1 00:00:17,999 --> 00:00:21,739 hello and welcome to another episode of Immunity by Design. 2 00:00:22,129 --> 00:00:26,779 My name is Hashem Kooy, and I'm delighted to be hosting this series where we 3 00:00:26,779 --> 00:00:31,449 explore the ideas, technologies, and people shaping the future of science. 4 00:00:32,249 --> 00:00:34,199 Today's episode is slightly different. 5 00:00:34,409 --> 00:00:38,549 Instead of discussing a science story, we will be discussing inclusive 6 00:00:38,549 --> 00:00:43,079 access to education and technology, and also barriers to success. 7 00:00:44,009 --> 00:00:48,989 Much of modern science is built on belief that talent, curiosity, and hard 8 00:00:49,029 --> 00:00:51,069 work lead to opportunity and impact. 9 00:00:51,729 --> 00:00:56,089 Yet around the world, countless gifted individuals never reach to their full 10 00:00:56,129 --> 00:01:02,149 potentials, not because they lack ability, but because they lack access: access to 11 00:01:02,149 --> 00:01:06,979 education, access to mentorship, access to network, access to opportunities 12 00:01:06,979 --> 00:01:09,039 that many of us take for granted. 13 00:01:10,009 --> 00:01:14,739 At the same time, we are living through a technological revolution driven 14 00:01:14,739 --> 00:01:18,139 by artificial intelligence, data science, and digital connectivity. 15 00:01:19,669 --> 00:01:24,549 Some see these technologies as great equalizers that can democratize knowledge 16 00:01:24,569 --> 00:01:30,429 and opportunity, whereas others fear that may widen existing inequalities and 17 00:01:30,439 --> 00:01:33,299 further concentrate power and privilege. 18 00:01:34,079 --> 00:01:39,909 So how do we build a future in which talent matters more than geography, 19 00:01:39,959 --> 00:01:41,749 background, or circumstance? 20 00:01:42,429 --> 00:01:47,309 How do we identify and support individuals who might otherwise be overlooked? 21 00:01:47,909 --> 00:01:52,629 And what role can science, technology, mentorship, and entrepreneurship, 22 00:01:52,629 --> 00:01:57,779 and you and I play in curating a more inclusive innovation ecosystem? 23 00:01:58,659 --> 00:02:02,539 To explore these questions today, I'm very delighted to be joined by 24 00:02:02,559 --> 00:02:08,769 Dr. Abhilash Mishra, a physicist, entrepreneur, and founder of Equatic 25 00:02:08,769 --> 00:02:14,759 Futures, an organization dedicated to expanding access to science, technology, 26 00:02:14,769 --> 00:02:20,339 innovation, and leadership opportunities for talented individuals across the world. 27 00:02:21,009 --> 00:02:25,429 In this conversation, we discuss the barriers that prevent talented people 28 00:02:25,449 --> 00:02:29,809 from succeeding, the realities of building and scaling a mission-driven 29 00:02:29,809 --> 00:02:35,599 organization, and the role of mentorship and community in shaping careers, 30 00:02:36,029 --> 00:02:40,819 and how we can create systems that enable more people to contribute to 31 00:02:40,819 --> 00:02:43,059 future of science and technology. 32 00:02:43,769 --> 00:02:46,489 Abhilash, welcome to Immunity by Design. 33 00:02:47,589 --> 00:02:48,529 Thank you for having me. 34 00:02:48,579 --> 00:02:50,079 I really appreciate the invitation. 35 00:02:50,629 --> 00:02:50,969 Thank you. 36 00:02:50,969 --> 00:02:51,809 It's a pleasure. 37 00:02:52,119 --> 00:02:56,409 So Abhilash, to start with, for listeners who might not know you well, 38 00:02:56,459 --> 00:03:01,139 could you please briefly introduce yourself, and tell us a little bit 39 00:03:01,179 --> 00:03:05,839 about the missions you are on and the, the missions that drive your work? 40 00:03:06,987 --> 00:03:07,417 Sure. 41 00:03:07,457 --> 00:03:08,947 So my name is Abhilash Mishra. 42 00:03:08,947 --> 00:03:13,527 I'm the founder and chief science officer of Equitech Futures. 43 00:03:13,607 --> 00:03:18,747 I was born in India in a small town in the eastern part of India. 44 00:03:18,757 --> 00:03:22,407 I always wanted to be a physicist since high school. 45 00:03:22,437 --> 00:03:26,257 I was fascinated by astronomy and physics and so I decided to 46 00:03:26,257 --> 00:03:28,437 pursue physics as an undergraduate. 47 00:03:28,537 --> 00:03:32,007 And I, pursued physics as an undergraduate in India. 48 00:03:32,277 --> 00:03:36,527 I went to Oxford for my master's and then finished my PhD 49 00:03:36,577 --> 00:03:38,127 in astrophysics at Caltech. 50 00:03:38,597 --> 00:03:43,437 And throughout this time I was very interested, given just the setting where 51 00:03:43,437 --> 00:03:49,947 I grew up in figuring out how we can have more people from around the world 52 00:03:50,227 --> 00:03:52,907 be part of the scientific enterprise. 53 00:03:52,957 --> 00:03:58,397 When I was growing up, I was very lucky to have amazing science teachers and mentors. 54 00:03:58,727 --> 00:04:03,437 My parents were very supportive in me pursuing science as a career. 55 00:04:03,837 --> 00:04:06,947 But even then, I saw that the kind of opportunities available 56 00:04:06,967 --> 00:04:11,387 for people to pursue scientific discovery and innovation were limited. 57 00:04:11,497 --> 00:04:15,557 And that's was the driving force behind what I wanted to do. 58 00:04:15,557 --> 00:04:19,977 I really wanted to figure out how we can enable more people in the world to 59 00:04:19,977 --> 00:04:21,667 participate in the scientific enterprise. 60 00:04:22,417 --> 00:04:22,747 great. 61 00:04:22,777 --> 00:04:26,907 Also we will be coming back to Equitech and we will be discussing about it, 62 00:04:27,387 --> 00:04:31,987 but to begin with, also introduce Equitech Futures, what it is what the 63 00:04:31,987 --> 00:04:34,297 missions are, and what they offer. 64 00:04:35,221 --> 00:04:35,651 Yeah. 65 00:04:35,661 --> 00:04:41,291 So Equitech Futures is a talent engine and an innovation lab. 66 00:04:41,341 --> 00:04:45,241 So by talent engine, a mechanism through which we identify the most 67 00:04:45,251 --> 00:04:50,261 promising innovators from across disciplines and from around the world 68 00:04:50,521 --> 00:04:55,441 who want to use science and technology to tackle societal challenges. 69 00:04:55,811 --> 00:05:00,551 The way we do that is by running institutes virtual institutes that 70 00:05:00,561 --> 00:05:05,011 students can participate in and go through courses in applied artificial 71 00:05:05,011 --> 00:05:10,591 intelligence, in applied data science, in communication, and societal and 72 00:05:10,591 --> 00:05:12,461 ethical perspectives in technology. 73 00:05:12,561 --> 00:05:17,811 And we also host challenges, innovation challenges through which innovators 74 00:05:17,811 --> 00:05:21,991 from around the world can participate and pitch new ideas that we then 75 00:05:22,001 --> 00:05:25,331 support through funding, through training, and through mentorship. 76 00:05:25,771 --> 00:05:31,571 And we invest a lot in our alumni network in trying to, again, support 77 00:05:31,641 --> 00:05:35,191 individuals who've been through our programs to find opportunities 78 00:05:35,511 --> 00:05:39,671 in research, in entrepreneurship or working in the civic sector. 