1
00:00:00,120 --> 00:00:04,280
Speaker 1: We're focusing on how IBM is advancing generative AI. Arvind

2
00:00:04,360 --> 00:00:07,080
Speaker 1: Krishna he is IBM chairman and CEO. He spoke with

3
00:00:07,160 --> 00:00:10,280
Speaker 1: Wall Street Week host David Weston yesterday at the Milkin

4
00:00:10,360 --> 00:00:12,799
Speaker 1: Institute Global Conference in Los Angeles.

5
00:00:15,120 --> 00:00:17,239
Speaker 2: Exactly a year. I think if edymon but I David.

6
00:00:17,239 --> 00:00:20,680
Speaker 3: We announced it what's the next product at think in

7
00:00:20,760 --> 00:00:24,000
Speaker 3: May last year, and since then, the excitement in our

8
00:00:24,040 --> 00:00:29,320
Speaker 3: clients embracing the technology, getting the technology deployed, asking for expertise,

9
00:00:29,360 --> 00:00:30,560
Speaker 3: and getting projects going.

10
00:00:30,800 --> 00:00:32,360
Speaker 2: I think all of that has been wonderful.

11
00:00:32,880 --> 00:00:35,560
Speaker 3: Our inception to date book of business nine seeds of

12
00:00:35,640 --> 00:00:36,400
Speaker 3: billion dollars.

13
00:00:36,640 --> 00:00:38,720
Speaker 2: That's pretty good for a year. And I think and

14
00:00:38,760 --> 00:00:39,960
Speaker 2: it speaks to the excitement.

15
00:00:40,240 --> 00:00:42,640
Speaker 3: And I think what's even more, our clients are excited

16
00:00:42,640 --> 00:00:44,760
Speaker 3: about what it does for them. You can see them

17
00:00:45,000 --> 00:00:49,360
Speaker 3: the user for customer experience, for programming apporting as it's called,

18
00:00:49,680 --> 00:00:52,640
Speaker 3: as well as for helping improve the enterprise. All of

19
00:00:52,680 --> 00:00:56,120
Speaker 3: this put together is really exciting in how our enterprise

20
00:00:56,160 --> 00:00:57,880
Speaker 3: clients are embracing the generative AI.

21
00:00:58,200 --> 00:01:00,360
Speaker 4: One of the things that people anticipate from general it's

22
00:01:00,360 --> 00:01:04,440
Speaker 4: an increase in productivity. Are you finding that with your customers.

23
00:01:04,520 --> 00:01:07,039
Speaker 4: Are they increasing criticulity and how do you measure that

24
00:01:07,120 --> 00:01:08,440
Speaker 4: increase in productivity?

25
00:01:08,840 --> 00:01:10,840
Speaker 2: I think David is both.

26
00:01:11,240 --> 00:01:14,520
Speaker 3: I think increase in productivity is important, but productivity can

27
00:01:14,560 --> 00:01:17,360
Speaker 3: be made into just cost cutting our efficiency. That's not

28
00:01:17,440 --> 00:01:20,240
Speaker 3: the primary reason. The primary reason I think our clients

29
00:01:20,240 --> 00:01:23,679
Speaker 3: are excited. Can they get more business done while holding

30
00:01:23,720 --> 00:01:26,880
Speaker 3: their costs in somewhat in control? And so it's really

31
00:01:26,959 --> 00:01:31,920
Speaker 3: about more of a revenue generator then productivity alone. Now,

32
00:01:31,920 --> 00:01:34,240
Speaker 3: of course it is a revenue generator because it's making

33
00:01:34,280 --> 00:01:36,560
Speaker 3: you more productive, and I think that is what is exciting.

34
00:01:36,720 --> 00:01:38,160
Speaker 2: Think about customer experience.

35
00:01:38,480 --> 00:01:40,720
Speaker 3: Yeah, you may save a dollar on somebody's time and

36
00:01:40,760 --> 00:01:43,560
Speaker 3: a call center, but that's not why. If you can

37
00:01:43,600 --> 00:01:46,679
Speaker 3: make the end client more satisfied they got that answer quicker,

38
00:01:46,840 --> 00:01:49,160
Speaker 3: they've got a better answer. Are they more likely to

39
00:01:49,200 --> 00:01:51,680
Speaker 3: come back and do more repeat business? I think that's

40
00:01:51,760 --> 00:01:52,720
Speaker 3: far more exciting.

