ViodiTV


Optimizing Locally Run AI

In the fast-moving world of on-device AI, the gap between a high-performing model and a functional product is often a hardware bottleneck. At CES 2026, ViodiTV caught up with Junyoung Seo, COO of Opt AI, to discuss how their award-winning platform, OptHancer™, is bridging that divide.

The “Surgical” Approach to AI

As Seo explains in the interview, the current industry trend of “on-device AI” often hits a wall when massive models—like Meta’s Llama 3 or Google’s Gemma 2—meet the physical constraints of a smartphone or an edge device. Traditionally, developers have had to choose between speed and accuracy.

Opt AI’s solution? Surgical Model Re-Architecture. Unlike “black box” optimization tools that treat hardware as an afterthought, OptHancer™ performs a deep analysis of the target silicon (such as Qualcomm’s Snapdragon 8 Elite or the latest NPUs). By rebuilding models to speak the hardware’s native language, Opt AI achieves what Seo calls the “Any Model, Any Device” vision—allowing complex vision and language models to run locally without a cloud connection.

Why OptHancer™ Matters

Opt AI’s advancements aren’t just about faster gadgets; they address real-world challenges and unlock new possibilities:

Innovation Honored

The industry has taken notice. Opt AI was named a CES 2026 Innovation Award Honoree in the Artificial Intelligence category. This recognition follows successful collaborations with major players like LG Electronics and Hanwha Aerospace, signaling that Opt AI’s optimization tech is ready for the global stage.

[Note: the above text was directed and edited by the author, but written by Google’s Gemini].

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.