1
00:00:00,840 --> 00:00:04,680
Speaker 1: Hello there, How I Work listener, I have some very

2
00:00:04,920 --> 00:00:08,479
Speaker 1: very exciting news to share with you today because I'm

3
00:00:08,560 --> 00:00:13,320
Speaker 1: launching a brand new podcast. It is called how I AI,

4
00:00:14,000 --> 00:00:17,119
Speaker 1: and it is going to be coming to you into

5
00:00:17,200 --> 00:00:21,960
Speaker 1: your How I Work feed every single Monday. If you

6
00:00:22,120 --> 00:00:24,680
Speaker 1: are a regular How I Work listener, you will know

7
00:00:24,720 --> 00:00:28,360
Speaker 1: that I've spent the last few years becoming absolutely obsessed

8
00:00:28,400 --> 00:00:31,440
Speaker 1: with AI. Not because I'm a tech geek, although i

9
00:00:31,480 --> 00:00:34,960
Speaker 1: am quite nerdy, but because I've discovered that when you

10
00:00:35,200 --> 00:00:38,040
Speaker 1: use the right AI tools in the right way, you

11
00:00:38,120 --> 00:00:41,800
Speaker 1: can reclaim hours of your week and do better work

12
00:00:41,880 --> 00:00:46,360
Speaker 1: in less time. Now on How I Ai, I am

13
00:00:46,400 --> 00:00:49,720
Speaker 1: going to be joined by Neo Applan, who heads up

14
00:00:49,800 --> 00:00:54,640
Speaker 1: Inventium dot Ai, which is my company, in Ventium's AI

15
00:00:54,800 --> 00:00:58,160
Speaker 1: training arm. So literally every day we are working with

16
00:00:58,360 --> 00:01:02,200
Speaker 1: countless organizations, team and individuals to upskill them on how

17
00:01:02,240 --> 00:01:06,360
Speaker 1: to get more out of AI. You might remember Neo

18
00:01:06,480 --> 00:01:09,080
Speaker 1: from some of the AI episodes that we did last year,

19
00:01:09,200 --> 00:01:11,240
Speaker 1: but in case you missed those, Neo who spent his

20
00:01:11,640 --> 00:01:15,360
Speaker 1: entire career in tech and IT and AI, which means

21
00:01:15,400 --> 00:01:18,800
Speaker 1: he spends his time testing things all day, every day

22
00:01:18,880 --> 00:01:21,920
Speaker 1: so that the rest of us don't have to. Now,

23
00:01:21,920 --> 00:01:25,360
Speaker 1: today's episode is a slightly longer one because Neo and

24
00:01:25,400 --> 00:01:30,199
Speaker 1: I are talking about thirteen AI tools that we use

25
00:01:30,440 --> 00:01:36,600
Speaker 1: every single day, essentially what is in our AI tool stack,

26
00:01:37,280 --> 00:01:40,080
Speaker 1: And when you tune into our regular episodes on Monday,

27
00:01:40,200 --> 00:01:42,560
Speaker 1: what you can expect is for Neo and I to

28
00:01:42,600 --> 00:01:45,400
Speaker 1: share just one practical way that you can use AI

29
00:01:45,480 --> 00:01:48,760
Speaker 1: better in work or in life. So with all that

30
00:01:48,800 --> 00:01:58,360
Speaker 1: in mind, let's get into it. Welcome to how IAI

31
00:01:58,640 --> 00:02:02,200
Speaker 1: with me Doctor amanth Im and Neo Applin, head of

32
00:02:02,320 --> 00:02:06,360
Speaker 1: Inventium AI. Each episode we share one practical way to

33
00:02:06,480 --> 00:02:10,200
Speaker 1: use AI better at work and in life. No fluff,

34
00:02:10,400 --> 00:02:13,400
Speaker 1: no deck jargon, just things you can use straight away.

35
00:02:14,639 --> 00:02:18,560
Speaker 1: So we're talking about the AI tools that Neo and

36
00:02:18,680 --> 00:02:22,680
Speaker 1: I personally use every day, and I think we just

37
00:02:22,680 --> 00:02:24,919
Speaker 1: want to get the big ones out of the way

38
00:02:24,960 --> 00:02:27,120
Speaker 1: so we can move on to maybe some that people

39
00:02:27,160 --> 00:02:29,280
Speaker 1: are not using or might have heard of, haven't tried,

40
00:02:29,360 --> 00:02:35,400
Speaker 1: but certainly in our AI stack. So Claude and chat GPT,

41
00:02:36,400 --> 00:02:38,840
Speaker 1: and I'm not going to count these in the count

42
00:02:38,960 --> 00:02:41,560
Speaker 1: for the tools that we're using every day. I'm certainly

43
00:02:41,639 --> 00:02:46,560
Speaker 1: using both of those and also Gemini, but I use

44
00:02:46,600 --> 00:02:50,440
Speaker 1: them for different purposes. Neo, what are your basics, and

45
00:02:50,480 --> 00:02:53,120
Speaker 1: then let's just have a quick chat about what we

46
00:02:53,240 --> 00:02:58,000
Speaker 1: use for what With those, you know, the fundamental platforms.

47
00:02:58,600 --> 00:03:01,239
Speaker 2: I'm unusual because I I need to keep up to

48
00:03:01,320 --> 00:03:03,320
Speaker 2: date with all of them, so I'll do the same

49
00:03:03,400 --> 00:03:06,079
Speaker 2: prompt into multiple ones, just so I can see each

50
00:03:06,120 --> 00:03:08,000
Speaker 2: of them and how they're responding and whether there's a

51
00:03:08,040 --> 00:03:10,920
Speaker 2: new engine, all those kind of things. However, Claude is

52
00:03:11,000 --> 00:03:14,160
Speaker 2: awesome for like copywriting, writing, those kind of things. I've

53
00:03:14,200 --> 00:03:16,680
Speaker 2: also use it for coding a lot. Does an amazing

54
00:03:16,760 --> 00:03:20,360
Speaker 2: job with coding stuff. I'm finding. Gemini is awesome for

55
00:03:20,520 --> 00:03:25,160
Speaker 2: so many things. At the moment, Chabt is still one

56
00:03:25,160 --> 00:03:28,480
Speaker 2: of the granddaddies, so it is excellent for thinking through problems,

57
00:03:28,639 --> 00:03:31,880
Speaker 2: all those kind of things. And I use Copilot as

58
00:03:31,880 --> 00:03:34,720
Speaker 2: my EA, so it knows everything about my files, my documents,

59
00:03:34,880 --> 00:03:38,680
Speaker 2: my emails, all those kind of things. So yeah, I

60
00:03:38,760 --> 00:03:41,000
Speaker 2: used them all, but in different ways. How about you.

