1
00:00:00,120 --> 00:00:02,840
Speaker 1: Hey everyone, it's Robert and Joe here. Today we've got

2
00:00:02,840 --> 00:00:04,720
Speaker 1: something a little bit different to share with you. It

3
00:00:04,840 --> 00:00:08,000
Speaker 1: is a new season of the Smart Talks with IBM

4
00:00:08,119 --> 00:00:09,119
Speaker 1: podcast series.

5
00:00:09,600 --> 00:00:11,680
Speaker 2: Today we are witnessed to one of those rare moments

6
00:00:11,680 --> 00:00:14,360
Speaker 2: in history, the rise of an innovative technology with the

7
00:00:14,360 --> 00:00:18,680
Speaker 2: potential to radically transform business and society forever. The technology,

8
00:00:18,760 --> 00:00:22,200
Speaker 2: of course, is artificial intelligence, and it's the central focus

9
00:00:22,239 --> 00:00:24,800
Speaker 2: for this new season of Smart Talks with IBM.

10
00:00:25,320 --> 00:00:28,400
Speaker 1: Join hosts from your favorite Pushkin podcasts as they talk

11
00:00:28,480 --> 00:00:31,640
Speaker 1: with industry experts and leaders to explore how businesses can

12
00:00:31,680 --> 00:00:35,360
Speaker 1: integrate AI into their workflows and help drive real change

13
00:00:35,400 --> 00:00:38,200
Speaker 1: in this new era of AI. And of course, host

14
00:00:38,280 --> 00:00:40,440
Speaker 1: Malcolm Gladwell will be there to guide you through the

15
00:00:40,479 --> 00:00:42,640
Speaker 1: season and throw in his two cents as well.

16
00:00:43,080 --> 00:00:46,120
Speaker 2: Look out for new episodes of Smart Talks with IBM

17
00:00:46,400 --> 00:00:49,519
Speaker 2: every other week on the iHeartRadio app, Apple Podcasts, or

18
00:00:49,560 --> 00:00:53,360
Speaker 2: wherever you get your podcasts. And learn more at IBM

19
00:00:53,479 --> 00:01:02,400
Speaker 2: dot com, slash smart Talks, Pushkin.

20
00:01:07,000 --> 00:01:10,480
Speaker 3: Hello, Hello, Welcome to Smart Talks with IBM, a podcast

21
00:01:10,520 --> 00:01:15,840
Speaker 3: from Pushkin Industries, iHeartRadio and IBM. I'm Malcolm Glamwell. This

22
00:01:15,959 --> 00:01:20,399
Speaker 3: season We're continuing our conversations with new creators visionaries who

23
00:01:20,440 --> 00:01:24,600
Speaker 3: are creatively applying technology and business to drive change, but

24
00:01:24,680 --> 00:01:28,360
Speaker 3: with a focus on the transformative power of artificial intelligence

25
00:01:28,680 --> 00:01:31,240
Speaker 3: and what it means to leverage AI as a game

26
00:01:31,319 --> 00:01:36,200
Speaker 3: changing multiplier for your business. On this special bonus episode

27
00:01:36,200 --> 00:01:39,560
Speaker 3: of Smart Talks, Tim Harford, host of the pushkin podcast

28
00:01:39,680 --> 00:01:43,560
Speaker 3: Cautionary Tales, sat down for a conversation with two leaders

29
00:01:44,040 --> 00:01:48,600
Speaker 3: forging new ways of working together encouraging collaboration to better

30
00:01:48,640 --> 00:01:53,360
Speaker 3: serve clients. Shriney Vawsan bent To Karajan is the director

31
00:01:53,440 --> 00:01:57,360
Speaker 3: of Global Partner Business, supervising Azure Data and AI as

32
00:01:57,440 --> 00:02:01,480
Speaker 3: well as Azure OpenAI at Microsoft. He's a leading thinker

33
00:02:01,840 --> 00:02:07,559
Speaker 3: behind digital transformation, business growth, and strategic innovation. And Chris

