Source: insights.dice.com Amazon’s new tool, CodeGuru, leverages machine learning to streamline the code-review process. But will it actually interest developers? CodeGuru features two components: a “Reviewer” that uses machine learning to scan code for bugs, and a “Profiler” that highlights latency and CPU utilization issues. Profiler will also produce an “estimated dollar value” for the active CPU costs of an issue, allowing Read More
Tag: Machine learning
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Source: Machine learning had a rich history long before deep learning reached fever pitch. Researchers and vendors were using machine learning algorithms to develop a variety of models for improving statistics, recognizing speech, predicting risk and other applications. While many of the machine learning algorithms developed over the decades are still in use today, deep learning — Read More
Source: healthitanalytics.com June 30, 2020 – An artificial intelligence algorithm can analyze electroencephalograph (EEG) electrodes to detect a seizure and accurately pinpoint its location, according to a study published in Scientific Reports. The researchers stated that epilepsy is one of the most common central nervous system disorders, with nearly four percent of people across different ages diagnosed with epilepsy during Read More
Source: analyticsinsight.net Machine learning-based personalization has gained traction over the years due to volume in the amount of data across sources and the velocity at which consumers and organizations generate new data. Traditional ways of personalization focused on deriving business rules using techniques like segmentation, which often did not address a customer uniquely. Recent progress Read More
Source: siliconangle.com Amazon Web Services Inc. said today its new Amazon CodeGuru service, which relies on machine learning to automatically check code for bugs and suggest fixes, is now generally available. Amazon announced the tool in preview at its AWS re:Invent event in December. “It’s challenging to have enough experienced developers with enough free time to do code reviews, Read More
Source: techrepublic.com Differential privacy has become an integral way for data scientists to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual’s data to be distinguished or re-identified. To help more researchers with their work, IBM released the open-source Differential Privacy Library. The library “boasts a suite 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: techxplore.com Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), Lawrence Livermore National Laboratory (LLNL) scientists reported. In a paper published by the Proceedings of the National Academy of Read More
Source: analyticsinsight.net Today as the competition is at surge among tech organizations, agile principles and priorities are employed for greater productivity. Most of them could be leveraged for data science (DS) projects. Moreover, data scientists do not know how to schedule the project because it is impossible to determine a specific timeline for the type of “research” Read More
Source: indiaeducationdiary.in Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future wireless systems. The Machine Learning for Wireless Networking Systems (MLWiNS) program is the latest in a series of joint efforts between the two partners to support research that accelerates innovation with the Read More
Source: eos.org Future telescopes like the James Webb Space Telescope (JWST) and the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) are designed to sample the chemistry of exoplanet atmospheres. Ten years from now, spectra of alien skies will be coming in by the hundreds, and the data will be of a higher quality than is currently Read More
Source:aithority.com Blue Ridge announced enhancements to its suite of next-gen cloud-based Price Optimization solutions, which leverage machine learning to quickly identify opportunities and simulate pricing strategies for peak margin, profits, revenues and sales. The pricing suite supports end-to-end pricing transformations, a strategy proven to minimize disruption and drive significant earnings expansion for distributors and retailers. Blue Ridge’s Price Optimization Read More
Source: scitechdaily.com Artificial intelligence and machine learning technologies are poised to supercharge productivity in the knowledge economy, transforming the future of work. But they’re far from perfect. Machine learning (ML) – technology in which algorithms “learn” from existing patterns in data to conduct statistically driven predictions and facilitate decisions – has been found in multiple Read More
Source: enterprisetalk.com AI is different as it decides for itself and that is not always necessary in most business cases. A CIO would not want the AI system to be taking crucial decisions related to finances, product management, recruiting, or network planning. AI system should be implemented focused on analytics and anomaly detection CIOs should Read More
Source: zdnet.com Models require algorithms and data, and when it comes to data, machine learning models have especially ravenous appetites. Yet, when it comes to transforming data into features consumed by the model, data scientists often have to reinvent the wheel as feature generation lacks the configuration management and automation processes associated with model workflows. Read More
