Remove Artificial Inteligence Remove Generative AI Remove Storage
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Should finance organizations bank on Generative AI?

CIO

As I work with financial services and banking organizations around the world, one thing is clear: AI and generative AI are hot topics of conversation. Financial organizations want to capture generative AI’s tremendous potential while mitigating its risks. In short, yes. But it’s an evolution. billion by 2032.

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Getting infrastructure right for generative AI

CIO

For generative AI, a stubborn fact is that it consumes very large quantities of compute cycles, data storage, network bandwidth, electrical power, and air conditioning. Infrastructure-intensive or not, generative AI is on the march. of the overall AI server market in 2022 to 36% in 2027.

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AI and generative AI are revolutionizing manufacturing…here’s how

CIO

Now, manufacturing is facing one of the most exciting, unmatched, and daunting transformations in its history due to artificial intelligence (AI) and generative AI (GenAI). Manufacturers are attaining significant advancements in productivity, quality, and effectiveness with early use cases of AI and GenAI.

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Accelerating generative AI requires the right storage

CIO

It’s an appropriate takeaway for another prominent and high-stakes topic, generative AI. Generative AI “fuel” and the right “fuel tank” Enterprises are in their own race, hastening to embrace generative AI ( another CIO.com article talks more about this). What does this have to do with technology?

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What is Oracle’s generative AI strategy?

CIO

While Microsoft, AWS, Google Cloud, and IBM have already released their generative AI offerings, rival Oracle has so far been largely quiet about its own strategy. Although not confirmed yet, Batta said new foundation models for industry sectors such as health and public safety could be added to the service in the future.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. Monitoring the performance and behavior of LLMs is a critical task for ensuring their safety and effectiveness.

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Medical content creation in the age of generative AI

AWS Machine Learning - AI

Generative AI and transformer-based large language models (LLMs) have been in the top headlines recently. These models demonstrate impressive performance in question answering, text summarization, code, and text generation. Amazon Bedrock : to interact with supported LLMs and embedding models.