Source: factorynet.at The partners in the “Rob-aKademI” research project, including the Fraunhofer IPA and the Institute for Industrial Manufacturing and Factory Operation IFF at the University of Stuttgart, are developing technologies that are intended to simplify robot programming for assembly tasks and automate them more. The basis for this is a purely digital image, i.e. a Read More
Tag: Reinforcement Learning
Source: analyticsinsight.net Developments in machine learning are significantly supporting QA Testing and Software Development process The advent of DevOps paves way for businesses to actively look for real-time risk assessment backed by machine learning algorithms throughout the various stages of the software delivery cycle. QA engineers face a plethora of difficulties in the juggle to find out Read More
Source: techspot.com Machine learning (ML) has become a hot topic in the last few years, but what you may not realize is that the concept of machine learning has been around for decades. The design of machine-learning systems used to this day is based on the human brain model described by Donald Hebb in 1949 in his Read More
Source: enterpriseai.news Autonomous vehicles are developed with a wide range of self-driving capabilities. Some vehicles provide basic automation, like cruise control and blind-spot detection, while other vehicles are reaching fully-autonomous capabilities. Many of these capabilities are being made possible by AI technology. However, before talking about big scale deployments for smart city transportation, more work is Read More
Source: analyticsinsight.net Artificial Intelligence (AI) environment has risen from data scientists to reach the boardroom as a pre-curser to digital transformation. Clayton Christensen, author of The Innovator’s Dilemma, a disruptive technology adds to the premise writing AI “enables new markets to emerge” to disrupts an existing market status-quo. The adoption path of AI needs a Read More
Source: techxplore.com For all the advances enabled by artificial intelligence, from speech recognition to self-driving cars, AI systems consume a lot of power and can generate high volumes of climate-changing carbon emissions. A study last year found that training an off-the-shelf AI language-processing system produced 1,400 pounds of emissions—about the amount produced by flying one Read More
Source: syncedreview.com Reinforcement Learning (RL) agents seem to get smarter and more powerful every day. But while it is relatively easy to compare a given agent’s performance against other agents or human experts for example in video gameplay, it is more difficult to objectively evaluate RL agents’ robustness and their all-important ability to generalize to Read More
Source: insidebigdata.com There’s no doubt that artificial intelligence continues to be swiftly adopted by companies worldwide. In just the last few years, most companies that were evaluating or experimenting with AI are now using it in production deployments. When organizations adopt analytic technologies like AI and machine learning (ML), it naturally prompts them to start Read More
Source: venturebeat.com In a preprint paper this week published on Arxiv.org, researchers at Intel describe Sample Factory, a system that achieves high throughput — higher than 105 environment frames per second — in reinforcement learning experiments. In contrast to the distributed servers and hardware setups those experiments typically require, Sample Factory is optimized for single-machine settings, enabling researchers to achieve Read More
Source: itbrief.com.au Smarter, faster AI, augmented data management and ‘X analytics’ are amongst the top technology trends for 2020, according to new analysis from Gartner. The analytics firm has released its top 10 data and analytics technology trends for 2020 that it says can help organisations prepare for a post-pandemic reset. “To innovate their way Read More
Source: which-50.com Technology research group Gartner has identified its top 10 data and analytics (D&A) technology trends to help organisations prepare for a post-pandemic reset. According to Rita Sallam, distinguished research vice president at Gartner, “To innovate their way beyond COVID-19, data and analytics leaders require an ever-increasing speed and scale of analysis in terms of Read More
Source: analyticsinsight.net Looking at quantum computing-fueled applications of the future, we much of the time look to the innovation’s capability to take care of computationally-intensive mathematical problems, which could lead to breakthroughs in drug discovery, logistics, cryptography, and finance. A research paper by Bernhard Dieber and different scholastics entitled Quantum Computation in Robotic Science and Applications, Read More
Source: umiacs.umd.edu A graduate student in the Computational Linguistics and Information Processing (CLIP) Laboratory has received funding from Microsoft Research that will support his work in reinforcement learning and machine learning. Kianté Brantley, a fourth-year doctoral student in computer science, is one of only 10 graduate students in North America to receive a $25,000 Microsoft Research Dissertation Grant(link Read More
Source: dpaonthenet.net Robots capable of the sophisticated motions that define advanced physical actions like walking, jumping, and navigating terrain can cost $50,000 or more, making real-world experimentation prohibitively expensive for many. Now, a collaborative team at the NYU Tandon School of Engineering and the Max Planck Institute for Intelligent Systems (MPI-IS) in Tübingen and Stuttgart, Read More
Source: yourstory.com AI is fast progressing in every field like healthcare, manufacturing, law, finance, retail, real estate, accountancy, digital marketing. Every field is being computational and becoming more advanced with some remarkable capabilities emerging these past years. Artificial Intelligence is reshaping the economy and career landscape with a wide range of diverse patterns from autonomous Read More
