התמלול המלא של Smart Talks with IBM - The Power of Collaboration: How IBM Teams Up with Microsoft

craft strategic quitions that align IBM's potential impact with Microsoft and did any value proposition. 00:03:38 Speaker 3: So, Chris, we've heard Schweney runs the Microsoft half of the partnership with IBM. I presumably you're on the other half of that partnership. 00:03:47 Speaker 5: Correct, correct, Yeah, about three years ago we decided to really go big with Microsoft as far as the chief partnership. 00:03:56 Speaker 3: So Microsoft and IBM are these giant aims in technology, very well known for decades. So why is it so important to have collaboration as well as competition in the enterprise generative AI space? 00:04:12 Speaker 5: It goes back to client first. Their needs have to be above everybody else's and if we're not meeting their needs, then we're not responsibly doing our job. And we have a platform. On the IBM tech side, Microsoft is a platform and we in the middle, as IBM consulting have the expertise to properly design and take the best interest of the client to heart and implement and help them get to whatever outcomes they're trying to get to, utilizing genera of AI to make better use of data and the investment they've made, and to properly scale. I mean, Microsoft has a unique approach to GENDERAI. They're doing desktop up so they have a great user base globally with all of their office products and other solutions that most people we use in the world today, so making general of AI available to them is fantastic. And then us, you know, we have a platform down approach at IBM, and if we do things right together, we'll meet in the middle and jointly help solve those clients problems. 00:05:15 Speaker 3: So just want to understand what this looks like. We're starting to discover that these AI systems actually it's possible to build lots of lots of different ones. There are different varieties that have different strengths different weaknesses. So from the point of view of a customer when they approach you, when you say, well, we've got this ecosystem, you've got access to various models. How what does that look like? Is it like an app store or is it something a bit different. 00:05:40 Speaker 4: Certain models are good for certain use cases. Now I think you might have heard that earlier. We used to hear about large language modess lms. Now the smaller language model also are becoming popular because it can do certain things very effectively. It just trained on certain domains and also respond faster. 00:06:00 Speaker 3: So a small language model is basically just we're going to train you on I know, the manuals for all our technical products, so you really understand if people have a problem with our product. 00:06:09 Speaker 4: Yeah, it could be for example, trained specifically for healthcare domain, right, things like that, or it could also be trained for certain user profiles, right for the typical work that they do, for example in a call center or in a hospital. How the certain things can be done faster, right. The advantage of small language models is that it makes it possible to run on smaller machines, so you don't need large service and things like that. 00:06:41 Speaker 3: So what I'm hearing is that people are coming to you while they're coming to IBM and basically going, hey, we've heard about all this cool AI stuff and what do we do? Because of course that's that's where your starting point is because the technology is so new the. 00:06:57 Speaker 4: In fact, in fact, IBM did a Hapaton Global hackat on and this was the first of its kind that they did where they actually brought in the client teams also okay, so they said that, okay, let us see how we can actually ideate with the clients to solve their problems, right, and they came up with quick innovative use cases and some of these actually translated into projects that the implemented. 00:07:23 Speaker 3: Can you think of an example one of these projects that sticks in your mind? 00:07:27 Speaker 4: Yeah, So there's a client Wintershell where IBM actually co created a knowledge extraction too to help the field engineers to retrieve relevant insights from the vast knowledge baser. So Wintershall is an energy company and as part of their innovation effort Edwinterishal, they also did identified eighty new AI use cases. 00:07:51 Speaker 3: Craz if a corporate leader were to come to you and say, look, I'm sure Jeni AI is going to shake up my industry. It's going to be a competitive threat. I'm sure there are loads of opportunities as well, but I don't know how to start thinking about it. What's the basic advice that you you'd give them to orient themselves and the questions that they should be asking themselves. 00:08:15 Speaker 5: Well, I mean, obviously it's our ability to get with a client and bring the relevant partners to the table to discuss the outcome that the client is trying to achieve and then design a solution. Because I mean, obviously, if you're you know, you want to make sure your your your money is well spent. And given that in the world of software everything has moved to a consumption model and you're only paying for what you use, you want to make sure you're getting the most efficient use out of those platforms. And you know, we at IBM Consulting have become extreme experts on advising clients how to do that. And you know, it's it's a great story now when we walk in together because over decades and decades, IBM and Microsoft have been there at the table as a trusted technology advisor and service provider. 00:09:05 Speaker 3: The theme of this season of Smart Talks is new Creators and that's you guys. Yeah, your new creators. So I wanted to ask you both, maybe start with Chris, what do you see as the most creative part of what you do? 00:09:24 Speaker 2: Well? 00:09:24 Speaker 5: I think it's it goes back to the ecosystem, but you know it's the age old saying two heads better than one, three heads better than two, on and on, and also that you know, what we like to say is the way we're doing our ecosmus one plus one equals three, especially when it comes to Microsoft. 00:09:40 Speaker 3: You know, generative aies never were very good at maths, were they so? 00:09:43 Speaker 5: Okay? 00:09:44 Speaker 3: Exactly, But they're creative so that's great. 00:09:47 Speaker 5: So it really is about solving clients real problems and using the very best of the technology that's available today to do that as fast as possible, and it get them to a where they're actually monetizing as fast as they can. It is really important that we take our part in this whole AI revolution very seriously and be very very responsible, and we take that job very seriously. And Microsoft is a very strong partner with us when we go into clients together. 00:10:18 Speaker 3: Shoney, what's creative about what you do. 00:10:20 Speaker 5: Yeah. 00:10:21 Speaker 4: So when I started my career, I was a software developer, so problem solving was one of the core competency that I had to work on. And that problem solving mindset, along with the industry knowledge that I gained over the years, help me identify the market trends, the consumer behavior, the disruptive technologies helped me come up with some creative ideas and solutions as part of my job. 00:10:48 Speaker 3: Chris Sheeney, thank you both very much. 00:10:55 Speaker 2: What an insightful conversation with Chris and Shreey shedding light on the efforts of IBM and Microsoft. Technologies like AI are complex and often difficult to scale without help. A partner ecosystem approach is crucial in the world of AI. By bringing together diverse expertise, collaboration can cater to a variety of industries, providing specialized solutions for unique challenges. As strategic partners, IBM and Microsoft aimed to guide enterprises through these challenges responsibly looking ahead. The possibilities opened by an ecosystem approach to AI are endless, from the integration of the tech into everyday devices in our pockets, all the way to its increased adoption in highly regulated intricate industries. A huge thank you is due to Chris and Trainey for sharing their expertise and insights. Smart Talks with IBM is produced by Matt Romano, Joey Fishground and Jacob Goldstein were edited by lydia Ji Being Caught. Our engineers are Sarah Buguaer and Ben Tolladay. Theme song by Gramoscope. Special thanks to Andy Kelly, Kathy Callahan and the eight Bar and IBM teams, as well as the Pushkin marketing team. Smart Talks with IBM is a production of Pushkin Industries and Ruby Studio at iHeartMedia. To find more Pushkin podcasts, listen on the iHeartRadio app, Apple Podcasts, or wherever you listen to podcasts. I'm Malcolm Glabwell. This is a paid advertisement from IBM.