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Healthcare organizations must create a strong data foundation to fully benefit from generative AI

CIO

Since the introduction of ChatGPT, the healthcare industry has been fascinated by the potential of AI models to generate new content. However, the effort to build, train, and evaluate this modeling is only a small fraction of what is needed to reap the vast benefits of generative AI technology. Consider the iceberg analogy.

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Thinking of building your own AI agents? Don’t do it, advisors say

CIO

Companies that fail to build their own AI agents will turn to outside AI consulting firms to build custom agents for them, or they will use agents embedded in software from their current vendors, write Forrester analysts Jayesh Chaurasia and Sudha Maheshwari. Kumar adds. Start with one [AI model], and you can start tailoring its behavior.

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CIOs confront generative AI’s workplace X factor

CIO

Still, to ensure workers gain the most out of the tools, Mayar suggested multimodal LLMs combining structured datasets and unstructured data should be designed smaller and for specific tasks. Chief among those foundations — at least for now — is the company’s workforce. Gen AI is not a magic bullet,” she said at the summit.

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10 most difficult-to-fill IT roles — and how to address the gap

CIO

The biggest challenge is finding talented team members at the market rate,” says Patrick Isaac, CTO at Accuro Solutions, adding that the current environment demands more intensive recruiting efforts. S&P Global also needs complementary skills in software architecture, multicloud, and data engineering to achieve its AI aims. “It

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6 generative AI hazards IT leaders should avoid

CIO

OpenAI’s recent announcement of custom ChatGPT versions make it easier for every organization to use generative AI in more ways, but sometimes it’s better not to. The customer will not let you off the hook for a data breach just because, ‘It was our AI’s fault.’”