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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. Chatbots are used to build response systems that give employees quick access to extensive internal knowledge bases, breaking down information silos. An overview.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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Why you should care about debugging machine learning models

O'Reilly Media - Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. We’ll review methods for debugging below. Random attacks can reveal all kinds of unexpected software and math bugs.

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This week in AI: Amazon ‘enhances’ reviews with AI while Snap’s goes rogue

TechCrunch

So until an AI can do it for you, here’s a handy roundup of the last week’s stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own. This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews.

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Are you ready for MLOps? 🫵

Xebia

The time when Hardvard Business Review posted the Data Scientist to be the “Sexiest Job of the 21st Century” is more than a decade ago [1]. Both the tech and the skills are there: Machine Learning technology is by now easy to use and widely available. Why is that? … that does not make things easier.

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Unlocking the full potential of enterprise AI

CIO

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1]

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The future of data: A 5-pillar approach to modern data management

CIO

Digital transformation started creating a digital presence of everything we do in our lives, and artificial intelligence (AI) and machine learning (ML) advancements in the past decade dramatically altered the data landscape. Finally, it is important to emphasize the Engineering aspect of this pillar.

Data 167