34
00:02:07,640 --> 00:02:11,880
Speaker 3: maguire is General Manager of the Global Microsoft Partnership for

35
00:02:11,919 --> 00:02:16,840
Speaker 3: IBM Consulting. He is responsible for driving IBM Consulting strategic

36
00:02:16,880 --> 00:02:21,600
Speaker 3: alignment and collaboration with Microsoft, bringing clients the technologies they

37
00:02:21,639 --> 00:02:25,480
Speaker 3: need with a focus on hybrid, cloud and AI. They

38
00:02:25,520 --> 00:02:28,600
Speaker 3: talked to Tim about the efforts of IBM and Microsoft

39
00:02:28,880 --> 00:02:32,880
Speaker 3: in the generative AI space. We're just at the beginning

40
00:02:32,880 --> 00:02:37,680
Speaker 3: of understanding what generative AI can create for customers, businesses,

41
00:02:38,000 --> 00:02:41,960
Speaker 3: and the broader world. This collaboration forward model will expand

42
00:02:42,000 --> 00:02:46,760
Speaker 3: the impact of AI, allowing innovation to thrive. Let's dive in.

43
00:02:49,720 --> 00:02:52,600
Speaker 4: Chris Sheeney, welcome both of you. Thank you so much

44
00:02:52,600 --> 00:02:56,680
Speaker 4: for joining me. Tell me a little bit about your roles. Scheney,

45
00:02:56,760 --> 00:02:58,839
Speaker 4: maybe you first just tell me a little bit about

46
00:02:58,840 --> 00:02:59,839
Speaker 4: what you do at Microsoft.

47
00:03:00,120 --> 00:03:02,280
Speaker 5: So I have about twenty seven years of experience in

48
00:03:02,320 --> 00:03:06,880
Speaker 5: the tech and consulting services industry, and in these twenty

49
00:03:06,919 --> 00:03:09,760
Speaker 5: seven years, I've had the privilege of leading the charge

50
00:03:09,800 --> 00:03:15,520
Speaker 5: and driving digital transformation, business growth, and strategic innovation for clients.

51
00:03:15,760 --> 00:03:20,160
Speaker 5: And in my current role as at Microsoft, I managed

52
00:03:20,200 --> 00:03:24,160
Speaker 5: the strategic partnership with IBM. I helped craft strategic questions

53
00:03:24,200 --> 00:03:27,919
Speaker 5: that align IBM's potential impact with Microsoft and did any

54
00:03:28,000 --> 00:03:28,760
Speaker 5: value proposition.

55
00:03:29,440 --> 00:03:33,800
Speaker 4: So, Chris, we've heard Suny runs the Microsoft half of

56
00:03:33,840 --> 00:03:36,640
Speaker 4: the partnership with IBM. Presumably you're on the other half

57
00:03:36,680 --> 00:03:38,160
Speaker 4: of that partnership.

58
00:03:38,080 --> 00:03:42,400
Speaker 6: Correct, correct, Yeah, about three years ago we decided to

59
00:03:43,080 --> 00:03:46,680
Speaker 6: really go big with Microsoft as far as the chief partnership.

60
00:03:47,520 --> 00:03:52,440
Speaker 4: So Microsoft and IBM are these giant names in technology,

61
00:03:52,800 --> 00:03:56,080
Speaker 4: very well known for decades So why is it so

62
00:03:56,160 --> 00:03:59,800
Speaker 4: important to have collaboration as well as competition in the

63
00:04:00,200 --> 00:04:02,040
Speaker 4: enterprise generative AI space.

64
00:04:02,920 --> 00:04:06,600
Speaker 6: It goes back to, you know, client first, their needs

65
00:04:06,680 --> 00:04:09,040
Speaker 6: have to be above everybody else's and if we're not

66
00:04:09,160 --> 00:04:12,280
Speaker 6: meeting their needs, then we're not responsibly doing our job.

