2013 AI Clustering 
IBM Journey to AI blog
NOVEMBER 2, 2023
Borg’s large-scale cluster management system essentially acts as a central brain for running containerized workloads across its data centers. In 2013, Google introduced Omega, its second-generation container management system. It was also in 2013 that Docker, a key player in Kubernetes history, came into the picture.
AWS Machine Learning Blog
FEBRUARY 2, 2024
One of the most useful application patterns for generative AI workloads is Retrieval Augmented Generation (RAG). Because embeddings are an important source of data for NLP models in general and generative AI solutions in particular, we need a way to measure whether our embeddings are changing over time (drifting).
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AWS Machine Learning Blog
MARCH 10, 2025
The intersection of AI and financial analysis presents a compelling opportunity to transform how investment professionals access and use credit intelligence, leading to more efficient decision-making processes and better risk management outcomes. It became apparent that a cost-effective solution for our generative AI needs was required.
IBM Journey to AI blog
FEBRUARY 29, 2024
Containers and Docker Container technology fundamentally changed in 2013 with Docker’s introduction and has continued unabated into this decade, steadily gaining in popularity and user acceptance. Docker containers were originally built around the Docker Engine in 2013 and run according to an application programming interface (API).
IBM Journey to AI blog
OCTOBER 16, 2023
Containers have increased in popularity and adoption ever since the release of Docker in 2013, an open-source platform for building, deploying and managing containerized applications. However, monitoring remains critical, so that organizations have a view into each Kubernetes cluster.
NOVEMBER 24, 2023
Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. Amazon Bedrock is the easiest way to build and scale generative AI applications with foundation models (FMs). Using AI, AutoLink automatically identified and suggested potential matches.
AWS Machine Learning Blog
MARCH 15, 2024
Solution overview We deploy FedML into multiple EKS clusters integrated with SageMaker for experiment tracking. EKS Blueprints helps compose complete EKS clusters that are fully bootstrapped with the operational software that is needed to deploy and operate workloads. He also holds an MBA from Colorado State University.
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