79 00:05:40,331 --> 00:05:40,631 Sure. 80 00:05:41,331 --> 00:05:46,361 In addition to your own career path that you mentioned, that was very impressive 81 00:05:46,401 --> 00:05:51,391 and also, y- coming to Oxford and then Caltech and seeing some opportunities 82 00:05:52,201 --> 00:05:58,391 was there any other specific gap or problem that, led you to think that 83 00:05:58,391 --> 00:06:00,791 eventually formed the Equitech Futures? 84 00:06:01,769 --> 00:06:02,329 Yeah. 85 00:06:02,339 --> 00:06:05,039 So two experiences come to mind. 86 00:06:05,049 --> 00:06:10,429 So when I was in high school, I was part of the mathematics Olympiad program- 87 00:06:10,489 --> 00:06:12,999 … in the state of Odisha where I grew up. 88 00:06:13,279 --> 00:06:18,829 It's a small, relatively impoverished state in India, and one a mathematician 89 00:06:18,949 --> 00:06:23,689 by the name of Swadhin Patnaik used to run these math Olympiad programs and that's 90 00:06:23,689 --> 00:06:25,909 where my interest in physics really began. 91 00:06:26,349 --> 00:06:27,569 He was a mentor to me. 92 00:06:27,589 --> 00:06:31,429 I was interested in pursuing science a- and physics and he 93 00:06:31,429 --> 00:06:34,719 gave me the opportunities to to really learn about science. 94 00:06:35,099 --> 00:06:39,119 So when I was in college, he launched a new program called the Rural Math 95 00:06:39,119 --> 00:06:43,329 Talent Search Program- … where he was identifying very mathematically 96 00:06:43,329 --> 00:06:48,119 gifted students from rural India and trying to support them by giving 97 00:06:48,119 --> 00:06:50,039 them training through summer camps. 98 00:06:50,119 --> 00:06:53,799 And he asked me to come back and teach at these summer camps, so I went back during 99 00:06:53,799 --> 00:06:57,689 summer vacations to, to teach at this Rural Mathematics Talent Search Program. 100 00:06:58,099 --> 00:07:01,399 And that was really a pivot point for me because when I was teaching 101 00:07:01,399 --> 00:07:06,459 these students, I would see students who would come from families that 102 00:07:06,959 --> 00:07:11,239 were making less than $50 a month. 103 00:07:11,639 --> 00:07:15,019 But these were students in eighth grade doing, college level 104 00:07:15,029 --> 00:07:17,099 math extraordinarily talented. 105 00:07:17,439 --> 00:07:22,759 And it just impressed upon me the fact that opportunity is truly… talent 106 00:07:22,759 --> 00:07:26,379 is widely distributed, but opportunity is not, and that if we gave this 107 00:07:26,379 --> 00:07:32,359 opportunity to folks we would find exceptional Marie Curies and Einsteins 108 00:07:32,539 --> 00:07:36,509 all around the world, not just in Silicon Valley or in Cambridge or in Oxford. 109 00:07:36,519 --> 00:07:41,269 And that support them, that could be a net benefit for not just the communities that 110 00:07:41,269 --> 00:07:44,009 they came from, but also for the world. 111 00:07:44,089 --> 00:07:47,959 The-- think of the kind of innovations that we miss out on because we don't 112 00:07:47,959 --> 00:07:49,759 support these amazingly gifted students. 113 00:07:49,759 --> 00:07:53,429 And so that was my kind of first experience that drove me towards 114 00:07:53,459 --> 00:07:58,099 working in identifying or developing new pathways for scientific talent. 115 00:07:58,755 --> 00:08:02,595 The second was when I got into graduate school at Caltech, I asked 116 00:08:02,595 --> 00:08:06,505 if I could take a year off and go work in education in India and Caltech 117 00:08:06,505 --> 00:08:08,085 was kind enough to let me do that. 118 00:08:08,095 --> 00:08:14,095 And when I went back to India, I founded a nonprofit that was placing science 119 00:08:14,135 --> 00:08:18,755 undergraduates as part-time science teachers in local low-income classrooms. 120 00:08:18,845 --> 00:08:21,825 So local low-income classrooms would typically not have teachers 121 00:08:21,835 --> 00:08:25,215 who were trained in science, and so we were providing assistant 122 00:08:25,225 --> 00:08:27,045 teachers to teach science and math. 123 00:08:27,105 --> 00:08:32,405 And I would visit these classrooms and I was just stunned at how some of the 124 00:08:32,405 --> 00:08:37,475 students would completely change their attitudes towards science and math 125 00:08:37,485 --> 00:08:43,435 because they had a mentor a teacher who was making the content interesting, 126 00:08:43,755 --> 00:08:49,305 making the the ideas interesting to people, giving them an avenue and an 127 00:08:49,305 --> 00:08:53,525 imagination where they could think of themselves as scientists in the future. 128 00:08:53,535 --> 00:08:57,875 And I just saw what a profound impact teachers and mentors really play. 129 00:08:58,205 --> 00:09:01,625 And that was the other kind of motivation behind founding Equitech Futures. 130 00:09:01,645 --> 00:09:06,505 How can we make access to learning not just via technology, but also 131 00:09:06,505 --> 00:09:12,165 via people more broadly accessible to the world and particularly in a world 132 00:09:12,225 --> 00:09:17,855 where the global majority does not live in, the UK or the US where the 133 00:09:17,855 --> 00:09:19,615 leading research universities are. 134 00:09:19,675 --> 00:09:22,725 So that was something that really drove me when I was founding Equitech Futures. 135 00:09:23,155 --> 00:09:23,835 Very impressive. 136 00:09:23,865 --> 00:09:24,755 Thank you for sharing. 137 00:09:25,355 --> 00:09:29,945 Now, looking back, what was the first irreversible step that made Equitech 138 00:09:30,035 --> 00:09:31,575 real rather than just an idea? 139 00:09:32,961 --> 00:09:33,361 Yeah. 140 00:09:33,361 --> 00:09:35,481 So I think it was the pandemic really. 141 00:09:35,571 --> 00:09:37,451 I had moved to Chicago after my PhD. 142 00:09:37,491 --> 00:09:41,251 I was at the University of Chicago, but I still have a position where 143 00:09:41,281 --> 00:09:45,551 I was setting up a research center on, on technology and public policy. 144 00:09:45,881 --> 00:09:50,351 And I saw the gap between the kind of research that was happening in 145 00:09:50,471 --> 00:09:56,141 academic institutions and the gap between how that research and ideas 146 00:09:56,411 --> 00:09:58,401 failed to percolate to society. 147 00:09:58,431 --> 00:10:02,091 And we saw that during the pandemic, during the early stages of the 148 00:10:02,091 --> 00:10:06,151 pandemic, when you had public health officials, talking about evidence, 149 00:10:06,151 --> 00:10:11,321 talking about scientific evidence, which was relevant for the pandemic 150 00:10:11,331 --> 00:10:13,431 and society wasn't quite responding. 151 00:10:13,761 --> 00:10:19,731 Or governments really struggled to- to, think about and communicate the scientific 152 00:10:19,781 --> 00:10:21,491 approaches to tackling the pandemic. 153 00:10:21,851 --> 00:10:25,501 And I thought that was real failure that we were going through where we 154 00:10:25,501 --> 00:10:28,751 have all these scientific advances, we're writing all these papers, making 155 00:10:28,751 --> 00:10:32,281 all these discoveries, but there clearly is a gap between scientific 156 00:10:32,281 --> 00:10:36,431 advances and the way society looks at science or adopts science. 