ABBYY updates its machine learning library

ABBYY announced a major update to NeoML, an open-source, cross-platform machine learning library that enables developers to build, train, and deploy machine learning models. The update adds support for Python programming language, The most popular language in machine learning and AI. In addition to a 5-10x acceleration, the framework also offers more than 20 new ML techniques, including 10 network layers and optimization techniques. In addition, NeoML now supports Apple M1 chips, GPUs on Linux machines, and Intel GPUs. This greatly expands the library’s use cases and addressable scenarios, allowing more developers to use the library to build AI-powered applications and solutions.

ABBYY updates its machine learning library

A 2020 study by CodinGame found that Python was related to Java in RedMonk’s quarterly rankings and was the “most popular programming language.” Python is widely used across all industries for tasks like automation, web development, scripting, web scraping, and data analysis by companies like Google, Pinterest, Spotify, and Dropbox. Python is commonly used in academia with students to learn programming, data science, and machine learning. Its versatility is only one of the reasons for its popularity. With the addition of Python support, more developers and organizations can leverage NeoML to build, train, and deploy models for identification, classification, semantic segmentation, validation, and predictive modeling. objects. You will be able to achieve your business goals. For example, healthcare facilities can streamline management processes, map infectious diseases, and personalize care. Insurers – Predict premiums and losses on insurance policies.

Pretty Accelerate NeoML has become one of the fastest machine learning frameworks on the market. It now offers up to 10x faster performance with traditional algorithms and up to 30% faster neural network training and inference than previous versions. Compared to the two most popular open source machine learning libraries, NeoML offers on average 50% faster performance.[1] This allows the framework to have a seamless user experience. Data processing on the device.. One of the main advantages of NeoML is the high efficiency of the cloud. This allows businesses to make the most of available cloud resources.

“Open source is a powerful driver of innovation. Bruce Okat, senior vice president of product marketing at ABBYY, said: Working with the developer community to further develop the open source library. By improving ourselves, we aim to support the advancement of artificial intelligence. “NeoML is a breakthrough for developers, leveraging the framework’s high inference speed, platform independence and mobile device support. It opens up new opportunities to experiment, build and start new initiatives. We encourage all developers, data scientists, and academics to contribute using NeoML on GitHub. ”

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ABBYY updates its machine learning library

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