1 00:00:00,120 --> 00:00:03,680 Speaker 1: You are listening to Ruthie's Table four in partnership with Montclair. 2 00:00:04,440 --> 00:00:07,160 Speaker 2: I have friends who are writers, friends who are artists, 3 00:00:07,200 --> 00:00:09,960 Speaker 2: friends who are chefs, and it's easy for me to. 4 00:00:10,000 --> 00:00:11,200 Speaker 3: Describe what they do. 5 00:00:11,960 --> 00:00:16,239 Speaker 2: Alexander Muzaviza Day, however, is my closest friend, and I 6 00:00:16,280 --> 00:00:19,520 Speaker 2: have little idea how to describe what she does. 7 00:00:20,040 --> 00:00:24,520 Speaker 3: It's complex, it's interesting, and so far a new world. 8 00:00:24,640 --> 00:00:25,480 Speaker 3: This I do know. 9 00:00:26,040 --> 00:00:29,760 Speaker 2: Alexander is an economist, an expert in game theory and AI, 10 00:00:30,120 --> 00:00:34,440 Speaker 2: and in twenty twenty two co founded Evident with Annabel Isles, 11 00:00:34,840 --> 00:00:38,960 Speaker 2: two women creating an index at Benchmark companies on their 12 00:00:39,080 --> 00:00:42,640 Speaker 2: AI performance. But if it's challenging to tell you about 13 00:00:42,680 --> 00:00:45,400 Speaker 2: her in professional terms, I can tell you what she's 14 00:00:45,479 --> 00:00:50,879 Speaker 2: like as a friend. Alexander is warm, she's empathetic, she's energetic, she's. 15 00:00:50,720 --> 00:00:52,440 Speaker 3: Brave, and she's resilient. 16 00:00:52,920 --> 00:00:55,080 Speaker 2: I know this as a fact, as I speak to 17 00:00:55,080 --> 00:00:59,880 Speaker 2: her most evenings before sleeping at Moe's mornings immediately after waking. 18 00:01:00,560 --> 00:01:03,200 Speaker 2: Early on in our friendship, I got a glimpse into 19 00:01:03,240 --> 00:01:07,080 Speaker 2: her character that has stayed with me ever since. Rescuing 20 00:01:07,080 --> 00:01:09,479 Speaker 2: one of her children's football she fell off a roof 21 00:01:09,520 --> 00:01:12,000 Speaker 2: and her wedding ring caught on the slats of a fence. 22 00:01:12,520 --> 00:01:15,280 Speaker 2: It was only when she heard its clink that she'd 23 00:01:15,319 --> 00:01:18,680 Speaker 2: realized she'd lost a finger. She picked it up, went 24 00:01:18,720 --> 00:01:21,520 Speaker 2: to the hospital, and the next morning was at her 25 00:01:21,560 --> 00:01:22,520 Speaker 2: desk at work. 26 00:01:22,880 --> 00:01:25,640 Speaker 3: No complaints, no self pity. That is true. 27 00:01:26,200 --> 00:01:28,200 Speaker 2: It wasn't the clinking of the We can do a 28 00:01:28,240 --> 00:01:30,600 Speaker 2: fact check if don't about it. It was basically never 29 00:01:30,680 --> 00:01:33,040 Speaker 2: let facts real. A good story, but it was a 30 00:01:33,080 --> 00:01:35,560 Speaker 2: clinking of the of the wedding ring. 31 00:01:36,160 --> 00:01:38,960 Speaker 4: It was oddly enough, I didn't feel the finger being 32 00:01:39,080 --> 00:01:41,560 Speaker 4: ripped out of my hand, but I only noticed it 33 00:01:41,560 --> 00:01:43,560 Speaker 4: when I saw the wedding ring and my finger on 34 00:01:43,600 --> 00:01:46,280 Speaker 4: the floor. And then I couldn't get an ambulance. Called 35 00:01:46,319 --> 00:01:49,320 Speaker 4: the ambulance and they said, sorry, only bit's a major 36 00:01:50,120 --> 00:01:52,480 Speaker 4: major injury, two figures, maybe one finger. 37 00:01:52,600 --> 00:01:54,200 Speaker 3: Sorry we're British. 38 00:01:54,760 --> 00:01:57,600 Speaker 4: That was not considered major. But I think, you know, 39 00:01:57,640 --> 00:01:59,720 Speaker 4: one of my biggest memories from that moment, and I 40 00:01:59,760 --> 00:02:02,400 Speaker 4: had just moved to London from New York, was what 41 00:02:02,560 --> 00:02:05,640 Speaker 4: happened right after was a knock on the hospital door 42 00:02:05,960 --> 00:02:10,000 Speaker 4: and in came a tray from you, Ruthy with sea 43 00:02:10,040 --> 00:02:14,200 Speaker 4: bass slow cook piece a bottle of wine. A bottle 44 00:02:14,240 --> 00:02:17,680 Speaker 4: of wine, a pink napkin or orange, a knife and fork, 45 00:02:18,160 --> 00:02:21,080 Speaker 4: and a piece of chocolate nemesis. And I think that 46 00:02:21,240 --> 00:02:24,360 Speaker 4: was why I could skip home the next day from 47 00:02:24,360 --> 00:02:25,040 Speaker 4: the hospital. 48 00:02:25,160 --> 00:02:29,000 Speaker 2: The NHS doesn't necessarily provide that kind of cure. 49 00:02:29,320 --> 00:02:30,120 Speaker 3: That was all due to you. 50 00:02:30,200 --> 00:02:31,840 Speaker 2: Has nothing to do with the food is due to 51 00:02:32,680 --> 00:02:34,520 Speaker 2: do to you. That was and that just is an 52 00:02:34,520 --> 00:02:35,880 Speaker 2: incredible memory. 53 00:02:36,320 --> 00:02:38,160 Speaker 3: Yeah, and you just were in New York, weren't you. 54 00:02:38,280 --> 00:02:43,279 Speaker 4: I was an Aspen Aspen Ideas festival life. It was fantastic. 55 00:02:43,880 --> 00:02:46,840 Speaker 4: It is the the great Aspen Ideas festival that has 56 00:02:46,880 --> 00:02:50,000 Speaker 4: been I think going for more than twenty years, and. 57 00:02:49,919 --> 00:02:52,000 Speaker 2: So it was just it was the world in the 58 00:02:52,000 --> 00:02:53,040 Speaker 2: place we were away. 59 00:02:53,200 --> 00:02:53,799 Speaker 3: Yeah, the world. 60 00:02:54,040 --> 00:02:56,200 Speaker 2: Yes, it was right a week after Iran. 61 00:02:56,440 --> 00:02:58,880 Speaker 4: Yeah, yes, yeah, So there's a lot of discussion. 62 00:02:59,240 --> 00:03:01,760 Speaker 3: Was that AI as well? 63 00:03:01,880 --> 00:03:04,399 Speaker 4: I think it was more convention, It was more sort 64 00:03:04,400 --> 00:03:08,200 Speaker 4: of traditional warfare, but of course AI plays a huge 65 00:03:08,240 --> 00:03:12,280 Speaker 4: role in warfare today and autonomous drones and the weaponry 66 00:03:12,360 --> 00:03:15,400 Speaker 4: that's built in the presition that we can we can 67 00:03:15,440 --> 00:03:18,480 Speaker 4: point the weapons at today. But yeah, it came right 68 00:03:18,520 --> 00:03:21,480 Speaker 4: after obviously, right at the sort of the heels of 69 00:03:21,520 --> 00:03:23,440 Speaker 4: the bombing of Iran, and so a lot of the 70 00:03:23,480 --> 00:03:27,120 Speaker 4: conversation was about the Middle East and what might happen. 71 00:03:27,760 --> 00:03:31,160 Speaker 2: You and I were a lunch at the River Cafe 72 00:03:31,560 --> 00:03:34,760 Speaker 2: two years ago, I think, and the host of the lunch, 73 00:03:34,840 --> 00:03:38,280 Speaker 2: Matthew Barton, asked a question to the table, which was 74 00:03:38,720 --> 00:03:44,200 Speaker 2: is there something an idea thought that the world is 75 00:03:44,240 --> 00:03:46,920 Speaker 2: afraid of that people are afraid of but you're not. 76 00:03:47,520 --> 00:03:49,720 Speaker 2: And when it came to you, you said that you 77 00:03:49,760 --> 00:03:53,800 Speaker 2: were not afraid of AI. But it always interested me 78 00:03:53,880 --> 00:03:57,160 Speaker 2: that the word fear came up so much and still 79 00:03:57,200 --> 00:03:59,440 Speaker 2: does when you talk about AI. 80 00:03:59,840 --> 00:04:01,840 Speaker 4: It's a question I get a lot, and I do 81 00:04:01,920 --> 00:04:04,720 Speaker 4: think it's a shame that the debate is where the 82 00:04:04,760 --> 00:04:09,040 Speaker 4: debate is today, because it is very dominated by a 83 00:04:09,200 --> 00:04:14,800 Speaker 4: fear around this technology and the way it's covered in 84 00:04:15,400 --> 00:04:21,560 Speaker 4: the press, but also by a lot of academics talking about, 85 00:04:21,880 --> 00:04:24,640 Speaker 4: you know, what is the non zero risk of things 86 00:04:24,640 --> 00:04:28,560 Speaker 4: can going wrong? And I think that it's getting too 87 00:04:28,640 --> 00:04:30,960 Speaker 4: much coverage in the sense that, of course we need 88 00:04:30,960 --> 00:04:33,559 Speaker 4: to talk about the risks, but we should also really 89 00:04:33,600 --> 00:04:36,839 Speaker 4: focus on all of the opportunities and what it will 90 00:04:36,839 --> 00:04:41,000 Speaker 4: do to our society, us as individuals, the businesses that 91 00:04:41,040 --> 00:04:45,040 Speaker 4: we're running, our education, our children. AI has a really 92 00:04:45,080 --> 00:04:47,359 Speaker 4: important and positive role to play in all of this. 93 00:04:47,920 --> 00:04:49,960 Speaker 4: And I'm not saying there isn't a risk out there 94 00:04:50,040 --> 00:04:52,839 Speaker 4: on the horizon, but that risk, I think is very 95 00:04:52,920 --> 00:04:55,960 Speaker 4: much overplayed, and I think it's underplayed what the opportunities 96 00:04:56,040 --> 00:04:59,520 Speaker 4: are and when I'm looking at, you know, just every 97 00:04:59,560 --> 00:05:01,880 Speaker 4: day day today, the way we use it, the way 98 00:05:01,920 --> 00:05:04,719 Speaker 4: that the businesses that we're working with use it, and 99 00:05:04,839 --> 00:05:07,440 Speaker 4: how that is helping and it's augmenting the way we 100 00:05:07,480 --> 00:05:11,120 Speaker 4: optimize our supply chains and that we can get you know, 101 00:05:11,200 --> 00:05:15,240 Speaker 4: things at a bit better and cheaper rate to our 102 00:05:15,320 --> 00:05:18,920 Speaker 4: tables is all AI driven. The way that we even 103 00:05:19,000 --> 00:05:21,400 Speaker 4: just interact with what we have in our fridge. Tell 104 00:05:21,440 --> 00:05:24,279 Speaker 4: me about that, well, you know, there are tools now 105 00:05:24,320 --> 00:05:26,279 Speaker 4: where you can take a photograph of your fridge and 106 00:05:26,400 --> 00:05:29,039 Speaker 4: optimize what you're cooking, simple as that, what do I 107 00:05:29,040 --> 00:05:32,240 Speaker 4: do with these ingredients or how do I optimize for 108 00:05:32,960 --> 00:05:36,160 Speaker 4: you know, shopping in a sustainable way. When I'm looking 109 00:05:36,240 --> 00:05:39,559 Speaker 4: at what the ingredients are in my kitchen, when should 110 00:05:39,560 --> 00:05:42,279 Speaker 4: I when should I make sure to eat this before 111 00:05:42,279 --> 00:05:44,240 Speaker 4: it goes off? So I don't open the fridge and 112 00:05:44,240 --> 00:05:46,440 Speaker 4: then suddenly it's gone off. And so there's lots of 113 00:05:46,440 --> 00:05:50,440 Speaker 4: these apps and ways to optimize reducing waste, is making 114 00:05:50,480 --> 00:05:52,400 Speaker 4: it as which is a good thing, which is making 115 00:05:52,400 --> 00:05:54,640 Speaker 4: it easier for families to cook, which is a good thing. 