157 00:10:36,761 --> 00:10:41,761 And so there was a missing layer, I think, of practitioners who are educated 158 00:10:41,761 --> 00:10:46,201 in science, know about science- … and then are actually working in problems 159 00:10:46,221 --> 00:10:50,591 in society as opposed to, just working in an academic setting where you are 160 00:10:50,821 --> 00:10:54,111 effectively preaching to the choir because you're talking to your peers 161 00:10:54,341 --> 00:10:55,801 as opposed to talking to society. 162 00:10:56,251 --> 00:10:58,871 And so the kind of irreversible part, I think, was when we were 163 00:10:58,911 --> 00:11:01,939 thinking about What should we do here? 164 00:11:02,179 --> 00:11:08,049 We said maybe we just start a summer program for individuals undergraduates 165 00:11:08,049 --> 00:11:12,659 or postgraduates who want to work in this space." We knew that there were 166 00:11:12,659 --> 00:11:16,689 people who want to work in this space, but they did not quite have an avenue 167 00:11:16,949 --> 00:11:21,479 to go learn about the kind of skills to, to translate science to society. 168 00:11:21,829 --> 00:11:24,219 So when we launched the summer school, initially we thought maybe 169 00:11:24,219 --> 00:11:26,219 we'll get 10 or 20 applicants. 170 00:11:26,669 --> 00:11:28,399 But we were flooded with applications. 171 00:11:28,439 --> 00:11:33,779 And this was also the early stages of the adoption of remote work, of 172 00:11:33,799 --> 00:11:39,449 Zoom and we were just fascinated to get applicants from constituencies 173 00:11:39,459 --> 00:11:44,659 which, where you absolutely see no representation in traditional academia. 174 00:11:44,659 --> 00:11:48,649 We were getting applicants from Sudan, where there was a war going on. 175 00:11:48,669 --> 00:11:53,999 We were getting applicants from rural Africa, where people were hopping on our 176 00:11:53,999 --> 00:11:57,299 institute using borrowed mobile phones. 177 00:11:57,339 --> 00:12:00,619 And that really struck a chord, that we realized there was something here. 178 00:12:00,659 --> 00:12:05,049 There's a hunger and a demand for opportunities like the institute that 179 00:12:05,049 --> 00:12:08,669 we were hosting, where students could come, learn about these tools, and 180 00:12:08,669 --> 00:12:12,929 then truly that ended up being the kind of pivot point for them to take 181 00:12:12,939 --> 00:12:18,269 their technical skills or their social practitioner skills, learn the kind of 182 00:12:18,319 --> 00:12:22,639 tools that we were providing them with, and then go work with their communities 183 00:12:22,669 --> 00:12:25,909 to to bring about the action that that they wanted to see in the world. 184 00:12:26,249 --> 00:12:28,989 And that really it is the students who always inspire me. 185 00:12:28,989 --> 00:12:31,859 It's it's the scholars that I work with always inspire me. 186 00:12:31,859 --> 00:12:35,559 They are the ones who get me up in the morning and excited to work. 187 00:12:35,579 --> 00:12:38,079 And and that was really the point where I realized, yeah, this 188 00:12:38,079 --> 00:12:39,239 is the work that we have to do. 189 00:12:39,239 --> 00:12:41,309 We have to create more avenues. 190 00:12:41,309 --> 00:12:46,349 We have to create more pathways for young, talented individuals around the world, 191 00:12:46,639 --> 00:12:50,429 not just from the sciences, by the way, from all across, from other disciplines. 192 00:12:50,719 --> 00:12:53,139 Because as in many parts of the world, I think people 193 00:12:53,139 --> 00:12:54,739 specialize a little too early. 194 00:12:55,059 --> 00:12:59,349 And I always try to think about science not as a discipline but as a way of 195 00:12:59,349 --> 00:13:04,651 life, as a way of thinking And that way of life and way of thinking translates 196 00:13:04,661 --> 00:13:08,071 to so many other things that we do in society, whether that's in public 197 00:13:08,071 --> 00:13:09,961 health, whether that is in cybersecurity. 198 00:13:10,171 --> 00:13:13,471 So we really wanted to have this kind of wide disciplinary 199 00:13:13,511 --> 00:13:15,191 global network of people. 200 00:13:15,241 --> 00:13:19,731 And and once we saw that there was a demand, we just decided to keep 201 00:13:19,821 --> 00:13:23,171 going and hosting new institutes and and growing our network. 202 00:13:23,691 --> 00:13:24,071 Excellent. 203 00:13:24,371 --> 00:13:28,331 So all these motivations and opportunities, that's all great, 204 00:13:28,331 --> 00:13:31,501 and in particular, you are presenting it in a very nice way. 205 00:13:31,911 --> 00:13:37,401 So thinking about the past did building Equitech require sacrifices 206 00:13:37,411 --> 00:13:42,311 or difficult decisions or were there any alternative path you could 207 00:13:42,321 --> 00:13:44,841 have pursued but you chose not to? 208 00:13:45,989 --> 00:13:46,599 Yes. 209 00:13:46,689 --> 00:13:50,249 I should mention that when we were-- when I was thinking about Equitech 210 00:13:50,249 --> 00:13:53,656 Futures, it was a s- the germ of an idea for about two or three years. 211 00:13:53,706 --> 00:13:56,516 Around twenty nineteen or twenty eighteen or so. 212 00:13:56,856 --> 00:14:02,316 The parallel kind of tech world was very much focused on edtech, 213 00:14:02,326 --> 00:14:04,176 where scale was the bet, right? 214 00:14:04,186 --> 00:14:08,306 So every organization and every company wa-wanted to have a million 215 00:14:08,306 --> 00:14:13,356 students and, wanted to reach X amount of revenue within one year. 216 00:14:13,826 --> 00:14:16,106 And there was real FOMO, I think. 217 00:14:16,116 --> 00:14:20,546 We would-- we thought of really am I really missing out on on building 218 00:14:20,546 --> 00:14:25,896 solutions which are scaling very rapidly and getting, lots of attention from 219 00:14:26,196 --> 00:14:28,236 either from funders or from people. 220 00:14:28,516 --> 00:14:34,746 And we took the difficult decision of growing slowly and not to scale rapidly 221 00:14:34,746 --> 00:14:37,156 and to be intentional about how we grow. 222 00:14:37,166 --> 00:14:42,166 And I think that was a difficult decision back then because everyone was puzzled 223 00:14:42,166 --> 00:14:46,206 with, why would you launch a program where you just select twenty-five students 224 00:14:46,206 --> 00:14:48,666 or, have smaller cohorts of people? 225 00:14:48,766 --> 00:14:52,286 But we intentionally wanted to do that because we wanted to figure out how 226 00:14:52,586 --> 00:14:56,096 to be able to, craft our curriculum, how to be able to craft the student 227 00:14:56,096 --> 00:14:58,566 experience deeply before we scaled. 228 00:14:58,916 --> 00:15:01,826 And so making that choice of doing things that, Paul Graham, the 229 00:15:01,826 --> 00:15:05,656 investor, the UK-based investor, has a saying, "Do things that don't 230 00:15:05,656 --> 00:15:09,076 scale." And I think we-- And I would still argue that we are still doing 231 00:15:09,086 --> 00:15:11,266 things that don't scale at this point. 