61
00:03:41,480 --> 00:03:46,280
Speaker 1: Yeah, I'm the same. So Claude I still find sounds

62
00:03:46,400 --> 00:03:49,400
Speaker 1: more like a human than any of the others. So

63
00:03:49,840 --> 00:03:53,360
Speaker 1: if I am working on editing a piece or drafting

64
00:03:53,360 --> 00:03:56,680
Speaker 1: a piece and I want input from AI generally clauds

65
00:03:56,720 --> 00:04:01,640
Speaker 1: my go to. I use chat GPT a lot more

66
00:04:01,840 --> 00:04:06,640
Speaker 1: around I would say research and problem solving and sometimes

67
00:04:06,680 --> 00:04:11,400
Speaker 1: actually working with me to draft something. And what I

68
00:04:11,480 --> 00:04:16,039
Speaker 1: mean by that is that I have the Chatapte app

69
00:04:16,080 --> 00:04:19,239
Speaker 1: on my phone and I will often use advanced voice mode.

70
00:04:19,320 --> 00:04:22,599
Speaker 1: So I'm sure we'll talk about different workflows in future episodes,

71
00:04:22,640 --> 00:04:28,560
Speaker 1: but I have particular workflows around writing my weekly newsletter

72
00:04:28,640 --> 00:04:31,080
Speaker 1: one percent Better. And often I'll be thinking of ideas

73
00:04:31,160 --> 00:04:34,960
Speaker 1: during the week and I go to a gym that's

74
00:04:34,960 --> 00:04:37,120
Speaker 1: about a ten minute drive away, and it's the perfect

75
00:04:37,160 --> 00:04:41,480
Speaker 1: amount of time to have a little conversation with chat GPT,

76
00:04:41,839 --> 00:04:44,960
Speaker 1: throw down my ideas, get it to ask me some questions,

77
00:04:45,080 --> 00:04:47,680
Speaker 1: and put together a bit of a rough draft that

78
00:04:47,720 --> 00:04:51,360
Speaker 1: I would then move into Claude. And one other thing

79
00:04:51,560 --> 00:04:56,440
Speaker 1: I would say is that I use I use different

80
00:04:57,640 --> 00:05:00,640
Speaker 1: different ais to do deep research, and I've compared and

81
00:05:00,680 --> 00:05:03,680
Speaker 1: contrasted the results for the exact same prompt, and I

82
00:05:03,760 --> 00:05:08,520
Speaker 1: actually feel like Gemini consistently gives me the best results,

83
00:05:08,560 --> 00:05:11,400
Speaker 1: So I do tend to go to Gemini for deep research.

84
00:05:12,279 --> 00:05:13,839
Speaker 2: I agree with the deep research. It does a great

85
00:05:13,880 --> 00:05:15,720
Speaker 2: job with that. And then how could it not. It's

86
00:05:15,720 --> 00:05:18,120
Speaker 2: got all the Google information at Google Data and things

87
00:05:18,160 --> 00:05:19,719
Speaker 2: like that, so they're doing a great job with that.

88
00:05:20,160 --> 00:05:23,440
Speaker 1: Yeah. Now a lot of people will use AI for

89
00:05:23,720 --> 00:05:27,120
Speaker 1: meetings in different way, shape or forms. You know, a

90
00:05:27,160 --> 00:05:29,719
Speaker 1: lot of certainly a lot of our clients at Inventium

91
00:05:30,000 --> 00:05:33,200
Speaker 1: are in the Microsoft ecosystem, so they will be using

92
00:05:33,560 --> 00:05:37,839
Speaker 1: teams Premium other clients a Zoom and there's you know,

93
00:05:37,920 --> 00:05:41,800
Speaker 1: great AI built into that. But I know, for me,

94
00:05:43,000 --> 00:05:45,919
Speaker 1: something that I use every single day, multiple times a

95
00:05:46,000 --> 00:05:50,440
Speaker 1: day is Granola. I am absolutely obsessed with this software.

96
00:05:50,480 --> 00:05:53,560
Speaker 1: I've been using it for I don't know, maybe a

97
00:05:53,680 --> 00:05:57,719
Speaker 1: year now. And it's a little bit different to other

98
00:05:58,080 --> 00:06:01,520
Speaker 1: meeting or AI meeting tools in that it doesn't take

99
00:06:01,640 --> 00:06:05,880
Speaker 1: an audio or video recording of the meeting. It only

100
00:06:06,360 --> 00:06:09,400
Speaker 1: records the words, so you get a full transcript and

101
00:06:09,440 --> 00:06:12,279
Speaker 1: then a lot of the other features that general meeting

102
00:06:12,360 --> 00:06:14,920
Speaker 1: software gives you. But I like it because it's unobtrusive.

103
00:06:15,279 --> 00:06:19,560
Speaker 1: Something a bit of a pet peeve of mine is when,

104
00:06:19,680 --> 00:06:22,320
Speaker 1: for example, I'm waiting for someone in a meeting and

105
00:06:22,360 --> 00:06:26,400
Speaker 1: the AI joins before then them, or where you know,

106
00:06:26,560 --> 00:06:30,240
Speaker 1: say doing a you know, it might be like a

107
00:06:30,320 --> 00:06:33,359
Speaker 1: virtual workshop or a webinar, a virtual webinar or something

108
00:06:33,440 --> 00:06:37,920
Speaker 1: like that, and people's AI note taker is there, but

109
00:06:37,960 --> 00:06:40,800
Speaker 1: they're not, and I just find that so off putting.

110
00:06:40,800 --> 00:06:45,120
Speaker 1: But Granola works in the background, So it's my go

111
00:06:45,160 --> 00:06:48,159
Speaker 1: to for just having on in the background for meetings

112
00:06:49,000 --> 00:06:51,159
Speaker 1: so that I don't have to take super fast notes.

113
00:06:51,920 --> 00:06:55,040
Speaker 1: But it does still let me take notes. And what's

114
00:06:55,080 --> 00:06:59,200
Speaker 1: really cool is that incorporates what it learns from the

115
00:06:59,279 --> 00:07:03,480
Speaker 1: meeting to my notes, to basically augment my notes, so

116
00:07:03,600 --> 00:07:05,440
Speaker 1: I know what I think is important in the moment,

117
00:07:05,440 --> 00:07:08,400
Speaker 1: and I'll make a note in the essentially the electronic

118
00:07:08,520 --> 00:07:11,520
Speaker 1: notebook that is Granola, and then it will augment that

119
00:07:11,800 --> 00:07:15,480
Speaker 1: with the transcript and all the details that I might

120
00:07:15,880 --> 00:07:18,080
Speaker 1: not have had a chance to write down. So I

121
00:07:18,120 --> 00:07:20,880
Speaker 1: just think it is absolutely gold. Do you have a

122
00:07:20,920 --> 00:07:23,960
Speaker 1: Granola equivalent, because I don't think you're using Granola like

123
00:07:24,000 --> 00:07:24,320
Speaker 1: I am.