Source: demand-planning.com But there’s a balance between not enough data and too much. What’s the right amount of data to work with as demand planner or data scientist? There is a debate about how much data is enough and how much data is too much. According to some, the rule of thumb is to think Read More
Source: bdtechtalks.com In the last few months, millions of dollars have been stolen from unemployment systems during this time of immense pressure due to coronavirus-related claims. A skilled ring of international fraudsters has been submitting false unemployment claims for individuals that still have steady work. The attackers use previously acquired Personally Identifiable Information (PII) such Read More
Source: analyticsinsight.net Having knowledge is not enough to survive, for survival, and for assured victory, one needs to test his/her capabilities. To test wisdom and capabilities, competitions are extremely beneficial. In the case of data science, data scientists mostly work theoretically and get rare chance to experiment with real-world data themselves. With data science competitions Read More
Source: techxplore.com Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), Lawrence Livermore National Laboratory (LLNL) scientists reported. In a paper published by the Proceedings of the National Academy of Read More
Source: securitytoday.com The following was issued as a joint release from the MIT AgeLab and Toyota Collaborative Safety Research Center. How can we train self-driving vehicles to have a deeper awareness of the world around them? Can computers learn from past experiences to recognize future patterns that can help them safely navigate new and unpredictable 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: swisscognitive.ch Organizations in a growing range of industries rely on machine learning solutions—and in turn their underlying algorithms—to carry out extensive analysis. Their ability to resolve business issues and work in tandem with human knowledge means there has been a high uptake for machine learning technology. But in-built and untraceable bias in the algorithms used in some applications Read More
Source: aithority.com In late 2015, NLP Logix Lead Data Scientist, Matt Berseth, entered the company into the Camelyon16 Grand Challenge. The Camelyon16 was a challenge for the medical and computer science communities to come together to train a computer to identify breast cancer tumors, at a level at or above the highest trained pathologists in the Read More
Source: analyticsindiamag.com Today most large companies are looking at the potential of AI/ML, and despite significant investments, hiring data scientists and investing time and money, data science fails to take things to the next level. One of the biggest challenges present in AI/ML is that a large majority of models are not deployed in production. Read More
Source: healthitanalytics.com June 16, 2020 – A clinical decision support system that leverages machine learning techniques could help patients control their glucose levels and enhance type 1 diabetes management, according to a study published in Nature Metabolism. People with type 1 diabetes do not produce their own insulin, so they have to take it continuously throughout the day using an Read More
Source: analyticsinsight.net Cognitive computing typically refers to simulate human intelligence to enable computers to understand data and derive insights, all through the use of AI and machine learning. Applications of cognitive computing are enormous giving computers the human-like brain to compute data at fast. As a collection of algorithmic capabilities, the technology strengthens employee performance, Read More
Source: techradar.com The time for experiments is over: Artificial Intelligence (AI) solutions are ready for the enterprise. Already, the early adopters are reaping the rewards and moving from trials to large-scale adoption. The chief executives of these companies are confident that – within just two years – AI deployments will deliver around 30% of both their new Read More
Source: bestgamingpro.com Corporations throughout industries are exploring and implementing artificial intelligence (AI) tasks, from huge knowledge to robotics, to automate enterprise processes, enhance buyer expertise, and innovate product growth. Based on McKinsey, “embracing AI guarantees appreciable advantages for companies and economies by way of its contributions to productiveness and development.” However with that promise comes challenges. Computer systems Read More
Source: iotforall.com Unless you’re an expert, there’s little difference between the Internet of Things (IoT) and the Internet of Everything (IoE). However, the latter term is broader, semantically. In this post, we’ll go into the details to explain why IoT software development companies use the term IoE comparatively rarely. The Difference The term IoT was Read More
Source: dqindia.com Microsoft and Udacity have announced a collaboration to confer scholarships for its all-new Machine Learning Nanodegree program in Microsoft Azure. The new Udacity Machine Learning Scholarship Program for Microsoft Azure represents the first of several programs from Udacity and Microsoft to deliver training for Azure cloud services. The scholarship will be conferred in Read More