232 00:15:11,276 --> 00:15:14,806 But I think it's important to do that because for a lot of innovators and 233 00:15:14,806 --> 00:15:19,436 entrepreneurs at the early stages, the pressure is to scale too fast. 234 00:15:19,466 --> 00:15:25,156 And I think that leads to mistakes later on or that ma- leads to compromises made 235 00:15:25,156 --> 00:15:26,896 later on that can hinder the mission. 236 00:15:27,646 --> 00:15:28,286 Yeah, exactly. 237 00:15:28,376 --> 00:15:33,106 Speaking of, this scaling up and growth, which are very essential for any business 238 00:15:33,126 --> 00:15:37,756 in particular at the beginning, and actually most they fail at this stage. 239 00:15:37,776 --> 00:15:43,276 So I would like to talk a little bit more about building and scaling And 240 00:15:43,286 --> 00:15:49,816 in that what structures or principles did you put in place that later proved 241 00:15:49,826 --> 00:15:52,576 essential for Equitech Futures' growth? 242 00:15:53,790 --> 00:15:57,170 Yeah and Hossein, I think as a scientist you will appreciate this, 243 00:15:57,190 --> 00:16:02,770 where we really thought about each of our institutes as a new experiment. 244 00:16:02,780 --> 00:16:07,830 Where you want to take this experimental approach towards building a company, 245 00:16:08,110 --> 00:16:12,070 where you have a hypothesis, you go, run the experiment, you run the 246 00:16:12,100 --> 00:16:15,610 institute or run the program, get some data on what worked and what 247 00:16:15,610 --> 00:16:17,390 did not work, and then you iterate. 248 00:16:17,800 --> 00:16:22,700 And I think taking that experimental approach towards building the organization 249 00:16:22,710 --> 00:16:28,400 has really benefited us a lot because, A, it helped us not to get stuck on 250 00:16:28,400 --> 00:16:33,750 solutions that were not working, and B, it helped us identify opportunities 251 00:16:33,830 --> 00:16:38,940 early on and pivot towards opportunities early on, when if we had just stuck 252 00:16:38,940 --> 00:16:42,300 to one way of doing things, we would not have found those opportunities. 253 00:16:42,340 --> 00:16:48,010 And so I I really think that having that experimental kind of attitude towards 254 00:16:48,010 --> 00:16:52,140 entrepreneurship is something that being a scientist taught me and that has been very 255 00:16:52,140 --> 00:16:54,840 beneficial as we have launched Equitech. 256 00:16:55,840 --> 00:17:01,960 And when trying to scale in a normal way, did you scale Equitech 257 00:17:02,010 --> 00:17:06,720 wi- without diluting its mission of accessibility and inclusion? 258 00:17:08,672 --> 00:17:09,282 Yes. 259 00:17:09,322 --> 00:17:13,402 I think that was and I should frame this as saying because we are philanthropically 260 00:17:13,402 --> 00:17:17,782 funded- … the reason why we were able to attract philanthropic funding was 261 00:17:17,842 --> 00:17:22,752 because philanthropy, the philanthropists who support us were aligned with our 262 00:17:22,752 --> 00:17:27,572 mission, and they wanted us to really double down on our mission and try 263 00:17:27,572 --> 00:17:31,842 to make it as accessible as possible as widely available as possible. 264 00:17:31,842 --> 00:17:36,192 And even today we have programs where, which have some kind of a tuition 265 00:17:36,232 --> 00:17:41,112 component to it, but we try to make it as accessible as possible for individuals. 266 00:17:41,402 --> 00:17:47,292 For example, for just this year we launched a new platform called 267 00:17:47,292 --> 00:17:54,432 futureshub.com where students can apply for challenges, read AI textbooks our 268 00:17:54,432 --> 00:17:56,582 curriculum that is now on the platform. 269 00:17:56,852 --> 00:18:00,322 And we have tried to make the platform as widely accessible. 270 00:18:00,572 --> 00:18:04,542 So a lot of the resources that are free a lot of the institutes that we 271 00:18:04,542 --> 00:18:06,712 host there are fully tuition funded. 272 00:18:07,062 --> 00:18:11,682 And so we've really tried to make sure that our mission remains aligned. 273 00:18:11,732 --> 00:18:16,362 And one of the things that a big part of my job is trying to work with funders 274 00:18:16,422 --> 00:18:20,252 from around the world who are aligned with what we are trying to do to make 275 00:18:20,252 --> 00:18:24,672 sure that we are continuing to able to grow this mission without diluting it. 276 00:18:24,742 --> 00:18:25,722 And so we've been lucky. 277 00:18:25,752 --> 00:18:29,322 I consider myself extremely lucky that we have philanthropic partners 278 00:18:29,322 --> 00:18:30,392 who believe in our mission. 279 00:18:30,722 --> 00:18:32,412 But yes, that is a trade-off, right? 280 00:18:32,412 --> 00:18:36,482 I think a lot of young entrepreneurs try to think of whether you want to, 281 00:18:36,502 --> 00:18:41,262 focus on commercial capital or patient capital and or philanthropic capital. 282 00:18:41,562 --> 00:18:44,152 And we intentionally looked at philanthropic capital. 283 00:18:44,202 --> 00:18:46,922 And that's-- And my advice when I'm talking to entrepreneurs is being 284 00:18:46,922 --> 00:18:51,602 very intentional about what kinds of capital they take in because that can 285 00:18:51,872 --> 00:18:56,702 determine what your kind of mission or your kind of core priorities are. 286 00:18:57,242 --> 00:18:57,452 Sure. 287 00:18:58,072 --> 00:19:03,905 And, during those periods of translating an idea to impact and also trying to 288 00:19:04,065 --> 00:19:12,195 scale without diverging from your goals and the goals of the your company, what 289 00:19:12,225 --> 00:19:17,795 mistakes or less successful initiatives taught you the most valuable lesson? 290 00:19:19,663 --> 00:19:21,603 Yeah, this is a great question. 291 00:19:21,663 --> 00:19:28,953 I think the kind of lessons that we learned was that, in instances where we 292 00:19:28,953 --> 00:19:34,713 did launch programs where we thought can we, without taking philanthropic capital, 293 00:19:34,723 --> 00:19:38,333 can we maybe have a revenue-based program? 294 00:19:38,663 --> 00:19:41,893 And we did launch a revenue-based program and we have launched revenue-based 295 00:19:41,893 --> 00:19:43,633 programs in recent years too. 296 00:19:43,993 --> 00:19:48,693 But we distinctly see that a lot of our revenue-based programs particularly, the 297 00:19:48,693 --> 00:19:52,193 way in which it is priced, particularly for American and European customers 298 00:19:52,243 --> 00:19:58,913 or users, they tend to overlook the kind of talented individuals that 299 00:19:58,913 --> 00:20:00,143 we are interested in supporting. 300 00:20:00,153 --> 00:20:05,423 And so really I think the kind of constant struggle that we have internally is how 301 00:20:05,423 --> 00:20:10,123 do we balance the economics of running an institution versus making it accessible? 