Pages with tag Machine Learning

Amazon employees demand stopping face-recognition contract with federal government Among the Amazon Web Services is Rekognition, a facial recognition system running on Amazon's cloud. Anyone can sign up with the service, to have video analyzed to identify people or objects. Turns out the federal government is using this service for various tasks including deportation and detention programs run by ICE, the Immigration Control force. A group of Amazon employees have written to Amazon CEO Jeff Bezos demanding that Amazon not do as IBM did during the 1940's when IBM's systems were used by Nazi Germany to help round up the Jews.
Congressman Ro Khanna calls for USA Universities to be innovation hubs serving the modern technology era Machine learning and artificial intelligence are not just the new hotness in software development, they represent a whole new model of computing. The old style of training software engineers does not work because the new model is so different. Generally speaking "Technology Breakthroughs" are showing no signs of slowing down, and therefore any country desiring to have a global leading role must have a smart educated workforce. Since it was the USA which invented most of these technologies you might think the USA would be doubling down on educating its children to ensure it maintains a leadership role in technology development. The current climate of USA politics is, however, not driven by wisdom. Silicon Valley's Congressman, Ro Khanna, has a different vision than what is currently driving American Politics.
FBI, ICE mined driver’s license photos for facial recognition Tens of millions of U.S. citizens have had their faces scanned by the FBI and Immigration and Customs Enforcement (ICE) without their knowledge or consent, according to new documents collected by researchers at Georgetown Law. The goal, to develop a facial recognition database that would recognize "illegal immigrants", is dubious at best. But the action was taken without approval by Congress, or the individual people.
Facial recognition technology used to solve cases like Capitol Gazette newspaper shooting in Annapolis

The immediate reaction on Thursday to the Capitol Gazette newspaper shooting was that the climate of violence encouraged by Pres. Trump, all the vindictive aimed at newspapers by Trump, has resulted in some lunatic acting out the grievances inflamed by Trump's rhetoric. In other words, some Patriot believing the Capitol Gazette to be a hub of Liberal nonsense could have decided to shoot the place up. Supposedly the shooter, to mess up law enforcement efforts, had damaged his fingerprints, and did not carry identification, making us think maybe this was some kind of terror attack. At the end of the day, "Facial Recognition Technology" was used to identify the shooter as a person with a long-standing personal grievance against the staff of that newspaper, because of reporting by that newspaper about that person.

In other words, there is no nefarious dark scheme here. While it is true that Pres. Trump, and others in his administration, are inflaming the public against journalists with eery similarity to the Nazi Germany playbook, this particular case is a straight-up personal grievance. And, we have proof that while we should be concerned about big brother implications of facial recognition technology, in some cases like this one the technology is higly useful.
Google employees demand AI rules to preclude use as weapons

Google's culture of open free-flowing discussion could be ending in the wake of an uproar over Google's partnership with the US Dept. of Defense, called Project Maven, on AI software to analyze drone footage. Since Google's participation in Project Maven was publicly revealed in March, a raging debate with Google has swirled around whether the company famous for its "Do No Evil" slogan should be involved with making weapons. Googlers even sent an open letter to Google CEO Sundar Pichai starting with the declaration "We believe that Google should not be in the business of war." That letter flatly called for Google's participation in Project Maven to be canceled.

On June 27, 2018, it is learned that Google has instituted new rules for internal discussion and workplace conduct within the company.

In China, facial recognition technology is used to create a Big Brother tracking system

Modern technology is gifting society with many wonders, including democratization by giving more creative power to individuals. In some countries the Internet is not allowed to be used for democratization, but for authoritarian control. One particular area is facial recognition technology which is how social media networks like Facebook can automatically tag your pictures with your friends. That same technology can be aimed at a crowd, and used to implement real-time tracking of where folks walk throughout a city. Supposedly the benefit is catching wrong-doers, but in every movie about ubiquitous monitoring the government doesn't use the information for the benefit of all, but to squash freedom.
Introduction to using DVC to manage machine learning project datasets DVC is a powerful set of tools for managing data files associated with data science or machine learning projects. The code for such a project is committed to a Git repository, and DVC manages the data files in parallel to that repository.
Managing versioned machine learning datasets in DVC, and easily share ML projects with colleagues DVC is a powerful set of tools for managing data files associated with data science or machine learning projects. It works hand-in-hand with a Git repository to track both the code and the datasets in an ML project. A core feature is for versioning datasets, meaning that it correlates the dataset to exactly match what existed at each Git commit. By using a DVC "remote cache" it is very easy to share a project with colleagues, or to copy the dataset to a remote machine.
NVIDIA Boosts World’s Leading Deep Learning Computing Platform, Bringing 10x Performance Gain in Six Months

NVIDIA is upping their game with GPU's meant for "machine learning" computational workloads. Such systems are installed in cloud server facilities to assist with Machine Learning computations. What NVIDIA is doing is to pivot their expertise in graphics processors into supplying high performance numerical calculation engines. These systems pack 2 petaflops of computation ability into a relatively small box, that also contains some conventional CPU's and a massive amount of SSD-based storage. The need being fulfilled is the massive computation required to implement artificial intelligence algorithms.

NVIDIA claims the improvement rate for this product line is faster than Moores Law - meaning that system capabilities are doubling faster than every 18 months - meaning that a revolution is underway in areas requiring this sort of massive computation capability.