Akamai Cloud Computing & The Age of Edge AI with Jay Jenkins

Akamai Cloud Computing & The Age of Edge AI with Jay Jenkins
Jay Jenkins shares the vision of Akamai's cloud computing and their new generalized edge compute, Gecko and how it works in the age of generative AI at the edge.

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.

"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


  • Jay Jenkins, CTO, Cloud Computing, Akamai (LinkedIn, @jaydjenkins)
  • Let’s start with the origin story, how did you start your career?
  • How did you end up working with Akamai and where are you currently based? 
  • What interesting lessons can you share with my audience in your career journey?

Akamai in the age of Edge AI

  • Let’s start with the market opportunity, can you explain your definition of AI at the edge, the total market opportunity and the value proposition for enterprises and specifically why Akamai is poised to capture this market?  
  • Can you introduce the company Akamai, its global vision and mission and its current footprint in the Asia Pacific region?
  • What is your current role and coverage as the CTO of Akamai? 
  • As CTO, what are your long-term visions for Akamai’s role in the evolving landscape of cloud computing and edge networks?
  • Can you elaborate on the core concept of Gecko and how it differentiates Akamai's cloud computing approach from traditional models?
  • What inspired the shift towards embedding cloud computing capabilities into Akamai's edge network?
  • How does Akamai's Generalized Edge Compute (Gecko) enhance the user experience, especially in terms of performance and latency?
  • Could you discuss the challenges Akamai faced while integrating cloud-native computing capabilities with its massive edge network?
  • How does integrating Gecko into Akamai’s network address the limitations of current cloud and edge architectures?
  • Can you provide some insights into the early trials of Gecko with enterprise customers and the feedback received?
  • What are the potential future use cases for Gecko, especially in fields like immersive retail and spatial computing?
  • What is the one thing you know about Gecko in generalized edge computing that very few do?
  • How does Akamai's Gecko platform plan to leverage edge AI capabilities to enhance its services, particularly in AI inferencing and data analytics?
  • In what ways can generative AI technologies benefit from Akamai's distributed cloud and edge computing infrastructure provided by Gecko?
  • Could you share insights on the role of edge computing in facilitating real-time AI processes and how Gecko is optimised for such tasks?
  • How does Akamai envision supporting the evolving needs of generative AI applications in terms of computational power and data processing at the edge?
  • Can you discuss any potential collaborations or innovations Akamai is exploring in generative AI using the Gecko platform?
  • What does great look like for Akamai in the next few years? 


Podcast Information: Bernard Leong (@bernardleongLinkedin) 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 (@gthomascraigLinkedIn).