124
00:07:24,840 --> 00:07:30,160
Speaker 2: No, I'm trialing out one called hyper note hyprnote, and

125
00:07:30,280 --> 00:07:34,040
Speaker 2: hyper note is an equivalent of an open source version

126
00:07:34,120 --> 00:07:38,040
Speaker 2: of Granola, And why am I trialing this one? It's

127
00:07:38,360 --> 00:07:40,880
Speaker 2: similar to Granola. It's got a note taking section where

128
00:07:40,920 --> 00:07:44,320
Speaker 2: you can take notes. It also records and can transcribe

129
00:07:44,440 --> 00:07:47,080
Speaker 2: It'll also kind of augment your notes if you'd like,

130
00:07:47,600 --> 00:07:51,600
Speaker 2: although not as elegantly as Granola does. Where it's unique

131
00:07:51,640 --> 00:07:54,400
Speaker 2: is it does all of this work locally on your computer.

132
00:07:55,520 --> 00:07:59,440
Speaker 2: So I'm always looking at privacy based AI tools so

133
00:07:59,480 --> 00:08:01,360
Speaker 2: that if you've got like a medical thing or you've

134
00:08:01,400 --> 00:08:03,760
Speaker 2: got secret squirrel stuff you can't share, how do you

135
00:08:03,800 --> 00:08:06,120
Speaker 2: do things without sharing? Or some other weird company in

136
00:08:06,160 --> 00:08:08,920
Speaker 2: the cloud, Not that I'm calling, you know, Google or

137
00:08:09,080 --> 00:08:12,520
Speaker 2: Microsoft weird companies, but Granoli. Maybe you don't know them,

138
00:08:12,560 --> 00:08:14,360
Speaker 2: maybe you don't trust them, maybe you've got health breacords

139
00:08:14,360 --> 00:08:17,120
Speaker 2: that can't live the state, the country. So hyper note

140
00:08:17,200 --> 00:08:19,200
Speaker 2: can do a similar thing, but not quite as good

141
00:08:19,200 --> 00:08:22,600
Speaker 2: as Granola. Now people may ask when you mentioned it

142
00:08:22,640 --> 00:08:25,840
Speaker 2: works in the background. What Granola's doing is it's listening

143
00:08:25,920 --> 00:08:30,440
Speaker 2: to your microphone and your speakers effectively to be able

144
00:08:30,480 --> 00:08:32,760
Speaker 2: to listen to things on your computer. So that's how

145
00:08:32,800 --> 00:08:37,160
Speaker 2: it listens to meetings. But also Amantha uses this so

146
00:08:37,240 --> 00:08:40,800
Speaker 2: many times when we're in real life, face to face together,

147
00:08:41,080 --> 00:08:43,280
Speaker 2: she'll pull out her phone and drop Granola on the

148
00:08:43,360 --> 00:08:45,760
Speaker 2: table to be able to help take notes. So it's

149
00:08:45,840 --> 00:08:50,320
Speaker 2: not a virtual meeting teams zoom thing. Only it's also

150
00:08:50,440 --> 00:08:51,480
Speaker 2: really good face to face.

151
00:08:52,480 --> 00:08:55,600
Speaker 1: And one way that we have used this at Inventium

152
00:08:55,720 --> 00:08:58,360
Speaker 1: is that we were a remote first organization, which means

153
00:08:58,400 --> 00:09:01,240
Speaker 1: we have no officers. We all work from wherever we want,

154
00:09:01,280 --> 00:09:04,360
Speaker 1: typically home. But when we do get together, we try

155
00:09:04,400 --> 00:09:07,520
Speaker 1: to get together once a month face to face, and

156
00:09:07,600 --> 00:09:10,960
Speaker 1: often you know, will have important things that we're talking about.

157
00:09:11,440 --> 00:09:14,160
Speaker 1: I would typically, and even if this is a two

158
00:09:14,280 --> 00:09:17,319
Speaker 1: or three hour workshop, I would typically put my phone

159
00:09:17,640 --> 00:09:20,680
Speaker 1: in the middle of the meeting room area, just on

160
00:09:20,720 --> 00:09:23,880
Speaker 1: the table. I would open up a granola meeting so

161
00:09:23,960 --> 00:09:27,480
Speaker 1: that I am capturing the whole thing, so again we're

162
00:09:27,480 --> 00:09:31,400
Speaker 1: not missing anything. No one has to take copious notes

163
00:09:31,480 --> 00:09:35,600
Speaker 1: or be ascribed, and it just makes for like a

164
00:09:35,640 --> 00:09:40,040
Speaker 1: real frictionless experience when you're trying to say ID eight,

165
00:09:40,160 --> 00:09:44,160
Speaker 1: or make decisions or you know, record key points of information.

166
00:09:44,400 --> 00:09:47,040
Speaker 1: So massive fan on that.

167
00:09:47,200 --> 00:09:49,560
Speaker 2: Just if for other people, Otto does a similar kind

168
00:09:49,559 --> 00:09:50,960
Speaker 2: of deal where you put it on the table, but

169
00:09:51,000 --> 00:09:53,520
Speaker 2: it'll also say who spoke what. So if you like

170
00:09:53,559 --> 00:09:56,360
Speaker 2: Otter for meetings, it's really good for the similar kind

171
00:09:56,360 --> 00:09:58,559
Speaker 2: of thing, so love it for that.