116 00:05:55,120 --> 00:05:57,320 Speaker 4: And at the sort of supply chain and sort of 117 00:05:57,680 --> 00:06:00,640 Speaker 4: the sort of industrial agriculture side, you know, you've got 118 00:06:00,640 --> 00:06:03,560 Speaker 4: the breakthroughs of AI that are helping to optimize the 119 00:06:03,600 --> 00:06:06,279 Speaker 4: way we plant things and the way we are growing 120 00:06:06,360 --> 00:06:09,279 Speaker 4: things in new and innovative ways. AI lies at the 121 00:06:09,279 --> 00:06:10,200 Speaker 4: heart of that as well. 122 00:06:11,320 --> 00:06:15,120 Speaker 5: So the future is right, yes, it is, no, it 123 00:06:15,200 --> 00:06:19,400 Speaker 5: is absolutely think in medicine and yeah, and we do 124 00:06:19,440 --> 00:06:24,120 Speaker 5: struggle with food poverty, food in prisons, food and the 125 00:06:24,200 --> 00:06:26,880 Speaker 5: way we feed our children, the way we feed our sick, 126 00:06:27,120 --> 00:06:31,800 Speaker 5: the way we don't have accessibility in poor neighborhoods for. 127 00:06:32,080 --> 00:06:35,320 Speaker 2: Fresh vegetables, the way we grow our vegetables, and as 128 00:06:35,360 --> 00:06:36,760 Speaker 2: you say, really. 129 00:06:36,520 --> 00:06:40,000 Speaker 3: Struck was waste. Do you know people who are working in 130 00:06:40,000 --> 00:06:42,440 Speaker 3: this field? Very Have you met any people? I do? 131 00:06:42,560 --> 00:06:45,760 Speaker 4: Tangentially yes, And we should come in and make sure 132 00:06:45,800 --> 00:06:48,119 Speaker 4: AI is at the heart of the River Cafe as well. 133 00:06:48,600 --> 00:06:52,919 Speaker 4: Optimizing no waste and all of that but there's a 134 00:06:52,920 --> 00:06:55,960 Speaker 4: lot of big organizations that are in the sort of 135 00:06:55,960 --> 00:07:00,799 Speaker 4: food industry where they are hiring heads of AI, heads 136 00:07:00,800 --> 00:07:03,680 Speaker 4: of technology working out how they can just do what 137 00:07:03,720 --> 00:07:07,479 Speaker 4: they do but better with less waste. And so it's 138 00:07:07,480 --> 00:07:12,720 Speaker 4: definitely absolutely being implemented in the food and agricultural industry already. 139 00:07:12,760 --> 00:07:16,160 Speaker 4: There's an amazing story about John Deere. You know, they 140 00:07:16,200 --> 00:07:21,760 Speaker 4: do farmed and equipment and it's completely AI driven. They 141 00:07:21,920 --> 00:07:24,880 Speaker 4: use they draw down from satellites that can predict the weather. 142 00:07:25,480 --> 00:07:29,400 Speaker 4: They have sensors in the soil they are now planting with, 143 00:07:29,520 --> 00:07:32,560 Speaker 4: you know, sort of optimizing for sort of being much 144 00:07:32,600 --> 00:07:35,600 Speaker 4: more precise, and so their yields are much higher. I mean, 145 00:07:35,640 --> 00:07:39,800 Speaker 4: it's an absolutely incredible story. Every part and side and 146 00:07:39,880 --> 00:07:42,920 Speaker 4: top and bottom of these John Deere machinery is AI 147 00:07:43,080 --> 00:07:46,920 Speaker 4: equipment and it is It is fantastic to see how 148 00:07:46,960 --> 00:07:50,200 Speaker 4: they've been able to transform the agricultural space. 149 00:07:51,000 --> 00:07:53,880 Speaker 2: We started with Aspen, And what did you come away 150 00:07:54,000 --> 00:07:57,640 Speaker 2: from Aspen with When you're listening to you, yeah, people, 151 00:07:57,680 --> 00:07:59,720 Speaker 2: but what did you feel when you came away from this? 152 00:07:59,880 --> 00:08:03,600 Speaker 4: I felt that it was there was a lot more optimism. 153 00:08:03,760 --> 00:08:08,360 Speaker 4: Maybe that's my you know, my prism to see things through. 154 00:08:08,440 --> 00:08:10,720 Speaker 4: But I thought that there was a lot of optimism. 155 00:08:11,240 --> 00:08:14,280 Speaker 4: We're talking about fear before. There's still a lot of 156 00:08:14,320 --> 00:08:16,600 Speaker 4: fear what Trump can do to the world, and I 157 00:08:16,640 --> 00:08:19,600 Speaker 4: think everyone's still holding their breath, but I also think 158 00:08:19,720 --> 00:08:23,080 Speaker 4: that everyone's a bit more prepared and therefore was so 159 00:08:23,120 --> 00:08:25,800 Speaker 4: a bit more optimistic that, you know, Europe is going 160 00:08:25,840 --> 00:08:29,400 Speaker 4: to be strengthened, the tariffs might not be crashing the 161 00:08:29,440 --> 00:08:33,079 Speaker 4: world economy as we feared on April tewcond when he 162 00:08:33,520 --> 00:08:36,200 Speaker 4: at first announced it. So there was a bit more 163 00:08:36,760 --> 00:08:41,120 Speaker 4: hope and optimism about economic growth, about employment. But there's 164 00:08:41,160 --> 00:08:43,600 Speaker 4: still a lot of concern about what these next couple 165 00:08:43,600 --> 00:08:45,880 Speaker 4: of years will look like with him at the HELM. 166 00:08:46,360 --> 00:08:48,760 Speaker 4: A lot of you know, talks from CEOs as well, 167 00:08:48,760 --> 00:08:50,800 Speaker 4: which I think one of the issues that we may 168 00:08:50,800 --> 00:08:53,440 Speaker 4: be underestimate is is just how difficult it is to 169 00:08:53,480 --> 00:08:55,920 Speaker 4: be a CEO today and the things that they've got 170 00:08:55,920 --> 00:09:00,560 Speaker 4: to navigate. Also on the AI front, but so that 171 00:09:00,640 --> 00:09:03,440 Speaker 4: was also very much on the agenda and so as 172 00:09:03,440 --> 00:09:06,200 Speaker 4: well as arts and culture and music. So but the 173 00:09:06,200 --> 00:09:07,560 Speaker 4: optimism definitely came through. 174 00:09:08,440 --> 00:09:10,920 Speaker 2: And also people you know, as you say, traveling to 175 00:09:11,000 --> 00:09:13,480 Speaker 2: a place slightly out of the world to talk, just 176 00:09:13,520 --> 00:09:16,880 Speaker 2: to have that, you know, shared communication, which you can 177 00:09:16,960 --> 00:09:19,600 Speaker 2: do over online. You can do it over computer, do 178 00:09:19,640 --> 00:09:20,960 Speaker 2: it over phone, do it over zoom. 179 00:09:21,000 --> 00:09:23,199 Speaker 3: But we actually have that. Did you eat well? What 180 00:09:23,280 --> 00:09:23,880 Speaker 3: was the food like? 181 00:09:24,000 --> 00:09:26,160 Speaker 4: The food was restaurants, good restaurants. 182 00:09:26,240 --> 00:09:30,800 Speaker 2: The food restaurants in Aspens in Yeah, it was. 183 00:09:31,000 --> 00:09:33,800 Speaker 4: It was very fresh in the and the walking in 184 00:09:33,840 --> 00:09:38,679 Speaker 4: the mountains is very special. Beautiful light and the smell 185 00:09:38,720 --> 00:09:41,920 Speaker 4: of the woods and there, and it's yeah, it was. 186 00:09:42,040 --> 00:09:43,920 Speaker 4: It was very special. So going on a lot of 187 00:09:44,000 --> 00:09:45,920 Speaker 4: hikes and bike rides. But the food was really good too. 188 00:09:46,040 --> 00:09:48,440 Speaker 2: Yes, you know, you went to school twenty miles from Aspen. 189 00:09:48,880 --> 00:09:51,800 Speaker 2: I spent my teenage years in a school called the 190 00:09:51,800 --> 00:09:56,679 Speaker 2: Colorado Rocky Mountain School, and it's in Carbondale, And this 191 00:09:56,760 --> 00:10:02,920 Speaker 2: is in you know, nineteen sixty eight, and and we 192 00:10:02,960 --> 00:10:05,640 Speaker 2: went to Asmen was a small town. You know, it 193 00:10:05,720 --> 00:10:09,760 Speaker 2: was still very beautiful. I mean it was the early days. 194 00:10:09,760 --> 00:10:12,840 Speaker 2: It didn't have the glamour of yet that it has 195 00:10:12,960 --> 00:10:15,360 Speaker 2: now or the as you say, the they. 196 00:10:15,120 --> 00:10:16,280 Speaker 3: Had the Assmen Center. 197 00:10:17,040 --> 00:10:19,560 Speaker 2: I think there was because I remember going to see 198 00:10:19,679 --> 00:10:24,719 Speaker 2: a warhole show there very early on. And it had 199 00:10:24,720 --> 00:10:27,240 Speaker 2: a it always had a kind of cultural emphasis as 200 00:10:27,280 --> 00:10:29,680 Speaker 2: as well as being a ski village in a mountain 201 00:10:29,760 --> 00:10:31,079 Speaker 2: village and beautiful. 