Why It’s Important
Intel has been slower than other companies like ARM, Google, and Nvidia to bring together its AI resources. This has limited Intel’s ability to compete in the wider AI market. Using more on-device AI alongside server-side processing gives enterprises more ways to handle faster, context-aware tasks at the data source. This helps reduce server load, improve responsiveness, and enable offline capabilities.
This will also help improve securing sensitive data, like healthcare or financial information, that most organisations refuse to upload to the Cloud due to legal or ethical restrictions. Through client-side AI, these types of data can be processed within secure local environments to ensure privacy and compliance.
Who’s Impacted
- CTO
- AI COE’s
- IT Teams
What’s Next?
- Consider looking into the enterprise’s regulations and standards that introduce additional compliance requirements for data security and privacy practices related to client-side AI. Evolving regulations may create uncertainty and require ongoing adjustments to AI practices, potentially increasing costs.
- Scrutiny of these products must be observed. This could include factors related to data privacy, bias mitigation, or specific edge cases relevant to their application domain.
Related IBRS Advisory
1. VENDORiQ: Intel Announces A Set Of 34 Open Source AI Reference Kits
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