172
00:09:58,559 --> 00:10:01,960
Speaker 1: That is true. Otter is is really good in that sense,

173
00:10:02,000 --> 00:10:05,000
Speaker 1: in that you can label each speaker, whereas with Granola

174
00:10:05,200 --> 00:10:11,280
Speaker 1: you cannot. Now, something that I use every day and

175
00:10:11,320 --> 00:10:14,720
Speaker 1: sometimes multiple times a day, depending on what project I'm

176
00:10:14,840 --> 00:10:19,960
Speaker 1: focusing on on that particular day is consensus Consensus dot app,

177
00:10:20,480 --> 00:10:24,080
Speaker 1: and this is what I found to be by far

178
00:10:24,280 --> 00:10:30,000
Speaker 1: the best tool for uncovering academic research and getting answers

179
00:10:30,040 --> 00:10:33,520
Speaker 1: to things from a science back or evidence back to

180
00:10:33,600 --> 00:10:37,199
Speaker 1: point of view, which if you're not familiar with inventium,

181
00:10:37,640 --> 00:10:40,880
Speaker 1: you will know that that is our DNA. Everything we

182
00:10:40,960 --> 00:10:45,320
Speaker 1: do is backed by science, and certainly everything I write,

183
00:10:45,360 --> 00:10:50,440
Speaker 1: all my books, they're heavily researched, and certainly with the

184
00:10:50,520 --> 00:10:54,200
Speaker 1: last couple, The Health Habit and The Energy Game, which

185
00:10:54,240 --> 00:10:58,400
Speaker 1: is coming out later this year, I you know, I

186
00:10:58,400 --> 00:11:02,760
Speaker 1: would easily spend an hour or more on consensus every

187
00:11:02,880 --> 00:11:07,040
Speaker 1: day trolling for research. I also find consensus is very

188
00:11:07,080 --> 00:11:11,560
Speaker 1: good for health in general. In my personal life. I

189
00:11:11,600 --> 00:11:14,400
Speaker 1: know Neo we have both used it for this. If,

190
00:11:14,440 --> 00:11:18,680
Speaker 1: for example, we read that there's some kind of supplementation

191
00:11:19,000 --> 00:11:23,080
Speaker 1: we should be having, you know, it's really great to

192
00:11:24,240 --> 00:11:26,959
Speaker 1: get consensus on that. It is called consensus because it's

193
00:11:27,000 --> 00:11:30,880
Speaker 1: particularly good for yes or no questions, So you know,

194
00:11:30,960 --> 00:11:33,600
Speaker 1: for example, I don't know, like.

195
00:11:33,960 --> 00:11:38,000
Speaker 2: I'll jump in. RFK was drinking this stuff called methylene blue,

196
00:11:38,040 --> 00:11:40,600
Speaker 2: which I've never heard of, and I actually run into

197
00:11:40,600 --> 00:11:43,680
Speaker 2: consensus like what does this? Who is it actually the thing?

198
00:11:43,920 --> 00:11:45,840
Speaker 2: So yeah, you've got those kinds of things are also

199
00:11:45,880 --> 00:11:48,920
Speaker 2: really good for interplays of different medications together. But also

200
00:11:49,360 --> 00:11:52,320
Speaker 2: just like the one I use is if you want

201
00:11:52,320 --> 00:11:55,520
Speaker 2: to try to get hybrid working happening at your workplace,

202
00:11:56,840 --> 00:12:01,480
Speaker 2: does hybrid working increase productivity? Find out there's more yess

203
00:12:01,559 --> 00:12:02,079
Speaker 2: than those.

204
00:12:07,120 --> 00:12:09,320
Speaker 1: We are taking a short break, but when we're back,

205
00:12:09,400 --> 00:12:11,280
Speaker 1: I'm going to be sharing a tool that I use

206
00:12:11,520 --> 00:12:14,120
Speaker 1: maybe one hundred or so times a day and it

207
00:12:14,160 --> 00:12:18,160
Speaker 1: has completely transformed how I work. We're also going to

208
00:12:18,160 --> 00:12:20,760
Speaker 1: be sharing my go to podcast app and more of

209
00:12:21,000 --> 00:12:29,960
Speaker 1: Nero's AI tech stack too. What's a tool that you're

210
00:12:30,280 --> 00:12:31,240
Speaker 1: a bit obsessed with?

211
00:12:31,400 --> 00:12:36,560
Speaker 2: Neo For me at the moment, perplexity. And this is

212
00:12:36,559 --> 00:12:39,120
Speaker 2: because I've been on holidays the last couple of weeks,

213
00:12:40,120 --> 00:12:42,640
Speaker 2: so i haven't been doing AI work. I've been doing

214
00:12:42,679 --> 00:12:47,720
Speaker 2: AI fun. So I've been doing research on random stuff

215
00:12:47,760 --> 00:12:50,280
Speaker 2: and w what that looks like an interesting product. I'll

216
00:12:50,320 --> 00:12:52,080
Speaker 2: have a little look at that, and so I've been

217
00:12:52,120 --> 00:12:55,560
Speaker 2: learning about products. I've been learning about food as well,

218
00:12:55,600 --> 00:12:59,839
Speaker 2: like learning about making kraft for example, sourkrap and so

219
00:13:00,280 --> 00:13:01,960
Speaker 2: how long do you put it in? For how much

220
00:13:02,000 --> 00:13:03,680
Speaker 2: salt do you put in? All those kind of things,

221
00:13:03,679 --> 00:13:06,840
Speaker 2: and perplexity has been fantastic for that. It's also been

222
00:13:06,960 --> 00:13:10,679
Speaker 2: really good for product searches as well. So how do

223
00:13:10,720 --> 00:13:13,040
Speaker 2: I compare product A to product B, which one's better?

224
00:13:13,080 --> 00:13:16,360
Speaker 2: Which when should I get? I use this about mid

225
00:13:16,480 --> 00:13:18,160
Speaker 2: last year something like that. I was after a pair

226
00:13:18,200 --> 00:13:20,880
Speaker 2: of hiking boots and there are so many damn hiking

227
00:13:20,880 --> 00:13:22,800
Speaker 2: boots on the market, and I can't tell the difference

228
00:13:22,800 --> 00:13:25,840
Speaker 2: between them. So I've got perplexity to compare it and

229
00:13:25,840 --> 00:13:27,240
Speaker 2: put them in a table and show me where the

230
00:13:27,280 --> 00:13:30,520
Speaker 2: different ones were. I even got it to search social

231
00:13:30,600 --> 00:13:34,360
Speaker 2: sources for reviews on each of these boots for different

232
00:13:34,480 --> 00:13:37,720
Speaker 2: kind of hiking needs and things like that. So for me,

233
00:13:37,800 --> 00:13:41,480
Speaker 2: it's awesome for shopping researching those kind of things. And

234
00:13:41,559 --> 00:13:43,800
Speaker 2: I think you and I've also talked about this before,

235
00:13:43,840 --> 00:13:46,920
Speaker 2: where it's not bad at finding those discount codes from

236
00:13:46,920 --> 00:13:48,160
Speaker 2: the major retailers as well.