Source: venturebeat.com A team of researchers at Nanyang Technological University in Singapore claim deep reinforcement learning (DRL) algorithms — algorithms that have been used to predict the shapes of proteins and teach robots to grasp objects — are prone to adversarial attacks that can extract and replicate them, enabling malicious actors to “steal” them. In a preprint Read More
Source: venturebeat.com DeepMind, the Alphabet-backed machine learning lab that’s tackled chess, Go, Starcraft 2, Montezuma’s Revenge, and beyond, believes the board game Diplomacy could motivate a promising new direction in reinforcement learning research. In a paper published on the preprint server Arxiv.org, the firm’s researchers describe an AI system that achieves high scores in Diplomacy while yielding “consistent improvements.” AI Read More
Source: In a paper published this week on the preprint server Arxiv.org, scientists at Google, DeepMind, the Alan Turing Institute, and the University of Cambridge propose Performer, an AI model architecture that scales linearly and performs well on tasks like protein sequence modeling. They claim that it has the potential to impact research on biological sequence Read More
Source: analyticsindiamag.com If you are a data scientist and wish to kickstart your career, learn in-demand skills, and connect to some of the best minds of the data science industry, then AIM Mentoring Circle is the perfect platform for you. It has always been a challenging task for data scientists to find good mentors, who can assist you Read More
Source: insidebigdata.com Data science is largely an enigma to the enterprise. Although there’s an array of self-service options to automate its various processes, the actual work performed by data scientists (and how it’s achieved) is still a mystery to your average business user or C-level executive. Data modeling is the foundation of this discipline that’s Read More
Source: analyticsindiamag.com Reinforcement Learning has become the base approach in order to attain artificial general intelligence. The ICLR (International Conference on Learning Representations) is one of the major AI conferences that take place every year. With more than 600 interesting research papers, there are around 44 research papers in reinforcement learning that have been accepted in this year’s Read More
Source: techxplore.com A classification algorithm for relational data that is more accurate, as well as orders of magnitude more efficient than previous schemes, has been developed through a research collaboration between KAUST and Nortonlifelock Research Group in France. The new algorithm, which uses an approach called reinforcement learning, demonstrates the power of machining learning techniques in Read More
Source: fresnobserver.com Revenue inequality is among the overarching issues of economics. Some of the efficient instruments policymakers have to handle its taxation: governments acquire cash from folks in line with what they earn and redistribute it both immediately, by way of welfare schemes, or not directly, by utilizing it to pay for public initiatives. However, Read More
Source: eandt.theiet.org Artificial intelligence has become a well-recognised and frequently used buzzword. However, it means different things in different situations and as such can be tricky to define. Whilst most people think of AI as a technology in its own right, it’s actually more of a general term used to refer to a number of Read More
Source: allaboutcircuits.com Many of us are familiar with the concept of machine learning as it pertains to neural networks. But what about TinyML? Surging Interest in TinyML TinyML refers to the machine learning technologies on the tiniest of microprocessors using the least amount of power (usually in mW range and lower) while aiming for maximized results. With the proliferation Read More
Source: hedgeweek.com RL One is a long/short strategy that generates returns through deep reinforcement learning, a category of machine learning that reacts and learns from its environment by determining which decision will result in the highest risk/reward trade-off. The reinforcement learning model predicts optimal long or short exposure to the S&P 500 Index on a Read More
Source: analyticsindiamag.com At the present scenario, video games portray a crucial role when it comes to AI and ML model development and evaluation. This methodology has been around the corner for a few decades now. The custom-built Nimrod digital computer by Ferranti introduced in 1951 is the first known example of AI in gaming that used the game nim Read More
Source: techxplore.com The automatic operation and maintenance of optical network is important for ensuring information communication and network operation. The growing variety of services has forced operation and maintenance personnel to face tremendous operational pressure. A recent study has constructed a control architecture called intent defined optical networks (IDON) to cope with the issue. The Read More
Source: venturebeat.com In a paper published this week on the preprint server Arxiv.org, scientists at DeepMind introduce the idea of simple sensor intentions (SSIs), a way to reduce the knowledge needed to define rewards (functions describing how AI ought to behave) in reinforcement learning systems. They claim that SSIs can help to solve a range of complex robotic tasks Read More
Source: analyticsindiamag.com Recently, researchers at Alphabet’s DeepMind and the University of California, Berkeley proposed an AI framework for comparing child and AI agent behaviours and hence developing new exploration techniques. While developing a reinforcement learning agent, there are several questions related to the exploring behaviour that comes into the mind of researchers — how should an agent gather enough experience Read More