Remove Data Processing Remove Experimentation Remove Risk
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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

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How to build a safe path to AI in Healthcare

CIO Business Intelligence

Data Security, Privacy, and Accuracy: One of the major hurdles to implementing AI in healthcare is the risk of accidental exposure to private health information. To learn more, visit us here.

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3 steps to eliminate shadow AI

CIO Business Intelligence

These same decision-makers identify a host of challenges in implementing generative AI, so chances are that a significant portion of use is “unsanctioned.” The perils of unsanctioned generative AI The added risks of shadow generative AI are specific and tangible and can threaten organizations’ integrity and security.

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Going ‘AI native’ with in-house ChatGPT the MITRE way

CIO Business Intelligence

The AI data center pod will also be used to power MITRE’s federal AI sandbox and testbed experimentation with AI-enabled applications and large language models (LLMs). We took a risk. based research organization into an “AI-native organization” that provides the most efficient, intelligent, and critical data for government agencies.

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DataRobot Notebooks: Enhanced Code-First Experience for Rapid AI Experimentation

DataRobot Blog

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. DataRobot Notebooks is a fully hosted and managed notebooks platform with auto-scaling compute capabilities so you can focus more on the data science and less on low-level infrastructure management. A host of open-source libraries.

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US Air Force seeks generative AI test pilots

CIO Business Intelligence

Proof that even the most rigid of organizations are willing to explore generative AI arrived this week when the US Department of the Air Force (DAF) launched an experimental initiative aimed at Guardians, Airmen, civilian employees, and contractors. For now, AFRL is experimenting with self-hosted open-source LLMs in a controlled environment.

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6 best practices to develop a corporate use policy for generative AI

CIO Business Intelligence

But just like other emerging technologies, it doesn’t come without significant risks and challenges. According to a recent Salesforce survey of senior IT leaders , 79% of respondents believe the technology has the potential to be a security risk, 73% are concerned it could be biased, and 59% believe its outputs are inaccurate.

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