237
00:13:48,920 --> 00:13:52,480
Speaker 1: Very good for that. Okay, something that I use to

238
00:13:52,600 --> 00:13:58,080
Speaker 1: listen to podcasts, having mucked around with many many podcast

239
00:13:58,160 --> 00:14:03,120
Speaker 1: players from Apple podcast to Google podcasts before it closed

240
00:14:03,160 --> 00:14:06,240
Speaker 1: down to man, I think I've tried it. I think

241
00:14:06,280 --> 00:14:10,240
Speaker 1: I've tried most of most of the things. Is I

242
00:14:10,280 --> 00:14:16,839
Speaker 1: love snipped, so that is spelled s nip D And

243
00:14:17,520 --> 00:14:19,800
Speaker 1: I should add we will link to all of these

244
00:14:19,840 --> 00:14:23,280
Speaker 1: tools in the show notes to make it easy for

245
00:14:23,360 --> 00:14:26,000
Speaker 1: you to grab it. But if you did happen to

246
00:14:26,000 --> 00:14:29,520
Speaker 1: be listening to this episode on Snipped and you heard

247
00:14:29,520 --> 00:14:32,680
Speaker 1: a tool and you're like, oh, that sounds really cool. Often,

248
00:14:32,800 --> 00:14:34,680
Speaker 1: like in a huge pain point of mind when I

249
00:14:34,720 --> 00:14:37,800
Speaker 1: was listening to particularly educational podcasts, is I'd hear something

250
00:14:37,840 --> 00:14:39,800
Speaker 1: and I'd want to remember it, and I'd have to

251
00:14:39,840 --> 00:14:43,560
Speaker 1: pause it and write it down or ask ask Siri

252
00:14:43,600 --> 00:14:46,200
Speaker 1: to like remind me about this at a certain time,

253
00:14:47,360 --> 00:14:50,600
Speaker 1: and not an ideal workflow. But with snipped, you can

254
00:14:50,840 --> 00:14:54,560
Speaker 1: simply press one button and it will capture that part

255
00:14:54,640 --> 00:14:56,360
Speaker 1: of the interview for you so that you can go

256
00:14:56,440 --> 00:14:58,600
Speaker 1: back to it whenever you want and you don't have

257
00:14:58,640 --> 00:15:02,840
Speaker 1: to lose your flow of being being you know, a

258
00:15:02,920 --> 00:15:05,840
Speaker 1: listener of that podcast episode. There's a lot more that

259
00:15:05,960 --> 00:15:09,520
Speaker 1: it does, but that is one super handy feature of

260
00:15:09,560 --> 00:15:14,040
Speaker 1: why I like snipped has become again over the last

261
00:15:14,120 --> 00:15:18,000
Speaker 1: year or so, my my go to podcast player. Now

262
00:15:18,120 --> 00:15:21,120
Speaker 1: another tool that I am obsessed with. I'm not sure

263
00:15:21,160 --> 00:15:24,080
Speaker 1: if this fits into an AI tool specifically, although it

264
00:15:24,120 --> 00:15:26,400
Speaker 1: does look I think it does it. You know it

265
00:15:26,480 --> 00:15:28,360
Speaker 1: uses a ne or you can tell me whether it's

266
00:15:28,600 --> 00:15:32,560
Speaker 1: you know, strictly speaking, an AI tool is whisper flow,

267
00:15:33,040 --> 00:15:35,640
Speaker 1: and let me get the spelling right, I think it's

268
00:15:35,960 --> 00:15:41,680
Speaker 1: wisp r flow. And what this is and again this

269
00:15:41,720 --> 00:15:45,320
Speaker 1: is a tool that I would use, I don't know,

270
00:15:45,520 --> 00:15:47,960
Speaker 1: one hundred times a day or something like that, is

271
00:15:48,000 --> 00:15:51,360
Speaker 1: that it is far faster, even for the fastest type

272
00:15:51,480 --> 00:15:54,640
Speaker 1: is amongst us. It is faster to talk than it

273
00:15:54,720 --> 00:15:58,880
Speaker 1: is to type. And I have also been battling a

274
00:15:59,040 --> 00:16:03,000
Speaker 1: very annoying neck and shoulder injury I think from being

275
00:16:03,040 --> 00:16:05,760
Speaker 1: at my computer for way too many hours a day

276
00:16:05,840 --> 00:16:08,280
Speaker 1: when I was hard at work doing the first draft

277
00:16:08,320 --> 00:16:11,800
Speaker 1: of my manuscript for the Energy game, and so where

278
00:16:11,880 --> 00:16:15,960
Speaker 1: I can avoid typing, it's certainly better just physically, but

279
00:16:15,960 --> 00:16:18,920
Speaker 1: also it's a whole lot faster. Now, what's really cool

280
00:16:19,000 --> 00:16:21,560
Speaker 1: about whisper flow because a lot of software has dictation

281
00:16:22,000 --> 00:16:25,040
Speaker 1: in it. I think word Microsoft Word has had dictation

282
00:16:25,240 --> 00:16:29,440
Speaker 1: in it for years, but it just hasn't been particularly accurate.

283
00:16:29,720 --> 00:16:35,320
Speaker 1: It doesn't format things, it doesn't listen intelligently, like, for example,

284
00:16:35,360 --> 00:16:37,560
Speaker 1: if you are saying when you were speaking, it's going

285
00:16:37,600 --> 00:16:41,280
Speaker 1: to put in the dictation. Whisper flow is really intelligent.

286
00:16:41,360 --> 00:16:43,520
Speaker 1: It listens to what you're saying. If it can tell

287
00:16:43,560 --> 00:16:46,080
Speaker 1: that you've kind of stumbled over something or stuffed up,

288
00:16:46,080 --> 00:16:49,760
Speaker 1: it will automatically correct that. If I use it all

289
00:16:49,840 --> 00:16:54,040
Speaker 1: the time to draft out emails, I'm actually a little

290
00:16:54,080 --> 00:16:56,160
Speaker 1: bit unusual in that I don't use AI a lot

291
00:16:56,200 --> 00:16:59,240
Speaker 1: to write my emails. I typically just use myself to

292
00:16:59,320 --> 00:17:01,760
Speaker 1: actually find that it's quicker unless it's a really lengthy

293
00:17:01,800 --> 00:17:05,040
Speaker 1: and complex email, and so I will talk that email

294
00:17:05,400 --> 00:17:08,000
Speaker 1: using whisper flow. And I've set up a shortcut where

295
00:17:08,000 --> 00:17:11,639
Speaker 1: I just press the function button on my keyboard, So

296
00:17:11,640 --> 00:17:13,240
Speaker 1: if you're a Mac user, that's like at the very

297
00:17:13,320 --> 00:17:16,920
Speaker 1: bottom left of your keyboard. I press that, whisper Flow

298
00:17:16,960 --> 00:17:20,240
Speaker 1: opens in whatever application I'm in, and I just talk.