202 00:10:31,160 --> 00:10:34,680 Speaker 3: But I love that area. Yeah, it's beautiful and. 203 00:10:34,760 --> 00:10:38,319 Speaker 4: It's a big There's the Anderson Institute there now, yeah, 204 00:10:38,320 --> 00:10:40,480 Speaker 4: which is a big art art institute and they have 205 00:10:40,600 --> 00:10:42,880 Speaker 4: taken a lot of artists and spend the summers and 206 00:10:42,920 --> 00:10:45,560 Speaker 4: winters there working. It was Yeah, it still has that 207 00:10:45,920 --> 00:10:49,960 Speaker 4: and very much you know, art, arts and culture scene. Yeah. 208 00:10:50,000 --> 00:10:52,120 Speaker 4: But with you, I've we've talked all the time, and 209 00:10:52,160 --> 00:10:55,760 Speaker 4: I didn't know you had went to school done more things. 210 00:10:57,080 --> 00:11:00,400 Speaker 2: Tell me about the early early years of of your 211 00:11:00,440 --> 00:11:02,240 Speaker 2: life or your parents' cooks. 212 00:11:02,880 --> 00:11:06,080 Speaker 4: So I was born in Copenhagen in nineteen seventy and 213 00:11:07,120 --> 00:11:10,960 Speaker 4: food back then Copenhagen was very different from the vibrant 214 00:11:10,960 --> 00:11:15,280 Speaker 4: food scene today. Why was and it was just still 215 00:11:15,320 --> 00:11:19,640 Speaker 4: slightly removed from the world, aside from Denmark having a 216 00:11:19,679 --> 00:11:23,400 Speaker 4: really big footprint in terms of furniture Hans Wagner Berg 217 00:11:23,480 --> 00:11:27,720 Speaker 4: Morgensen from the nineteen fifties and sixties. It was quite removed. 218 00:11:28,679 --> 00:11:34,119 Speaker 4: My family was a slightly odd one because my mother's English. 219 00:11:34,280 --> 00:11:37,160 Speaker 4: They met and that's a funny story. We can get 220 00:11:37,160 --> 00:11:40,320 Speaker 4: into how they met but they met in London in 221 00:11:40,360 --> 00:11:45,360 Speaker 4: fifty six. They met because they were introduced to each 222 00:11:45,440 --> 00:11:49,760 Speaker 4: other as being direct descendants of men who had destroyed 223 00:11:50,160 --> 00:11:54,760 Speaker 4: or sunk the Danish fleet. And that was an unusual 224 00:11:55,160 --> 00:11:55,920 Speaker 4: background to have. 225 00:11:56,040 --> 00:11:57,840 Speaker 2: On my mother's side, I was going to say, because 226 00:11:57,960 --> 00:12:01,040 Speaker 2: the day wouldn't necessarily want to sank the Danish. 227 00:12:01,559 --> 00:12:01,760 Speaker 3: No. 228 00:12:01,880 --> 00:12:04,480 Speaker 4: So on my father's side, his father had was at 229 00:12:05,040 --> 00:12:06,840 Speaker 4: head of the navy, so he was an admiral in 230 00:12:06,880 --> 00:12:10,120 Speaker 4: the navy during the Second World War, and when it 231 00:12:10,160 --> 00:12:13,080 Speaker 4: became known that the Germans wanted to put their hands 232 00:12:13,160 --> 00:12:15,160 Speaker 4: on the Danish fleet to get to the Baltics and 233 00:12:15,200 --> 00:12:19,360 Speaker 4: to get to the UK, he got word early and 234 00:12:20,360 --> 00:12:23,839 Speaker 4: jumped on his bicycle and rode out to the harbor 235 00:12:23,840 --> 00:12:27,200 Speaker 4: where all of the Danish fleet was waiting, and said, 236 00:12:27,559 --> 00:12:31,480 Speaker 4: you know, pull the plugs, pull the plugs, and destroyed 237 00:12:31,520 --> 00:12:34,960 Speaker 4: and sank the entire Danish fleet. And was a hero 238 00:12:35,120 --> 00:12:37,920 Speaker 4: on account of that, because it would have been a disaster. 239 00:12:38,360 --> 00:12:41,079 Speaker 4: It could have been a different, not necessarily a different 240 00:12:41,080 --> 00:12:42,600 Speaker 4: outcome of the war, but it would not have been 241 00:12:42,880 --> 00:12:45,920 Speaker 4: good if the Germans had got hold of a quite 242 00:12:46,000 --> 00:12:48,520 Speaker 4: strong Danish navy, and they could have done a lot 243 00:12:48,559 --> 00:12:51,080 Speaker 4: of damage with that, so he sunk the Danish fleet. 244 00:12:51,480 --> 00:12:54,640 Speaker 4: And on my mother's side, being a direct descendant of 245 00:12:54,720 --> 00:12:58,880 Speaker 4: Lord Nelson, had bombed Copenhagen in eighteen oh one and 246 00:12:58,960 --> 00:13:03,199 Speaker 4: sunk the Danish fleet. So they were introduced to each 247 00:13:03,240 --> 00:13:05,920 Speaker 4: other in fifty six at some cocktail party in London 248 00:13:06,040 --> 00:13:09,160 Speaker 4: and said, here's the You know, two people who both 249 00:13:09,360 --> 00:13:12,319 Speaker 4: you know, have have sunk the Danish fleet, so combined 250 00:13:12,320 --> 00:13:15,200 Speaker 4: they're quite dangerous. So they met and they married. My 251 00:13:15,280 --> 00:13:19,640 Speaker 4: mother was nineteen and she moved to Copenhagen in fifty 252 00:13:19,679 --> 00:13:23,480 Speaker 4: seven and it was, yeah, I think it was difficult 253 00:13:23,559 --> 00:13:26,800 Speaker 4: for her to live in Copenhagen. It was, you know, 254 00:13:26,880 --> 00:13:30,160 Speaker 4: London was changing so much and music and you know, 255 00:13:30,440 --> 00:13:34,319 Speaker 4: arts and years before all of that and the swinging sixties, 256 00:13:34,520 --> 00:13:36,679 Speaker 4: and you came to Copenhagen in fifty seven and it 257 00:13:36,720 --> 00:13:38,800 Speaker 4: was it was a bit bleak. It was still sort 258 00:13:38,840 --> 00:13:41,600 Speaker 4: of post war, a lot of restrictions on what you 259 00:13:41,600 --> 00:13:44,240 Speaker 4: could cook with and what came into the country, and 260 00:13:44,640 --> 00:13:47,000 Speaker 4: she refused to learn Danish. So I grew up in 261 00:13:47,000 --> 00:13:49,800 Speaker 4: a household where it was my very Danish father and 262 00:13:49,840 --> 00:13:53,240 Speaker 4: my very English mother and it was complete mayhem at 263 00:13:53,240 --> 00:13:56,160 Speaker 4: the dinner table. Because we were always speaking both languages. 264 00:13:57,960 --> 00:14:01,840 Speaker 4: But in terms of cooking shed she was very brilliant 265 00:14:02,120 --> 00:14:05,160 Speaker 4: and skipped four grades at school and had a very 266 00:14:05,240 --> 00:14:08,679 Speaker 4: high IQ. But was her big dream was to become 267 00:14:08,679 --> 00:14:11,800 Speaker 4: a doctor or a scientist. And then her parents said 268 00:14:12,520 --> 00:14:15,839 Speaker 4: it wasn't done for girls at the time to go 269 00:14:15,920 --> 00:14:17,760 Speaker 4: and get that kind of education, and of course she 270 00:14:17,760 --> 00:14:19,760 Speaker 4: shouldn't have listened, and she should have just have done it, 271 00:14:19,800 --> 00:14:22,480 Speaker 4: but they sent her to finishing school in Paris, and 272 00:14:22,520 --> 00:14:25,720 Speaker 4: then she met my father. So she was a really 273 00:14:25,760 --> 00:14:31,320 Speaker 4: good cook, but she was also really disorganized. So when 274 00:14:31,360 --> 00:14:35,520 Speaker 4: she was cooking, it would be Martini's and cooking, and 275 00:14:35,560 --> 00:14:38,000 Speaker 4: dinner would be on the table and it would be amazing, 276 00:14:38,040 --> 00:14:40,040 Speaker 4: but it would be eleven PM or would be midnight. 277 00:14:40,200 --> 00:14:41,560 Speaker 3: How many of you were there sailing? 278 00:14:41,680 --> 00:14:43,880 Speaker 4: So were I was the youngest and I had two 279 00:14:43,880 --> 00:14:46,960 Speaker 4: older brothers. So anyway, my father ended up doing all 280 00:14:47,000 --> 00:14:49,840 Speaker 4: the cooking and did and did what was his career. 281 00:14:50,560 --> 00:14:54,560 Speaker 4: So he actually was ran the well. He was in 282 00:14:54,600 --> 00:14:58,440 Speaker 4: the navy early on, and then he entered the Royal 283 00:14:58,480 --> 00:15:01,760 Speaker 4: Copenhagen with the beautiful plate and he was number two 284 00:15:01,800 --> 00:15:04,360 Speaker 4: there and sort of co ran the business for many 285 00:15:04,400 --> 00:15:06,560 Speaker 4: many years. So I grew up with all of the 286 00:15:06,640 --> 00:15:11,080 Speaker 4: Royal Copenhagen Portlain, lots of artists and potters that came 287 00:15:11,120 --> 00:15:14,160 Speaker 4: in to test out new lines. So our house was 288 00:15:14,200 --> 00:15:18,920 Speaker 4: always filled with Danish writers and artists, and my father 289 00:15:18,960 --> 00:15:22,160 Speaker 4: loved that job very much. But yeah, he ended up. 290 00:15:22,120 --> 00:15:24,240 Speaker 3: So he would come home from work and cook. 291 00:15:24,760 --> 00:15:27,320 Speaker 4: He would often be the one who would cook, or 292 00:15:27,360 --> 00:15:31,880 Speaker 4: we would always eat at eleven PM or twelve, so when. 293 00:15:30,960 --> 00:15:33,400 Speaker 2: You finished your homework and then and then eight. 294 00:15:33,640 --> 00:15:38,200 Speaker 4: Yes, I was very unsupervised, but yes, my brothers would 295 00:15:38,280 --> 00:15:40,040 Speaker 4: usually if there was any homework done, it would be 296 00:15:40,120 --> 00:15:42,680 Speaker 4: under the supervision of my older brothers, and they always 297 00:15:42,680 --> 00:15:45,040 Speaker 4: thought it was fun to experiment on how young, at 298 00:15:45,120 --> 00:15:48,080 Speaker 4: a young how younger age can you learn mathematics. So 299 00:15:48,120 --> 00:15:51,520 Speaker 4: that was my early sort of learnings of math. Probably 300 00:15:51,600 --> 00:15:55,320 Speaker 4: led to the love of mathematics later on. Did you cook, Yes, 301 00:15:55,720 --> 00:15:59,280 Speaker 4: I actually did. I think it's inevitable you you, especially 302 00:15:59,280 --> 00:16:01,080 Speaker 4: if it's going to take eight hours to cook, you 303 00:16:01,160 --> 00:16:03,000 Speaker 4: end up sitting in the kitchen and watching and then 304 00:16:03,000 --> 00:16:04,200 Speaker 4: there was the stirring and there. 