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Ben-Gurion University Researchers Develop Machine Learning Platform to Streamline Clinical Trials

ben-gurion university researchers develop machine learning platform to streamline clinical trials

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BEER-SHEVA, Israel, Oct. 21, 2020 /PRNewswire/ — Researchers at Ben-Gurion University of the Negev (BGU) have developed a novel platform to streamline clinical trials, lower costs, and increase the efficiency and success rate of the drug or medical device development process. The technology has been licensed for further development and commercialization to Panacea, a new company founded by BGN Technologies, the technology transfer company of BGU, and Prof. Boaz Lerner of the BGU Department of Industrial Engineering and Management, and Panacea’s scientific founder. Panacea is a portfolio company of the Oazis accelerator, formed by the Yazamut360 entrepreneurship center of BGU.The new platform leverages machine learning to optimize a clinical trial’s chances of success, analyzing patient population recruitment and dropout rate, as well as identifying and prioritizing monitored markers. The technology offers efficient pre-trial recommendations, in-trial interim analysis, and post-trial insights in preparation for the next trial, as well as potential salvage in case of failure.”Clinical trials haven’t fundamentally changed in the past two decades,” said Prof. Lerner. “They are extremely costly, and the probability of success for new drugs is in the single digit. Therefore, our platform is highly beneficial for pharma and biotech companies, enabling them to increase efficiency …

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Researchers develop machine learning model that will support safe and accurate decision making for the Halifax Harbour

researchers develop machine learning model that will support safe and accurate decision making for the halifax harbour

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A Smart Buoy floating on the ocean. Credit: Dalhousie University

Researchers at Dalhousie and ocean data analytics innovation environment DeepSense have developed a machine learning method for predicting wind speed and wave height measurements. Such measurements support safe and more accurate decision making by the Halifax Port Authority and the Halifax Marine Pilots.

Results published in the Journal for Ocean Technology demonstrate how the team used data from smart buoys to provide predictions for use during periods of scheduled buoy maintenance and/or spontaneous sensor failures. These predictions will be valuable to the Port community in providing continuity of critical information used in the safe navigation of vessels within the Port of Halifax and the safe transfer of Halifax Marine Pilots between pilot boats and commercial vessels.
The DeepSense/SmartAtlantic project is a collaboration between the Center for Ocean Ventures and Entrepreneurship (COVE), DeepSense, the Halifax Port Authority (HPA) and the Canadian Marine Pilots’ Association (CMPA).
Based out of the Faculty of Computer Science with funding and support from the Atlantic Canada Opportunities Agency (ACOA), the Province of Nova Scotia, the Ocean Frontier Institute (OFI) and IBM, DeepSense drives growth in the ocean economy through artificial intelligence, machine learning and …

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Ivanti Adds New Ivanti Neurons Innovations Powered by Machine Learning

ivanti adds new ivanti neurons innovations powered by machine learning

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Ivanti Neurons for Patch Intelligence and Spend Intelligence Leverages Supervised and Unsupervised Machine Learning Algorithms to Automate Vulnerability Remediation and Optimize Software Spend
Ivanti, the company that automates IT and Security Operations to discover, manage, secure and service from cloud to edge, announces the release of Ivanti Neurons for Patch Intelligence and Ivanti Neurons for Spend Intelligence. These solutions build on the Ivanti Neurons hyper-automation platform, first announced in July 2020, which empowers organizations to autonomously self-heal and self-secure devices and self-service end users.
“The future of work, where working from anywhere on any device is the new normal, means that proactively managing the ever-increasing security risks and asset spend is top of mind for every enterprise,” said Nayaki Nayyar, executive vice president and chief product officer, Ivanti. “Our latest additions to the Ivanti Neurons Platform for Patch and Spend Intelligence leverage our strength in patching to assess patch reliability and risk-based patch prioritization using supervised and unsupervised machine learning algorithms to automate vulnerability remediation and proactively manage software spend.”
Recommended AI News: Newly-Renamed IDX Launches IDX Privacy, the First All-in-One Consumer Privacy Protection Product
Ivanti Neurons enables the self-healing autonomous edge with adaptive security and a contextualized, personalized experience for …