299
00:17:20,680 --> 00:17:22,560
Speaker 1: And you know, with something like an email where you

300
00:17:22,640 --> 00:17:24,960
Speaker 1: kind of want it formatted, you know, with dot points

301
00:17:24,960 --> 00:17:29,960
Speaker 1: and paragraphs. It intelligently listens and automatically does that for you.

302
00:17:30,040 --> 00:17:31,840
Speaker 1: I have to give it a quick once over. Sometimes

303
00:17:31,880 --> 00:17:36,359
Speaker 1: it americanizes spelling, which is a bit annoying, but it is.

304
00:17:37,240 --> 00:17:39,160
Speaker 1: I just love it so much.

305
00:17:40,000 --> 00:17:42,199
Speaker 2: I couldn't agree more. I've been playing with that as

306
00:17:42,240 --> 00:17:45,159
Speaker 2: well as an open source version of Whisper, because this

307
00:17:45,320 --> 00:17:47,840
Speaker 2: is an open source library. But that's the geey part.

308
00:17:48,760 --> 00:17:53,320
Speaker 2: But being able to intelligently go, so Julie, let's meet

309
00:17:53,400 --> 00:17:58,159
Speaker 2: up next Tuesday, No, next Wednesday. It won't write next Tuesday, no,

310
00:17:58,480 --> 00:18:02,080
Speaker 2: next Wednesday. It'll actually say next Wednesday, so you can

311
00:18:02,119 --> 00:18:05,040
Speaker 2: correct yourself while you're talking. And I love that part

312
00:18:05,119 --> 00:18:07,480
Speaker 2: about it because actually it's like you're talking to a

313
00:18:07,600 --> 00:18:09,639
Speaker 2: human being to be able to dictate your stuff for you.

314
00:18:09,720 --> 00:18:13,200
Speaker 2: So highly highly recommend whisker Flow. It's an awesome little application.

315
00:18:13,880 --> 00:18:16,159
Speaker 1: Okay, your tour neo, tell me something else that's in

316
00:18:16,240 --> 00:18:17,679
Speaker 1: your daily AI stack.

317
00:18:18,840 --> 00:18:21,959
Speaker 2: This one notebook LM. And we've covered this one before

318
00:18:22,560 --> 00:18:23,920
Speaker 2: and I'm sure we're going to cover it again because

319
00:18:23,920 --> 00:18:26,719
Speaker 2: it is such a great tool put out by Google.

320
00:18:26,840 --> 00:18:29,840
Speaker 2: Now this is a whole episode. We can talk about

321
00:18:29,880 --> 00:18:31,320
Speaker 2: this for an hour and a half, but I'll just

322
00:18:31,320 --> 00:18:35,200
Speaker 2: give you one little snippet once again, this is fun stuff.

323
00:18:35,280 --> 00:18:37,439
Speaker 2: Over the Christmas holidays, I've been doing some research on

324
00:18:37,480 --> 00:18:39,760
Speaker 2: things and want to learn about things. But I've been

325
00:18:39,760 --> 00:18:42,520
Speaker 2: watching a lot of YouTube videos for that. Have you

326
00:18:42,560 --> 00:18:45,159
Speaker 2: watched a YouTube video where you thought that could have

327
00:18:45,280 --> 00:18:46,840
Speaker 2: been half page pdf?

328
00:18:47,720 --> 00:18:48,800
Speaker 1: Many? Many yes.

329
00:18:48,880 --> 00:18:50,720
Speaker 2: Yeah, it's kind of like you've been into a meeting

330
00:18:50,760 --> 00:18:52,840
Speaker 2: and that that meeting could have been an email. Right,

331
00:18:53,160 --> 00:18:56,159
Speaker 2: So how do you instead of going through half an

332
00:18:56,200 --> 00:19:02,040
Speaker 2: hour worth of set up, bad jokes, all those kind

333
00:19:02,080 --> 00:19:04,680
Speaker 2: of things to finally get their learning you want? How

334
00:19:04,680 --> 00:19:07,280
Speaker 2: do you do that faster? Well, what you can do

335
00:19:07,359 --> 00:19:10,199
Speaker 2: is open up Notebook LM and it's freedom paid. If

336
00:19:10,240 --> 00:19:12,120
Speaker 2: you want the free, I'm on the free. It's great,

337
00:19:12,560 --> 00:19:16,080
Speaker 2: and you can upload or reference a YouTube video. It

338
00:19:16,119 --> 00:19:18,760
Speaker 2: will then factically read the transcript for that YouTube video

339
00:19:18,800 --> 00:19:22,400
Speaker 2: and then you can ask Notebook LM about that YouTube.

340
00:19:23,000 --> 00:19:26,439
Speaker 2: So for me, I've doing air quotes. Now, I've air

341
00:19:26,520 --> 00:19:30,440
Speaker 2: quotes watched like four times more YouTube videos this last

342
00:19:30,480 --> 00:19:34,439
Speaker 2: summer than I have by using a notebook LM that

343
00:19:34,480 --> 00:19:37,840
Speaker 2: I've actually watched because I'm learning a lot more and

344
00:19:37,880 --> 00:19:40,760
Speaker 2: I'm doing it a lot faster. So if you are

345
00:19:40,800 --> 00:19:42,719
Speaker 2: like me, your time poor. You don't want to hear

346
00:19:42,720 --> 00:19:45,440
Speaker 2: the rambling even two times speeders too slow for you.

347
00:19:45,760 --> 00:19:47,760
Speaker 2: Throw it into notebook LM and get it to talk

348
00:19:47,760 --> 00:19:49,919
Speaker 2: to you about your YouTube.

