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Nowhere to Go But Up: Bold AI Predictions for 2022

Uniphore

We’ve seen big tech like Apple, Amazon and Microsoft enter the healthcare market , even becoming worthy competitors to major healthcare players. Automotive, healthcare, retail, banking, transportation, entertainment, education, human resources, legal services – and more. This isn’t a new phenomenon.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

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A practitioner’s guide to ABM during a recession

Hero Digital

For example, if you lead with a message about how well your solution works in hospitals, the content you’re driving to needs to be primarily about the healthcare vertical. Find a popular (but invalid) objection to your solution and challenge it in the most specific, entertaining way possible.

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Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning

In this innovation talk, hear how the largest industries, from healthcare and financial services to automotive and media and entertainment, are using generative AI to drive outcomes for their customers. Additionally, SaaS providers need scalable and cost-effective ways to serve hundreds of models to their customers.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

Marco is a digital native cloud advisor with experience in the FinTech, Healthcare & Life Sciences, Software-as-a-service, and most recently, in Telecommunications industries. Although very few differences are visible between the advanced techniques discussed, they are by far more informative than regular retriever chains.

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Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

He is an experienced software engineer, architect, and leader with over 20 years in the SaaS space for various industries. He has helped companies in insurance, financial services, media and entertainment, healthcare, utilities, and manufacturing. He has built and managed numerous B2B and B2C systems on AWS and GCP.

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Simplify iterative machine learning model development by adding features to existing feature groups in Amazon SageMaker Feature Store

AWS Machine Learning

He has helped companies in many industries, including insurance, financial services, media and entertainment, healthcare, utilities, and manufacturing. Prior to AWS, she was leading growth and monetization strategy for SaaS services at VMware. Mark holds six AWS certifications, including the ML Specialty Certification.

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