WEBVTT

00:00:03 --> 00:02:25
Transitioning to accelerated computing for application developers

00:02:25 --> 00:03:52
Demonstrating parallel processing capabilities and execution speeds

00:03:52 --> 00:05:53
Cost and power economics of hardware acceleration

00:05:53 --> 00:07:55
Refactoring software applications with domain specific SDKs

00:07:55 --> 00:09:58
Accelerating pandas dataframes using cudf module plugins

00:09:58 --> 00:12:44
Evolving traditional coding logic into LLM prompting

00:12:44 --> 00:16:00
Composing real time video flow applications utilizing multiple AI models

00:16:00 --> 00:18:05
Optimizing and deploying containerized AI inference workloads

00:18:05 --> 00:19:11
Accessing API microservices and extensible developer training programs

00:19:11 --> 99:59:59
Generating runtime optimizations across evolving physical hardware architectures