Neural Networks


Computer Vision / Machine Learning Engineer

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We have the largest annotated dataset for the construction industry ever assembled with all of its real world attributes: dirty, unexplored, and rich. This role is for you if you want hands-on experience with ML on image, speech, and video data. We are looking for someone excited to design, train, apply and evaluate the latest deep learning models on customer data within our cloud based research and production environments. The goal is to generate an automated assessment of job site safety risks and feed the data to a predictive pipeline that will help our clients better manage their workforce and ultimately save lives. Most of our programming is done in Python3 using AWS resources.


Computing students seek out applications of AI - BCIT News

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"Generative adversarial network" and "deep convolutional neural network": the terms sound daunting, but behind them lies potential for AI to positively impact human lives. The BCIT class of 2019 Artificial Intelligence and Machine Learning (AIML) Option students in the Computer Systems Technology Diploma program recently wrapped a year of specialty study with their project demos. Led by Option Head Dr. Chi En Huang, students took on public datasets from the City of Vancouver Open Data Portal, and chose an angle to tackle with AIML. They were tasked with developing a machine learning solution that could use the various datasets to answer questions, create meaning, form insights, and inspire action. "Defining a use case is the first step in a project like this, maybe also the hardest. That is, what can we try to gain from this data?"


All-in-one chips seen boosting computer power for artificial intelligence needs

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Researchers at the Technion-Israel Institute of Technology and Israeli chipmaker TowerJazz said they have developed a "revolutionary" technology that transforms a commercial flash memory chip into a device that contains both memory and computing ability. This will help provide the computing power needed for artificial intelligence-based applications, the researchers said. The new device enables the creation of a "hardware neural network" inspired by the operation of the human brain, and will "significantly" accelerate the operation of AI-based computing, the Technion said in a statement. Get The Start-Up Israel's Daily Start-Up by email and never miss our top stories Free Sign Up "We have made a big jump forward" with just a small change, Prof. Shahar Kvatinsky of the Andrew & Erna Viterbi Faculty of Electrical Engineering at the Technion, who led the project, said in a phone interview. "We have taken an existing commercial technology and made a small change, transforming it into something that is very much needed."


RPA & AI (UiPath and Machine Learning)

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Robotics Process Automation (RPA) is a technology that helps you in automating your business process. It is a technology which mimic human actions in interacting with digital system. To understand what's RPA in a more intuitive way: What can RPA do for you? UiPath is one of the top leaders which develops Robotics Process Automation platforms. By deploying RPA into your business process, it helps your business in reducing operation cost, eliminate human error and saving time.


How Deep Learning is Transforming the Insurance Industry - Appen

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Fraud detection is another important application for machine learning in insurance. With the amount of payment channels on the rise leading to rapid growth in the number of overall transactions occurring worldwide, machine learning algorithms are used to develop automated fraud screening systems that are faster and more accurate than systems that rely on transaction rules combined with human reviews. Machine learning distinguishes between normal and fraudulent behavior, and adapts over time based on variations of fraud patterns in the data. This is the true power of machine learning as compared to traditional analytics methods -- the ability to detect types of fraud that are similar but not identical to existing patterns, as well as the ability to spot completely new types of fraud altogether.


How Deep Learning is Transforming the Insurance Industry - Appen

#artificialintelligence

Fraud detection is another important application for machine learning in insurance. With the amount of payment channels on the rise leading to rapid growth in the number of overall transactions occurring worldwide, machine learning algorithms are used to develop automated fraud screening systems that are faster and more accurate than systems that rely on transaction rules combined with human reviews. Machine learning distinguishes between normal and fraudulent behavior, and adapts over time based on variations of fraud patterns in the data. This is the true power of machine learning as compared to traditional analytics methods -- the ability to detect types of fraud that are similar but not identical to existing patterns, as well as the ability to spot completely new types of fraud altogether.


Artificial Intelligence - How AI Took Over Our Lives in the 2010s

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Bots are a lot like humans: Some are cute. Some are annoying ... and a little racist. Bots serve their creators and society as helpers, spies, educators, servants, lab technicians, and artists. In the 2010s, automation got better, cheaper, and way less avoidable. That means driving directions are more reliable, instant translations are almost good enough, and everyone gets to be an adequate portrait photographer, all powered by artificial intelligence.


Nvidia researchers create AI renderer to create 3D from 2D

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Nvidia researchers have published a paper describing a rendering framework that can produce 3D objects from 2D images. Not only that, due to the power of machine learning and AI, the tech does a good job of predicting the correct shape, colour, texture and lighting of the real-life 3D objects. The research could have important impacts in machine vision with depth perception, for robotics, self driving cars, and more. The full research paper, typically dryly entitled Learning to Predict 3D Objects with an Interpolation-Based Renderer, is available as a PDF by clicking the link. A new rendering framework called DIB-R, a differentiable interpolation-based renderer, is the main topic of the paper.


Artificial intelligence boosts MRI detection of ADHD

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IMAGE: Schematic diagram of the proposed multichannel deep neural network model analyzing multiscale functional brain connectome for a classification task. OAK BROOK, Ill. - Deep learning, a type of artificial intelligence, can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD), according to a study published in Radiology: Artificial Intelligence. Researchers said the approach could also have applications for other neurological conditions. The human brain is a complex set of networks. Advances in functional MRI, a type of imaging that measures brain activity by detecting changes in blood flow, have helped with the mapping of connections within and between brain networks.


Do We Need A Theory of AI?

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What would a theory of artificial intelligence look like, and how might it be achieved? When designing a new engine or airplane wing, engineers can apply theories that have withstood years of scientific scrutiny, such as the Laws of Thermodynamics or Newton's Laws of Motion. To what theories --if any --can artificial intelligence (AI) researchers and technology pioneers turn when designing neural networks or algorithms? We asked experts from the fields of computer science, theoretical physics, and philosophy for their insights. The Encyclopedia Britannia defines a scientific theory as a "systematic ideational structure of broad scope, conceived by the human imagination, that encompasses a family of empirical (experiential) laws regarding regularities existing in objects and events, both observed and posited."