forward as possible.

  AI-Alerts: 2018 > 2018-06 > AAAI AI-Alert for Jun 19, 2018 (1.00)
  Country:
  Industry:

Machine learning predicts World Cup winner

#artificialintelligence

The random-forest technique has emerged in recent years as a powerful way to analyze large data sets while avoiding some of the pitfalls of other data-mining methods. It is based on the idea that some future event can be determined by a decision tree in which an outcome is calculated at each branch by reference to a set of training data. However, decision trees suffer from a well-known problem. In the latter stages of the branching process, decisions can become severely distorted by training data that is sparse and prone to huge variation at this kind of resolution, a problem known as overfitting. The random-forest approach is different.

  AI-Alerts: 2018 > 2018-06 > AAAI AI-Alert for Jun 19, 2018 (1.00)
  Country:
  Industry: Leisure & Entertainment > Sports > Soccer (1.00)