The most popular Topic Modeling algorithm is LDA, Latent Dirichlet Allocation. Let's first unravel this imposing name to have an intuition of what it does. Figure 1 below describes how the LDA steps articulate to find the topics within a corpus of documents. "A document is generated by sampling a mixture of these topics and then sampling words from that mixture" (Andrew Ng, David Blei and Michael Jordan from the LDA original paper). NB: In the Figure 1 above, we have set K 3 topics and N 8 words in our vocabulary for illustration ease.

The "Artificial Intelligence in Retail Market" Report offers an inclusive and decision-making overview, including definitions, classifications and its …

To enable wider use of this powerful deep learning architecture, we propose two new methods. The first, adaptive attention span is a way to make Transformer networks more efficient for longer sentences. With this method, we were able to increase the attention span of a Transformer to over 8,000 tokens without significantly increasing computation time or memory footprint. The second, all-attention layer is a way to simplify the model architecture of Transformer networks. Even with a much simpler architecture, our all-attention network matched the state-of-the-art performance of Transformer networks.

This facial mapping technology has been designed to improve television language dubbing, but it also has strong potential for those seeking to deceive. BBC's Media Editor Amol Rajan looks at the benefits and risks - and tries it out himself. This story is part of a series by the BBC on disinformation and fake news - a global problem challenging the way we share information and perceive the world around us. To see more stories and learn more about the series visit www.bbc.co.uk/beyondfakenews

Lucidea, provider of ArchivEra, CuadraSTAR SKCA and Eloquent Archives, will participate in the Archives & Records Association (ARA) annual conference on 28th and 30th August in Leeds. Visit Lucidea at Stand #5 in the Queens Hotel to see how easily their archival collections management solutions enable researchers and the public to connect with the historic materials archivists work hard to preserve. Lucidea's archives specialists will demonstrate the powerful and versatile capabilities of ArchivEra, CuadraSTAR SKCA, and Eloquent Archives that make them a valued technology partner in the archives community. ARA attendees will be first in the UK to see Lucidea's exciting new AI prototype for archives. With Artificial Intelligence (AI) integration now available in ArchivEra, Lucidea's clients will enjoy powerful automatic categorization functionality.

In 2009, Netflix was sued for releasing movie ratings data from half a million subscribers who were identified only by unique ID numbers. The video streaming service divulged this "anonymized" information to the public as part of its Netflix Prize contest, in which participants were asked to use the data to develop a better content recommendation algorithm. But researchers from the University of Texas showed that as few as six movie ratings could be used to identify users. A closet lesbian sued Netflix, saying her anonymity was compromised. The lawsuit was settled in 2010. The Netflix case reveals a problem about which the public is just starting to learn, but that data analysts and computer scientists have known for years. In anonymized datasets where distinguishing characteristics of a person such as name and address have been deleted, even a handful of seemingly innocuous information can lead to identification.

A humanoid robot sent by Russia's Vladimir Putin to the International Space Station (ISS) has failed to dock. A live stream of the six-foot Fedor robot - strapped in the pilot seat of the Soyuz spacecraft while wielding a Russia's white, blue and red flag - had to be interrupted with the humanoid still 100 meters away, news agency AFP reported. Fedor, an artificially intelligent robot known officially as Skybot F-850, was on an automated and unmanned mission to the space station, where he is supposed to help out crews for ten days. He is said to be the first humanoid sent to space by Russia. Having failed its landing at 05:30 BST on Saturday, Fedor will now have to wait until Monday to try reaching the ISS again.

A humanoid robot sent by Russia's Vladimir Putin to the International Space Station (ISS) has failed to dock. A live stream of the six-foot Fedor robot - strapped in the pilot seat of the Soyuz spacecraft while wielding a Russia's white, blue and red flag - had to be interrupted with the humanoid still 100 meters away, news agency AFP reported. Fedor, an artificially intelligent robot known officially as Skybot F-850, was on an automated and unmanned mission to the space station, where he is supposed to help out crews for ten days. He is said to be the first humanoid sent to space by Russia. Having failed its landing at 05:30 BST on Saturday, Fedor will now have to wait until Monday to try reaching the ISS again.

Consumers International has released a new study on consumer experiences of artificial intelligence (AI) and the ways in which AI enabled services shape their consumer journeys and experiences, and consumer outcomes. The report'Artificial Intelligence: consumer experiences in new technology' contains a summary of new findings about the consumer experience of AI from IPSOS Global's participatory research with families and individuals in India, Australia and Japan, and insights from interviews with expert stakeholders from the region. It also incorporates the results of the multi-stakeholder roundtable held in Singapore in March 2019, where consumer organisations, businesses, academics and regulators discussed how AI enabled technology can deliver the best possible outcomes for consumers, whilst recognising and mitigating against potential challenges and risks.