67
00:04:12,800 --> 00:04:16,600
Speaker 6: And we have a platform. On the IBM tech side,

68
00:04:16,960 --> 00:04:19,360
Speaker 6: Microsoft is a platform and we in the middle as

69
00:04:19,400 --> 00:04:24,640
Speaker 6: IBM consulting have the expertise to properly design and take

70
00:04:24,680 --> 00:04:27,400
Speaker 6: the best interest of the client to heart and implement

71
00:04:27,560 --> 00:04:30,320
Speaker 6: and help them get to whatever outcomes they're trying to

72
00:04:30,360 --> 00:04:33,560
Speaker 6: get to, utilizing genera of AI to make better use

73
00:04:33,600 --> 00:04:37,720
Speaker 6: of data and the investment they've made, and to properly scale.

74
00:04:37,960 --> 00:04:41,680
Speaker 6: I mean, Microsoft has a unique approach to GENDERAI. They're

75
00:04:41,680 --> 00:04:45,880
Speaker 6: doing desktop up so they have a great user base

76
00:04:45,960 --> 00:04:49,680
Speaker 6: globally with all of their office products and other solutions

77
00:04:49,680 --> 00:04:52,719
Speaker 6: that most people use in the world today, so making

78
00:04:52,839 --> 00:04:56,400
Speaker 6: genera of AI available to them is fantastic. And then us,

79
00:04:56,440 --> 00:04:59,159
Speaker 6: you know, we have a platform down approach at IBM,

80
00:04:59,640 --> 00:05:01,960
Speaker 6: and if we do things right together, we'll meet in

81
00:05:01,960 --> 00:05:05,120
Speaker 6: the middle and jointly help solve those clients problems.

82
00:05:06,040 --> 00:05:08,000
Speaker 4: So just want to understand what this looks like we're

83
00:05:08,000 --> 00:05:12,440
Speaker 4: starting to discover that these AI systems actually it's possible

84
00:05:12,440 --> 00:05:14,200
Speaker 4: to build lots and lots of different ones. There are

85
00:05:14,440 --> 00:05:19,480
Speaker 4: different varieties that have different strengths, different weaknesses. So from

86
00:05:19,520 --> 00:05:23,760
Speaker 4: the point of view of a customer when they approach you,

87
00:05:23,760 --> 00:05:25,720
Speaker 4: when you say, well, we've got this ecosystem, you've got

88
00:05:25,720 --> 00:05:27,599
Speaker 4: access to various models. How what does that look like?

89
00:05:27,680 --> 00:05:29,280
Speaker 4: Is it like an app store or is it something

90
00:05:29,279 --> 00:05:29,880
Speaker 4: a bit different.

91
00:05:30,839 --> 00:05:34,240
Speaker 5: Certain models are good for certain use cases. Now I

92
00:05:34,279 --> 00:05:37,000
Speaker 5: think you might have heard that earlier. We used to

93
00:05:37,040 --> 00:05:41,600
Speaker 5: hear about large language models LM's. Now the smaller language

94
00:05:41,600 --> 00:05:45,159
Speaker 5: model also are becoming popular because it can do certain

95
00:05:45,200 --> 00:05:49,359
Speaker 5: things very effectively. It just trained on certain domains and

96
00:05:49,480 --> 00:05:50,479
Speaker 5: also respond faster.

97
00:05:50,880 --> 00:05:52,919
Speaker 4: So a small language model is basically just we're going

98
00:05:53,000 --> 00:05:56,400
Speaker 4: to train you on I know, the manuals for all

99
00:05:56,400 --> 00:05:59,120
Speaker 4: our technical products, so you really understand if people have

100
00:05:59,160 --> 00:05:59,960
Speaker 4: a problem with our product.

