This week on the Konvoy Newsletter audio edition, host Josh Chapman explores the tradeoffs between running AI locally on-device versus in the cloud. As the cost of inference has fallen 1,000x in just three years, developers and enterprises now face a strategic choice: prioritize privacy, control, and real-time performance with local AI — or embrace scalability, accessibility, and low entry costs in the cloud.

From healthcare diagnostics to autonomous vehicles, from generative chatbots to fraud detection, the future of AI won’t be one-size-fits-all. Instead, it’s about matching infrastructure to use case — and increasingly, hybrid approaches like Apple’s “Private Cloud” are bridging the gap.

What You’ll Learn in This Episode:

• Why local AI is gaining traction after years of hardware and complexity barriers

• The unique advantages of on-device inference: privacy, latency, and offline reliability

• How cloud AI powers scalability, collaboration, and data-heavy applications

• The hybrid strategies big tech players are adopting to balance both worlds

• Which industries are best positioned for local AI vs. cloud AI adoption

• The key tradeoffs between cost, control, and scale that every team must weigh

Whether you’re building AI-driven products, investing in next-gen infrastructure, or tracking how enterprises adopt new technologies, this episode unpacks the future of AI deployment — and what it means for both consumers and businesses.

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