Can responsible AI beat hallucinations?
Businesses are more eager than ever to implement AI in their workflows, but ambition doesn’t always translate into success
Hallucinations are an eternal problem in generative AI in particular, and while it’s true that large language models (LLMs) require vast amounts of data, the quality of that information will affect the quality of the output.
What can businesses do to ensure they’re using AI both effectively and responsibly?
In this episode of the ITPro Podcast, Jane and Ross are joined by Amanda Stent, head of AI strategy and research in the office of the CTO at Bloomberg, to examine what responsible AI is, how organizations can use it, and what has been achieved at Bloomberg.
Highlights
Links
- Why doesn't more data produce better results?
- This new technique could improve AI accuracy by 80%
- AI hallucinations, accuracy still top concerns for UK tech leaders as adoption continues
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Jane McCallion is Managing Editor of ITPro and ChannelPro, specializing in data centers, enterprise IT infrastructure, and cybersecurity. Before becoming Managing Editor, she held the role of Deputy Editor and, prior to that, Features Editor, managing a pool of freelance and internal writers, while continuing to specialize in enterprise IT infrastructure, and business strategy.
Prior to joining ITPro, Jane was a freelance business journalist writing as both Jane McCallion and Jane Bordenave for titles such as European CEO, World Finance, and Business Excellence Magazine.
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