Source: McKinsey See also Security Ledger
Only 16% say their company is well prepared for the challenge of IoT security
Posted in Internet of Things
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Richard Socher, Salesforce (Emerging AI Leaders Series)
“AI teaches us who we are,” says Richard Socher. The recent rapid progress in the field of artificial intelligence is the result of successfully processing “a large amount of known training data, doing things [the computer] has seen before,” he says. Unlike humans, computers cannot create something new and unique.
Human creativity has been the driving force behind scientific and engineering advances, including making computers do more human-like activities such as identifying objects or words. Socher’s creativity, his ability to come up with new approaches to solving computers’ language and visual processing challenges, has made him a rising star of the deep learning movement that has spawned exciting new applications of artificial intelligence.
Deep learning has also spawned a number of emerging AI leaders and Richard Socher exemplifies their career trajectories and ambitions—advancing AI research as PhD candidates but not pursuing an academic career, starting companies and/or joining forces with established ones, all with a burning drive to make a big practical impact on the work and lives of as many people as possible.
“I always liked math and languages” says Socher. “Math is beautiful, abstract, it might be true in a thousand light years. Language is the most interesting manifestation of human intelligence, it’s what makes us most unique in the Animal Kingdom. Those two are best combined in linguistic computer science.”
Deep Learning, Not AI, Most Effective Term in Job Listings
Textio: These phrases appear to be following the pattern of big data before them. As AI language has become more common in job ads, the less interesting it has become to potential job applicants. No surprise: when everyone is using the same language, no one stands out…
Textio looked at a bunch of tech terms that appear to be trending based on their recent usage growth. While all of these phrases still occur much less often than AI or ML, they’re all on the rise in a statistically unexpected way…
Enjoy your 15 minutes of fame, chatbots. Everyone knows what happens next.
Posted in AI, deep learning
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Deep Learning Drives Great Progress in Online Translations
Recent translation from Italian to English on Facebook:
The Flea market of square has no longer existed for a few years in its original place in square square. It has been moved against the will and protests of the owners of the stands, in in, cemetificato, less central and assolatissimo. It seemed that the city couldn’t wait for a minute so much was the rush that had to “retrain the area” (and I still didn’t understand what to do next). About two years after eviction (month plus, month less), space remains boarded, covered with weeds and holes, with a digger in between. A space like this is waiting for him in Mosul. Not in the middle of Florence. He follows pictures, as soon as the sun sets and me me on the outside.
Facebook recently switched its backend translation systems entirely to neural networks, which handle more than 2,000 translation directions and 4.5 billion translations every day. They say that these translations are more accurate than Facebook’s previous system, which used phrase-based machine translation models.
Sources: SiliconAngle, Facebook
Imperial College London professor Erol Gelenbe says artificial neural networks can ease language translation by executing a three-step process. The process includes word translations, syntax mapping, and contextual translation, which Gelenbe, recipient of the 2008 ACM SIGMETRICS Achievement Award, says the neural networks can achieve by storing and matching patterns. A key element of the translation process is long short-term memories (LSTMs), which support machine learning and can learn from experience. Swiss Dalle Molle Institute for Artificial Intelligence president Jurgen Schmidhuber expects LSTM recurrent neural networks to eventually enable “end-to-end video-based speech recognition and translation, including lip-reading and face animation.” Meanwhile, Google Brain recently announced its researchers are using neural networks to improve speech-to-text translation. Microsoft Research’s Rick Rashid says the creation and deployment of deep-learning neural networks by his company’s researchers has significantly reduced word error rates in transcribed translations, which he notes could be useful to international business dealings, and have a major effect on cross-industry learning.
Source: ITpro
Posted in deep learning
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Mobile Becomes AI
…Microsoft Form 10K 2017: Vision: “Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).”
……# Mentions AI or artificial intelligence: 7
…Microsoft Form 10K 2016: Vision: “Our strategy is to build best-in-class platforms and productivity services for a mobile-first, cloud-first world.”
……# Mentions AI or artificial intelligence: 0
Source: AI Import
Posted in AI
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AI will Eclipse Hadoop, Says Forrester
When you start a revolution, you need to go public before the next revolution starts. Hadoop used to be the “revolutionary” technology behind the “big data” revolution but it has now been buried deep by deep learning, at least as far as the tech hype is concerned. One Hadoop distribution vendor, Hortonworks, sensed the passing of the “revolution” baton early, and went public in 2014. “In a year or two we may look back at November 10, 2014 [the day it filed for IPO] as the beginning of the end of the Hadoop Bubble,” I wrote in The End of the Hadoop Bubble?
Digital Disruption: 5 Top Technologies
Digital disruption is the flip side of digital opportunity. Established companies and startups alike enlist new technologies in the fight to dislodge incumbents, protect entrenched positions, or re-invent entire industries and business activities.
To help business and IT executives evaluate emerging technologies and their potential impact on the digital transformation of their organizations, Forrester recently published “Top Technologies for Digital Predators, 2017,” a detailed analysis of 15 emerging technologies with a wide range of disruptive potential and time-to-impact. Here’s my summary description of the 5 technologies with the highest potential to create competitive advantage, change markets, or alter the business landscape altogether:
Intelligent Agents
AI solutions that can interact with their users, learn their behavior and understand their needs, and even make decisions on their behalf. Today’s prototypes include Amazon’s Alexa, Microsoft’s Cortana, Google Now and Google Home, and Apple’s Siri. The landscape for this emerging technology is expanding rapidly to include a wide range of chatbots, virtual agents, robotic process automation, and other digital assistants. Personalized, high-quality experiences promise to increase customer loyalty and reduce customer attrition. As minders of internal processes, Intelligent Agents also promise to reduce costs, improve productivity and optimize all types of business activities. Example of current use: Artificial Intelligence From Salesforce Partner DigitalGenius To Boost KLM Customer Service.
Read the rest of the article at Forbes.com