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The growing popularity of open source for AI and ML and other technological advancements are spurring market growth. Open-source technologies are expanding to interface smoothly with cloud platforms, allowing organizations to benefit from the cloud's scale and agility. Open-source frameworks, such as TensorFlow and PyTorch, are making AI/ML development more accessible, creating a demand for model training, deployment, and optimization.
Furthermore, technologies, such as Docker and Kubernetes, are transforming application deployment and administration, prompting the need for service providers with experience in containerized open-source solutions. Also, security concerns have always been a hurdle to open-source adoption. However, advancements in security procedures and code auditing tools are improving the security posture of open-source software. Open-source groups are implementing increasingly stringent security measures during development.
For instance, in February 2024, Hugging Face, ServiceNow, and NVIDIA collaborated to release StarCoder2, a family of open-access Large Language Models (LLMs) designed for code generation to enhance developer productivity and innovation in building enterprise applications. This initiative aims to set new standards for performance, transparency, and cost-effectiveness in the field of generative AI. StarCoder2, trained in 619 programming languages, offers three model sizes: a 3-billion-parameter model by ServiceNow, a 7-billion-parameter model by Hugging Face, and a 15-billion-parameter model by NVIDIA.