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Cnvrg.io launches a free version of its data science platform – TechCrunch

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Dubbed'CORE,' this version includes most -- but not all -- of the standard feature in cnvrg's main commercial offering. As the company's CEO Yochay Ettun told me, CORE users will be able to use the platform either on-premise or in the cloud, using Nvidia-optimized containers that run on a Kubernetes cluster. Because of this, it natively handles hybrid- and multi-cloud deployments that can automatically scale up and down as needed -- and adding new AI frameworks is simply a matter of spinning up new containers, all of which are managed from the platform's web-based dashboard. Ettun describes CORE as a'lightweight version' of the original platform but still hews closely to the platform's original mission. "As was our vision from the very start, cnvrg.io "With the growing technical complexity of the AI field, the data science community has strayed from the core of what makes data science such a captivating profession -- the algorithms.


How to use continual learning in your ML models

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Academics and practitioners alike believe that continual learning (CL) is a fundamental step towards artificial intelligence. CL is the ability of a model to learn continually from a stream of data. In practice, this means supporting the ability of a model to autonomously learn and adapt in production as new data comes in. The idea of CL is to mimic humans ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. CL of models in production will improve accuracy, and bring AI one step closer to real human intelligence.


Continual Learning of Models in Production Open Data Science Conference

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Abstract: Academics and practitioners alike believe that continual learning (CL) is a fundamental step towards artificial intelligence. Continual learning is the ability of a model to learn continually from a stream of data. In practice, this means supporting the ability of a model to autonomously learn and adapt in production as new data comes in. The idea of CL is to mimic humans ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. CL of models in production will improve accuracy, and bring artificial intelligence one step closer to real human intelligence.


Cnvrg.io's Free CORE Community Version Empowers Data Scientists to Focus on Innovation Transforming Data with Intelligence

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New, no-cost community version helps advance the AI landscape. Note: TDWI's editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements. Cnvrg.io, the enterprise data science platform, has released its community version, CORE, amid extended remote work and social distancing to advance ML development and help the data science community leverage its model management and MLOps capabilities at no cost. The data science community has been central to the rapid growth of AI and machine learning innovation.


insideBIGDATA Latest News – 4/7/2020 - insideBIGDATA

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In this regular column, we'll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we're in close touch with vendors from this vast ecosystem, so we're in a unique position to inform you about all that's new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive. Mist Systems, a Juniper Networks company and a pioneer in secure AI-driven networks, announced the launch of Mist Premium Analytics, a new service that offers enterprises a comprehensive network visibility and business insights platform to support the increasing demands of digital transformation projects.