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Ivanti Adds New Ivanti Neurons Innovations Powered by Machine Learning to Improve Security Posture and Optimize Asset Spend

ivanti adds new ivanti neurons innovations powered by machine learning to improve security posture and optimize asset spend

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SALT LAKE CITY, Oct. 21, 2020 /PRNewswire/ — Ivanti, the company that automates IT and Security Operations to discover, manage, secure and service from cloud to edge, announces the release of Ivanti Neurons™ for Patch Intelligence and Ivanti Neurons™ for Spend Intelligence. These solutions build on the Ivanti Neurons hyper-automation platform, first announced in July 2020, which empowers organizations to autonomously self-heal and self-secure devices and self-service end users. 
“The future of work, where working from anywhere on any device is the new normal, means that proactively managing the ever-increasing security risks and asset spend is top of mind for every enterprise,” said Nayaki Nayyar, executive vice president and chief product officer, Ivanti. “Our latest additions to the Ivanti Neurons Platform for Patch and Spend Intelligence leverage our strength in patching to assess patch reliability and risk-based patch prioritization using supervised and unsupervised machine learning algorithms to automate vulnerability remediation and proactively manage software spend.”
Ivanti Neurons enables the self-healing autonomous edge with adaptive security and a contextualized, personalized experience for today’s remote workforce. Customers of Ivanti Neurons are realizing over 50 percent reductions in support call times, eliminating duplicate work between IT operations and security teams, reducing the number of vulnerable devices by …

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Artificial intelligence and machine learning algorithms to transform chatbots – Techiexpert.com

artificial intelligence and machine learning algorithms to transform chatbots – techiexpert.com

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The increasing technology has always been a saviour for us. Technology still provides us with solutions for existing problems. One of the answers offered by technology to a current issue is the chatbot. A chatbot is an artificial intelligence software. It helps to communicate with a user in natural language. It uses websites, message applications, mobile apps, or telephone to provide interaction.

Chatbots have influenced many marketers and many organizations. Everyone who needs interaction with a client prefers chatbots nowadays. Many brands are using these chatbots. Bots can interact with their clients very quickly. Trending technologies algorithms help to create chatbots with Machine learning algorithms. 

These chatbots are helping marketers to increase their sales. An increase in sales is because they provide perfect interaction with the customer. Chatbots can also help to increase profits, improve branding, and grow our business. Before, our customers used to wait for a long time to contact our customer service executive. But by using chatbots, we no more face this issue. Besides, these chatbots can also provide clients with solutions. One more advantage of the chatbot is that it works all day in a year. This advantage can help clients to use it any time …

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Translating lost languages using machine learning

translating lost languages using machine learning

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Recent research suggests that most languages that have ever existed are no longer spoken. Dozens of these dead languages are also considered to be lost, or “undeciphered” — that is, we don’t know enough about their grammar, vocabulary, or syntax to be able to actually understand their texts.

Lost languages are more than a mere academic curiosity; without them, we miss an entire body of knowledge about the people who spoke them. Unfortunately, most of them have such minimal records that scientists can’t decipher them by using machine-translation algorithms like Google Translate. Some don’t have a well-researched “relative” language to be compared to, and often lack traditional dividers like white space and punctuation. (To illustrate, imaginetryingtodecipheraforeignlanguagewrittenlikethis.)

However, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) recently made a major development in this area: a new system that has been shown to be able to automatically decipher a lost language, without needing advanced knowledge of its relation to other languages. They also showed that their system can itself determine relationships between languages, and they used it to corroborate recent scholarship suggesting that the language of Iberian is not actually related to Basque.