101
00:06:00,560 --> 00:06:04,799
Speaker 5: Yeah, it could be for example, trained specifically for healthcare

102
00:06:04,839 --> 00:06:09,520
Speaker 5: domain right, things like that, or it could also be

103
00:06:09,720 --> 00:06:14,280
Speaker 5: trained for certain user profiles, right for the typical work

104
00:06:14,320 --> 00:06:17,200
Speaker 5: that they do, for example in a call center or

105
00:06:17,279 --> 00:06:22,560
Speaker 5: in a hospital. How the certain things can be done faster.

106
00:06:22,760 --> 00:06:22,960
Speaker 2: Right.

107
00:06:23,960 --> 00:06:27,080
Speaker 5: The advantage of small language models is that it makes

108
00:06:27,120 --> 00:06:29,599
Speaker 5: it possible to run on smaller missines so that you

109
00:06:29,600 --> 00:06:31,560
Speaker 5: don't need large service and things like that.

110
00:06:32,720 --> 00:06:36,080
Speaker 4: So what I'm hearing is that people are coming to

111
00:06:36,120 --> 00:06:39,400
Speaker 4: you while they're coming to IBM and basically going, hey,

112
00:06:39,440 --> 00:06:42,320
Speaker 4: we've heard about all this cool AI stuff and what

113
00:06:42,360 --> 00:06:44,800
Speaker 4: do we do? Because of course that's that's where your

114
00:06:44,839 --> 00:06:48,560
Speaker 4: starting point is because the technology is so new the In.

115
00:06:48,480 --> 00:06:52,279
Speaker 5: Fact, in fact, IBM did a hackaton Global Hackaton, and

116
00:06:52,760 --> 00:06:55,719
Speaker 5: this was the first of its kind that they did

117
00:06:55,800 --> 00:06:59,799
Speaker 5: where they actually brought in the client teams also okay,

118
00:06:59,839 --> 00:07:02,080
Speaker 5: so they said that, okay, let us see how we

119
00:07:02,160 --> 00:07:06,000
Speaker 5: can actually ideate with the clients to solve their problems, right,

120
00:07:06,440 --> 00:07:10,080
Speaker 5: and they came up with quick innovative use cases and

121
00:07:10,200 --> 00:07:13,840
Speaker 5: some of these actually translated into projects that the implemented.

122
00:07:14,520 --> 00:07:16,800
Speaker 4: Can you think of an example one of these projects

123
00:07:16,640 --> 00:07:17,760
Speaker 4: that sticks in your mind?

124
00:07:18,080 --> 00:07:22,960
Speaker 5: Yeah, So there's a client wintershell where IBM actually co

125
00:07:23,080 --> 00:07:27,240
Speaker 5: created a knowledge extraction too to help the field engineers

126
00:07:27,280 --> 00:07:31,240
Speaker 5: to retrieve relevant insights from the vast knowledge baser. So

127
00:07:31,560 --> 00:07:35,560
Speaker 5: winter Shall is an energy company and as part of

128
00:07:35,600 --> 00:07:40,440
Speaker 5: the innovation effort, Edminterschal. They also did identified eighty new

129
00:07:40,640 --> 00:07:42,880
Speaker 5: AI use cases chrise.

130
00:07:43,440 --> 00:07:46,560
Speaker 4: If a corporate leader were to come to you and say, look,

131
00:07:47,280 --> 00:07:50,920
Speaker 4: I'm sure Jeni AI is going to shake up my industry.

132
00:07:52,240 --> 00:07:54,560
Speaker 4: It's going to be a competitive threat and show there

133
00:07:54,600 --> 00:07:56,960
Speaker 4: are loads of opportunities as well, but I don't know

134
00:07:57,000 --> 00:08:00,200
Speaker 4: how to start thinking about it. What's the basic advance

135
00:08:00,240 --> 00:08:04,000
Speaker 4: that you'd give them to orient themselves and the questions

136
00:08:04,000 --> 00:08:05,320
Speaker 4: that they should be asking themselves.

