Media
Audioburst turns the best part of podcasts into personalized news briefs
Tel Aviv-based Audioburst has been developing a search engine for audio news, which allows users to locate audio content within podcasts and other talk radio programs. Today, the company is capitalizing on its technology to launch personalized playlists that deliver custom news briefs that get better over time the more you use the product. The feature has been built using deep AI learning, the company says. The content itself is drawn from top podcasts and the radio stations in Audioburst's index, and will alert you to new information based on your chosen keywords and topics. To use the feature, you first sign up on the Audioburst website, then select from a set of interests or add your own.
Three Ways To Use AI And Machine Learning To Create Customers For Life
Only a few years ago, business to business (B2B) technology companies would sell a solution to a customer, wait three to five years, then reapproach that same customer to offer a renewal or a completely new product. But these days, the initial purchase doesn't necessarily translate into a continuum of sales, and it doesn't hold the promise of customer retention like it once did. That's because today's customers have much higher expectations in order to remain loyal. Getting them to love your brand and love your products takes a customer-first mindset and a company-wide commitment to improve the customer experience. Companies that excel at customer experience are using artificial intelligence (AI) and machine learning heavily to produce immersive, authentic experiences across every customer touch point.
Is Google Image SEO Relevant Again? What New Data Tells Us
Image SEO used to be a huge aspect of content and site optimization, with the potential to drive tons of image search traffic. File names, alt tags, and image sitemaps were all super important. The "view image" button was added to Google Images in 2013. With the new implementation, sites saw an average decrease of 63 percent in image search traffic. While image optimization is still an extensive practice, it hasn't been effective for driving much traffic.
Will automation and AI give us four-day weekends โ or simply leave us without jobs?
In 1900 many people worked in dreadful conditions, doing repetitive and tedious jobs. The streets were full of horses and carts. Life expectancy for someone born that year was just 41. Wind forward to 1962 and working conditions had greatly improved. The streets were full of cars and trucks and the jet age had begun. Life expectancy had nearly doubled, to 71.
r/MachineLearning - [R][1806.05086] Group Equivariant Capsule Networks
Abstract: We present group equivariant capsule networks, a framework to introduce guaranteed equivariance and invariance properties to the capsule network idea. Our work can be divided into two contributions. First, we present a generic routing by agreement algorithm defined on elements of a group and prove that equivariance of output pose vectors, as well as invariance of output activations, hold under certain conditions. Second, we connect the resulting equivariant capsule networks with work from the field of group convolutional networks. Through this connection, we provide intuitions of how both methods relate and are able to combine the strengths of both approaches in one deep neural network architecture.
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Zhong, Victor, Xiong, Caiming, Keskar, Nitish Shirish, Socher, Richard
End-to-end neural models have made significant progress in question answering, however recent studies show that these models implicitly assume that the answer and evidence appear close together in a single document. In this work, we propose the Coarse-grain Fine-grain Coattention Network (CFC), a new question answering model that combines information from evidence across multiple documents. The CFC consists of a coarse-grain module that interprets documents with respect to the query then finds a relevant answer, and a fine-grain module which scores each candidate answer by comparing its occurrences across all of the documents with the query. We design these modules using hierarchies of coattention and self-attention, which learn to emphasize different parts of the input. On the Qangaroo WikiHop multi-evidence question answering task, the CFC obtains a new state-of-the-art result of 70.6% on the blind test set, outperforming the previous best by 3% accuracy despite not using pretrained contextual encoders.
What's coming up in 2019? Upcoming tech trends we can't wait to see
The Gadget Flow Daily Digest highlights and explores the latest in tech trends to keep you informed. With every new update comes further upgrades, sending us on a never-ending quest of innovation month after month. Check out these upcoming tech trends to stay ahead of the curve in 2019. Like every year, we can't wait to explore the latest tech and announcements at CES 2019 coming up next week. This event is not just about exploring new tech but also about paving the way for a brighter future with technology around you. While last year surprised us with the LG TV canyon and unbelievable robots, this year seems like even more fun in terms of new tech and innovation.