305 00:16:04,080 --> 00:16:06,360 Speaker 2: Would be like it was something you wanted to do 306 00:16:06,440 --> 00:16:08,560 Speaker 2: because you were one of the best cooks I know but. 307 00:16:08,600 --> 00:16:10,760 Speaker 4: It's terrifying to cook for you with you, It really is. 308 00:16:10,840 --> 00:16:12,760 Speaker 3: But I got over that. 309 00:16:12,960 --> 00:16:19,440 Speaker 4: But yes, I really cooking for me. I connected with conversation. 310 00:16:19,760 --> 00:16:20,000 Speaker 3: Yeah. 311 00:16:20,400 --> 00:16:22,800 Speaker 2: I always said that about my family, is that it 312 00:16:22,840 --> 00:16:26,920 Speaker 2: was a very Jewish family, not religiously, but just in 313 00:16:26,960 --> 00:16:30,200 Speaker 2: the sense that it was the talking was more important 314 00:16:30,240 --> 00:16:32,280 Speaker 2: than the food. And a lot of people that we 315 00:16:32,320 --> 00:16:35,480 Speaker 2: talked to talk about the meals around the table, which 316 00:16:35,480 --> 00:16:38,960 Speaker 2: sometimes I feel is over romanticized that idea we all 317 00:16:39,040 --> 00:16:41,880 Speaker 2: sat around the table, because you also talk to a 318 00:16:41,920 --> 00:16:45,440 Speaker 2: lot of kids who found it slightly torturous, you know, 319 00:16:45,880 --> 00:16:48,360 Speaker 2: having to sit at a meal at night with your 320 00:16:48,400 --> 00:16:51,440 Speaker 2: parents discussing something or not or silence. 321 00:16:51,880 --> 00:16:54,240 Speaker 3: But as you say, you know it sticks. 322 00:16:53,880 --> 00:16:55,280 Speaker 4: With you, does, Yeah, it does. 323 00:16:58,600 --> 00:17:01,560 Speaker 2: An open kitchen and the river means we as chefs 324 00:17:01,600 --> 00:17:04,480 Speaker 2: are able to talk to our guests dining in the restaurant, 325 00:17:04,840 --> 00:17:07,840 Speaker 2: and now we're bringing that same ethos to our podcast, 326 00:17:08,320 --> 00:17:11,040 Speaker 2: a question and answer episode with me and our two 327 00:17:11,080 --> 00:17:14,639 Speaker 2: executive chefs. Send a voice note with your question to 328 00:17:14,840 --> 00:17:19,400 Speaker 2: Questions at Rivercafe dot co dot uk and you might 329 00:17:19,520 --> 00:17:22,960 Speaker 2: just be our next great guest. On Ruthie's Table four, 330 00:17:30,960 --> 00:17:34,720 Speaker 2: we left this beautiful city, your family and you went 331 00:17:34,880 --> 00:17:38,480 Speaker 2: to New York And was that a kind of shock 332 00:17:38,680 --> 00:17:40,879 Speaker 2: or was it just did you just smeld right into it? 333 00:17:40,920 --> 00:17:43,399 Speaker 3: Did it feel very different? What was it like? 334 00:17:43,680 --> 00:17:48,320 Speaker 4: It was fantastic. It was nineteen ninety five, yeah, or 335 00:17:48,400 --> 00:17:50,399 Speaker 4: ninety four actually end of ninety four. 336 00:17:50,240 --> 00:17:53,919 Speaker 2: We begin to university and yeah, just finish university. And 337 00:17:54,720 --> 00:17:56,680 Speaker 2: I had you been before to New York or was 338 00:17:56,720 --> 00:17:59,160 Speaker 2: it did you get off the plane and say, wow, 339 00:17:59,160 --> 00:17:59,960 Speaker 2: these buildings are. 340 00:18:00,920 --> 00:18:02,800 Speaker 4: I was a bit like that. I had been there 341 00:18:02,840 --> 00:18:07,000 Speaker 4: as a child because as working at the role Copenhagen, 342 00:18:07,080 --> 00:18:09,919 Speaker 4: my father also opened up the US branch of that. 343 00:18:10,119 --> 00:18:12,520 Speaker 4: So I did spend a little time as a child 344 00:18:13,119 --> 00:18:17,200 Speaker 4: in New York. But you know from you know, six seven, 345 00:18:17,200 --> 00:18:20,159 Speaker 4: eight years old. So when I arrived there, I was, 346 00:18:20,280 --> 00:18:21,360 Speaker 4: you know, twenty four. 347 00:18:21,320 --> 00:18:23,040 Speaker 3: And what we were doing, we were working. 348 00:18:23,760 --> 00:18:28,360 Speaker 4: I was well, I moved because my now ex husband 349 00:18:28,760 --> 00:18:31,680 Speaker 4: was said, I am going to be in New York. 350 00:18:31,760 --> 00:18:34,480 Speaker 4: Come with me, come join me. And I was like absolutely, 351 00:18:34,640 --> 00:18:37,639 Speaker 4: and that sounds like a great idea. And had finished 352 00:18:37,640 --> 00:18:41,800 Speaker 4: my degree and came over with this degree in economics 353 00:18:41,840 --> 00:18:44,160 Speaker 4: math and I'd really focus on this on game theory, 354 00:18:44,200 --> 00:18:46,879 Speaker 4: which today is actually really helpful, but back then it 355 00:18:46,920 --> 00:18:48,959 Speaker 4: was a slightly esoteric thing to study. 356 00:18:49,119 --> 00:18:50,080 Speaker 3: Maybe you should be. 357 00:18:50,040 --> 00:18:52,200 Speaker 2: At this point tell us what game theory is. 358 00:18:52,800 --> 00:18:57,160 Speaker 4: Yeah, so, well, game theory is. We actually use it 359 00:18:57,240 --> 00:19:00,520 Speaker 4: today more than we realize. Game theory is the sort 360 00:19:00,560 --> 00:19:06,639 Speaker 4: of the mathematical calculation of how sort of multiple actors 361 00:19:06,960 --> 00:19:10,040 Speaker 4: you know, strategize it for poor particular outcome. That's a 362 00:19:10,080 --> 00:19:12,480 Speaker 4: bit technical, but what it means is, for example, the 363 00:19:12,480 --> 00:19:14,160 Speaker 4: way you use it every day is when you get 364 00:19:14,160 --> 00:19:17,560 Speaker 4: on your ways app that is trying to optimize your 365 00:19:17,680 --> 00:19:20,200 Speaker 4: you know, your fastest route, but then it also takes 366 00:19:20,200 --> 00:19:23,879 Speaker 4: into consideration other drivers and so it then recalculates and 367 00:19:23,920 --> 00:19:25,800 Speaker 4: it says, well, every if every driver is going to 368 00:19:25,840 --> 00:19:28,479 Speaker 4: go to you know, find the fastest route, then everyone's 369 00:19:28,520 --> 00:19:29,760 Speaker 4: going to be on that route, so it's going to 370 00:19:29,760 --> 00:19:32,600 Speaker 4: recalculate and take you to another route. In a sense, 371 00:19:32,680 --> 00:19:35,119 Speaker 4: that sort of game theory is at the at the 372 00:19:35,160 --> 00:19:38,120 Speaker 4: base of that. So it's trying to figure out what's 373 00:19:38,119 --> 00:19:41,080 Speaker 4: the outcome when you've got a lot of different people 374 00:19:41,359 --> 00:19:44,040 Speaker 4: or you know, or decisions that are being made at 375 00:19:44,040 --> 00:19:48,080 Speaker 4: the same time. And that's actually at the base of 376 00:19:48,160 --> 00:19:49,320 Speaker 4: a lot of the AI today. 377 00:19:50,640 --> 00:19:52,240 Speaker 3: What are you working on this. 378 00:19:52,359 --> 00:19:55,359 Speaker 4: So I said that in from ninety two to ninety two. 379 00:19:55,480 --> 00:19:58,800 Speaker 2: Well, so that with those the really early days it 380 00:19:58,960 --> 00:20:00,359 Speaker 2: was fail you. 381 00:20:00,160 --> 00:20:02,760 Speaker 4: Was when, Yeah, well I picked it because I loved 382 00:20:02,800 --> 00:20:07,480 Speaker 4: mathematics and I also was toying. My brothers were both 383 00:20:07,520 --> 00:20:10,119 Speaker 4: engineers and did physics and and one went on to 384 00:20:10,160 --> 00:20:13,280 Speaker 4: do quantum physics and went to Zurin and Zurich to 385 00:20:13,280 --> 00:20:16,840 Speaker 4: split atoms, and so you know, I had I had 386 00:20:16,880 --> 00:20:19,280 Speaker 4: always thought that I might go in and study physics, 387 00:20:19,640 --> 00:20:22,639 Speaker 4: but then I decided to do economics math and focus 388 00:20:22,680 --> 00:20:26,600 Speaker 4: on game theory because I really enjoyed the mathematical base 389 00:20:26,680 --> 00:20:30,200 Speaker 4: of it, and it ended up being being a great 390 00:20:30,280 --> 00:20:32,520 Speaker 4: choice for me. I'm so happy I did that. So 391 00:20:32,600 --> 00:20:34,840 Speaker 4: that was a that was in the early time. 392 00:20:35,000 --> 00:20:37,120 Speaker 3: Many women in the was it male? 393 00:20:37,960 --> 00:20:40,159 Speaker 4: Was like maybe two percent women in the whole in 394 00:20:40,200 --> 00:20:43,280 Speaker 4: the whole sort of group starting every year, it was 395 00:20:43,359 --> 00:20:47,040 Speaker 4: very few women. I wasn't retaken seriously though, was it? 396 00:20:47,160 --> 00:20:51,040 Speaker 3: Did you find any issues with nothing? Never a man's world? Never? 397 00:20:51,359 --> 00:20:53,199 Speaker 4: I mean growing up with brothers who are giving you 398 00:20:53,200 --> 00:20:56,520 Speaker 4: a hard time all the time? Lotistics, liss, that's peanuts. 399 00:20:56,560 --> 00:20:56,960 Speaker 3: What do you do? 400 00:20:57,080 --> 00:20:59,159 Speaker 4: Go in and choose something where there a lot of 401 00:20:59,400 --> 00:21:01,560 Speaker 4: you know, where it's very male dominated, and to this day, 402 00:21:01,680 --> 00:21:04,560 Speaker 4: and I've always been in areas in my career and 403 00:21:04,560 --> 00:21:07,200 Speaker 4: also now in sort of very you know, something you 404 00:21:07,200 --> 00:21:09,960 Speaker 4: would consider very male dominated, and I don't even think 405 00:21:10,000 --> 00:21:12,480 Speaker 4: about it. It's not something I think about. But it 406 00:21:12,560 --> 00:21:14,560 Speaker 4: was interesting because back in the nineties was sort of 407 00:21:14,640 --> 00:21:16,840 Speaker 4: a is what you sort of call the AI winter. 