Remove .Net Remove Artificial Inteligence Remove Generative AI
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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. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.

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AI in action: Stories of how enterprises are transforming and modernizing

CIO

Generative and agentic artificial intelligence (AI) are paving the way for this evolution. AI practitioners and industry leaders discussed these trends, shared best practices, and provided real-world use cases during EXLs recent virtual event, AI in Action: Driving the Shift to Scalable AI.

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Salesforce plans generative AI boost for ESG reporting with Net Zero Cloud

CIO

Generative AI will soon be everywhere — including in Salesforce’s Net Zero Cloud environmental, social, and governance (ESG) reporting tool. Net Zero Cloud uses data held within the Salesforce platform to help enterprises report on their carbon footprint and manage other social and governance metrics.

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AI agents loom large as organizations pursue generative AI value

CIO

Yet as organizations figure out how generative AI fits into their plans, IT leaders would do well to pay close attention to one emerging category: multiagent systems. Agents come in many forms, many of which respond to prompts humans issue through text or speech.

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How ServiceNow gets the most out of generative AI

CIO

Competition among software vendors to be “the” platform on which enterprises build their IT infrastructure is intensifying, with the focus of late on how much noise they can make about their implementation of generative AI features. One reason we’re releasing early is because we’re ready,” says ServiceNow CIO Chris Bedi.

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5 tips for better business value from gen AI

CIO

CIOs should return to basics, zero in on metrics that will improve through gen AI investments, and estimate targets and timeframes. Set clear, measurable metrics around what you want to improve with generative AI, including the pain points and the opportunities, says Shaown Nandi, director of technology at AWS.

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Harness the power of MCP servers with Amazon Bedrock Agents

AWS Machine Learning - AI

AI agents extend large language models (LLMs) by interacting with external systems, executing complex workflows, and maintaining contextual awareness across operations. In this post, we show you how to build an Amazon Bedrock agent that uses MCP to access data sources to quickly build generative AI applications.