41
00:01:53,520 --> 00:01:56,040
Speaker 4: There's a lot of discussion about how general AI will

42
00:01:56,080 --> 00:01:59,880
Speaker 4: grow and how it will evolve. You've really staked your

43
00:02:00,080 --> 00:02:04,480
Speaker 4: claim on an open architecture, including for IBM, but also

44
00:02:04,600 --> 00:02:08,240
Speaker 4: with Meta in your AI alliance. Tell us why that's important.

45
00:02:08,240 --> 00:02:10,639
Speaker 4: Why is open architecture important in AI?

46
00:02:11,200 --> 00:02:13,960
Speaker 2: Look, it's always around how do you drive innovation?

47
00:02:14,600 --> 00:02:16,800
Speaker 3: And in a case where people worry a lot about

48
00:02:16,880 --> 00:02:19,680
Speaker 3: what is the fair use, what is the copyright, what

49
00:02:19,760 --> 00:02:22,639
Speaker 3: is the IP protection of the data and methodology used

50
00:02:22,639 --> 00:02:24,920
Speaker 3: to train AI, you have both those going on.

51
00:02:25,400 --> 00:02:27,400
Speaker 2: So in order to drive open.

52
00:02:27,360 --> 00:02:29,320
Speaker 3: What we are doing is we're taking some of our

53
00:02:29,360 --> 00:02:32,680
Speaker 3: base models, as Meta has done, and we are putting

54
00:02:32,680 --> 00:02:36,040
Speaker 3: them out under an open license for the epaty license,

55
00:02:36,240 --> 00:02:38,200
Speaker 3: which means people are free to build upon it.

56
00:02:38,480 --> 00:02:40,239
Speaker 2: And what the build upon is their. They don't have

57
00:02:40,320 --> 00:02:41,200
Speaker 2: to give it back to us.

58
00:02:41,720 --> 00:02:44,280
Speaker 3: When you care a lot about maybe some proprietary data

59
00:02:44,320 --> 00:02:47,400
Speaker 3: instead an enterprise and you use that AD skills to

60
00:02:47,480 --> 00:02:50,280
Speaker 3: an AI model and you can now say, oh, because

61
00:02:50,320 --> 00:02:52,920
Speaker 3: yours is open, it's now mine what is best?

62
00:02:53,120 --> 00:02:56,400
Speaker 2: I think it makes it block got interesting to the enterprise.

63
00:02:56,600 --> 00:03:00,519
Speaker 4: So IBM with wats an excess really pursuing enterprise base AI.

64
00:03:01,120 --> 00:03:05,520
Speaker 4: Does that get around the challenges of intellectual property because

65
00:03:05,520 --> 00:03:09,800
Speaker 4: there are issues in consumer facing about copyright about what

66
00:03:09,800 --> 00:03:11,560
Speaker 4: you're going to learn on? Is it the way it

67
00:03:11,600 --> 00:03:14,560
Speaker 4: works for you? The customers using their own data to

68
00:03:14,680 --> 00:03:16,399
Speaker 4: actually educate the model.

69
00:03:16,520 --> 00:03:19,800
Speaker 3: Absolutely, and we're just putting out you talked about open

70
00:03:20,000 --> 00:03:24,040
Speaker 3: right now, we're also right today and tomorrow putting out

71
00:03:24,040 --> 00:03:28,520
Speaker 3: a new technology, a really innovative technology called instruct lab.

72
00:03:28,960 --> 00:03:31,639
Speaker 3: This allows a client to take one of us or

73
00:03:31,639 --> 00:03:35,360
Speaker 3: maybe somebody else's model, take it inside that enterprise, train

74
00:03:35,440 --> 00:03:37,920
Speaker 3: it with some data and some methodology of their own,

75
00:03:38,240 --> 00:03:40,960
Speaker 3: and then the layer on top inside instruct lab is this.