408 00:21:17,440 --> 00:21:19,400 Speaker 4: AI had sort of you know, there's been a lot 409 00:21:19,400 --> 00:21:22,159 Speaker 4: of progress in the fifties and sixties and seventies, and 410 00:21:22,200 --> 00:21:23,679 Speaker 4: then it sort of stood still for a bit for 411 00:21:23,680 --> 00:21:26,239 Speaker 4: a number of reasons. So picking Game three, it was 412 00:21:26,320 --> 00:21:28,399 Speaker 4: not sort of linked to AI. Back then, it was 413 00:21:28,480 --> 00:21:31,280 Speaker 4: just sort of I enjoyed the thinking of it. And 414 00:21:31,680 --> 00:21:35,040 Speaker 4: now it's certainly have had a resurgence, so that is 415 00:21:36,119 --> 00:21:38,480 Speaker 4: so just yeah, so that was sort of a lucky choice, 416 00:21:38,520 --> 00:21:39,040 Speaker 4: I guess. 417 00:21:39,359 --> 00:21:42,040 Speaker 2: So you were introduced to New York, to New York 418 00:21:42,400 --> 00:21:45,919 Speaker 2: and the world of being in America, the world of 419 00:21:45,960 --> 00:21:50,600 Speaker 2: science and starting something new. But then with your with 420 00:21:50,640 --> 00:21:53,280 Speaker 2: your relationship you were thrust into. Were you thrust into 421 00:21:53,280 --> 00:21:55,840 Speaker 2: a kind of Iranian culture as well? Or was that 422 00:21:56,520 --> 00:21:58,200 Speaker 2: was that sort of slightly in the background. 423 00:21:58,240 --> 00:22:00,600 Speaker 4: Yeah, So I came to New York with the degree, 424 00:22:00,720 --> 00:22:03,240 Speaker 4: and I was thinking, I was like, what should I 425 00:22:03,640 --> 00:22:06,320 Speaker 4: you know, how can I use this? And I spoke 426 00:22:06,359 --> 00:22:08,119 Speaker 4: to a friend of mine who had the same degree, 427 00:22:08,600 --> 00:22:11,639 Speaker 4: and he said, there's sort a couple of options, but 428 00:22:11,760 --> 00:22:15,919 Speaker 4: there is Moody's Sovereign team that has a legendary economists 429 00:22:15,920 --> 00:22:18,800 Speaker 4: called David Levy, and I would send him an application 430 00:22:18,920 --> 00:22:21,360 Speaker 4: because it would fit exactly what you have. It's very 431 00:22:21,400 --> 00:22:25,000 Speaker 4: you know, it's building these methodologies and rankings and it's 432 00:22:25,040 --> 00:22:27,359 Speaker 4: you know, very mathematical, but it's also really interesting. And 433 00:22:27,400 --> 00:22:29,920 Speaker 4: I thought that sounds great, and so I sent her 434 00:22:30,000 --> 00:22:33,639 Speaker 4: application in on Monday, and David Levy called me up 435 00:22:33,640 --> 00:22:37,359 Speaker 4: on Friday and said, do you want to cover Russia? 436 00:22:37,400 --> 00:22:41,159 Speaker 4: And I said absolutely, And so I started the following Monday. 437 00:22:41,560 --> 00:22:44,120 Speaker 4: But that year was when that was nineteen ninety five, 438 00:22:44,800 --> 00:22:47,720 Speaker 4: and then in terms of the Iranian culture going on 439 00:22:47,800 --> 00:22:51,199 Speaker 4: in Russia right well back then it was the big 440 00:22:51,359 --> 00:22:56,800 Speaker 4: privatization moment and the you know, it had opened up 441 00:22:56,880 --> 00:23:00,359 Speaker 4: and the big privatization moment in ninety two, there was 442 00:23:00,400 --> 00:23:05,240 Speaker 4: an enormous amount of excitement of you know, opening up 443 00:23:05,400 --> 00:23:10,000 Speaker 4: and diversifying from oil and set you know, opening up 444 00:23:10,040 --> 00:23:12,560 Speaker 4: all of these big, big assets that the country had 445 00:23:12,600 --> 00:23:17,200 Speaker 4: and the population that was so brilliantly educated but needed 446 00:23:17,200 --> 00:23:19,800 Speaker 4: to you know, this turnaround of an economy that had 447 00:23:19,840 --> 00:23:23,159 Speaker 4: been completely close to the outside world and then opened up. 448 00:23:23,240 --> 00:23:25,879 Speaker 4: And it wasn't easy because obviously there was a big, 449 00:23:26,760 --> 00:23:28,919 Speaker 4: you know, disruption to the economy and a lot of 450 00:23:29,240 --> 00:23:31,800 Speaker 4: safe jobs and you know, suddenly you had inflation and 451 00:23:31,840 --> 00:23:34,760 Speaker 4: you had opening to the outside world and things that 452 00:23:34,800 --> 00:23:37,840 Speaker 4: were guaranteed the Russian population were no longer guaranteed. So 453 00:23:37,880 --> 00:23:39,600 Speaker 4: it was a bit of a it was a bit 454 00:23:39,640 --> 00:23:43,760 Speaker 4: of a you know, tricky time also, and I always 455 00:23:43,800 --> 00:23:46,400 Speaker 4: remember every time I went and I ended up covering 456 00:23:46,480 --> 00:23:49,359 Speaker 4: Russia for seventeen years among you know, other nations in 457 00:23:49,440 --> 00:23:52,439 Speaker 4: Central Asia and Middle East from New York, which was 458 00:23:52,720 --> 00:23:55,600 Speaker 4: you know interesting, but always went to see Gorbachev. And 459 00:23:55,640 --> 00:23:58,480 Speaker 4: he wasn't revered back in Russia then because he was 460 00:23:58,560 --> 00:24:01,439 Speaker 4: very much blamed for the sort of the complications in 461 00:24:01,480 --> 00:24:04,400 Speaker 4: the economy. But he had a think tank just outside 462 00:24:04,440 --> 00:24:07,760 Speaker 4: of outside of Moscow, and we always made a point, 463 00:24:07,760 --> 00:24:10,080 Speaker 4: me in my colleague to go and see him every 464 00:24:10,080 --> 00:24:13,800 Speaker 4: time to talk about life and Russia and how he's 465 00:24:13,800 --> 00:24:16,159 Speaker 4: seen it in the past and the future and it 466 00:24:16,200 --> 00:24:18,440 Speaker 4: was a real treat. And it was also interesting to 467 00:24:18,480 --> 00:24:21,400 Speaker 4: see the inside workings of a of an economy going 468 00:24:21,400 --> 00:24:24,359 Speaker 4: through a transition and and sort of the corruption that 469 00:24:24,520 --> 00:24:27,080 Speaker 4: was was very much there, and sort of seeing the 470 00:24:27,160 --> 00:24:30,080 Speaker 4: rise of put In and sort of bringing us to today. Yeah, 471 00:24:30,160 --> 00:24:33,320 Speaker 4: it was, it was, but it was, it was, it was. 472 00:24:33,400 --> 00:24:35,480 Speaker 4: It was a really interesting time. I was very grateful 473 00:24:35,520 --> 00:24:39,280 Speaker 4: for that. So not only just getting to you know, 474 00:24:39,440 --> 00:24:44,520 Speaker 4: to help build these these rankings for nations on their 475 00:24:44,520 --> 00:24:47,040 Speaker 4: sort of growth capacity, which essentially is a is what 476 00:24:47,080 --> 00:24:50,000 Speaker 4: a credit reading is, and a sort of capacity to 477 00:24:50,040 --> 00:24:53,760 Speaker 4: pay back debt is all basically a benchmark putting all 478 00:24:53,880 --> 00:24:56,000 Speaker 4: this all of these data points together and figuring out 479 00:24:56,040 --> 00:24:59,679 Speaker 4: what's the likelihood. It's sort of a probability calculation, what 480 00:24:59,800 --> 00:25:03,119 Speaker 4: is it likelihood that a country will will default? But 481 00:25:03,200 --> 00:25:06,720 Speaker 4: being able to do that, alongside traveling to to Moscow 482 00:25:06,920 --> 00:25:10,520 Speaker 4: and to you know, to Kazakhstan and Kykistan and all 483 00:25:10,560 --> 00:25:13,679 Speaker 4: of these places that were just emerging, was as an 484 00:25:13,720 --> 00:25:14,840 Speaker 4: economist such a treat. 485 00:25:15,000 --> 00:25:18,760 Speaker 2: Yeah, as an economist was a traveler, as I as 486 00:25:18,800 --> 00:25:21,000 Speaker 2: a historian to be in that that time. 487 00:25:21,280 --> 00:25:23,520 Speaker 3: Do you remember the food and I bring it down 488 00:25:23,560 --> 00:25:25,159 Speaker 3: to the field. Do you remember what you ate? 489 00:25:25,760 --> 00:25:29,040 Speaker 4: The food was was well. I went with a colleague 490 00:25:29,080 --> 00:25:31,119 Speaker 4: who knew Moscow very well, and he said, let's go 491 00:25:31,160 --> 00:25:32,320 Speaker 4: to the Georgian restaurants. 492 00:25:32,480 --> 00:25:33,800 Speaker 3: Yeah. 493 00:25:33,160 --> 00:25:36,400 Speaker 4: Yeah, so that was and of course there was your 494 00:25:36,560 --> 00:25:38,640 Speaker 4: you know, so you know, it was a mix of things. 