137
00:08:06,040 --> 00:08:09,520
Speaker 6: Well, I mean, obviously it's our ability to get with

138
00:08:09,560 --> 00:08:13,120
Speaker 6: a client and bring the relevant partners to the table,

139
00:08:13,520 --> 00:08:16,400
Speaker 6: uh to discuss the outcome that the client is trying

140
00:08:16,440 --> 00:08:20,880
Speaker 6: to achieve and then design a solution because I mean, obviously,

141
00:08:20,920 --> 00:08:22,880
Speaker 6: if you're you know, you want to make sure your

142
00:08:23,160 --> 00:08:25,480
Speaker 6: your your money is well spent. And given that in

143
00:08:25,520 --> 00:08:28,280
Speaker 6: the world of software everything has moved to a consumption

144
00:08:28,400 --> 00:08:31,280
Speaker 6: model and you're only paying for what you use, you

145
00:08:31,320 --> 00:08:33,360
Speaker 6: want to make sure you're getting the most efficient use

146
00:08:33,360 --> 00:08:35,880
Speaker 6: out of those platforms. And you know, we at IBM

147
00:08:36,000 --> 00:08:40,400
Speaker 6: Consulting have become extreme experts on advising clients how to

148
00:08:40,400 --> 00:08:43,160
Speaker 6: do that. And you know, it's it's a great story

149
00:08:43,200 --> 00:08:47,480
Speaker 6: now when we walk in together because over decades and decades,

150
00:08:47,640 --> 00:08:50,920
Speaker 6: IBM and Microsoft have been there at the table as

151
00:08:51,040 --> 00:08:54,880
Speaker 6: a trusted technology advisor and service provider.

152
00:08:56,559 --> 00:09:00,240
Speaker 4: The theme of this season of Smart Talks is new

153
00:09:00,280 --> 00:09:06,360
Speaker 4: Creators and that's you guys. Yeah, your new creators. So

154
00:09:06,480 --> 00:09:08,360
Speaker 4: I wanted to ask you both, maybe start with Chris,

155
00:09:08,880 --> 00:09:11,400
Speaker 4: what do you see as the most creative part of

156
00:09:12,960 --> 00:09:13,560
Speaker 4: what you do?

157
00:09:15,360 --> 00:09:15,520
Speaker 5: Well?

158
00:09:15,559 --> 00:09:17,760
Speaker 6: I think it's it goes back to the ecosystem, but

159
00:09:18,000 --> 00:09:20,680
Speaker 6: you know it's the age old saying two heads better

160
00:09:20,720 --> 00:09:22,679
Speaker 6: than one, three heads better than two, on and on,

161
00:09:23,040 --> 00:09:25,680
Speaker 6: and also that you know, what we like to say

162
00:09:25,760 --> 00:09:28,440
Speaker 6: is the way we're doing origosmus one plus one equals three,

163
00:09:28,960 --> 00:09:30,800
Speaker 6: especially when it comes to Microsoft.

164
00:09:30,920 --> 00:09:33,120
Speaker 4: You know, generative AI is never were very good at maths,

165
00:09:33,120 --> 00:09:37,640
Speaker 4: were they so? Okay exactly, but they're creative so that's great.

166
00:09:37,840 --> 00:09:44,520
Speaker 6: So it really is about solving clients real problems and

167
00:09:44,679 --> 00:09:47,720
Speaker 6: using the very best of the technology that's available today

168
00:09:47,760 --> 00:09:50,120
Speaker 6: to do that as fast as possible and get them

169
00:09:50,480 --> 00:09:53,480
Speaker 6: to a place where they're actually monetizing as fast as

170
00:09:53,520 --> 00:09:56,360
Speaker 6: they can. It is really important that we take our

171
00:09:56,600 --> 00:09:59,760
Speaker 6: part in this whole AI revolution very seriously and be

172
00:09:59,840 --> 00:10:02,720
Speaker 6: very very responsible, and we take that job very seriously,

173
00:10:02,760 --> 00:10:06,439
Speaker 6: and Microsoft is a very strong partner with us when

174
00:10:06,440 --> 00:10:07,680
Speaker 6: we go into clients together.

