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The coming shift from cloud AI to personal AI
Hello, friends. AI’s future may depend less on gigantic cloud models and more on bringing intelligence closer to people on the devices they use every day. In our latest podcast episode, we explore why the next phase of AI could run across laptops, phones, and personal devices, and why affordability, privacy, energy, and trust continue to stand out as some of the industry’s biggest challenges. Thank you to Airia for sponsoring this episode of The Deep View Conversations. —Jason Hiner
The coming shift from cloud AI to personal AI
What happens when AI moves from cloud-only to running everywhere, including on your laptop, your phone, and other devices around you?
In this episode of The Deep View: Conversations, senior reporter Sabrina Ortiz sits down with Olena Zhu, who leads AI for the client computing group at Intel, to explore one of the biggest shifts underway in AI: the move toward accessible, affordable, and privacy-first AI systems.
Zhu explains why the economics and infrastructure demands of cloud-only AI may not scale indefinitely, and why on-device AI could become a critical part of the industry's future. She also reflects on the evolution from traditional AI systems to LLMs and now to agentic AI, and why this wave feels fundamentally different from the hype cycles that came before it.
The conversation also dives into how AI is changing the way people work, learn, and experiment, including the surprising mindset Zhu believes helps people get the most value from AI tools today.
Topics covered include:
Why cloud-only AI has limits
The future of on-device and edge AI
AI affordability, energy use, and data sovereignty
How agentic AI changed Zhu’s workflow
Why experimentation matters more than expertise
Intel’s vision for privacy-first AI systems
The hidden infrastructure challenge behind AI growth
Why AI adoption may depend on trust and accessibility
If you're concerned about the affordability, accessibility, and privacy of AI, you don't want to miss this episode.
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