495 00:25:38,640 --> 00:25:41,199 Speaker 4: But you've got your borsched and you've got your Georgian wine, 496 00:25:41,280 --> 00:25:43,560 Speaker 4: and you've got it was such a it was It 497 00:25:43,600 --> 00:25:46,359 Speaker 4: was so exciting, I have to say, being you know, 498 00:25:46,400 --> 00:25:49,000 Speaker 4: in Moscow through those years where there was the Russian 499 00:25:49,000 --> 00:25:50,919 Speaker 4: food and the Georgian food and the wine coming in 500 00:25:50,920 --> 00:25:54,600 Speaker 4: from various places, and and sort of sitting and breaking 501 00:25:54,640 --> 00:25:57,960 Speaker 4: bread with and and hearing the stories of everyone, in 502 00:25:58,000 --> 00:26:01,160 Speaker 4: addition to sort of quite tense meetings Russian. I know, 503 00:26:01,320 --> 00:26:04,359 Speaker 4: I did a little bit. My colleagues spoke Russian. And 504 00:26:04,400 --> 00:26:07,400 Speaker 4: the interesting thing was that up you know, the first 505 00:26:07,520 --> 00:26:10,720 Speaker 4: years in Moscow, everyone, especially when we had meetings with 506 00:26:10,800 --> 00:26:12,920 Speaker 4: the government and so on, it was all done in 507 00:26:13,000 --> 00:26:16,600 Speaker 4: Russian with translators. And right after they defaulted in ninety eight, 508 00:26:16,680 --> 00:26:18,879 Speaker 4: it switched to English when we came after that, so 509 00:26:18,960 --> 00:26:21,800 Speaker 4: there was a big change there and then obviously a 510 00:26:21,800 --> 00:26:22,760 Speaker 4: big change, but. 511 00:26:22,680 --> 00:26:25,000 Speaker 2: We went, we went and I think when Richard was 512 00:26:25,160 --> 00:26:28,200 Speaker 2: Chairman of the Tate and early eighties, I think it 513 00:26:28,280 --> 00:26:30,840 Speaker 2: was and you know it was. 514 00:26:31,119 --> 00:26:32,280 Speaker 3: It was spartan, it was. 515 00:26:32,440 --> 00:26:36,360 Speaker 2: There was little, but there we you know, people say 516 00:26:36,440 --> 00:26:38,639 Speaker 2: you'll you'll eat really badly, they won't be for we 517 00:26:38,840 --> 00:26:41,280 Speaker 2: ate so well, I remember it wasn't there wasn't a 518 00:26:41,280 --> 00:26:44,040 Speaker 2: lot of it, but people made the effort to cook 519 00:26:44,080 --> 00:26:47,880 Speaker 2: for us. So we were in people's homes and there 520 00:26:48,000 --> 00:26:52,680 Speaker 2: was kind of pride and concern and interest and as 521 00:26:52,680 --> 00:26:54,720 Speaker 2: you said, and I think it's delicious food, don't you. 522 00:26:54,840 --> 00:26:57,720 Speaker 2: I think it is the you know the little I 523 00:26:57,800 --> 00:26:59,440 Speaker 2: kept with those little ones filled with. 524 00:26:59,400 --> 00:27:06,880 Speaker 3: Spinach, yes, exactly. I remember the boiled meats, yes, deliciously. Yeah. 525 00:27:06,880 --> 00:27:11,040 Speaker 2: It's beautiful, beautiful culture. What about Iran? So when you 526 00:27:11,080 --> 00:27:12,600 Speaker 2: were in when did you get married? 527 00:27:13,520 --> 00:27:14,200 Speaker 4: Ninety seven? 528 00:27:14,480 --> 00:27:17,359 Speaker 2: So at that time were his family there? Did you 529 00:27:17,440 --> 00:27:20,840 Speaker 2: feel that you were taken into this Iranian culture? 530 00:27:21,040 --> 00:27:21,200 Speaker 3: Well? 531 00:27:21,200 --> 00:27:25,600 Speaker 4: His mother was Danish actually, and she was she was 532 00:27:25,640 --> 00:27:30,560 Speaker 4: born in Denmark and was very adventurous. This is my 533 00:27:31,280 --> 00:27:34,480 Speaker 4: former mother in law that her mother was Danish. They 534 00:27:34,520 --> 00:27:37,879 Speaker 4: were all they were all Danish and in sort of 535 00:27:37,960 --> 00:27:41,600 Speaker 4: late fifties or was it nineteen sixty, she decides to 536 00:27:41,680 --> 00:27:46,320 Speaker 4: move to Tehran by herself because there was a job there. 537 00:27:46,520 --> 00:27:49,080 Speaker 4: There was a connection between Iran and Denmark because a 538 00:27:49,080 --> 00:27:51,760 Speaker 4: lot of the engineers that built the infrastructure were Danish 539 00:27:51,760 --> 00:27:54,520 Speaker 4: engineers and architects, so there was sort of a link there. 540 00:27:55,040 --> 00:27:58,120 Speaker 4: And at a very young age, she goes to Iran 541 00:27:58,280 --> 00:28:03,800 Speaker 4: and and very blonde, beautiful, you know, blue eyed, young girl. 542 00:28:03,920 --> 00:28:07,240 Speaker 4: And she goes and works for this company and meets 543 00:28:07,680 --> 00:28:10,480 Speaker 4: you know, her husband, and they get married and she 544 00:28:10,560 --> 00:28:13,680 Speaker 4: lives there for almost twenty years. And so the revolution 545 00:28:13,880 --> 00:28:18,040 Speaker 4: is in nineteen seventy nine, but in seventy seven they leave, 546 00:28:19,000 --> 00:28:23,359 Speaker 4: and so left they left before the revolution, and she 547 00:28:23,560 --> 00:28:25,600 Speaker 4: was the one who didn't want to leave. She was 548 00:28:25,600 --> 00:28:29,800 Speaker 4: so happy in Tehran and she loved living there, and 549 00:28:30,680 --> 00:28:35,080 Speaker 4: it was was her resisting the leaving of Iran. And 550 00:28:35,080 --> 00:28:38,240 Speaker 4: then they came to Denmark and split their time between 551 00:28:38,280 --> 00:28:40,560 Speaker 4: the US and Denmark. But she's the one who taught 552 00:28:40,560 --> 00:28:43,680 Speaker 4: me to cook. And it was hours and hours sitting 553 00:28:44,120 --> 00:28:45,400 Speaker 4: patiently watching her. 554 00:28:47,080 --> 00:28:49,120 Speaker 3: Cooking the food of Iran. What do you call it? 555 00:28:49,120 --> 00:28:49,880 Speaker 3: Persian food? 556 00:28:50,000 --> 00:28:50,640 Speaker 4: Persian food? 557 00:28:50,720 --> 00:28:51,280 Speaker 3: Version food? 558 00:28:51,320 --> 00:28:51,560 Speaker 4: Yes? 559 00:28:51,960 --> 00:28:54,520 Speaker 2: And did you sit there because you felt you wanted 560 00:28:54,560 --> 00:28:56,360 Speaker 2: to learn it? Did you feel sad that this is 561 00:28:56,400 --> 00:28:58,560 Speaker 2: what you did when you were with your mother in law? 562 00:28:58,920 --> 00:29:01,680 Speaker 3: I certainly learned to cook my mother in law, but it's. 563 00:29:01,720 --> 00:29:04,600 Speaker 4: Joy of also sharing again and sort of doing something together. 564 00:29:04,880 --> 00:29:06,720 Speaker 4: And it was also frankly because it was the most 565 00:29:06,720 --> 00:29:12,520 Speaker 4: delicious food I've ever tasted. Unbelievable. It's the most sensual, careful, 566 00:29:15,400 --> 00:29:20,000 Speaker 4: beautiful food I've ever like the rice and the saffron 567 00:29:20,280 --> 00:29:25,000 Speaker 4: and the herbs. It's not spicy, So I thought, I 568 00:29:25,040 --> 00:29:27,200 Speaker 4: have to learn this. I have to just have to 569 00:29:27,240 --> 00:29:28,360 Speaker 4: know how to cook this food. 570 00:29:28,520 --> 00:29:30,320 Speaker 3: Is it very much based on rice? 571 00:29:30,400 --> 00:29:33,520 Speaker 2: I mean I always think Persian food and rice, and 572 00:29:33,520 --> 00:29:34,680 Speaker 2: what tells about the rice. 573 00:29:34,880 --> 00:29:38,240 Speaker 4: The rice in itself takes days to make. The rice 574 00:29:38,320 --> 00:29:42,040 Speaker 4: is the core, the anchor of the Persian cuisine. But 575 00:29:42,280 --> 00:29:45,640 Speaker 4: it is with so much care that you cook this rice. 576 00:29:46,240 --> 00:29:50,200 Speaker 4: So you take long grain basmati rice and it has 577 00:29:50,240 --> 00:29:53,000 Speaker 4: to soak for a day or even two in a 578 00:29:53,000 --> 00:29:54,959 Speaker 4: lot of water. You've got to rinse it over and 579 00:29:55,000 --> 00:29:58,120 Speaker 4: over again and let it soak again with salt, and 580 00:29:58,560 --> 00:30:00,680 Speaker 4: that is to clean it up, but it also gives 581 00:30:00,720 --> 00:30:04,080 Speaker 4: it that special lovely aroma. 582 00:30:04,240 --> 00:30:06,640 Speaker 2: How do you put it in a large quantity of water. 583 00:30:07,040 --> 00:30:09,240 Speaker 3: It is large. You don't have to have a lot 584 00:30:09,280 --> 00:30:10,000 Speaker 3: of water for this. 585 00:30:10,560 --> 00:30:13,880 Speaker 4: Yes, no, she said, no rice cooker. Do not cook 586 00:30:13,920 --> 00:30:15,840 Speaker 4: in a rice cooker. And it has to be a 587 00:30:16,000 --> 00:30:19,120 Speaker 4: big iron pot that is thick, and you fill it 588 00:30:19,160 --> 00:30:21,160 Speaker 4: with water and you put your rice in the salt 589 00:30:21,520 --> 00:30:24,080 Speaker 4: and it has to just be cooked to the point 590 00:30:24,080 --> 00:30:27,320 Speaker 4: where it's just, you know, not too cooked, but just 591 00:30:27,320 --> 00:30:28,600 Speaker 4: just a bit sort of a bite in it. 592 00:30:28,680 --> 00:30:30,280 Speaker 3: Did she have to taste the rice? So? Did she 593 00:30:30,360 --> 00:30:30,960 Speaker 3: know when it was? 594 00:30:31,640 --> 00:30:33,880 Speaker 4: I think at the end she'd do, but she always 595 00:30:33,960 --> 00:30:36,280 Speaker 4: tasted it. And then it has to be then put 596 00:30:36,320 --> 00:30:39,080 Speaker 4: back in the pot to make the famous tadique, which 597 00:30:39,120 --> 00:30:41,120 Speaker 4: is the crispy rice on the bottom of the pot. 598 00:30:41,720 --> 00:30:43,560 Speaker 4: I think, I swear. I think it must have taken 599 00:30:43,560 --> 00:30:45,280 Speaker 4: me ten years to figure that out, and I did 600 00:30:45,320 --> 00:30:45,720 Speaker 4: a lot. 601 00:30:45,600 --> 00:30:48,320 Speaker 2: Of You have a hint for anyone planning to make 602 00:30:48,360 --> 00:30:49,600 Speaker 2: this characrice what to do? 603 00:30:49,880 --> 00:30:52,239 Speaker 4: I think it's just you've got to keep going at it. 604 00:30:52,240 --> 00:30:54,840 Speaker 2: It is very difficult, sick, right, but you don't want 605 00:30:54,840 --> 00:30:56,040 Speaker 2: it to work because you have to lift. 606 00:30:56,840 --> 00:30:58,080 Speaker 3: Yeah, how do you get it out? 607 00:30:58,560 --> 00:31:01,600 Speaker 4: Yes, you've got to mix it with saffron and yogurt, 608 00:31:02,080 --> 00:31:04,720 Speaker 4: and then it's the it's the delicate balance of enough 609 00:31:04,760 --> 00:31:07,800 Speaker 4: heat but not too much for the first twenty minutes, 610 00:31:07,880 --> 00:31:10,240 Speaker 4: and then you let it steam for an hour. But 611 00:31:10,320 --> 00:31:12,560 Speaker 4: in the first I mean I must have. I cannot 612 00:31:12,600 --> 00:31:14,680 Speaker 4: tell you how many parts I had to throw out 613 00:31:14,720 --> 00:31:17,880 Speaker 4: and how many times I got burned. But it is 614 00:31:18,640 --> 00:31:21,880 Speaker 4: when it comes to cooking today, it's the Persian food. 615 00:31:21,880 --> 00:31:23,160 Speaker 4: I go back to that so often. 