Key Takeaways:
- 1. The true value of AI lies in inference, where AI models put training to use in real-world workflows.
- 2. Establishing trust in AI systems is crucial for reliable outcomes and productivity gains.
- 3. Organizations are shifting focus from model-centric to data-centric thinking to generate continuous intelligence.
HPE emphasizes the importance of inference in AI, highlighting the need for trust in AI systems for reliable outcomes and productivity gains. Organizations are moving towards a data-centric approach, focusing on breaking down data silos and unlocking value. To achieve AI success, it is essential to establish structure, governance, and standardize infrastructure while aligning technology ambition with value creation.
Insight: AI's true potential lies in operationalizing inference at scale, requiring a shift to data-centric thinking and governance to ensure successful AI deployments.
This article was curated by memoment.jp from the feed source: MIT Technology Review.
Read the original article here: https://www.technologyreview.com/2025/11/18/1128007/realizing-value-with-ai-inference-at-scale-and-in-production/
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