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Optimize your workloads with Amazon Redshift Serverless AI-driven scaling and optimization

AWS Big Data

To address this requirement, Redshift Serverless launched the artificial intelligence (AI)-driven scaling and optimization feature, which scales the compute not only based on the queuing, but also factoring data volume and query complexity. The slider offers the following options: Optimized for cost – Prioritizes cost savings.

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The great repatriation? IT leaders reset cloud strategies to optimize value

CIO Business Intelligence

IT leader and former CIO Stanley Mwangi Chege has heard executives complain for years about cloud deployments, citing rapidly escalating costs and data privacy challenges as top reasons for their frustrations. They, too, were motivated by data privacy issues, cost considerations, compliance concerns, and latency issues.

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Optimizing Cost with DevOps on the Cloud

Smart Data Collective

Are you looking for a way to reduce the cost of your development efforts? The cost savings associated with DevOps on the cloud are significant. By leveraging existing cloud-based services, businesses can save time and money by avoiding costly IT overhead costs like maintenance, licensing fees, and server infrastructure setup.

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Cloud migration best practices: Optimizing your cloud migration strategy 

IBM Big Data Hub

Businesses are increasingly embracing cloud infrastructure due to its scalability, flexibility and cost-effectiveness, among other benefits. Recent statistics indicate a significant rise in companies adopting cloud services to meet their operational and cost saving needs.

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Supply Chain Network Design Use Cases; From Lowering Cost to Going Green

Speaker: Aanand Pandey and Catalina Perez

Need to lower your supply chain costs, speed up delivery times or decrease carbon emissions? Start optimizing your supply chain! Finding optimal locations for plants and other resources. Finding optimal locations for plants and other resources. Modeling carbon cost. Dealing with abrupt changes in demand.

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Top 8 failings in delivering value with generative AI and how to overcome them

CIO Business Intelligence

Data privacy and compliance issues Failing: Mismanagement of internal data with external models can lead to privacy breaches and non-compliance with regulations. Bias and hallucinations Failing: GenAI models often produce biased or inaccurate outputs, leading to misinformation and potential legal issues.

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Achieving cloud excellence and efficiency with cloud maturity models

IBM Big Data Hub

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.