616 00:31:23,200 --> 00:31:26,160 Speaker 2: It is yeah, and dear children, they love it because 617 00:31:26,160 --> 00:31:29,480 Speaker 2: you have three sons, three magnificent sons. And one of them, 618 00:31:29,640 --> 00:31:32,360 Speaker 2: look I know very well because he is a They're 619 00:31:32,360 --> 00:31:35,280 Speaker 2: all good cooks. I know that, but Luka is particularly 620 00:31:36,320 --> 00:31:37,560 Speaker 2: and interested in cooking. 621 00:31:37,760 --> 00:31:39,600 Speaker 3: Is he interested in Persian food? 622 00:31:39,800 --> 00:31:45,719 Speaker 4: Or they're all try They are all big. The cooking 623 00:31:45,800 --> 00:31:49,680 Speaker 4: is what they enjoy doing together. Actually, even when I'm 624 00:31:49,720 --> 00:31:52,760 Speaker 4: not home, they will close themselves into the kitchen and 625 00:31:53,360 --> 00:31:55,800 Speaker 4: prepare for hours and hours, and that's where they really 626 00:31:55,880 --> 00:32:00,280 Speaker 4: talk and and share things in their lives. And it'sul 627 00:32:00,320 --> 00:32:03,760 Speaker 4: to see them cook together. But yes, the youngest Lucas 628 00:32:03,520 --> 00:32:06,720 Speaker 4: is the one that really took it upon himself not 629 00:32:06,840 --> 00:32:10,560 Speaker 4: just to cook normal things, but to really experiment. And 630 00:32:10,640 --> 00:32:14,520 Speaker 4: he's interned in kitchen since he was fourteen because he 631 00:32:14,640 --> 00:32:17,360 Speaker 4: just wanted to learn the craft. So but he's particularly 632 00:32:17,400 --> 00:32:18,040 Speaker 4: interested in it. 633 00:32:18,240 --> 00:32:19,880 Speaker 3: That's why he cooks for you. 634 00:32:19,960 --> 00:32:23,400 Speaker 4: He always cooks for me in the last three four 635 00:32:23,480 --> 00:32:25,640 Speaker 4: years when I start After I started the business and 636 00:32:25,680 --> 00:32:28,240 Speaker 4: I just didn't have time, I would come home and 637 00:32:28,760 --> 00:32:31,360 Speaker 4: instead of me cooking for him, he cooked for me. 638 00:32:34,360 --> 00:32:37,560 Speaker 2: Imagine estate bottled olive oil chosen and bottled for the 639 00:32:37,640 --> 00:32:42,040 Speaker 2: River Cafe, arriving at your door every month. Our subscription 640 00:32:42,240 --> 00:32:45,800 Speaker 2: is available for six or twelve months, with each oil 641 00:32:45,960 --> 00:32:49,840 Speaker 2: chosen personally by our head chefs and varying with each delivery. 642 00:32:50,360 --> 00:32:52,040 Speaker 3: It's a perfect way to bring. 643 00:32:51,880 --> 00:32:55,080 Speaker 2: Some River Cafe flavor into your home or to show 644 00:32:55,160 --> 00:32:58,320 Speaker 2: someone you really care for them with the gift. Visit 645 00:32:58,360 --> 00:33:02,760 Speaker 2: our website shop the Rivercafe dot co uk to place 646 00:33:02,800 --> 00:33:11,120 Speaker 2: your order. Now of all the recipes that you've chose. 647 00:33:11,160 --> 00:33:12,840 Speaker 2: When and I asked you last night, what are you 648 00:33:12,920 --> 00:33:15,000 Speaker 2: going to before I went to bed? What are you 649 00:33:15,080 --> 00:33:18,880 Speaker 2: going to read? And I was both surprised and not 650 00:33:18,960 --> 00:33:21,840 Speaker 2: surprised to hear that you chose grilled squid. There was 651 00:33:21,840 --> 00:33:24,440 Speaker 2: a recipe that Rose came with. I think we all 652 00:33:24,440 --> 00:33:27,719 Speaker 2: brought those early days some of our own recipes. So 653 00:33:27,800 --> 00:33:31,000 Speaker 2: you chose grilled squid with chilian rocket, and would you 654 00:33:31,080 --> 00:33:33,920 Speaker 2: like to read it, and would you like to change 655 00:33:33,960 --> 00:33:36,840 Speaker 2: anything you want to change on it, or read it 656 00:33:36,880 --> 00:33:38,840 Speaker 2: the way you would cook it, or you'd like to 657 00:33:38,880 --> 00:33:39,280 Speaker 2: eat it? 658 00:33:39,520 --> 00:33:42,160 Speaker 4: Well, I have, Actually I've got to admit I've never 659 00:33:42,160 --> 00:33:46,000 Speaker 4: cooked it myself. Okay, but there has never been in 660 00:33:46,040 --> 00:33:48,240 Speaker 4: that How many years have I come to the River 661 00:33:48,320 --> 00:33:52,640 Speaker 4: Cafe thirty at least? I have never once been here 662 00:33:53,040 --> 00:33:57,560 Speaker 4: without ordering the squirt, never once. I So, of all 663 00:33:57,600 --> 00:34:00,440 Speaker 4: of the many that you have sold, Alexandra, I think 664 00:34:00,520 --> 00:34:04,120 Speaker 4: I have. I am the consumer of many, many of them. 665 00:34:04,600 --> 00:34:09,840 Speaker 4: So grill squid, fresh red chili and rocket. Eight medium squid, 666 00:34:10,200 --> 00:34:13,279 Speaker 4: six large fresh red chilies, one hundred and fifty milliliters 667 00:34:13,320 --> 00:34:15,960 Speaker 4: of virgin olive oil, two hundred and twenty five grams 668 00:34:15,960 --> 00:34:19,080 Speaker 4: of rocket, four tablespoons of oil, and lemon dressing. One 669 00:34:19,160 --> 00:34:22,040 Speaker 4: lemon cut into squares for the chili sauce. Put the 670 00:34:22,080 --> 00:34:24,280 Speaker 4: chopped chilies in a bowl and cover with the extra 671 00:34:24,680 --> 00:34:28,600 Speaker 4: virgin olive oil. Season Heat a grill until hot. Place 672 00:34:28,640 --> 00:34:32,160 Speaker 4: the squid scored side down on the grill, season and 673 00:34:32,200 --> 00:34:34,680 Speaker 4: grill for one to two minutes. Turn the squid pieces 674 00:34:34,680 --> 00:34:38,280 Speaker 4: over they'll immediately curl up, by which time they'll be cooked. 675 00:34:38,840 --> 00:34:41,960 Speaker 4: Toss the rocket and the dressing. Arrange two squid bodies 676 00:34:42,160 --> 00:34:45,120 Speaker 4: with tentacles on each plate with some of the rocket. 677 00:34:45,440 --> 00:34:47,680 Speaker 4: Put a little of the chili sauce on the squid, 678 00:34:48,000 --> 00:34:52,320 Speaker 4: and serve them with lemon the perfect dish. 679 00:34:52,640 --> 00:34:53,080 Speaker 3: Thank you. 680 00:34:56,760 --> 00:34:59,080 Speaker 2: Tell me about starting the business. 681 00:34:59,000 --> 00:34:59,719 Speaker 3: Yes, well it was. 682 00:35:00,160 --> 00:35:03,239 Speaker 4: It was rather I wouldn't say accidental, but it was. 683 00:35:04,239 --> 00:35:07,640 Speaker 4: It was a moment where you realize that you have 684 00:35:07,680 --> 00:35:09,399 Speaker 4: to go and set up business because there's a real 685 00:35:09,440 --> 00:35:14,440 Speaker 4: need for what you're doing. And so this was in 686 00:35:14,520 --> 00:35:16,359 Speaker 4: twenty two, so it's just three years ago. 687 00:35:16,480 --> 00:35:17,880 Speaker 3: And what did you feel the need was? 688 00:35:18,600 --> 00:35:23,520 Speaker 4: I spent my entire career building rankings, indices, you know, benchmarking. 689 00:35:24,040 --> 00:35:27,239 Speaker 4: I love just I think organizing the world through a 690 00:35:27,239 --> 00:35:32,000 Speaker 4: benchmark is my idea of heaven because you're using you know, 691 00:35:32,040 --> 00:35:35,839 Speaker 4: your data points to come up with a clear, comparable 692 00:35:36,280 --> 00:35:39,880 Speaker 4: analysis on what's up and what's down. So the combination 693 00:35:40,080 --> 00:35:43,680 Speaker 4: of building an index and doing it on AI, it 694 00:35:43,760 --> 00:35:46,319 Speaker 4: was something no one else had had done before. So 695 00:35:46,360 --> 00:35:50,080 Speaker 4: building these this ranking for businesses on their AI capabilities 696 00:35:50,320 --> 00:35:54,839 Speaker 4: didn't exist, and so set up evident with my co 697 00:35:54,920 --> 00:35:59,240 Speaker 4: founder Annabelle Ales, three years ago now and we've grown 698 00:35:59,600 --> 00:36:02,239 Speaker 4: very rare pridly sense because it is something that's in 699 00:36:02,280 --> 00:36:04,120 Speaker 4: a lot of demand and again sort of being the 700 00:36:04,120 --> 00:36:08,440 Speaker 4: only one ones out there measuring and tracking AI adoption 701 00:36:09,080 --> 00:36:12,000 Speaker 4: has meant that we've grown really really fast, and that's difficult, 702 00:36:12,480 --> 00:36:16,400 Speaker 4: but I'm very fortunate to have a co founder like Annabelle. 703 00:36:17,080 --> 00:36:20,760 Speaker 4: We perfectly complement each other. My weaknesses are her strengths 704 00:36:20,800 --> 00:36:25,360 Speaker 4: and vice versa. So together we execute and move really fast. 705 00:36:25,920 --> 00:36:28,600 Speaker 4: And I think that when you know, part of the 706 00:36:28,680 --> 00:36:31,439 Speaker 4: secret I think of building a business is of course 707 00:36:31,440 --> 00:36:33,440 Speaker 4: that the idea has to be there. There has to 708 00:36:33,440 --> 00:36:35,480 Speaker 4: be a demand for what you do, whatever it is, 709 00:36:35,520 --> 00:36:37,880 Speaker 4: whether it is food or in our case, you know, 710 00:36:37,960 --> 00:36:41,680 Speaker 4: a benchmark And the other half of the equation is 711 00:36:41,719 --> 00:36:45,600 Speaker 4: execution and so so having the idea but is great. 