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Geoff Hinton And His Team File A Patent For Capsule Neural Networks

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"According to the filing, the inventors claimed that capsule networks can be used in place of conventional convolutional neural networks." Looks like Google won't be stopping its infamous patenting spree anytime soon. Earlier this month, Google filed a patent for capsule networks. Turing award recipient and Google researcher Geoff Hinton was named amongst the list of inventors in the filing. According to the patent filed, the inventors claimed that capsule networks can be used in place of conventional convolutional neural networks for traditional computer vision applications. Capsule networks are aimed at alleviating the extra dimensionality which surfaces with a convolutional neural network.


Google launches AI lip-sync challenge

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Google has launched a lip-sync challenge for anyone who cares to participate. Those interested can visit the site Google has set up and test their lip-synching skills. The challenge is being run by Google's AI Experiments group--the same group behind Google's Pixel device. The purpose of the challenge is to allow Google to use real singers to teach its AI system (which the company is calling simply LipSync by YouTube) how to read lips. Google hopes to use the AI system as part of an effort to develop applications for people with speaking disabilities such as ALS.


NLP Trends and Use Cases in 2020

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Natural Language Processing (NLP) is one of the most exciting fields of artificial intelligence that enables computers to understand human languages. NLP techniques are constantly evolving and promising applications are increasingly implemented by organizations to solve a wide range of problems. What exactly are companies using NLP for? What are exciting NLP techniques in a practical context and what are the challenges when applying them? We talked to thought leaders applying NLP in different industries about their favorite NLP techniques, the biggest trends, as well as opportunities and challenges of NLP in 2020.


Can we rely on machine intelligence to fix our climate?

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As more and more industries take on artificial intelligence to solve some of their biggest challenges, can machines help us understand and fix climate change issues? So your phone recognises your face, and your bank can block any transaction unlike your spending habits. And your online supermarket nudges you with their vegan products just because you've bought that oat milk once, while your online movie platform keeps throwing B-movies at you after you watched that soap opera last month. A growing number of our devices and services are relying on artificial intelligence (AI), a technology that continues to branch out and pop up in more and more areas of our lives. Scientists, entrepreneurs, and governments are leveraging AI to explore solutions for some of society's biggest challenges.


AI's Latest Breakthrough Will Transform Learning--Here Are 5 Ways

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The Fourth Industrial Revolution just took a huge step forward, thanks to a breakthrough artificial intelligence (AI) model that can learn virtually anything about the world -- and produce the content to tell us about it. The AI program is GPT-3 by OpenAI, which started out as a language model to predict the next word in a sentence and has vastly exceeded that capability. Now, drawing from voluminous data -- essentially all of Wikipedia, links from Reddit, and other Internet content -- GPT-3 has shown it can also compose text that is virtually indistinguishable from human-generated content. Asger Alstrup Palm, Area9's chief technology officer, explained that GPT-3 was tasked with testing the "scaling hypothesis" -- to see if a bigger model with ever-increasing amounts of information would lead to better performance. Although it's too early to call the scaling hypothesis proven, there are some strong indications that this is, indeed, the case. Further validating the potential of GPT-3, Microsoft recently announced it will exclusively license the model from OpenAI, with the intention of developing and delivering AI solutions for customers and creating new solutions using natural language generation.


Breakthrough in safety-critical machine learning could be just the beginning

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Safety is the central focus on driverless vehicle systems development. Artificial intelligence (AI) is coming at us fast. It's being used in the apps and services we plug into daily without us really noticing, whether it's a personalized ad on Facebook, or Google recommending how you sign off your email. If these applications fail, it may result in some irritation to the user in the worst case. But we are increasingly entrusting AI and machine learning to safety-critical applications, where system failure results in a lot more than a slight UX issue.


Top 12 Data Science Skills to Learn in 2020

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"We're entering a new world in which data may be more important than software." If you want to stay competitive in this rapidly evolving domain, you need to regularly update your skills with the latest changes. In the following section, we will share the top Data Science skills that not only a practicing Data Scientist would benefit from, but also anyone who's passionate about working his way around large volumes of data. If you code anything at all, we're sure you must've heard about GitHub. GitHub is among the most commonly used tools by the developers today after Stack Overflow.


5 Companies Using AI to Generate Creative Advertisement Content

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Advertisements are a front runner in marketing. Consumers get a hint of the product range of a company and its features mostly through advertisement strategy. It plays a vital role in improving the sales of products. Starting from choosing models to picking a shooting location and affording to the cameramen, and machinery used for the process, advertisements come with a lofty sum of money spent. It is not normal for an MSME to spend a lot on such video ads.


The Complete Neural Networks Bootcamp: Theory, Applications

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In this section, we will introduce the deep learning framework we'll be using through this course, which is PyTorch. We will show you how to install it, how it works and why it's special, and then we will code some PyTorch tensors and show you some operations on tensors, as well as show you Autograd in code!


3 Things You Need to Know About Deep Learning

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Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Deep learning is getting lots of attention lately and for good reason. It's achieving results that were not possible before.