349
00:19:50,200 --> 00:19:53,680
Speaker 1: Okay, I'll go next with one that I think you

350
00:19:54,160 --> 00:19:59,320
Speaker 1: hadn't heard of, Neo, and it's called letterly. So letter

351
00:19:59,359 --> 00:20:02,520
Speaker 1: is in writing a letter l Y again or linked

352
00:20:02,560 --> 00:20:04,840
Speaker 1: to in the show notes. This is an app that

353
00:20:06,440 --> 00:20:09,240
Speaker 1: solved a bit of a pain point for me. Now, you, Neo,

354
00:20:09,359 --> 00:20:13,120
Speaker 1: I know, are very good at keeping a nightly journal,

355
00:20:13,840 --> 00:20:16,000
Speaker 1: and you have done for several years. I have a

356
00:20:16,040 --> 00:20:19,360
Speaker 1: journal by my bedside table for whatever reason, I don't

357
00:20:19,359 --> 00:20:22,199
Speaker 1: really use it all that much. And so this is

358
00:20:22,280 --> 00:20:24,560
Speaker 1: this is where letterally comes in. Is that often you

359
00:20:24,560 --> 00:20:26,520
Speaker 1: know something will happened during the day. It might be

360
00:20:26,560 --> 00:20:29,560
Speaker 1: a story or an anecdote or something that I just

361
00:20:29,640 --> 00:20:33,840
Speaker 1: I want to remember. And so with letterly, it's it's

362
00:20:33,840 --> 00:20:37,280
Speaker 1: a voice app where you open it up, you hit record,

363
00:20:37,560 --> 00:20:40,359
Speaker 1: and you do a brain dump of your thoughts. For me,

364
00:20:40,400 --> 00:20:43,320
Speaker 1: it might be recounting you know, maybe something that my

365
00:20:43,400 --> 00:20:47,119
Speaker 1: daughter Frankie did, or you know, something memorable that happened

366
00:20:47,160 --> 00:20:49,080
Speaker 1: during the day that I don't want to forget, or

367
00:20:49,359 --> 00:20:51,720
Speaker 1: you know, it might just be emotions that I was feeling,

368
00:20:51,920 --> 00:20:56,080
Speaker 1: and I kind of want to capture that. And then

369
00:20:56,359 --> 00:20:59,960
Speaker 1: with letterly you can prompt how you would like it

370
00:21:00,240 --> 00:21:04,960
Speaker 1: to rewrite essentially that brain dump, and one of those

371
00:21:05,320 --> 00:21:08,280
Speaker 1: is as a journal entry. And so for me it

372
00:21:08,400 --> 00:21:10,720
Speaker 1: solves the problem of I've been really bad at having

373
00:21:10,800 --> 00:21:13,560
Speaker 1: a habit of journal writing, but I find that journal

374
00:21:13,600 --> 00:21:16,600
Speaker 1: talking is so much easier, and you know, rather than

375
00:21:16,640 --> 00:21:19,480
Speaker 1: having to actually pay attention to how I'm writing to

376
00:21:19,520 --> 00:21:21,320
Speaker 1: capture it in a way that makes sense for me,

377
00:21:22,520 --> 00:21:25,040
Speaker 1: it will do that for me, so that I'm capturing

378
00:21:25,080 --> 00:21:28,439
Speaker 1: that memory or that thought or that emotion in a

379
00:21:28,560 --> 00:21:32,200
Speaker 1: really in a really easy but accurate way.

380
00:21:33,600 --> 00:21:35,840
Speaker 2: Are you one of these people who, when you're writing

381
00:21:35,840 --> 00:21:38,359
Speaker 2: a journal, how do I phrase this? How do I

382
00:21:38,359 --> 00:21:40,280
Speaker 2: get this right? Because you're a writer, right, so then

383
00:21:41,200 --> 00:21:43,080
Speaker 2: that there's a blank piece of paper that needs to

384
00:21:43,080 --> 00:21:45,399
Speaker 2: be filled in the right way. Yeah.

385
00:21:45,520 --> 00:21:47,280
Speaker 1: Yeah, And I've tried all sorts of things, like I've

386
00:21:47,280 --> 00:21:51,399
Speaker 1: done morning pages where you have to write three pages NonStop,

387
00:21:51,520 --> 00:21:54,119
Speaker 1: like you know, just train of thought sort of stuff.

388
00:21:54,680 --> 00:21:58,240
Speaker 1: I actually and I think it's I don't know, maybe

389
00:21:58,280 --> 00:22:01,600
Speaker 1: people our age neo not very good at handwriting because

390
00:22:01,600 --> 00:22:04,439
Speaker 1: we rarely have to handwrite, but I really hate the

391
00:22:04,480 --> 00:22:07,320
Speaker 1: process of having to handwrite something and that is a

392
00:22:07,320 --> 00:22:11,359
Speaker 1: real blocker for journal writing for me. So, you know,

393
00:22:11,440 --> 00:22:15,000
Speaker 1: for listeners that can relate that really just don't like

394
00:22:15,560 --> 00:22:20,040
Speaker 1: writing with pen and paper, I highly recommend latterly. Now,

395
00:22:20,080 --> 00:22:22,240
Speaker 1: do we have one more recommendation Neo.

396
00:22:22,800 --> 00:22:28,000
Speaker 2: Yeah, this one is a little bit gikky, but once

397
00:22:28,040 --> 00:22:30,800
Speaker 2: again it can be handy for those people who need it.

398
00:22:31,760 --> 00:22:35,320
Speaker 2: So you can run AI models on your own computer.

399
00:22:35,400 --> 00:22:37,639
Speaker 2: Now you do need a beefy ish kind of computer

400
00:22:37,760 --> 00:22:39,520
Speaker 2: or if you've got to Mac. The recent Max pretty

401
00:22:39,520 --> 00:22:41,159
Speaker 2: good for this if you've got a little bit of RAM.

402
00:22:41,760 --> 00:22:45,000
Speaker 2: But you can run not as intelligent models as sayt

403
00:22:45,440 --> 00:22:47,960
Speaker 2: and Gemini and whatnot, but you can run small, light

404
00:22:48,040 --> 00:22:49,240
Speaker 2: models on your own laptop.

405
00:22:49,800 --> 00:22:52,280
Speaker 1: So why would someone want to do that though, Like,

406
00:22:52,359 --> 00:22:55,119
Speaker 1: why can't we just rely on the great big models

407
00:22:55,160 --> 00:22:55,560
Speaker 1: out there?

408
00:22:55,760 --> 00:22:58,399
Speaker 2: Yeah, it's a great quazy So a couple of reasons.

409
00:22:58,520 --> 00:23:01,560
Speaker 2: One is maybe you don't want to give your data

410
00:23:01,560 --> 00:23:04,720
Speaker 2: to those companies. Maybe you can't give your data to

411
00:23:04,720 --> 00:23:06,879
Speaker 2: the company. So I'm just say I'm working at a

412
00:23:06,880 --> 00:23:12,320
Speaker 2: pharmaceutical company, I'm in defense, or I'm got my health

413
00:23:12,359 --> 00:23:14,639
Speaker 2: records that I just don't want to give to AI.

414
00:23:15,240 --> 00:23:18,520
Speaker 2: Then running it locally and giving my data to a

415
00:23:18,680 --> 00:23:21,479
Speaker 2: local AI knows it means that information is not going

416
00:23:21,480 --> 00:23:25,160
Speaker 2: to leave my computer ever, and I've got full control

417
00:23:25,280 --> 00:23:27,760
Speaker 2: over that. And so for a security for privacy, it

418
00:23:27,840 --> 00:23:31,640
Speaker 2: is absolutely number one. Also for utility, it's pretty good.

