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As AI solutions accelerate across enterprises, it becomes increasingly expensive to use public models, which have the added risk of enterprise data potentially being exposed to third parties. The Models-as-a-Service (MaaS) approach enables enterprises to offer open source models (and the required AI technology stack) that can be used as a shared resource by the entire company.Additionally, as an enterprise's AI adoption accelerates, there’s often a lack of consistency as each business group strives to build their own bespoke AI solutions covering a wide range of use cases (Chatbot, code assi

via Red Hat Blog https://ift.tt/dYaKyt0

As AI solutions accelerate across enterprises, it becomes increasingly expensive to use public models, which have the added risk of enterprise data potentially being exposed to third parties. The Models-as-a-Service (MaaS) approach enables enterprises to offer open source models (and the required AI technology stack) that can be used as a shared resource by the entire company.Additionally, as an enterprise's AI adoption accelerates, there’s often a lack of consistency as each business group strives to build their own bespoke AI solutions covering a wide range of use cases (Chatbot, code assi

via Red Hat Blog https://ift.tt/dYaKyt0


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