Source: viterbischool.usc.edu Drones, specifically quadcopters, are an adaptable lot. They’ve been used to assess damage after disasters, deliver ropes and life-jackets in areas too dangerous for ground-based rescuers, survey buildings on fire and deliver medical specimens. But to achieve their full potential, they have to be tough. In the real world, drones are forced to Read More
Category: Reinforcement Learning
Reinforcement Learning
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Source: spectrum.ieee.org A version of this article was originally published on Medium. The views expressed here are solely those of the authors and do not represent positions of IEEE Spectrum or the IEEE. We here at Skydio have been developing and deploying machine learning systems for years due to their ability to scale and improve Read More
Source: newsdio.com In 1997, Hiroaki Kitano, a research scientist at Sony, helped organize the first Robocup, a robot soccer tournament that attracted teams of robotics and artificial intelligence researchers to compete in the picturesque city of Nagoya, Japan. At the beginning of the first day, two teams of robots took the field. While the machines Read More
Source: analyticsindiamag.com A team at NYU and Modl.ai have posited in their recent work, that simple image processing techniques (listed below) can improve the generalisation in deep reinforcement learning systems. RL systems are typically trained on gaming platforms which are test beds for teaching agents new tasks through visual cues. By exploiting the field of views of Read More
Source: venturebeat.com In reinforcement learning, the goal generally is to spur an AI-driven agent to complete tasks via systems of rewards. This is achieved either by learning a mapping (a policy) from states to actions that maximize an expected return (policy gradients), or by inferring such a mapping by calculating the expected return for a given Read More
Source: e27.co CEOs are confronted daily with the speed of technology evolution, under pressure to transform organisations to ensure they stay competitive, relevant and prepared for the next wave of change. Business leaders are also challenged to be informed about new technology and resources and to determine the best for their organisations. All while also Read More
Source: techannouncer.com Artificial intelligence, or AI, has undoubtedly been the 2019 buzzword in financial services. While not new – the term “artificial intelligence” was coined in 1956 – AI is seemingly becoming the future of everything. The hype around its potential is certainly justified economically. According to a recent report by Autonomous Next, the cost Read More
Source: syncedreview.com “Generalization” is an AI buzzword these days for good reason: most scientists would love to see the models they’re training in simulations and video game environments evolve and expand to take on meaningful real-world challenges — for example in safety, conservation, medicine, etc. One concerned research area is deep reinforcement learning (DRL), which Read More
Source: newswise.com Newswise — The future of commuter traffic probably looks something like this: ride-hailing companies operating fleets of autonomous electric vehicles alongside an increasing number of semi-autonomous EVs co-piloted by humans, all supported by a large infrastructure of charging stations. This scenario is particularly likely in California, which has committed to reducing carbon emissions Read More
Source: crn.in Modern day enterprises need to be very agile and efficient in order to succeed in today’s hyper-competitive business markets. Manufacturing is no different. Technology has revolutionised how manufacturing is done and new advances in technology are continuing to make their way in high-tech manufacturing industries in 2020 and beyond. Particular sets of technologies Read More
Source: edgy.app A team of researchers has developed a predictive touch response mechanism for enhanced human-to-machine Interaction. Experts have predicted that the next phase of IoT could be Tactile Internet. So, humans will be able to interact with a remote or virtual object and experience realistic haptic feedback. Now a team of researchers led by Elaine Wong at the University of Melbourne has brought us Read More
Source: eurekalert.org Imagine that you met a charming girl in school. She is an excellent student who concerns about the world welfare and is anti-war and anti-nuclear. Which do you think she is most likely to become in the future, a bank counter clerk, or, a bank counter clerk and feminist? Surveys show that most Read More
Source: analyticsinsight.net We usually hear a lot about human-level AI or artificial intelligence but little do we realize that the human mind and AI are actually quite interlinked. The brain’s neural network and artificial neural network possess some similarities between themselves. Both are trained on data, while the brain learns from real-life data and experiences Read More
Source:bdtechtalks.com Two separate studies, one by UK-based artificial intelligence lab DeepMind and the other by researchers in Germany and Greece, display the fascinating relations between AI and neuroscience. As most scientists will tell you, we are still decades away from building artificial general intelligence, machines that can solve problems as efficiently as humans. On the path to Read More
Source: techxplore.com A team of researchers from DeepMind, University College and Harvard University has found that lessons learned in applying learning techniques to AI systems may help explain how reward pathways work in the brain. In their paper published in the journal Nature, the group describes comparing distributional reinforcement learning in a computer with dopamine processing Read More