The team’s ultimate …

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Watch live: Big data solutions, machine learning featured at Io-Tahoe SmartData Marketplaces event

watch live: big data solutions, machine learning featured at io-tahoe smartdata marketplaces event

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Automated data management tools are in high demand as data volumes continue to rise across the enterprise. Io-Tahoe LLC, founded in 2014, leverages machine-learning algorithms — and other tech — to helps organizations manage and gain insights from the ever-expanding stores of information.
Enabling the discovery of data across the multicloud remains key to Io-Tahoe’s success in the industry. In today’s multicloud and hybrid computing world, APIs have become an important means to that end. Io-Tahoe is deepening integration for its automated solutions, tying in with major partners such as Google, Amazon Web Services and Red Hat Inc. The company’s ability to leverage APIs has helped open the door for a critical part of data discovery in the enterprise landscape, according to Ajay Vohora, Io-Tahoe’s chief executive officer.
“One of the trends that I wanted us to be part of was being open, having an open architecture,” said Vohora, during a June interview with theCUBE, SiliconANGLE Media’s livestreaming studio. “I wanted to ensure we could openly plugin using APIs that were available.”
Back by popular demand, theCUBE is re-airing Io-Tahoe’s SmartData Marketplaces event on Oct. 21 at 3 p.m. EDT. The event will feature interviews surrounding big data

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AI and machine learning: a gift, and a curse, for cybersecurity

ai and machine learning: a gift, and a curse, for cybersecurity

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The Universal Health Services attack this past month has brought renewed attention to the threat of ransomware faced by health systems – and what hospitals can do to protect themselves against a similar incident.  Security experts say that the attack, beyond being one of the most significant ransomware incidents in healthcare history, may also be emblematic of the ways machine learning and artificial intelligence are being leveraged by bad actors.
With some kinds of “early worms,” said Greg Foss, senior cybersecurity strategist at VMware Carbon Black, “we saw [cybercriminals] performing these automated actions, and taking information from their environment and using it to spread and pivot automatically; identifying information of value; and using that to exfiltrate.”
The complexity of performing these actions in a new environment relies on “using AI and ML at its core,” said Foss.
Once access is gained to a system, he continued, much malware doesn’t require much user interference. But although AI and ML can be used to compromise systems’ security, Foss said, they can also be used to defend it. 
“AI and ML are something that contributes to security in multiple different ways,” he said. “It’s not something that’s been explored, even until just recently.”
One …

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NXP Invests in Au-Zone to Enhance Machine Learning Capabilities

nxp invests in au-zone to enhance machine learning capabilities

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NXP is hoping to improve its machine learning offerings after making a strategic investment in Au-Zone Technologies. The exclusive arrangement specifically concerns Au-Zone’s DeepView ML Tool Suite, which will be used to bolster NXP’s eIQ Machine Learning software development environment and lead to the creation of new Edge machine learning products. In that regard, the DeepView Suite comes with a graphical user interface (GUI) and workflows that will make it easier to import datasets, and to train neural network models for Edge devices. DeepView’s run-time inference engine will give eIQ developers more insight into system memory usage, data movement, and other performance metrics in real time, which will in turn allow them to optimize their model before deploying it in a System-on-Chip (SoC) solution.“This partnership will accelerate the deployment of embedded Machine Learning features,” said Au-Zone CEO Brad Scott. “This will serve as a catalyst to deliver more advanced Machine Learning technologies and turnkey solutions as [Original Equipment Manufacturers] continue to transition inferencing to the Edge.”In other news, NXP also revealed that it will be integrating Arm’s Ethos-U65 microNPU (neural processing unit) into its own i.MX applications processors. The Ethos-U65 is comparable to …

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Machine Learning, Crowdsourcing Speed Up Online Surveys – Multichannel Merchant

machine learning, crowdsourcing speed up online surveys – multichannel merchant

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Online surveys have grown in popularity because of the ease with which they give organizations valuable insights into everything from product design and packaging to consumer buying habits. But today’s research platforms often impose a tradeoff between speed and simplicity and the richness of actionable insights.
A combination of machine learning technology and crowdsourcing concepts is solving this problem.  It enables researchers to shorten online survey time without having to resort to matrix tables that often make surveys uncomfortably long and can skew results. At the same time, these technologies deliver the higher accuracy, deeper insights and superior user experience of open-ended questions.
Matrix Table Challenges
Researchers have typically accelerated online surveys by asking questions not one by one but in a more space-efficient matrix format (questions are in the table’s rows, response scale options in its columns). Our study, however, shows this can skew answers to the midrange, as shown in Figure 1. It also may encourage “straight-lining” (i.e., selecting the same response for all rows of the matrix) and even prime respondents to answer in a certain way.

A second study we conducted tested whether this observed midpoint drift could be replicated in a different set …

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