Understanding why organizations struggle with AI for video and what the industry can do to overcome these specific barriers is essential to unlocking adoption.
An AI system needs many of the same organizational structures that surround any worker carrying responsibility.
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As AI systems become more capable of acting independently, organizations need guardrails designed specifically for autonomy.
The architect of the water bankruptcy concept explains why the problem is so difficult to solve politically, even when the solutions are known.
A robot learning to load a dishwasher or hand someone a glass is learning a culturally and geographically specific version of that skill.
A former Susan G. Komen CEO’s new institute wants breast arterial calcification, a heart disease marker, on every mammogram report. No clinical guideline exists yet.
Most pilots are built and tested against a clean, static dataset, disconnected from the systems they would eventually need to run alongside.
Before AI goes live, you need to define what it can do, who can intervene and how decisions will be traced.
Richard Ho, who helped create Google’s first TPU chip, also built OpenAI’s semiconductor unit from scratch. Now he’s grappling with deploying the first chips, doomerism and “competing among friends” with Nvidia.