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📝 Editorial: AWS’ Generative AIStrategy Starts to Take Shape and Looks a Lot Like Microsoft’s The AWS re:Invent conference has long been regarded as the premier event of the year for cloud computing. Bedrock has emerged as the cornerstone of AWS's generative AIstrategy, now supporting Anthropic’s Claude 2.1
It can also aid in platform engineering, for example by generating DevOps pipelines and middleware automation scripts. Here, we’ll prioritize discussion of four workflows to which generative AI can be applied. Begin by reskilling the HR professionals themselves, who are likely already using AI-driven hiring tools.
Responsibility for maintenance and troubleshooting: Rockets DevOps/Technology team was responsible for all upgrades, scaling, and troubleshooting of the Hadoop cluster, which was installed on bare EC2 instances. Despite the support of our internal DevOps team, our issue backlog with the vendor was an unenviable 200+.
About the Authors Dr. Björn Blomqvist is the Head of AIStrategy at Axfood AB. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team. Pavel has extensive experience in the development of frameworks, infrastructure, and tools in the domains of DevOps and ML/AI on the AWS platform.
Anant Sharma is a software engineer at AWS Annapurna Labs specializing in DevOps. With over 15 years of experience in architecting and building AI based products and platforms, he holds multiple patents and publications in AI and eCommerce.
Budget restrictions (41%), shortage of AI talent (38%), and technical complexity (35%) were cited as primary obstacles. Michal Szymczak, Head of AIStrategy at Zartis, commented on this apparent contradiction: “AI adoption isn’t some ‘on or off’ switch.
Budget restrictions (41%), shortage of AI talent (38%), and technical complexity (35%) were cited as primary obstacles. Michal Szymczak, Head of AIStrategy at Zartis, commented on this apparent contradiction: “AI adoption isn’t some ‘on or off’ switch.
Archana Joshi brings over 24 years of experience in the IT services industry, with expertise in AI (including generative AI), Agile and DevOps methodologies, and green software initiatives. As I mentioned earlier, security is a key concern with the use of any AI tool or application.
As part of LSEGs multi-stage AIstrategy, LCH has been exploring the role that generative AI services can have in this space. Elias has experience in migration delivery, DevOps engineering and cloud infrastructure. Marcin Czelej is a Machine Learning Engineer at AWS Generative AI Innovation and Delivery.
AI is being implemented in key workflows like talent acquisition and retention, customer service, and application modernization, especially paired with other technologies like virtual agents or chatbots. This includes adopting governance tools and incorporating governance into workflows to maintain consistent standards.
At a recent technical talk, Verma and Radha Krishna Kunni from OpsRamp (recently acquired by HPE) delved into the transformative impact of AI and machine learning on IT operations, DevOps, and SRE for hybrid multi-cloud environments. Vishesh Jha is a Senior Solutions Architect at AWS.
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