WEBVTT 00:00:00.041 --> 00:00:02.460 We are here at AWS re:Invent 00:00:02.460 --> 00:00:05.338 and the future of Cloud and Gen 00:00:05.422 --> 00:00:08.425 AI and the overlap is a key focus. 00:00:08.550 --> 00:00:12.804 With me is an expert on both matters, Filippo Scognamiglio 00:00:13.013 --> 00:00:15.598 He is a Managing Director and Partner at BCG. 00:00:15.598 --> 00:00:18.476 He is also Global Head of Cloud Advisory. 00:00:18.476 --> 00:00:21.312 Filippo, thanks in advance for the time. Thanks for having me. 00:00:21.312 --> 00:00:24.315 So this year has been a breakout year. 00:00:24.315 --> 00:00:26.609 Gen AI: super hot topic. 00:00:26.609 --> 00:00:30.071 What effects are you seeing on the cloud industry? 00:00:30.155 --> 00:00:32.741 Well, first and foremost, tremendous amounts of investment. 00:00:32.741 --> 00:00:36.953 Microsoft clearly has a leading partnership with Open AI and they've been 00:00:37.037 --> 00:00:41.207 making great inroads and building capabilities on their cloud platform, Azure. 00:00:41.291 --> 00:00:45.503 Amazon and Google have been racing to catch up, and potentially even leapfrog 00:00:45.503 --> 00:00:47.297 what Microsoft has been doing and pouring 00:00:47.297 --> 00:00:50.258 tremendous amounts of investment in this space. 00:00:50.258 --> 00:00:53.928 So at BCG, you have introduced a standardized 00:00:53.928 --> 00:00:56.931 pricing index for the cloud industry. 00:00:57.098 --> 00:00:58.683 What are you seeing? 00:00:58.683 --> 00:01:00.143 Well, lots of surprises. 00:01:00.143 --> 00:01:02.562 In fact, it's our first attempt at creating the equivalent 00:01:02.562 --> 00:01:05.398 of a Big Mac index, but for cloud resources specifically 00:01:05.398 --> 00:01:08.818 to make them comparable in a space where historically, prices 00:01:08.818 --> 00:01:12.155 really were not that comparable considering their complexity. 00:01:12.238 --> 00:01:15.784 In looking at these comparisons, we found actually quite a lot of surprises. 00:01:15.825 --> 00:01:20.205 I think the biggest one is that cloud is not more affordable in emerging economies. 00:01:20.288 --> 00:01:23.541 Matter of fact, it is more expensive in emerging economies, 00:01:23.625 --> 00:01:26.503 the cheapest location to run cloud workloads actually happens 00:01:26.503 --> 00:01:29.923 to be the US, which is not what we expected when we initiated this research. 00:01:30.006 --> 00:01:31.382 Yeah that’s surprising. 00:01:31.382 --> 00:01:36.387 So when you think of the year ahead and for those who are looking to utilize 00:01:36.429 --> 00:01:40.391 GenAI, I have to ask you an age old tech question, 00:01:40.391 --> 00:01:43.394 is it better to build or is it better to buy? 00:01:43.478 --> 00:01:47.398 When it comes to web scale, large language models; buy is definitely the choice 00:01:47.398 --> 00:01:50.443 right now. Trying to replicate what some of these companies have done 00:01:50.443 --> 00:01:54.531 in your own local environment is prohibitively expensive. 00:01:54.614 --> 00:01:55.323 I do believe that 00:01:55.323 --> 00:01:58.326 in the future we will find more specialized models 00:01:58.326 --> 00:02:02.163 that can operate at a smaller scale for specific purposes and use cases. 00:02:02.247 --> 00:02:06.376 And with that class of models, I think we'll find an opportunity to build, 00:02:06.376 --> 00:02:12.006 in addition to relying on the quote “bought” models from cloud service parts themselves. 00:02:12.090 --> 00:02:13.508 Filippo, thank you very much. 00:02:13.508 --> 00:02:16.636 Filippo Scognamiglio joining us there.