175
00:10:08,920 --> 00:10:10,880
Speaker 4: Shoney, what's creative about what you do?

176
00:10:11,679 --> 00:10:14,800
Speaker 5: Yeah? So when I started my career, I was a

177
00:10:14,800 --> 00:10:18,280
Speaker 5: software developer, so problem solving was one of the core

178
00:10:18,360 --> 00:10:22,800
Speaker 5: competency that I had to work on. And that problem

179
00:10:22,840 --> 00:10:27,040
Speaker 5: solving mindset, along with the industry knowledge that I gained

180
00:10:27,080 --> 00:10:30,880
Speaker 5: over the years, helped me identify the market trends, the

181
00:10:31,040 --> 00:10:35,640
Speaker 5: consumer behavior, the disruptive technologies has helped me come up

182
00:10:35,679 --> 00:10:38,000
Speaker 5: with some creative ideas and solutions as part of my job.

183
00:10:39,200 --> 00:10:41,400
Speaker 4: Chris Sheeney, thank you both very much.

184
00:10:46,000 --> 00:10:49,760
Speaker 3: What an insightful conversation with Chris and Schreeney shedding light

185
00:10:49,840 --> 00:10:54,720
Speaker 3: on the efforts of IBM and Microsoft. Technologies like AI

186
00:10:54,840 --> 00:10:59,160
Speaker 3: are complex and often difficult to scale without help. A

187
00:10:59,240 --> 00:11:02,920
Speaker 3: partner eco system approach is crucial in the world of AI.

188
00:11:03,640 --> 00:11:07,760
Speaker 3: By bringing together diverse expertise, collaboration can cater to a

189
00:11:07,840 --> 00:11:13,120
Speaker 3: variety of industries, providing specialized solutions for unique challenges. As

190
00:11:13,120 --> 00:11:17,480
Speaker 3: strategic partners, IBM and Microsoft aimed to guide enterprises through

191
00:11:17,520 --> 00:11:22,840
Speaker 3: these challenges responsibly. Looking ahead. The possibilities opened by an

192
00:11:22,840 --> 00:11:27,160
Speaker 3: ecosystem approach to AI are endless, from the integration of

193
00:11:27,200 --> 00:11:30,400
Speaker 3: the tech into everyday devices in our pockets all the

194
00:11:30,400 --> 00:11:35,280
Speaker 3: way to its increased adoption in highly regulated, intricate industries.

195
00:11:35,880 --> 00:11:38,640
Speaker 3: A huge thank you is due to Chris and Trainey

196
00:11:39,040 --> 00:11:44,480
Speaker 3: for sharing their expertise and insights. Smart Talks with IBM

197
00:11:44,600 --> 00:11:48,959
Speaker 3: is produced by Matt Romano, Joey Fishground and Jacob Goldstein

198
00:11:49,360 --> 00:11:52,839
Speaker 3: were edited by Lydia Jane Kott. Our engineers are Sarah

199
00:11:52,840 --> 00:11:57,480
Speaker 3: Bugaier and Ben Tolliday. Theme song by Gramoscope. Special thanks

200
00:11:57,679 --> 00:12:01,120
Speaker 3: to Andy Kelly, Kathy Callahan and the eight Bar and

201
00:12:01,240 --> 00:12:05,440
Speaker 3: IBM teams, as well as the Pushkin marketing team. Smart

202
00:12:05,440 --> 00:12:08,280
Speaker 3: Talks with IBM is a production of Pushkin Industries and

203
00:12:08,360 --> 00:12:12,880
Speaker 3: Ruby Studio at iHeartMedia. To find more Pushkin podcasts, listen

204
00:12:12,920 --> 00:12:17,360
Speaker 3: on the iHeartRadio app, Apple Podcasts, or wherever you listen

205
00:12:17,559 --> 00:12:22,120
Speaker 3: to podcasts. I'm Malcolm Glabwell. This is a paid advertisement

206
00:12:22,400 --> 00:12:36,240
Speaker 3: from IBM.