302 00:20:10,173 --> 00:20:13,213 And there have been mistakes that we've made in terms of, offering a 303 00:20:13,213 --> 00:20:18,413 program that was just clearly not going to be accessible to students in the 304 00:20:18,413 --> 00:20:20,173 African continent or in South Asia. 305 00:20:20,473 --> 00:20:23,793 And then we've had to course correct and- … figure out, okay, how do we make 306 00:20:23,793 --> 00:20:28,683 sure that these programs are accessible, whether we do that via philanthropic 307 00:20:28,693 --> 00:20:33,713 funding, or we do that via coming up with more flexible tuition structures. 308 00:20:34,003 --> 00:20:36,343 I think those are the lessons that we are still learning, I would say. 309 00:20:36,353 --> 00:20:38,133 I don't think that we have full answers yet. 310 00:20:38,193 --> 00:20:41,723 But those are places which have definitely helped us make relevant pivots. 311 00:20:42,403 --> 00:20:46,553 speaking of failure, actually this brings me nicely to my next few 312 00:20:46,573 --> 00:20:52,605 questions, which are about why talented people fail and barriers to success. 313 00:20:52,725 --> 00:20:58,535 And in that regard, when we talk about inequalities in science and technology, 314 00:20:59,095 --> 00:21:01,615 people often focus on funding. 315 00:21:02,035 --> 00:21:05,665 So in your experience, what are the biggest barriers talented 316 00:21:05,695 --> 00:21:07,255 individuals actually face? 317 00:21:07,285 --> 00:21:12,475 Is it money, mentorship, network, confidence, geography, credentials, 318 00:21:12,475 --> 00:21:14,475 or perhaps combination of everything? 319 00:21:15,573 --> 00:21:17,273 Oh, I think it's a combination of everything. 320 00:21:17,273 --> 00:21:20,713 What you just described I think is a classic sort of wicked problem, right? 321 00:21:20,763 --> 00:21:24,463 There are so many different reasons that drive why talented individuals 322 00:21:24,493 --> 00:21:28,543 cannot find the opportunities and one obviously is money and funding. 323 00:21:28,553 --> 00:21:32,253 I was able to pursue science because in undergraduate the government of 324 00:21:32,253 --> 00:21:37,793 India launched a scholarship program for emerging young scientists. 325 00:21:37,793 --> 00:21:42,163 There was a test and, I had to do work on a project, and based on my, interview 326 00:21:42,163 --> 00:21:45,443 with professional scientists, I got a scholarship from the government. 327 00:21:45,753 --> 00:21:50,503 And that really gave me a confidence in pursuing science, but also gave confidence 328 00:21:50,503 --> 00:21:54,053 to my parents and to people around me to say, "Yeah, this is something that 329 00:21:54,053 --> 00:21:57,673 is worth pursuing." So I think funding matters a lot when pursuing science. 330 00:21:57,823 --> 00:22:02,513 Definitely pursuing science at Oxford, I went to Oxford on a Rhodes Scholarship. 331 00:22:02,773 --> 00:22:05,713 I would never have been able to go to Oxford had I not been fully funded. 332 00:22:05,963 --> 00:22:07,473 Same with a PhD program. 333 00:22:07,513 --> 00:22:12,553 And so I, I cannot emphasize the role of philanthropy and government 334 00:22:12,553 --> 00:22:13,913 funding enough around science. 335 00:22:13,943 --> 00:22:18,253 The reason why science has re- really flourished in Europe and 336 00:22:18,253 --> 00:22:22,783 in and in North America has been because of government investments in 337 00:22:23,073 --> 00:22:24,703 science and because of philanthropy. 338 00:22:24,753 --> 00:22:28,653 And I think one of the things that I'm really alarmed about today 339 00:22:28,923 --> 00:22:32,673 is how government funding both in North America and across the pond 340 00:22:32,673 --> 00:22:35,063 in Europe is going down in science. 341 00:22:35,103 --> 00:22:37,193 This is definitely true in the UK where you are. 342 00:22:37,443 --> 00:22:40,573 As well as how philanthropy is shrinking around science as well. 343 00:22:40,623 --> 00:22:43,263 I think this is something that, that really as a society we need to 344 00:22:43,263 --> 00:22:47,143 confront if we want to make sure that scientific progress is equitable. 345 00:22:47,253 --> 00:22:52,203 But beyond funding, I think, even in environments where funding exists the 346 00:22:52,253 --> 00:22:59,113 two things that I have seen being a big blocker tends to be credentials. 347 00:22:59,163 --> 00:23:01,053 And you would know this Hashim. 348 00:23:01,063 --> 00:23:04,553 We-- You and I have talked about how the fact that you go to a particular 349 00:23:04,553 --> 00:23:08,743 type of school if you're a, a- an Oxford undergraduate and you're applying to a 350 00:23:08,743 --> 00:23:13,033 PhD p- position at Cambridge people are likely to see your application much more 351 00:23:13,033 --> 00:23:19,083 favorably than if you're applying from a university in in the African continent or 352 00:23:19,093 --> 00:23:21,373 in India, say, which is not as well known. 353 00:23:21,423 --> 00:23:24,893 Which is not to say that there are not talented students in these places. 354 00:23:24,913 --> 00:23:29,773 It's just that I think there is a bias of a lot of departments and research 355 00:23:29,773 --> 00:23:33,983 institutions to, to select from, quote unquote, "elite institutions." And there's 356 00:23:33,983 --> 00:23:38,963 actually a lot of evidence now, Daniel Larrimore a professor at U- University 357 00:23:38,963 --> 00:23:43,143 of Colorado did this fantastic paper where he looked at who gets hired at 358 00:23:43,173 --> 00:23:48,573 top PhD programs science PhD programs in the US, and you constantly see that, 359 00:23:48,623 --> 00:23:52,843 it's the universities feeding each other's graduate programs, and it's the 360 00:23:52,843 --> 00:23:55,743 same graduate students who are going to become faculty and so on and so forth. 361 00:23:56,253 --> 00:24:00,653 So that I think is is a place where credentials like really for us to start 362 00:24:00,673 --> 00:24:05,713 thinking about what credentials mean is I think, the… This is especially at a 363 00:24:05,713 --> 00:24:10,803 time when AI is disrupting the role of credentials it's worth asking how how 364 00:24:10,803 --> 00:24:14,623 we can change the credentialing system to make sure that more people are able 365 00:24:14,623 --> 00:24:17,083 to enter s- the scientific enterprise. 366 00:24:17,593 --> 00:24:23,703 The third and important thing I would say is is mentorship and networks of people. 367 00:24:23,753 --> 00:24:28,663 I got into science because of access to some incredible mentors 368 00:24:28,743 --> 00:24:30,163 and because of my parents. 369 00:24:30,163 --> 00:24:32,283 Both my parents were professors. 370 00:24:32,333 --> 00:24:35,643 They were very supportive of my scientific interests. 371 00:24:35,663 --> 00:24:38,943 In fact, again, going back to Daniel Larrimore's work, one of the things he 372 00:24:38,943 --> 00:24:43,193 saw was that if you look at top the top university or the top faculty at top 373 00:24:43,193 --> 00:24:49,733 universities in in North America the faculty are 50 times more likely to have 374 00:24:49,733 --> 00:24:52,533 had a parent who also worked in sciences. 375 00:24:52,593 --> 00:24:56,483 And so which means that the kind of the training and the environment that you 376 00:24:56,503 --> 00:25:00,143 grow up in, whether it is through parents, whether it is through mentors, whether 377 00:25:00,143 --> 00:25:05,033 it is through teachers, really has a profound influence in in entering science. 