1
00:00:00,800 --> 00:00:04,240
Speaker 1: Jersey and Amanda gam Nation. Do you have lots of

2
00:00:04,280 --> 00:00:05,600
Speaker 1: old photos on your phone?

3
00:00:06,440 --> 00:00:06,880
Speaker 2: Yeah?

4
00:00:06,960 --> 00:00:07,880
Speaker 1: We all do, don't we?

5
00:00:08,160 --> 00:00:10,040
Speaker 2: And you go through from time to time and scroll

6
00:00:10,080 --> 00:00:11,240
Speaker 2: through and delete the ones.

7
00:00:11,360 --> 00:00:12,160
Speaker 1: Do you, yep?

8
00:00:12,200 --> 00:00:13,840
Speaker 2: I get rid of shots?

9
00:00:14,120 --> 00:00:17,239
Speaker 1: Do you ones that I'm not going to use? Use for? What? Though?

10
00:00:17,400 --> 00:00:19,320
Speaker 1: I just ones that I've got pictures of that. It's

11
00:00:19,280 --> 00:00:21,000
Speaker 1: so funny because do we all remember the photos that

12
00:00:21,000 --> 00:00:24,279
Speaker 1: we've got. I don't think we do it. It's just

13
00:00:24,320 --> 00:00:26,560
Speaker 1: a storage facility really on your phone. And this is

14
00:00:26,600 --> 00:00:29,080
Speaker 1: what I think is interesting is the UK government is

15
00:00:29,120 --> 00:00:31,200
Speaker 1: asking people to get rid of their photos and older

16
00:00:31,200 --> 00:00:35,120
Speaker 1: emails to help tackle a water shortage. You wouldn't think

17
00:00:35,120 --> 00:00:38,599
Speaker 1: that that would correlate with an environmental crisis. It's been

18
00:00:38,600 --> 00:00:41,839
Speaker 1: described as a nationally significant incident five areas in the

19
00:00:41,920 --> 00:00:46,080
Speaker 1: UK officially and drought. And what they're saying is that

20
00:00:46,200 --> 00:00:49,000
Speaker 1: all of your stuff is stored up in the cloud

21
00:00:49,880 --> 00:00:52,720
Speaker 1: and it's the cloud that needs water to cool those

22
00:00:52,760 --> 00:00:56,080
Speaker 1: computers that are taking up all this water. Have a listen.

23
00:00:56,640 --> 00:00:59,600
Speaker 2: Whatever you store something up in the cloud, it requires

24
00:00:59,680 --> 00:01:03,920
Speaker 2: complete and computer servers to save that. Those servers generate heat.

25
00:01:04,000 --> 00:01:06,240
Speaker 2: That heat needs to be called somehow They oftentimes use

26
00:01:06,280 --> 00:01:07,600
Speaker 2: water to cool the servers.

27
00:01:08,000 --> 00:01:11,000
Speaker 1: Some data centers use up to nineteen million liters of

28
00:01:11,040 --> 00:01:15,360
Speaker 1: water a day. That's the same as about fifteen thousand households.

29
00:01:15,760 --> 00:01:18,399
Speaker 1: So the government, the UK government is saying by deleting

30
00:01:19,120 --> 00:01:22,720
Speaker 1: one thousand old emails with attachments could save seventy seven

31
00:01:22,800 --> 00:01:26,320
Speaker 1: liters of water. It's worth going through the phone. You'll

32
00:01:26,360 --> 00:01:30,080
Speaker 1: save space and water. But AI is really going to

33
00:01:30,120 --> 00:01:34,720
Speaker 1: be impacting this more and more environmental impact from AI.

34
00:01:35,240 --> 00:01:39,520
Speaker 1: Training and using large AI models requires vast amounts of electricity,

35
00:01:39,840 --> 00:01:43,200
Speaker 1: with AI workloads projected to consumingly half of all global

36
00:01:43,280 --> 00:01:46,320
Speaker 1: data center electricity by the end of twenty twenty five.

37
00:01:46,720 --> 00:01:50,520
Speaker 1: So this surge and energy use contributes to rising greenhouse

38
00:01:50,560 --> 00:01:55,920
Speaker 1: gas emissions, surpassing even the aviation industry, so that's quite extraordinary.

39
00:01:56,160 --> 00:01:59,360
Speaker 1: AI data centers rely heavily on water for cooling. These

40
00:01:59,400 --> 00:02:04,120
Speaker 1: figures are extraordinary in terms of water usage. AIDATA centers

41
00:02:04,160 --> 00:02:08,920
Speaker 1: in the US alone consumed seventeen billion gallons of water

42
00:02:08,960 --> 00:02:13,440
Speaker 1: in twenty twenty three, so they're extrapolating this mats so

43
00:02:13,520 --> 00:02:15,640
Speaker 1: it's going to be about one hundred and forty eight

44
00:02:15,680 --> 00:02:18,960
Speaker 1: billion gallons of water annually. Let me put that in

45
00:02:18,960 --> 00:02:21,120
Speaker 1: a context. One hundred and forty eight billion gallons of

46
00:02:21,160 --> 00:02:25,919
Speaker 1: water is ninety three billion flushes of a toilet, two

47
00:02:26,040 --> 00:02:28,560
Speaker 1: hundred and twenty four thousand Olympic sized pools. This is

48
00:02:28,600 --> 00:02:32,320
Speaker 1: what's being used annually, three hundred and forty three thousand

49
00:02:32,320 --> 00:02:35,920
Speaker 1: football fields. This water would supply New York City with

50
00:02:36,080 --> 00:02:40,000
Speaker 1: water for five months. It's about one point eight five

51
00:02:40,120 --> 00:02:43,720
Speaker 1: billion bath tubs and pretty much the equivalent of my

52
00:02:43,800 --> 00:02:47,320
Speaker 1: ankle water. Okay, so this is a public service announcement.

53
00:02:47,360 --> 00:02:51,760
Speaker 1: If your old photos, your old emails have a cul really,

54
00:02:51,800 --> 00:02:55,480
Speaker 1: because the environmental impact is extraordinary, be a delete mynudes

55
00:02:56,360 --> 00:03:00,920
Speaker 1: of who to see if everything's in in peak condition,

56
00:03:01,160 --> 00:03:04,840
Speaker 1: you they need some cooling there. Well, you know what

57
00:03:05,040 --> 00:03:10,079
Speaker 1: you could do? Send it off to you. Hell, what's this?

58
00:03:10,720 --> 00:03:14,359
Speaker 1: Is that a knuckle? But you can You can send

59
00:03:14,400 --> 00:03:16,480
Speaker 1: this stuff to chat GPT and it will tell you

60
00:03:16,480 --> 00:03:20,320
Speaker 1: your medical information. Chat GPT is very useful, but it

61
00:03:20,400 --> 00:03:22,720
Speaker 1: also has a big downside. We'll talk about that next

62
00:03:22,720 --> 00:03:23,400
Speaker 1: in the pub test