712 00:36:45,640 --> 00:36:47,279 Speaker 4: But if you can't, if it's not, if you're not 713 00:36:47,360 --> 00:36:51,480 Speaker 4: executing the business to run on rails, to move that pace, 714 00:36:51,600 --> 00:36:55,600 Speaker 4: to build the product, to you know, build efficiencies, to 715 00:36:55,600 --> 00:36:57,520 Speaker 4: to you know, go out and make sure that you're 716 00:36:57,560 --> 00:37:00,160 Speaker 4: constantly iterating it. That requires a lot of things. King 717 00:37:00,239 --> 00:37:03,839 Speaker 4: on the process side, and she's absolutely brilliant at that 718 00:37:04,040 --> 00:37:06,000 Speaker 4: and I don't think we would be moving at the 719 00:37:06,000 --> 00:37:11,480 Speaker 4: pace that we're moving if it wasn't for combined combined capabilities. 720 00:37:11,800 --> 00:37:14,239 Speaker 4: And then building a team is as you know, it's 721 00:37:14,239 --> 00:37:17,320 Speaker 4: all about people. We're all pulling in the same direction. 722 00:37:17,920 --> 00:37:20,239 Speaker 4: And we're now going to be somewhere between eighty and 723 00:37:20,280 --> 00:37:22,360 Speaker 4: one hundred people by the end of this year already, 724 00:37:22,800 --> 00:37:24,799 Speaker 4: So it is something that's growing at pace, and so 725 00:37:24,840 --> 00:37:28,399 Speaker 4: you've got to hire with care and communicate a lot 726 00:37:28,840 --> 00:37:31,120 Speaker 4: with your team and make sure that everyone is happy 727 00:37:31,640 --> 00:37:35,480 Speaker 4: and feel that they're progressing and learning. But we're all 728 00:37:36,000 --> 00:37:38,520 Speaker 4: got our north star and that's what we set Annabella 729 00:37:38,520 --> 00:37:38,799 Speaker 4: and I. 730 00:37:39,040 --> 00:37:40,120 Speaker 3: You have huge respect. 731 00:37:40,160 --> 00:37:42,600 Speaker 2: I've met your investors because sometimes you bring them here 732 00:37:42,600 --> 00:37:46,920 Speaker 2: for dinner. I've met them in other situations. Would you 733 00:37:47,000 --> 00:37:50,839 Speaker 2: say to other women who want to do what you've 734 00:37:50,880 --> 00:37:52,280 Speaker 2: done in other fields? 735 00:37:53,440 --> 00:37:54,600 Speaker 3: What did you encourage them? 736 00:37:54,640 --> 00:37:58,080 Speaker 2: Do you think that being a woman and again starting 737 00:37:58,120 --> 00:38:00,160 Speaker 2: something that you're looked on in a different way, do 738 00:38:00,239 --> 00:38:02,560 Speaker 2: you find that people are as enlightened as you need? 739 00:38:03,200 --> 00:38:06,560 Speaker 4: I think it's a man or women. It's a fantastic 740 00:38:06,680 --> 00:38:09,720 Speaker 4: area to be in and starting a business. I think 741 00:38:10,080 --> 00:38:11,960 Speaker 4: I think men and women do go at it in 742 00:38:12,000 --> 00:38:14,719 Speaker 4: a slightly different way, but I do think so. But 743 00:38:14,800 --> 00:38:17,400 Speaker 4: I think the statistics are particular, you know, you know, 744 00:38:17,440 --> 00:38:19,840 Speaker 4: are not good on sort of you know, when you 745 00:38:19,840 --> 00:38:22,520 Speaker 4: look at how many female founders there are, and when 746 00:38:22,560 --> 00:38:25,120 Speaker 4: you look at VC funding for women is very low. 747 00:38:25,320 --> 00:38:27,880 Speaker 4: I think it's only six percent of VC funding that 748 00:38:27,920 --> 00:38:30,560 Speaker 4: go to female founders. I don't think it's because they're 749 00:38:30,560 --> 00:38:34,360 Speaker 4: female founders. I just think that that minimal risk taking. 750 00:38:34,440 --> 00:38:36,000 Speaker 4: I think there are a lot of other reasons that 751 00:38:36,280 --> 00:38:39,160 Speaker 4: are driving those figures. But I do think we do 752 00:38:39,280 --> 00:38:41,759 Speaker 4: lead in slightly different ways. I think, I mean, I'm 753 00:38:41,800 --> 00:38:44,919 Speaker 4: generalizing hugely here, but I think that men do tend 754 00:38:44,960 --> 00:38:46,719 Speaker 4: to shoot from the hip a bit and I think 755 00:38:46,760 --> 00:38:49,440 Speaker 4: women are a bit more deliberate. I also think we 756 00:38:49,520 --> 00:38:51,680 Speaker 4: bring in some other layers. I think we as women, 757 00:38:52,320 --> 00:38:55,319 Speaker 4: you know, have a million plates spinning in the air 758 00:38:55,480 --> 00:38:57,799 Speaker 4: or one time. We are the ones who deal with 759 00:38:57,800 --> 00:39:00,840 Speaker 4: the kids and the family and the relationships and social 760 00:39:01,200 --> 00:39:02,960 Speaker 4: things and so on. So I do think that we 761 00:39:03,080 --> 00:39:07,600 Speaker 4: do that in addition to being you know, business builders 762 00:39:07,600 --> 00:39:10,440 Speaker 4: and founders and CEOs, And I think that's a good thing. 763 00:39:10,480 --> 00:39:12,319 Speaker 4: You bring that in. I think you're also a bit 764 00:39:12,440 --> 00:39:15,879 Speaker 4: more careful. We did our as you know, we did 765 00:39:15,920 --> 00:39:18,960 Speaker 4: our series A recently and we were really careful about it. 766 00:39:19,040 --> 00:39:21,920 Speaker 4: We wanted to be at a certain point. We didn't 767 00:39:21,960 --> 00:39:24,880 Speaker 4: do it too soon. As I said, I think we 768 00:39:24,880 --> 00:39:25,960 Speaker 4: women are a bit more deliberate. 769 00:39:26,800 --> 00:39:30,240 Speaker 2: We always try to end with a kind of question 770 00:39:30,360 --> 00:39:32,920 Speaker 2: which I think you've listened to and you knew was coming, 771 00:39:32,960 --> 00:39:36,720 Speaker 2: which should be if you know, if you needed food 772 00:39:37,440 --> 00:39:40,800 Speaker 2: for comfort, and there's times and you must be working 773 00:39:40,840 --> 00:39:43,240 Speaker 2: all day, and you've heard people asking you a hundred 774 00:39:43,239 --> 00:39:46,480 Speaker 2: times a day as I do, what is how scary 775 00:39:46,600 --> 00:39:49,960 Speaker 2: is AI? And we feel I can't take this question 776 00:39:50,239 --> 00:39:53,600 Speaker 2: anymore because I'm not scared of AI. I'm scared of 777 00:39:53,600 --> 00:39:57,240 Speaker 2: the questions, not that knowing you're not scared of anything. 778 00:39:58,320 --> 00:40:00,279 Speaker 2: But if you were to think that you just did 779 00:40:00,360 --> 00:40:02,560 Speaker 2: need some comfort, or one of your kids was there 780 00:40:02,560 --> 00:40:04,600 Speaker 2: to cook for you, or you're going to cook for yourself, 781 00:40:04,680 --> 00:40:07,160 Speaker 2: or just maybe buy something on your hair home. Is 782 00:40:07,239 --> 00:40:14,360 Speaker 2: there a food from your Danish, Iranian, American, British or 783 00:40:14,520 --> 00:40:16,960 Speaker 2: just playing you food that you might go for. 784 00:40:17,120 --> 00:40:17,919 Speaker 3: What would that be? 785 00:40:18,080 --> 00:40:23,279 Speaker 4: I would come straight here, I would call you. If 786 00:40:23,280 --> 00:40:25,080 Speaker 4: the kitchen is closed, can I please knock on the 787 00:40:25,120 --> 00:40:28,399 Speaker 4: door and come to your food, I think, and that's 788 00:40:28,560 --> 00:40:32,920 Speaker 4: honest you My comfort food is is I like so 789 00:40:33,000 --> 00:40:36,400 Speaker 4: many others, it's chicken soup. It's chicken soup, and yours 790 00:40:36,440 --> 00:40:39,320 Speaker 4: is a particularly good And is there a Danish one? 791 00:40:39,760 --> 00:40:44,080 Speaker 4: I think chicken soup is. There is no chicken soup. 792 00:40:44,120 --> 00:40:46,200 Speaker 4: There is no person, not to my knowledge, I might be. 793 00:40:46,880 --> 00:40:52,839 Speaker 4: But comfort food, if i'm is often Persian. Interestingly, being 794 00:40:52,840 --> 00:40:56,040 Speaker 4: a day, it is often Persian. There's something about the 795 00:40:56,080 --> 00:40:59,600 Speaker 4: time it takes and the gathering around the table and 796 00:41:00,719 --> 00:41:05,400 Speaker 4: around the Persian rice and beautiful stews. Is just is 797 00:41:05,400 --> 00:41:06,200 Speaker 4: this very special? 798 00:41:06,320 --> 00:41:08,879 Speaker 2: Do you eat out Persian food and London? We've never 799 00:41:08,920 --> 00:41:10,800 Speaker 2: been to a Persian as always at your house. 800 00:41:11,120 --> 00:41:14,120 Speaker 4: It is difficult, and restaurants are Persian. Restaurants are difficult. 801 00:41:14,120 --> 00:41:16,520 Speaker 4: It is always always better at home. There are some 802 00:41:16,600 --> 00:41:19,600 Speaker 4: good ones in London, but it will never never be 803 00:41:19,719 --> 00:41:24,279 Speaker 4: the same as cooking it at home in your iron pot. 804 00:41:24,760 --> 00:41:26,480 Speaker 4: I have never been. I would love to go one 805 00:41:26,520 --> 00:41:29,040 Speaker 4: day after this. We should go after this. 806 00:41:29,280 --> 00:41:32,759 Speaker 2: I always wanted to go to tan and Isfahan and 807 00:41:33,000 --> 00:41:35,600 Speaker 2: eat the food there and travel and be together. 808 00:41:35,960 --> 00:41:43,240 Speaker 1: Thank you, my darling, thank you for listening to Ruthie's 809 00:41:43,280 --> 00:41:45,680 Speaker 1: Table four in partnership with Montclair