378 00:25:05,033 --> 00:25:08,763 And, if you talk to any scientist I'm sure you and I can talk about the 379 00:25:08,763 --> 00:25:12,523 profound influence that, that some of the mentors in our lives had on us. 380 00:25:12,863 --> 00:25:16,623 And so really having access to that mentorship and to that support I think 381 00:25:16,633 --> 00:25:20,153 can be a life-changing experience, and that's something that we at 382 00:25:20,153 --> 00:25:22,423 Equitech Futures really believe in. 383 00:25:22,423 --> 00:25:26,933 We don't think that scientific learning is just about, having access to, to 384 00:25:26,933 --> 00:25:31,413 content or having access to to high curr- quality curricula or credentials. 385 00:25:31,413 --> 00:25:34,333 It is really about having access to amazing mentors who 386 00:25:34,333 --> 00:25:37,473 can support how students evolve in their scientific careers. 387 00:25:38,173 --> 00:25:38,383 Yeah. 388 00:25:38,383 --> 00:25:38,773 Excellent. 389 00:25:39,603 --> 00:25:45,133 Abhilash, y- firstly, you actually very nicely answered my next question that 390 00:25:45,183 --> 00:25:52,063 was whether we have become too reliant on prestigious credentials and institutional 391 00:25:52,063 --> 00:25:57,973 reputation when identifying talent, because you answered that very nicely. 392 00:25:57,973 --> 00:26:03,461 So perhaps, a slightly different question how we can change the system? 393 00:26:05,751 --> 00:26:09,391 So let me contextualize it just in terms of sheer numbers, right? 394 00:26:09,411 --> 00:26:14,541 If you think about the number of young people in the age of 15 to 25 today, 395 00:26:14,541 --> 00:26:16,371 there are about 1.2 billion people. 396 00:26:16,371 --> 00:26:20,231 If you think about even 1% of those 1.2 billion people, 397 00:26:20,231 --> 00:26:21,871 that's about 12 million people. 398 00:26:22,201 --> 00:26:27,961 If you think about how many students are in the top 100 or 200 universities 399 00:26:28,011 --> 00:26:31,101 in one of, one of these rankings, you'll get maybe in the ballpark 400 00:26:31,101 --> 00:26:32,271 of two million people, right? 401 00:26:32,621 --> 00:26:37,781 A- and just relying on elite institutions as the only kind of drivers of 402 00:26:37,781 --> 00:26:41,841 scientific discovery, I think is the wrong approach, because it's not 403 00:26:41,841 --> 00:26:46,391 like these elite institutions are increasing their intake significantly. 404 00:26:46,451 --> 00:26:50,601 I was talking to the president of, or the former president of a major research 405 00:26:50,601 --> 00:26:54,541 university, and I asked him, "You have a massive multi-billion dollar endowment. 406 00:26:54,971 --> 00:26:58,031 Why don't you double the number of undergraduate students or graduate 407 00:26:58,031 --> 00:27:01,871 students that you take up?" And they basically said the faculty would not 408 00:27:01,871 --> 00:27:03,821 allow us to grow the number of people." 409 00:27:03,991 --> 00:27:09,001 So there's these heavy, currents of conservatism, small C conservatism 410 00:27:09,261 --> 00:27:13,431 amongst universities not to grow because people feel like, oh, if 411 00:27:13,431 --> 00:27:16,781 we grow too much, then it'll dilute our brand or value or what have you. 412 00:27:17,141 --> 00:27:19,661 So I think we, we should really therefore, and when we are thinking 413 00:27:19,661 --> 00:27:23,181 about access, when we are thinking about about scientific talent, we should 414 00:27:23,181 --> 00:27:27,391 be thinking about how we can support scientific talent in institutions 415 00:27:27,391 --> 00:27:31,921 that are not in these, top 200 and thinking about alternative mechanisms 416 00:27:31,931 --> 00:27:33,261 through which we can support them. 417 00:27:33,651 --> 00:27:36,701 One way of supporting them is through things like fellowships. 418 00:27:36,791 --> 00:27:40,941 I think especially as the number of PhD positions is going down 419 00:27:40,941 --> 00:27:44,421 significantly, at least here in North America because of funding cuts. 420 00:27:44,431 --> 00:27:47,421 There's a real kind of a reckoning right now of thinking about what are 421 00:27:47,431 --> 00:27:53,361 alternative pathways to having, to training people in sciences without 422 00:27:53,391 --> 00:27:58,091 having, without having people to go through a five or six-year PhD. 423 00:27:58,141 --> 00:27:59,661 What does that training look like? 424 00:27:59,971 --> 00:28:03,241 Can we do that training without, the traditional institutional 425 00:28:03,241 --> 00:28:06,931 structures that have been built over the past 100, 120 years? 426 00:28:07,311 --> 00:28:11,041 And so I think we, this is a real kind of time for creative thinking amongst 427 00:28:11,041 --> 00:28:13,911 academics and and academic leaders to, to think about how we can re- 428 00:28:14,151 --> 00:28:19,221 reimagine scientific talent and training in in different parts of the world. 429 00:28:19,661 --> 00:28:22,511 And so m- my kind of short answer is that, I think we really need to 430 00:28:22,511 --> 00:28:26,651 move away from the credentialing and elite credentialing signals. 431 00:28:26,751 --> 00:28:31,051 And part of that, I think is is the kind of work that you are doing, Hashem, 432 00:28:31,121 --> 00:28:35,741 of as a professor at the University of Oxford for you to send a signal out 433 00:28:35,741 --> 00:28:38,881 to the world saying, and to your own colleagues saying, "This is the kind 434 00:28:38,881 --> 00:28:43,991 of work that we should be doing, that this is our responsibility as citizens, 435 00:28:44,041 --> 00:28:48,831 as benefactors of, the largesse of the public and taxpayer money that we 436 00:28:48,831 --> 00:28:50,461 should be doing this for the world." 437 00:28:50,691 --> 00:28:54,511 But also for the fact that, we are going to be able to identify some 438 00:28:54,511 --> 00:28:58,401 exceptional scientific talent that's going to make the next big discovery. 439 00:28:58,411 --> 00:29:01,471 Think about all the discoveries that we are leaving out on the 440 00:29:01,501 --> 00:29:06,451 table because we've narrowed our lens of who we think is, talented 441 00:29:06,451 --> 00:29:07,901 versus who we think is not talented. 442 00:29:07,951 --> 00:29:12,031 And I think the more we are able to increase that aperture of thinking 443 00:29:12,031 --> 00:29:16,281 about where talent lives and how we can su- support them I think, 444 00:29:16,591 --> 00:29:17,751 science will be better for that. 445 00:29:17,751 --> 00:29:19,111 Society will be better for that. 446 00:29:19,551 --> 00:29:20,091 Absolutely. 447 00:29:20,471 --> 00:29:27,309 Based on your experience with participants from many countries and backgrounds What 448 00:29:27,599 --> 00:29:33,439 qualities consistently predict success that traditional systems often overlook? 449 00:29:36,077 --> 00:29:39,947 I think the biggest quality that I find in the scientific 450 00:29:39,947 --> 00:29:44,667 enterprise and in entrepreneurship is persistence and resilience. 