Source: independent.co.uk An artificial intelligence learning technique has been used to make a breakthrough in understanding several previously unexplained features of the human brain Researchers at Google-owned DeepMind discovered that a recent development in computer science regarding reinforcement learning could be applied to how the brain’s dopamine system works. The research, published in the scientific journal Nature, has implications for Read More
Source: oreilly.com Roger Magoulas recently sat down with Edward Jezierski, reinforcement learning AI principal program manager at Microsoft, to talk about reinforcement learning (RL). They discuss why RL’s role in AI is so important, challenges of applying RL in a business environment, and how to approach ethical and responsible use questions. Here are some highlights Read More
Source: towardsdatascience.com Machine learning is a powerful concept of finding patterns from data. However, if you have tried building a machine model from scratch, you should be aware of the challenges involved in designing a scalable machine learning workflow. Labeling, training, and fine-tuning parameters are all time-consuming activities involved in building a machine learning model Read More
Source: infoq.com Uber AI open-sourced their plug-and-play language model (PPLM) which can control the topic and sentiment of AI-generated text. The model’s output is evaluated by human judges as achieving 36% better topic accuracy compared to the baseline GPT-2 model. The team provided a full description of the system and experiments in a paper published Read More
Source: unite.ai Over the past few months, Microsoft and other companies researching machine learning challenged teams of AI developers to create an AI system that could play Minecraft and find a diamond within the game. As reported by the BBC, while AI platforms have managed to dominate chess and go, but it has struggled to master a task Read More
Source: forbes.com This year, we have seen all the hype around AI Deep Learning. With recent innovations, deep learning demonstrated its usefulness in performing tasks such as image recognition, voice recognition, price forecasting, across many industries. It’s easy to overestimate deep learning’s capabilities and pretend it’s the magic bullet that will allow AI to obtain General Intelligence. In truth, we are Read More
Source: venturebeat.com Former Google CEO Eric Schmidt urged cooperation with Chinese scientists, warned against the threat of misinformation, and advised against overregulation by governments today in a broad-ranging speech about AI ethics and regulation of big tech companies. He also talked about conflict deterrence between nation-states in the age of AI and pondered how secretaries Read More
Source: eurekalert.org As a source of inspiration, aquatic creatures such as fish, cetaceans, and jellyfish could inspire innovative designs to improve the ways that manmade systems operate in and interact with aquatic environments. Jellyfishes in nature propel themselves through their surroundings by radially expanding and contracting their bell-shaped bodies to push water behind them, which Read More
Source: thevistek.com There is a vast number of products sold online through various outlets all over the world. distinguishing, matching and cross-checking product for functions like worth comparison becomes a challenge as there aren’t any international distinctive identifiers. There are several things wherever accurately distinguishing a product match is crucial. as an example, stores might Read More
Source:techxplore.com Since its invention by a Hungarian architect in 1974, the Rubik’s Cube has furrowed the brows of many who have tried to solve it, but the 3-D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine. DeepCubeA, a deep reinforcement learning algorithm programmed by Read More
Source:- hbr.org Last year, U.S. companies spent roughly $90 billion on learning and development efforts, a sum higher than the gross domestic product of 130 countries. In 2018, the average American employee received training at a cost close to $1,000 per person. On its own that might not sound like much, but to put those numbers into perspective: for Read More
Source:- forbes.com Machine learning is one of the cornerstones of artificial intelligence. If systems can’t learn, they can’t adapt or apply knowledge from one domain to another. And yet, machine learning is just a component of the overall goals of AI. Beyond machine learning, we still need ways to interact with the external environment, reason about Read More
Source:- analyticsindiamag.com 1| Natural Language Processing About: This online course covers from the basic to advanced NLP and it is a part of the Advanced Machine Learning Specialisation from Coursera. You can enroll this course for free where you will learn about sentiment analysis, summarization, dialogue state tracking, etc. The topics you will learn such as introduction to Read More
Source:- bdtechtalks.com This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding artificial intelligence. Today, artificial intelligence programs can recognize faces and objects in photos and videos, transcribe audio in real-time, detect cancer in x-ray scans years in advance, and compete with humans in some of the Read More
Source:- towardsdatascience.com Generally, in machine learning, we want to put similar things in similar places. This rule is universal to all of machine learning, be it supervised, unsupervised, classification, regression. The question is, how do we exactly determine what is similar? In order to shed light on the matter, we are going to start with the Read More