Goto

Collaborating Authors

 Telecommunications


Qualcomm Acquires Machine Learning Startup Scyfer

#artificialintelligence

Qualcomm Technologies (QCOM) announced that it has acquired machine learning startup Scyfer for an undisclosed amount. Scyfer B.V. is a startup that is affiliated with University of Amsterdam and focuses on applying machine learning techniques to different fields. Through the acquisition, Qualcomm hopes to further incorporate AI technology into different devices, including cars, machines and robotics. Netherlands-based Scyfer was founded in 2013 to provide AI for companies in industries such as manufacturing, healthcare and finance. Management was headed by Co-founder and CTO Tijmen Blankevoort, who was previously co-founder of Cyno Intelligent System.


Qualcomm outline AI research roadmap

#artificialintelligence

Qualcomm has unveiled its roadmap for bringing artificial intelligence capabilities to smart devices and goals to bring complementary AI features to the cloud. Sparked in 2007, Qualcomm's efforts to improve AI services use neuron-based approaches to machine learning, and their efforts aim to make AI a cornerstone of most digital-enabled products, including automobiles and machinery. Qualcomm's initial AI efforts, before the smart device boom was in full swing, initially focused on motion control and computer vision applications, fields inspired by biological counterparts. Their efforts later extended into neural net fields supplemented by deep learning algorithms. On August 16, 2017, Qualcomm further expanded their capabilities by purchasing the University of Amsterdam-affiliated Scyfer BV, an AI-focused company with experience in healthcare, finance, and manufacturing.


Qualcomm takes over Scyfer

#artificialintelligence

Scyfer was established about four years ago at Amsterdam Science Park as a spinoff of the University of Amsterdam. The company works with the latest and most advanced technologies in the field of deep learning. Founder and CEO of Scyfer is Max Welling, professor of Machine Learning at the Faculty of Natural Sciences, Mathematics and Informatics at the University of Amsterdam. He is also employed at the University of California Irvine, the Canadian Institute for Advanced Research (CIFAR).


Google Home can now make calls and it won't cost you a dime

#artificialintelligence

Google has just pushed an update to its Home smart speaker that lets you make calls to any phone number in the US and Canada for free. As with its other features, you can place a call with your voice: just say, "Hey Google, Call Abhimanyu," or whoever else you've been dying to talk to, and it'll do your bidding instantly over Wi-Fi. It'll recognize your voice to load your own contacts, so when you ask it to "Call Dad," it'll phone your father and not someone else's. Plus, you can also ask Home to ring businesses by name, even if they aren't stored in your contact list. With that, Google might have just replaced your landline and beat Amazon et al to the punch as well. Echo speakers can currently talk to each other, but not to phones; Apple and Microsoft are yet to introduce these features in their upcoming smart speakers.


Ditch That Landline and Use Google Home Instead

WIRED

You probably don't have a landline phone, because it's not 1995. But you miss it sometimes, don't you? Knowing where the phone was all the time, having something anyone could pick up and use, avoiding the rock-paper-scissors over who has to waste their cell phone battery calling Dominos. Earlier this year at its developer conference, Google promised to turn its Home smart speaker into a sort of futuristic landline. You can now call any business or person in your contacts, as long as they live in the US or Canada, just by asking Google to do so.


Smartphone cameras are getting

FOX News

Big changes are coming to your phone's smartphone camera next year, with Qualcomm previewing an update to its image signal processor (ISP) that will better support features like face recognition and mixed reality. Qualcomm's Spectra ISP is a part of the Snapdragon system on chip that's a popular mobile processor platform for many Android phones. While the next major Snapdragon update won't arrive until next year, the changes planned for the Spectra ISP have major implications not just for the cameras on 2018 Android phones but for virtual- and augmented reality headsets as well. That's because the next version of the Spectra ISP introduces a new architecture to support advances in image quality, image recognition and power efficiency. Specifically, Qualcomm is promising that its new camera module will feature improved biometric sensing for detecting people's faces and support for depth sensing that can power mixed reality features for smartphones and headsets.


Qualcomm's new depth-sensing camera is surprisingly effective

Engadget

Dual cameras are so passé. Qualcomm is getting ready to define the next generation of cameras for the Android ecosystem. It's adding three new camera modules to its Spectra Module Program, which lets device manufacturers select ready-made parts for their products. The additions are an iris-authentication front-facing option, an "Entry-Level Computer Vision" setup and a "Premium Computer Vision" kit. The latter two carry out passive and active depth-sensing respectively, using Qualcomm's newly revamped image signal processing (ISP) architecture.


2018 Android AR, VR And Smartphones To Feature Updated Qualcomm Spectra ISP

International Business Times

Qualcomm camera technology to be featured on products scheduled for release in 2018 will focus on high-resolution depth sensing. The semiconductor manufacturer announced Tuesday, its second generation Spectra ISP camera module. The updated technology is expected to further improve image quality and effects, not only for mobile cameras but also for iris scanning and facial recognition features as well as for AR and VR. Qualcomm has planned, announcements at IFA in September with more details pertaining to its new chips and technology. Consumers can expect future devices running the new Spectra ISP camera module to up the ante on trends that are already being tested.


Top 7 Technology Trends in 2017 That Are Moving Faster Than Ever

#artificialintelligence

With the progressing year, the technology diversified ways in which we could communicate and retrieve the information from the pocket fitting devices. Technologies such as IoT, automation, and cognitive computing moved beyond the conceptual stages in 2016. As the year takes up, companies throughout the world are developing their business strategies. In order to move forward in the competition, companies are turning towards major investments in technology. The world's biggest consumer technology convention, CES is one of the best places to find a handful of key technologies. CES 2017 finished another spectacular year with pioneering technology trends including smart homes to self-driving cars. This year is assumed to bring transformative technology trends for us to explore and invest in. AI, also known as Artificial Intelligence has been studied for decades and now the vision of transforming insentient objects into intelligence is gradually becoming a reality. AI based Innovations are now pondering into the market and becoming part of our daily lives with quick adaptability. Artificial intelligence assists humans and handles the tasks flawlessly, without interrupting your comfort. Whether to set an alarm, or remind you of something important, or to play your favorite music or to read out general news for you or to find your phone, AI can make the task more convenient and smart. Sit back and relax while you command your device to do things for you.


Call Detail Record Analysis – K-means Clustering with R

@machinelearnbot

Call Detail Record (CDR) is the information captured by the telecom companies during Call, SMS, and Internet activity of a customer. Most of the telecom companies use CDR information for fraud detection by clustering the user profiles, reducing customer churn by usage activity, and targeting the profitable customers by using RFM analysis. The actual dataset contains 8 numerical features about SMS in and out activity, call in and out activity, Internet traffic activity, square grid ID where the activity has happened, country code, and timestamp information about when the activity has been started. Here, K-means is applied among "total activity and activity hours" to find the usage pattern with respect to the activity hours.