76
00:03:41,520 --> 00:03:43,440
Speaker 2: It does not need to come back to anybody else.

77
00:03:43,800 --> 00:03:46,920
Speaker 2: I think that gets rid of the whole question of

78
00:03:47,000 --> 00:03:48,560
Speaker 2: copyright and fair use.

79
00:03:49,320 --> 00:03:53,120
Speaker 4: How does AI alignes fit with possible government regulation. We

80
00:03:53,200 --> 00:03:55,360
Speaker 4: have some moves in Europe, as you know, there's an

81
00:03:55,360 --> 00:03:58,640
Speaker 4: executive order in the United States divide administration is put out.

82
00:03:58,800 --> 00:04:01,080
Speaker 4: How do those two things fit? Because you talk about

83
00:04:01,080 --> 00:04:03,920
Speaker 4: standards as part of the AI Alliance.

84
00:04:03,840 --> 00:04:07,160
Speaker 3: I think every regulator is worried about three topics, not

85
00:04:07,360 --> 00:04:11,240
Speaker 3: just safety in regulation. They're wanted about innovation. They're worried

86
00:04:11,280 --> 00:04:14,440
Speaker 3: about competition, and they're worried about safety and regulation.

87
00:04:14,720 --> 00:04:17,600
Speaker 2: So when you take those three together, the AI Alliance

88
00:04:17,640 --> 00:04:20,840
Speaker 2: that open really come together to help you foment innovation.

89
00:04:21,240 --> 00:04:23,560
Speaker 3: So I think that that actually helps the regulators to

90
00:04:23,640 --> 00:04:26,880
Speaker 3: think about what is going on here. While I in caution,

91
00:04:27,360 --> 00:04:29,960
Speaker 3: there will be some gardens that are always fut but

92
00:04:30,120 --> 00:04:33,640
Speaker 3: in my experience, open technologies have always been safer and

93
00:04:33,720 --> 00:04:35,920
Speaker 3: more secure than close technologies.

94
00:04:36,320 --> 00:04:38,719
Speaker 4: Is one of the risks that maybe you're obviating with

95
00:04:38,800 --> 00:04:41,240
Speaker 4: your emphasis on open architecture. That's some of that. I'll

96
00:04:41,240 --> 00:04:43,680
Speaker 4: call them big guys get an advantage and really have

97
00:04:43,760 --> 00:04:44,640
Speaker 4: an entrenched position.

98
00:04:45,520 --> 00:04:47,680
Speaker 2: Well, I'll use the concert of a wall garden.

99
00:04:49,080 --> 00:04:53,120
Speaker 3: When you have a walled garden, has those areas and

100
00:04:53,160 --> 00:04:55,440
Speaker 3: technologies been more innovative.

101
00:04:55,000 --> 00:04:55,880
Speaker 2: Or less innovative?

102
00:04:56,279 --> 00:04:58,000
Speaker 3: All of a sudden, the wall garden has always been

103
00:04:58,080 --> 00:05:01,239
Speaker 3: less innovative, and so I think that it actually helps

104
00:05:01,279 --> 00:05:05,440
Speaker 3: you create more competition. Does it avoid regulatory lock in

105
00:05:05,640 --> 00:05:07,880
Speaker 3: off a certain one or two players?

106
00:05:08,240 --> 00:05:10,279
Speaker 2: Likely? But isn't that good for all of us?

107
00:05:10,800 --> 00:05:12,680
Speaker 4: Are you pro regulation?

108
00:05:13,520 --> 00:05:16,080
Speaker 3: I am pro regulation as long as is it as

109
00:05:16,160 --> 00:05:19,320
Speaker 3: light touch and allows innovation to happen.

110
00:05:19,680 --> 00:05:21,360
Speaker 2: I absolutely would be pro regulation.

111
00:05:21,760 --> 00:05:32,240
Speaker 3: If regulation tries to reduce innovation, I think that's a problem.

112
00:05:28,920 --> 00:05:31,159
Speaker 1: And that, of course was Arvind Krishna. He is IBM

113
00:05:31,279 --> 00:05:34,520
Speaker 1: Chairman and CEO and Wall Street Week hoast David Wesson