Navigating the Challenges of Cloud-Native Integration in Hybrid Networks

"So already this year we've rolled out 10 of these regions. So two in APJ and Kuala Lumpur and Hong Kong. But 75 of these locations by the end of the year along with our core computing regions will give us 100 locations where customers can run these workloads, and we're not going to stop there. So we're going to have hundreds of these regions over the next few years, and we're going to focus on those locations where hyper-scalers don't have compute. Africa and South America, for example, have been extremely underserved when it comes to computing capabilities. There's a huge potential for those countries if we could get them the compute. And that's exactly what we intend to do. But, those are extreme regions. Even in places like the U.S., which are well served by the hyper-scalers, there's certainly the middle of the U.S. which is ignored. In Southeast Asia, if you're in Singapore or Jakarta, you're served by everybody. But if you're in Vietnam, how are you served? If you're in Thailand, how are you served? The internet is inherently unfair. We want to make it more fair for our customers and our customers' customers." - Jay Jenkins

Fresh off the studio, Jay Jenkins, CTO of Cloud Computing in Akamai, dives deep into the transformative potential of edge AI in a dynamic conversation on Akamai's latest technological advancements. Discussing the company's strategic edge computing platform, Gecko, Jenkins describes how it is redefining cloud computing paradigms by embedding capabilities directly into the edge network. He explores the broader implications of edge AI for real-time applications and generative AI technologies, highlighting Akamai's vision to support the burgeoning demands of data processing and AI inferencing at the network edge. With insights into early trials and future use cases, he shares how Akamai is set to revolutionize industries, from immersive retail to spatial computing and explores what great would look like for Akamai in cloud computing and AI at the edge.

Episode Highlights: [0:40] Quote of the Day #QOTD by Jay Jenkins. [1:45] Introduction: Jay Jenkins, CTO of Cloud Computing from Akamai. [4:29] Lessons learnt from Jay’s career journey. [6:31] Total Market Opportunity for AI at the Edge and Akamai’s value proposition. [8:55] Introduction to Akamai and its global footprint. [11:18] Jay’s role as global CTO in Cloud Computing and future vision. [16:23] Generalized Edge Compute aka Gecko and why it differs from the hyper-scalers such as AWS. [19:53] How Gecko enhances the user experience in terms of performance and latency. [22:59] Challenges to integrate cloud native computing at a massive edge network. [25:38] Lessons learned from Gecko’s early trials with enterprise customers of Akamai. [28:01] Applications of Gecko beyond immersive retail. [30:33] The One Thing that Jay knows about Gecko in generalized edge computing that very few do. [33:07] Generative AI with Akamai Gecko’s platform. [37:30] Inference at the edge with Large Language Models (LLMs). [39:41] Role of Edge Computing for real-time AI processes. [41:47] What does great look like for Akamai in the cloud computing space? [43:53] Closing.

Podcast Information: Bernard Leong hosts and produces the show. Proper credits for the intro and end music: "Energetic Sports Drive" and the episode is mixed & edited in both video and audio format by G. Thomas Craig

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