As its name implies, open source knows no bounds and extends even into proprietary hardware companies. Intel's use of open source for model optimisation showcases its ability to nurture a wide array of products in the rapidly expanding field of artificial intelligence and machine learning. This approach has not only showcased the potential of open source but has also established a brilliant business model within a proprietary ecosystem.
With its open visual inference and neural network optimisation (Open VINO) toolkit, tailored for developers, Intel trains computers to recognise patterns, quickly and accurately. Initially aimed at the computer vision market, this open sourced toolkit has expanded its versatility to optimise models to understand language or generate content (text or images) through artificial intelligence across various domains, including NLP, generative AI, and emerging large language models.
There is an abundance of open source toolkits in the field of deep learning and neural network optimisation. Whether it's Facebook's PyTorch for research, Keras for userfriendly applications, or Apache's
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Helgrind: Detecting Synchronisation Issues in Multithreaded Programs
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Containerisation: The Cornerstone of Multi-Cloud and Hybrid Cloud Success
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Containerisation and Kubernetes have eased software development, making it faster and better. Let's see where these are headed, looking at trends that are making life easier for developers.
India's Leap in Supercomputing: Innovating for Tomorrow
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SageMath: A Quick Introduction to Cybersecurity
In the previous articles in this SageMath series, we delved into graph theory and explored its applications using SageMath. In this seventh article in the series, it is time to shift our focus to another crucial subfield of computer science: cybersecurity and cryptography.
Efficient Prompt Engineering: Getting the Right Answers
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Analysing Linus Torvald's Critique of Docker
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