Understanding call center artificial intelligence


Maybe it's because the new high-tech sex robots have been in the news lately that we are hearing again about the death of call centers due to "artificial intelligence." It might be well to point out that it is called "artificial" for a reason. Likewise, a "sexbot" is artificial intelligence that it stops talking when you push the "mute" button. There is a great misconception about the role of new technologies --broadly lumped as artificial intelligence--in the customer-service industry. The hysterical articles you read that sooner or later all Filipino call-center agents are going to be replaced by armies of computers is simply false and with no basis in reality.

Deep-learning AI evolves beyond Internet, cloud


That would allow devices to operate independent of the internet while using AI that performs almost as well as tethered neural networks. "We feel this has enormous potential," said Alexander Wong, a systems design engineering professor and Waterloo and co-creator of the technology. "This could be an enabler in many fields where people are struggling to get deep-learning AI in an operational form." The use of stand-alone deep-learning AI could lead to much lower data processing and transmission costs, greater privacy and use in areas where existing technology is impractical due to expense or other factors. Deep-learning AI, which mimics the human brain by processing data through layers and layers of artificial neurons, typically requires considerable computational power, memory and energy to function.

Deep Learning Could Be The Future Of Online Streaming


Video streaming has been popular for quite some time, but its growth seems to keep expanding. While it was initially popularized by platforms such as YouTube and then Facebook, today they are being joined by video-on-demand services such as Netflix, Amazon and Hulu. Recently a study suggested that as much as 70% of all online traffic consists of streaming video and audio, and it is placing a heavy demand on internet bandwidths across the world. Although internet speeds and bandwidth have grown over the years, the demand for videos with higher resolutions and bitrates has grown as well. To help optimize the usage of available bandwidth for streaming video, most streaming platforms use algorithms known as Adaptive Bitrate (ABR).

AI and the future of healthcare


Discussed much more thoroughly in the last article AI in Banking, Artificial Intelligence (AI) is a powerful force for business. Does it have a place in Healthcare, too? In this country, healthcare is a business, even if it is full of altruistic individuals that are just seeking to help others. We thwart disease; we repair damage; we cope with aberrations in bell-curve physiology; and most importantly, we make lives better. But that doesn't work very well without a solid business foundation!

'Amazon's Alexa is now part of the family – I just hope she doesn't replace me'

The Guardian

The most futuristic thing I have ever bought used to be a Sonos music player. I'd have people over just to show it off. "Name a song," I'd say. "Go on, any version of any song by any act that ever lived. So they would, and I'd pull out my phone and – hey presto – seconds later, that song would boom out across my living room like magic.

Asia Pacific youth expect Artificial Intelligence to have biggest impact on their future: Microsoft survey - Asia News Center


SINGAPORE, 22 February 2017 -- In our increasingly digital world, new and emerging innovations are set to disrupt the way people live, work and play. According to youth across the Asia Pacific region, the most exciting technologies expected to have the largest impact on their future lives will be artificial intelligence (AI), virtual/mixed/augmented reality (VR/MR/AR), and Internet of Things (IoT), based on survey findings released today by Microsoft. In the Microsoft Asia Digital Future Survey, 1,400 youth were polled across 14 markets across the Asia Pacific region, comprising Australia, China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, New Zealand, Philippines, Singapore, Taiwan, Thailand and Vietnam. Artificial intelligence (AI) is ranked as the top technology that youth expect to have the biggest impact on their lives. In recent years, the confluence of power devices, cloud and data has enabled bold visions on how AI can be an integrated part of our digital future.

9 Must-Have Datasets for Investigating Recommender Systems


Lab41 is currently in the midst of Project Hermes, an exploration of different recommender systems in order to build up some intuition (and of course, hard data) about how these algorithms can be used to solve data, code, and expert discovery problems in a number of large organizations. Anna's post gives a great overview of recommenders which you should check out if you haven't already. The ideal way to tackle this problem would be to go to each organization, find the data they have, and use it to build a recommender system. But this isn't feasible for multiple reasons: it doesn't scale because there are far more large organizations than there are members of Lab41, and of course most of these organizations would be hesitant to share their data with outsiders. Instead, we need a more general solution that anyone can apply as a guideline.

Which Bugs Will Hackers Exploit First? Machine Learning Promises a Better Guess


The vast majority of the bugs that hackers exploit aren't fancy zero-days that no one has ever seen or reported. Most are vulnerabilities that have gotten out into the wild and spread via chat rooms and hacker forums on the dark web. Guessing which bugs will cause the most damage -- useful in knowing which ones to patch first -- is still mostly a guess. But researchers from Arizona State University have developed a machine-learning model to predict which vulnerabilities are the most likely to cause the next headline-grabbing incident. Today's most common methods for anticipating the likelihood that a previously disclosed software vulnerability will cause major damage are imperfect at best.

How to use AI Machine Learning in B2B Marketplace – Becoming Human


Machine Learning has certainly come a long way. The confluence of factors such as the evolution of data growth, advancements in computational algorithm and faster machine processing helped create an ideal environment for Deep Neural network and AI to finally gain adoption in the main stream. Now we have a mother load of data thanks to increasing amount of social sharing and rise of digital devices, Internet of Things (IOT) etc etc. Just look at the data we have accumulated over the last decade since the creation of Online streaming, Social Media, Mobile and Internet of Things (IOTs). We are creating about 1.7MB of new information per human being on the planet.

Google ad revenue rises as machine learning grows


Google ad revenue rises as machine learning grows Internet giant Google has boosted quarterly revenue with strong advertising sales on mobiles and growing demand for video content. Google chief executive Sundar Pichai says the company continuing to develop machine learning, artificial intelligence and plans to take the internet to remote corners of the world. Internet giant Google has boosted quarterly revenue with strong advertising sales on mobiles and growing demand for video content. Google chief executive Sundar Pichai says the company continuing to develop machine learning, artificial intelligence and plans to take the internet to remote corners of the world.