451 00:29:44,727 --> 00:29:46,477 Science is about failure, right? 452 00:29:46,477 --> 00:29:49,127 Science is about failing multiple times. 453 00:29:49,207 --> 00:29:54,537 You cannot, make a discovery or a novel invention first time around. 454 00:29:54,547 --> 00:29:57,447 You have to be resilient to to discovery. 455 00:29:57,447 --> 00:30:02,297 And I find that the most interesting students that I meet and who go 456 00:30:02,297 --> 00:30:06,277 through our programs are the ones who are extraordinarily resilient. 457 00:30:06,337 --> 00:30:07,817 I have a story to share. 458 00:30:07,867 --> 00:30:13,397 One of our scholars Mohammed, who was in Sudan when the war broke, and he joined 459 00:30:13,397 --> 00:30:15,587 our program when the war was erupting. 460 00:30:15,637 --> 00:30:20,127 And, he attended the program while he and his family were basically 461 00:30:20,127 --> 00:30:24,477 moving from Sudan to, to Rwanda, and then finally to the UAE. 462 00:30:24,477 --> 00:30:29,977 And he would just show up every day and was extraordinarily diligent 463 00:30:29,987 --> 00:30:32,847 in working through the program. 464 00:30:32,857 --> 00:30:36,997 A-and after the, program, we hired him as a venture fellow 465 00:30:36,997 --> 00:30:38,297 and a research fellow with us. 466 00:30:38,567 --> 00:30:41,937 And he won the Chevening Scholarship and went and did a master's at 467 00:30:41,937 --> 00:30:43,127 the University of Birmingham. 468 00:30:43,757 --> 00:30:48,077 And I think that's a story of someone who shows extraordinary resilience. 469 00:30:48,077 --> 00:30:52,207 And I think people with extraordinary resilience are the ones who will 470 00:30:52,257 --> 00:30:54,067 really thrive in the future. 471 00:30:54,167 --> 00:30:56,937 I think there is a misconception that science is for, 472 00:30:56,937 --> 00:30:58,437 quote-unquote, smart people. 473 00:30:58,467 --> 00:31:02,977 I find that the most effective scientists tend to be the ones who 474 00:31:03,297 --> 00:31:06,337 are not merely smart in the kind of problem-solving sense of the term, 475 00:31:06,337 --> 00:31:11,647 but are extremely resilient in-- to failure, don't give up very quickly. 476 00:31:11,947 --> 00:31:14,807 And these are the kind of things that I think oftentimes, we don't 477 00:31:14,817 --> 00:31:18,407 measure when we are trying to recruit for high-quality scientific talent. 478 00:31:18,417 --> 00:31:22,657 We look at things like SAT scores or the kind of scores that they have in a test. 479 00:31:22,907 --> 00:31:24,887 That's not really measuring resilience. 480 00:31:24,917 --> 00:31:27,587 And I think resilience matters a lot for being a good scientist. 481 00:31:28,377 --> 00:31:33,298 I want to also cover entrepreneurship innovation, and ask you to share 482 00:31:33,298 --> 00:31:34,508 your experience about that. 483 00:31:35,038 --> 00:31:41,138 And in that regard, many young scientists are curious about en-entrepreneurship, 484 00:31:41,338 --> 00:31:43,668 but have little idea where to start. 485 00:31:44,398 --> 00:31:47,658 Where they have to start and a little bit of advice about that. 486 00:31:49,048 --> 00:31:49,358 Yeah. 487 00:31:49,358 --> 00:31:53,278 I think the kind of landscape has changed dramatically, I 488 00:31:53,278 --> 00:31:54,758 would say, in the last 10 years. 489 00:31:54,778 --> 00:31:59,268 When I was graduating from my PhD people were moving to industry 490 00:31:59,268 --> 00:32:01,468 and doing data science stuff. 491 00:32:01,478 --> 00:32:03,488 Some people were starting, new companies. 492 00:32:03,748 --> 00:32:07,678 I think it has become much more commonplace now for scientists to 493 00:32:07,948 --> 00:32:09,768 start companies for two reasons. 494 00:32:09,768 --> 00:32:15,508 I think the kind of AI boom has really allowed for people with technical training 495 00:32:15,848 --> 00:32:19,918 to go out there and apply a lot of these tools to new applications, right? 496 00:32:19,918 --> 00:32:24,658 Whether that's in healthcare, cybersecurity, education, what have you. 497 00:32:25,028 --> 00:32:28,598 The second is I think university systems unfortunately it's still the kind of elite 498 00:32:28,598 --> 00:32:35,008 university systems that have built these ecosystem of innovation competitions or 499 00:32:35,018 --> 00:32:40,678 accelerators which are embedded inside the university that help scientists translate 500 00:32:40,978 --> 00:32:43,938 the stories to… discoveries to industry. 501 00:32:44,358 --> 00:32:48,938 And so I think for a lot of scientists, my advice in general 502 00:32:48,938 --> 00:32:52,128 is, A, you have an unfair advantage. 503 00:32:52,168 --> 00:32:55,898 Being an entrepreneur, having an unfair advantage helps, and the unfair advantage 504 00:32:55,898 --> 00:33:00,858 you have is that you have a deep expertise in some topic that probably 505 00:33:00,898 --> 00:33:02,968 10 other people understand in the world. 506 00:33:03,018 --> 00:33:07,568 And if that expertise can translate to something that is applicable to 507 00:33:07,568 --> 00:33:11,448 the larger world to society, whether that is through medicine, whether 508 00:33:11,448 --> 00:33:15,038 that is through a scientific tool or a technical tool I think you, you have 509 00:33:15,038 --> 00:33:17,248 a real kind of edge in doing that. 510 00:33:17,298 --> 00:33:20,098 So identifying the problem, I think is the first kind of step. 511 00:33:20,118 --> 00:33:23,678 So when a lot of people particularly those who are in the sciences come and 512 00:33:23,688 --> 00:33:28,268 ask me for advice on entrepreneurship, my first question is: Is there a problem 513 00:33:28,268 --> 00:33:31,728 that really drives you, that, that really that you're really passionate about? 514 00:33:32,088 --> 00:33:34,888 And so I think identifying the problem is key and is step one. 515 00:33:35,298 --> 00:33:41,638 The second is to actually realize that as scientists, we are trained in a 516 00:33:41,638 --> 00:33:47,648 particular mode of thinking that is very beneficial to an entrepreneur, and 517 00:33:47,648 --> 00:33:51,848 that is the kind of scientific style of thinking where you're thinking of a 518 00:33:51,848 --> 00:33:55,628 product or a program as a hypothesis. 519 00:33:55,648 --> 00:33:58,128 And you have a hypothesis, you go run an experiment. 520 00:33:58,448 --> 00:34:01,998 But… and by experiment I mean you go have a bunch of users use your tool, 521 00:34:02,218 --> 00:34:05,878 get some feedback, see what they're saying, and then you fine-tune your 522 00:34:05,878 --> 00:34:08,718 experiment or you fine-tune your product, and then you iterate on it. 523 00:34:08,728 --> 00:34:13,498 And this iterative style of this kind of scientific style of of thinking is 524 00:34:13,498 --> 00:34:15,348 really beneficial in, in entrepreneurship. 525 00:34:15,358 --> 00:34:20,674 In fact the reason I think scientists have an edge over those who might not 526 00:34:20,674 --> 00:34:24,094 think scientifically is that I think a lot of times entrepreneurs it's very easy 527 00:34:24,094 --> 00:34:27,704 for entrepreneurs to get too married to the solution as opposed to the problem. 