419
00:23:31,840 --> 00:23:33,680
Speaker 2: So a couple of months back, I was on a

420
00:23:33,680 --> 00:23:36,800
Speaker 2: plane to Perth for a client and I was working

421
00:23:36,840 --> 00:23:41,119
Speaker 2: on some AI stuff, doing some lesson design, and I

422
00:23:41,160 --> 00:23:44,000
Speaker 2: was also doing some programming at the time for our

423
00:23:44,119 --> 00:23:48,280
Speaker 2: Agentic course. Now I used to be a programmer, but

424
00:23:48,320 --> 00:23:50,280
Speaker 2: you do not want me to program anything anymore. I'm

425
00:23:50,280 --> 00:23:53,080
Speaker 2: just terrible. So I need AI always to help me

426
00:23:53,119 --> 00:23:55,119
Speaker 2: with my programming. And so I was stuck on this

427
00:23:55,200 --> 00:23:58,520
Speaker 2: programming problem. Now the Wi Fi was down on the

428
00:23:58,560 --> 00:24:01,680
Speaker 2: aircraft on the entire flo to Perth. So my heart

429
00:24:01,840 --> 00:24:05,440
Speaker 2: sank as I was boarding the aircraft when they found

430
00:24:05,520 --> 00:24:09,439
Speaker 2: this out. But luckily I had this local large language

431
00:24:09,440 --> 00:24:13,359
Speaker 2: bottle on my laptop. It wasn't as smart ASGBT, but

432
00:24:13,480 --> 00:24:16,200
Speaker 2: it helped me solve my problems, particularly with those programming

433
00:24:16,800 --> 00:24:19,080
Speaker 2: and also need to get some show notes put together,

434
00:24:19,200 --> 00:24:20,960
Speaker 2: and so I got to clean up my show notes

435
00:24:20,960 --> 00:24:24,240
Speaker 2: for me to make sure there's a graphical errors fixed up.

436
00:24:24,280 --> 00:24:27,560
Speaker 2: So here I was able to use my own laptop

437
00:24:28,280 --> 00:24:31,000
Speaker 2: on a flight with no Wi Fi to still do

438
00:24:31,200 --> 00:24:34,280
Speaker 2: AI ish things, to still be productive. So if you

439
00:24:34,320 --> 00:24:37,000
Speaker 2: need to do this for security, for proprivacy, maybe that's

440
00:24:37,040 --> 00:24:38,080
Speaker 2: one of the ways you could do it. Like if

441
00:24:38,119 --> 00:24:41,240
Speaker 2: you can pharmaceuticals or healthcare or medical records, maybe you

442
00:24:41,400 --> 00:24:43,239
Speaker 2: can set that up and got to check with your

443
00:24:43,240 --> 00:24:46,600
Speaker 2: company of course, or maybe you just go my health records.

444
00:24:46,640 --> 00:24:48,200
Speaker 2: I don't want to give that to the big companies

445
00:24:48,200 --> 00:24:50,679
Speaker 2: because I don't trust them, and that's fair enough. Or

446
00:24:50,920 --> 00:24:53,880
Speaker 2: you like me, and occasionally you don't have internet connection

447
00:24:53,960 --> 00:24:55,840
Speaker 2: to be able to use those favorite tools, well maybe

448
00:24:55,840 --> 00:24:58,200
Speaker 2: you just a be geeky download and leave one of

449
00:24:58,240 --> 00:25:01,520
Speaker 2: these tools. So one of them is called anything l

450
00:25:01,800 --> 00:25:06,040
Speaker 2: l M. Another one's called OLAMA. Now what you can

451
00:25:06,040 --> 00:25:08,800
Speaker 2: do with these is you can affectively download the application

452
00:25:09,160 --> 00:25:11,840
Speaker 2: and then after that you can then download these AI

453
00:25:12,000 --> 00:25:14,879
Speaker 2: models to run on your laptop. And there's different flavors

454
00:25:14,880 --> 00:25:17,439
Speaker 2: out there you can try. It's a bit geeky bit.

455
00:25:17,480 --> 00:25:19,320
Speaker 2: Given a tray, you might find that fire is the

456
00:25:19,359 --> 00:25:21,720
Speaker 2: one you want. Maybe LAMA is the one you want.

457
00:25:21,920 --> 00:25:24,960
Speaker 2: Maybe Mistral is the There's different flavors out there, but

458
00:25:25,040 --> 00:25:27,440
Speaker 2: go down the rabbit hole has some fun. But also

459
00:25:27,720 --> 00:25:30,280
Speaker 2: know that you're running this locally on your laptop, so

460
00:25:30,400 --> 00:25:33,160
Speaker 2: everything is stored on your laptop.

461
00:25:34,440 --> 00:25:38,359
Speaker 1: What a great geeky recommendation to finish on. Now, Neo

462
00:25:38,440 --> 00:25:41,560
Speaker 1: and I are going to be in your ears every

463
00:25:41,840 --> 00:25:45,880
Speaker 1: Monday this year with how i AI. So if you

464
00:25:45,960 --> 00:25:49,840
Speaker 1: want short, sharp, practical tips on how to get more

465
00:25:50,000 --> 00:25:54,359
Speaker 1: out of AI in your work and life, hit follow

466
00:25:54,640 --> 00:25:58,119
Speaker 1: or subscribe to how I Work because it's in the

467
00:25:58,160 --> 00:26:01,680
Speaker 1: How I Work feed that the how IAI episodes will

468
00:26:01,760 --> 00:26:06,800
Speaker 1: drop and we will see you Monday. If you want

469
00:26:06,840 --> 00:26:12,359
Speaker 1: more shortshut practical conversations about AI, follow how I Work

470
00:26:12,520 --> 00:26:17,200
Speaker 1: in your podcast feed because how IAI drops right here

471
00:26:17,680 --> 00:26:22,280
Speaker 1: every Monday. How IAI was hosted by me, Amantha Imber

472
00:26:22,359 --> 00:26:25,080
Speaker 1: and Leo Applan. A big thank you to Martin Imber

473
00:26:25,119 --> 00:26:29,040
Speaker 1: who does our sound editing, and Jem Rubio for production support,

474
00:26:29,359 --> 00:26:31,960
Speaker 1: and thank you to John Kilby who composed the theme

475
00:26:32,040 --> 00:26:32,399
Speaker 1: music