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To promote the success of this migration, we collaborated with the AWS team to create automated and intelligent digital experiences that demonstrated Rockets understanding of its clients and kept them connected. With just one part-time MLengineer for support, our average issue backlog with the vendor is practically non-existent.
This cutting-edge model supports long-context processing, complex segmentation scenarios, and fine-grained analysis, making it ideal for automating processes for various industries such as medical imaging in healthcare, satellite imagery for environment monitoring, and object segmentation for autonomous systems. Meta SAM 2.1 Meta SAM 2.1
Automation of building new projects based on the template is streamlined through AWS Service Catalog , where a portfolio is created, serving as an abstraction for multiple products. This functionality enables us to build generative AI applications in the future for increased understanding of how the model works.
Lifecycle management Within the AI/ML CoE, the emphasis on scalability, availability, reliability, performance, and resilience is fundamental to the success and adaptability of AI/ML initiatives. Incident management AI/ML solutions need ongoing control and observation to manage any anomalous activities.
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