Goto

Collaborating Authors

 SPE


Artificial Intelligence, Machine Learning, and Cognitive Computing: Market and Outlook for Communications, Applications, Content and Commerce 2016 - 2021

#artificialintelligence

Overview: Artificial Intelligence is a technology that uses machine intelligence and human like thinking ability to process historical, and increasingly, real-time data to make predictions, recommendations, and decisions. AI is not a single technology but a convergence of various technologies, statistical models, algorithms, and approaches. Machine Learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in AI. Cognitive Computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. AI is increasingly integrated in many areas including Internet search, entertainment, commerce applications, content optimization, and robotics.


Researchers Train AI To Defeat Face Blurring Technologies

Popular Science

Researchers fed the software this picture of actor J.K. Simmons, among others, to teach it to recognize specific faces. Since 1989, Cops has famously aired footage of suspected criminals, many with their faces blurred out to protect their privacy. Ever since then, blurred or pixelated faces have become standard fare for concealing the identity of individuals who prefer not to be recognized in the media. YouTube got in the game a few years ago, offering a facial blurring tool to help protect protestors against retribution from law enforcement or employers. But machine learning researchers at Cornell Tech and the University of Texas at Austin have developed software that makes it possible for users to recognize a person's concealed face in photographs or videos.


Marc Andreessen on the atomization of AI

#artificialintelligence

Earlier this year, Andreessen Horowitz investor Chris Dixon noted that how challenging it's become for investors to help groom promising AI startups, given how quickly Facebook, Google, and Amazon are bringing aboard related talent. Dixon noted, for example, that Wit.ai, a Y Combinator startup that built voice-activated interfaces that Facebook bought and which now powers its Messenger platform, was only in Andreessen Horowitz's portfolio for a few months when Facebook bought it. But firm co-founder Marc Andreessen said on stage at Disrupt today that the firm is beginning to see things swing in the opposite direction. "Two years ago, it seemed like four or five companies were hoovering up all the talent . . . I think something like 1,500 people over four years [were involved in] building Alexa," the technology that powers Amazon's voice-controlled home computer Echo.


Ex-Google Guy Builds English Teaching App That Adapts to Student

#artificialintelligence

Yi Wang was hearing the same refrain over and over: Why are English classes in China so expensive? The former Google product manager decided to do something about it and started an app called LiuLiShuo, which basically means "speaking fluently" in Mandarin. The app, which claims more than 30 million users, is one of scores of English-learning startups looking to disrupt China's hidebound language schools. To differentiate itself from products started by Internet giants like Baidu and Tencent, LiuLiShuo brings gaming and social media features to the genre. Users win points when they move to the next level and text each other encouragement and tips.


Pixelated photos and license plates can be unblurred using artificial intelligence

#artificialintelligence

The researchers managed to defeat three privacy protection technologies. Firstly, they successfully identified faces from YouTube's blur tool, which allows users to automatically blur out objects and faces in their uploaded videos. It could also identify people and numbers from pixelated images created by Photoshop and the JPEG photo format's P3 - designed to be a secure way of hiding information. The algorithm is successful but not complete. It is only able to identify people or things it has previously been shown. However, an attacker, for instance, could use online social media photos to train the computer, which could make the method mainstream and dangerous.


Chatbot Sensay wants to connect the world by sharing knowledge

#artificialintelligence

Chatbots are a major trend in tech today. Facebook Messenger has more than 30,000 bots; Kik has 20,000 -- but how many of those are actually useful? Nobody can go through that many bots individually, but it is certain that few early players in the "chatbot rush" have taken off in a major way. Sensay, one contestant at the TechCrunch Disrupt SF Battlefield, is aiming to be that first breakout cross-platform chatbot -- but, unlike most that provide services and information at a convenience via chat, its currency is people. Founders Ariel Jalali (CEO) and Crystal Rose (CMO) told TechCrunch that the premise of the service is to connect people by sharing knowledge, information and experiences.


Meet the Artists Who Have Embraced Artificial Intelligence

#artificialintelligence

Sam Kronick has a bunch of rocks arrayed in front of him on a raised desk in his Oakland studio. He's an artist and his plan is to sketch the rocks, but not with pen and paper. He and his artistic partner Tara Shi are going to do a 3D scan of them so that an artificial intelligence program can map their contours, learn to recognize rocks and then start generating its own craggy depictions. The project is deceptively simple: trying to get artificial intelligence to make nature art. Kronick and Shi are using a neural net, a computer program loosely modeled on biological neural systems like the human brain.


#splunkconf16 preview: What's the next big thing in big data? Machine learning.

#artificialintelligence

Big data, especially machine data, is fueling the latest machine learning (ML) trend and we've got you covered with 18 sessions at .conf2016. Cut through the hype and learn how to operationalize ML in your organization to prevent service outages, manage inventory, identify insider threats, or to simply manage your alerts better. Whether you've been using the ML Toolkit since it was introduced last year or you're just curious what all the excitement is about, you can hear directly from Splunk product managers and developers and customers like Emerson, NTT Docomo, Dunkin' Donuts, Zillow, and others. Follow all the conversations coming out of #splunkconf16!


[Discussion] Defeating Image Obfuscation with Deep Learning • /r/MachineLearning

#artificialintelligence

They have the torch network configuration for each network at the end of the paper. I notice they use some linear units, why? Also, why are the networks so different? Is there a good resource on one designs their network? I notice they use some linear units, why?


Susan Athey on Machine Learning, Big Data, and Causation EconTalk Library of Economics and Liberty

#artificialintelligence

And so, you want to give different treatment to those. And in classic econometrics you just kind of put everything in a regression, and the econometrics were the same--like, you'd put in a dummy variable for whether there was a higher minimum wage, and you would put in all these other covariates; but you'd use the same statistical analysis for both. And so I think the starting point for doing causal inference, which is mostly what we're interested in, in economics, is that you treat these things differently. So, I'm going to use machine learning methods, or sort of data mining techniques, to understand the effects of covariates, like, you know, all the characteristics of the patients; but I'm going to tell my model to do something different about the treatment effect. That's the variable I'm concerned about.