Articles about Machine Learning

The mayor of New York City, Bill de Blasio, has announced the formation of a new task force to examine the fairness of the algorithms used in the city's automated systems.

The Automated Decision Systems Task Force will review algorithms that are in use to determine that they are free from bias. Representatives from the Department of Social Services, the NYC Police Department, the Department of Transportation, the Mayor's Office of Criminal Justice, the Administration for Children's Services, and the Department of Education will be involved, and the aim is to produce a report by December 2019.

Continue reading →

Today at its I/O developer conference, Google revealed major changes for Google News. The company says that the revamp combines the best of artificial intelligence with the best of human intelligence, and it sees Google try to rebuild the trust people have in online news.

As well as a revamp of the underlying technology, there are also changes in presentation. A "For You" section in the app provides easy access to the most relevant stories that will be of personal interest, and there are also new opportunities for readers to delve deeper into stories via various news outlets, social media, videos and more via a new timeline tool.

Continue reading →

Over the past year or so the idea of using artificial intelligence as an aid to cyber security has gained a lot of support.

But what role does AI and machine learning have, and what will the future of security look like when it's in widespread use? We spoke to Gene Stevens, co-founder and CTO of network security company ProtectWise to find out.

Continue reading →

Threat intelligence is becoming an essential part of protecting systems. But this information often comes from many different sources, making it hard to see the big picture and limiting flexibility and effectiveness.

To address this issue, Recorded Future is launching a new product providing centralization, collaboration, and customization of intelligence. Called Fusion, it's powered by machine learning and allows users to centralize and customize proprietary and internal threat data with external threat intelligence.

Continue reading →

Machine learning (ML) is getting a lot of attention these days. Search engines that autocomplete, sophisticated Uber transportation scheduling and recommendations from social sites and online storefronts are just a few of the daily events that ML technologies make possible.

Cybersecurity is another area where ML is having a big impact and providing many benefits. For instance, ML can help security analysts shorten response times and dramatically improve accuracy when deciding if a security alert is an actual threat or just a benign anomaly. Many view ML as the primary answer to help save organizations from the severe shortage of skilled security professionals, and the best tool to protect companies from future data breaches.

Continue reading →

Machine learning is taking the tech world by storm. Recently, an announcement that Google was open-sourcing Tensor Flow, their machine learning (ML) software, and Microsoft quickly followed suit. Baidu and Amazon unveiled their own deep learning platforms a few months later, while Facebook began supporting the development of two ML frameworks. But the revolution has spread far beyond the tech realm. In fact, some of the more recent applications of ML technology aren’t just innovative; they’re weird and surprising.

As machine learning (ML) continues to take over the tech world, companies and researchers outside the tech bubble have started using ML in strange and surprising ways. Here are ten unexpected ways machine learning is being used:

Continue reading →

Companies are increasingly turning to AI and machine learning solutions to combat cyber threats, but sometimes there is no substitute for the insight that comes with human analysis.

Threat intelligence specialist Recorded Future recognizes this and is expanding its platform to give security operations centers access to analyst-originated intelligence to offer relevant expert insights and analysis needed for operational improvements and targeted risk reduction.

Continue reading →

Hackers and criminal syndicates are attacking enterprises with increasingly stealthy and sophisticated techniques. In response, companies are deploying a new generation of firewalls, IDS appliances, and Security Information and Event Monitoring (SIEM) servers to detect suspicious activity as quickly as possible.

Two problems are undermining these recent investments in IT security.

Continue reading →

Splunk has revealed plans to boost the power of its enterprise software offerings thanks to the power of machine learning.

Speaking at the opening keynote of the company’s conf2017 event in Washington, Splunk chief product officer Richard Campione highlighted how machine learning could help the company’s customers get even more insight out of their data.

Continue reading →

Facial detection technology is usually used to identify individuals for the purposes of crime prevention, or as a biometric security method. But a paper published by Stanford University -- entitled simply "Deep neural networks are more accurate than humans at detecting sexual orientation from facial images" -- shows that it could also be used to determine people's sexuality.

Using AI and deep neural networks, algorithms have been shown to have a far better gaydar than people. Working with a sample of more than 35,000 photographs, the system was able to correctly determine whether individuals were gay or straight with staggering accuracy -- 81 percent of men and 74 percent of women. While on one hand the results are impressive, there are also ethical concerns.

Continue reading →

Oracle has revealed a major upgrade to its IoT cloud offering that it says will help businesses get more value out of the platform.

The company has revealed it will be imbuing its IoT Cloud with built-in artificial intelligence and machine learning capabilities which will be able to provide businesses with more detailed data than ever before.

Continue reading →

Amazon Web Services has launched a new machine learning service aimed at helping organizations protect their sensitive data in the cloud.

Macie's general premise is quite simple: it analyzes data on the S3 storage service, and is capable of identifying names, addresses, credit card numbers, driver licenses or social security numbers, stuff like that.

Continue reading →

In my series, I’ve looked at the different ways in which data can be deployed to help people make decisions. Over time, more of the decision-making process has shifted from people manually collating data from different sources in their heads to using data sets that can be automatically joined together. This networked approach to data makes it easier for people of all skill levels to work with data.

This has evolved to make more use of automation over time. By making it easier for individuals to link up data sets and form connections between these assets, businesses have been able to spread analytics to more users within their organizations. This is now being taken further with machine learning.

Continue reading →

Facebook has revealed it is harnessing the power of AI to support its growth across the world.

The social media giant, which has over two billion users worldwide, is now using neural networks for to automatically translate content in foreign markets.

Continue reading →

There are four key areas where digital businesses can make a significant profit, and Google's parent company Alphabet appears to be gaining in all four of them according to its latest earnings report.

In a recent call to reveal its results, Alphabet said revenue rose 21 percent to $26 billion, in the second quarter of 2017. Net income was $3.5 billion.

Continue reading →