- Consumer-facing businesses use cognitive tools to tease out key behavioral patterns to reach customers in the right ways and over the right channels.
- By using cognitive tools to improve their search capabilities, customer care and workflow management, business leaders are accelerating productivity and efficiency.
- Cognitive technology is helping defense and other intelligence organizations track an unprecedented variety of data to detect signals, protect the public, and direct intelligence resources more effectively.
- Professional services firms and insurers are employing cognitive solutions to improve sampling and modeling, which is helping them improve client and risk outcomes.
- Contact centers have turned to cognitive technology to provide more efficient and personalized customer service.
By becoming a cognitive business, early adopters have been able to evolve customer acquisition, increase customer engagement, and improve customer service.
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- It’s in this context of convergence that we present Forcepoint’s Security Predictions for 2017.
- RISE OF THE CORPORATE INCENTIVIZED INSIDER THREAT
- In preparing the report, the persistent and compelling theme that kept surfacing as we identified our security predictions for 2017 was that of convergence.
- The following highlights a few of this year’s 10 predictions
- The rise of voice-activated AI to access Web, data and apps will open up creative new attack vectors and data privacy concerns.
Conventional thinking divides the digital and physical worlds into two distinct and separate realms. But is that still true?
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- The repository provides code, exercises and solutions for popular Reinforcement Learning algorithms.
- All code is written in Python 3 and uses RL environments from OpenAI Gym .
- Exercises and Solutions to accompany Sutton’s Book and David Silver’s course.
- Latest commit f117e5d Nov 27, 2016 dennybritz committed on GitHub Merge pull request #36 from alvarosg/bug-epsilons-total-t
- In addition to exercises and solution, each folder also contains a list of learning goals, a brief concept summary, and links to the relevant readings.
reinforcement-learning – Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton’s Book and David Silver’s course.
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- What’s your AI IQ?
- What’s your AI IQ?
- 2016 salesforce.com, inc.
- All rights reserved
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- NVIDIA helps the US build an AI for cancer research
- The AI will also automatically extract and study “millions” of patient records to understand how cancer spreads and reoccurs, and accelerate the simulation of protein interactions to see how they create the conditions for cancer.
- CANDLE will tackle three core problems.
- Microsoft isn’t the only big-name tech company using AI to fight cancer .
- The partners haven’t said when they expect CANDLE to be ready, and it could be a while after that happens before you see the practical results.
Microsoft isn’t the only big-name tech company using AI to fight cancer. NVIDIA is partnering with the US Department of Energy and the National Cancer Institute…
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- The software uses a deep-learning algorithm that was trained on two million unlabeled videos amounting to a year’s worth of screen time.
- Posted by Shane Hinshaw in categories: information science , robotics/AI , transportation
- The new software is claimed to be more accurate, by producing up to 32 frames per second and building out entire scenes in one go.
- The technology is still bare-bones, but could one day make for smarter self-driving cars that are better prepared for the unexpected, among other applications.
- Well, scientists at MIT have just trained machines to do the same thing, with artificial intelligence software that can take a single image and use it to to create a short video of the seconds that followed.
MIT’s deep-learning software produces videos of the future
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- DeepMind is using dreams in a parallel fashion, accelerating the rate at which an AI learns by focusing on the negative or challenging content of a situation within a game.
- A snapshot of the method published by the DeepMind researchers to enable AI “dreams”.
- You might ask why AI “dreams” are necessary given that robots can already dominate humans in most games such as Chess and Go.
- Google’s DeepMind AI gives robots the ability to dream
- One of the primary discoveries scientists made when seeking to understand the role of dreams from a neuroscientific perspective was that the content of dreams is primarily negative or threatening.
Thanks to Google’s DeepMind AI, Robots can now dream, significantly increasing the speed at which they can learn and ultimately …
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