Скачать или смотреть [37] MediaTek Interview: Finbarr Moynihan and Amy Guesner

After the last few years in the industry, I've noticed that we've been speaking about AI on the edge, and there has been a concerted effort to bring the best models onto our handheld devices. However, there are limitations. Memory capacity is the big one, but these models work best when they support built-in acceleration. These are AI accelerators in everything from edge to TV to automotive to smartphone to PC. Time to first token and how many tokens per second are becoming the de facto standard metrics in generative AI. However, the AI and machine learning space is more than just generative. Not only do we have large language models and stable diffusion, but we also have machine learning to do many things on many devices. Even something as simple as power management these days is optimized by machine learning. This is why you need stuff on the device to help with battery life, to help with performance.

In order to find out more, I spoke to MediaTek's Finbarr Moynihan and Amy Guesner about what it takes to enable NPUs from edge to cloud.

https://i.mediatek.com/ai to find out more.

[00:00] - Introduction to AI on the Edge
[01:00] - Limitations of Edge Devices
[02:40] - Importance of Running AI Models on the Edge
[05:00] - Applications of AI Beyond Generative Models
[07:00] - Power Management Optimized by AI
[09:30] - MediaTek’s End-to-End Strategy for AI
[11:00] - MediaTek’s Market Position and AI Portfolio
[13:20] - Generative AI and Its Future Impact
[16:00] - MediaTek's AI Strategy and Cross-Device Integration
[19:00] - The Role of AI in Automotive and Consumer Devices
[22:00] - MediaTek's Partnership with Nvidia
[25:00] - Developer Ecosystem and AI Tools
[28:00] - MediaTek's Future Direction in AI and Custom Silicon


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