March 15, 2023
The quest for Nirvana: Applying AI at scale
With ChatGPT and generative AI grabbing the news spotlight, AI will likely be technology’s Person of the Year.
Beyond the splashy news of search engine AIs having weird conversations with humans, and 2,700 new generative AI APIs flooding the market (slight exaggeration), what does AI mean for regular enterprise companies? Specifically, how are ordinary businesses implementing AI at scale?
In this special issue, we look at real-life AI use cases, and efforts by companies to scale those cases. Featuring stories from end-user companies in banking, insurance, healthcare and other industries, we explore how they took the time to get their initial AI projects under control, and then were able to launch their AI transformation more ambitiously by implementing technology, processes, governance and strategy across the organization.
So whether you have questions about synthetic data, responsible AI or MLOps, we have answers. Written by real people, not AI.
— Matt Marshall
CEO and Editor-in-Chief
The quest for AI Nirvana has never been just about AI. It’s about going beyond harnessing it in specific applications to implementing it at scale, generating value across the organization.
The trend toward AI at scale has gained significant momentum over the past year. Last July, for example, Gartner research analyst Whit Andrews told VentureBeat that the “colossal” AI trend underlying all other AI trends today is the increased scale of artificial intelligence in organizations.
Can healthcare show the way forward for scaling AI?
With global shortages of radiologists and physicians looming, AI is becoming a “game-changer.”
Aflac takes on claims challenges to scale AI efforts
For Aflac, delivering AI at scale across the organization has become a top priority since the pandemic.
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