528 00:34:27,704 --> 00:34:31,574 But as a scientist, we are trained to not get too married to the solution. 529 00:34:31,584 --> 00:34:33,874 We are trained to get really invested in the problem. 530 00:34:34,054 --> 00:34:36,674 The solutions can come in different shapes and forms. 531 00:34:36,764 --> 00:34:40,104 And I think that, that attitude can be very valuable for an 532 00:34:40,134 --> 00:34:41,124 early-stage entrepreneur. 533 00:34:41,994 --> 00:34:42,294 Yeah. 534 00:34:42,334 --> 00:34:45,984 Because I myself, I'm a scientist, and actually I've been thinking 535 00:34:46,004 --> 00:34:52,714 about perhaps setting up a company or bringing an idea to action. 536 00:34:53,314 --> 00:34:54,424 There are two issues here. 537 00:34:54,494 --> 00:34:57,374 One is the use of AI. 538 00:34:57,694 --> 00:35:00,624 So on the one hand, AI is very helpful. 539 00:35:00,674 --> 00:35:02,884 It can do different jobs for you. 540 00:35:02,884 --> 00:35:07,484 You don't perhaps need to hire some people at the beginning, and with, 541 00:35:07,684 --> 00:35:09,764 AI agent, you can do quite a lot. 542 00:35:10,194 --> 00:35:13,984 But at the same time, for exactly the same reason, AI has 543 00:35:13,984 --> 00:35:15,794 made the market very crowded. 544 00:35:16,114 --> 00:35:17,484 So this is one issue. 545 00:35:17,544 --> 00:35:23,374 And the other issue that I would like to again hear your advice on that is that 546 00:35:23,864 --> 00:35:30,464 scientists mostly are very perfectionist, and they don't like to take risk. 547 00:35:30,504 --> 00:35:33,564 They don't know, when is a perfect time. 548 00:35:34,304 --> 00:35:38,594 Perhaps an imperfect is a perfect for, you know- Yeah … putting up a business. 549 00:35:39,034 --> 00:35:42,844 But when to start I really I struggle to, find that point. 550 00:35:42,844 --> 00:35:45,194 So what your advice is for that? 551 00:35:46,164 --> 00:35:49,254 I'm so glad you brought this up because I think this is one of 552 00:35:49,254 --> 00:35:52,374 those kind of personality traits that we as scientists have, right? 553 00:35:52,414 --> 00:35:56,414 We… Before we, i'm sure you've done this, where before you hit publish on 554 00:35:56,414 --> 00:35:58,944 a paper you go through it for a week. 555 00:35:58,954 --> 00:35:58,974 Yeah. 556 00:35:58,984 --> 00:36:02,824 You try to make sure that every single thing is accurate. 557 00:36:02,844 --> 00:36:04,664 And I think, we are rewarded for that, right? 558 00:36:04,664 --> 00:36:07,034 The community rewards you for rigor. 559 00:36:07,424 --> 00:36:12,954 Whereas in entrepreneurship, what matters is whether the thing that you're building 560 00:36:12,964 --> 00:36:15,194 matters to your users and your customers. 561 00:36:15,244 --> 00:36:22,214 And so there you want to think about your, launching a startup as launching 562 00:36:22,214 --> 00:36:25,884 a lab, as opposed to launching a startup as publishing a paper. 563 00:36:25,884 --> 00:36:30,354 Because what you're doing while you're building the product is actually doing the 564 00:36:30,354 --> 00:36:34,594 kind of hidden things that you do in a lab where you are making a lot of mistakes. 565 00:36:34,594 --> 00:36:38,134 You are, building things that might look messy or wrong. 566 00:36:38,524 --> 00:36:40,984 The problem of course is that, you're doing… When you're a 567 00:36:40,984 --> 00:36:43,834 scientist, you're making these mistakes in the privacy of your lab. 568 00:36:44,074 --> 00:36:47,764 When you're doing a startup or a product, you're building that in public. 569 00:36:48,114 --> 00:36:51,924 And one of the things that we focus a lot with our entrepreneurs in, at Equitech 570 00:36:51,924 --> 00:36:56,954 Futures, is to get them to become a com- become comfortable in building in public. 571 00:36:57,324 --> 00:36:59,104 Building in public means that it's gonna be messy. 572 00:36:59,104 --> 00:37:00,504 You are going to make mistakes. 573 00:37:00,514 --> 00:37:01,614 Things are going to break. 574 00:37:01,914 --> 00:37:05,424 But that's just part of the process, and that you have to be be responsive 575 00:37:05,434 --> 00:37:09,044 to that part of the process and not wait till till you have the 576 00:37:09,044 --> 00:37:10,824 perfect product that you can ship. 577 00:37:11,312 --> 00:37:12,502 That's easier said than done. 578 00:37:12,542 --> 00:37:17,012 I suffer from the perfectionism thing too, where I feel embarrassed that, 579 00:37:17,012 --> 00:37:20,232 oh my gosh if I'm gonna put something out there which is not perfectly- 580 00:37:20,242 --> 00:37:22,082 … polished people are gonna judge me. 581 00:37:22,312 --> 00:37:23,972 People are gonna think I'm not rigorous. 582 00:37:24,002 --> 00:37:27,322 And I think that's something that, that, that kind of just comes with practice. 583 00:37:27,412 --> 00:37:30,962 And one of the things that I've learned is that actually people 584 00:37:30,972 --> 00:37:33,302 are quite sympathetic to seeing. 585 00:37:33,312 --> 00:37:38,492 And a- as long as you are open with people saying, "Hey, we are building 586 00:37:38,492 --> 00:37:42,312 things," "Help us figure out, what is working, what is not working," 587 00:37:42,312 --> 00:37:45,192 people are quite sympathetic to the act of building in public. 588 00:37:45,202 --> 00:37:47,992 And so sometimes it is just our own the voice in our own 589 00:37:48,072 --> 00:37:49,572 head that is holding us back. 590 00:37:50,722 --> 00:37:52,602 And the second was about AI. 591 00:37:53,022 --> 00:37:59,252 So as I said in my intro, generally speaking, AI can be, an equalizer and 592 00:37:59,252 --> 00:38:04,192 democratize technology, networking, mentorship, but at the same time it 593 00:38:04,192 --> 00:38:09,492 can be actually a barrier and it can widen the gap widen the inequalities. 594 00:38:09,522 --> 00:38:11,422 So what do you say about that? 595 00:38:13,134 --> 00:38:15,064 I think yes and yes, right? 596 00:38:15,064 --> 00:38:19,394 In the sense that I'm-- I think it has been remarkable to see how the access 597 00:38:19,394 --> 00:38:28,634 to AI tools has made building easier for so many students and en- entrepreneurs. 598 00:38:29,104 --> 00:38:32,954 I think the real kind of gap that we are seeing right now 599 00:38:33,304 --> 00:38:35,654 is, A the fact that, the… 600 00:38:35,714 --> 00:38:42,344 using these AI tools still requires taste and skill that is cultivated 601 00:38:42,374 --> 00:38:44,034 over a long period of time, right? 602 00:38:44,034 --> 00:38:49,134 So I'm sure when you're using an AI tool, you are bringing to it this 603 00:38:49,344 --> 00:38:54,604 wealth of experience that you've had as a scientist as a mentor, and the kind 604 00:38:54,604 --> 00:38:58,104 of questions that you are asking, the kind of issues that you are pursuing 605 00:38:58,454 --> 00:39:03,974 is something that is quite different from, say a student or an individual who 606 00:39:03,974 --> 00:39:08,064 might not have had access to the kind of training and networks that you've been in. 607 00:39:08,374 --> 00:39:10,534 And so I think that's the thing that I really worry about. 608 00:39:10,554 --> 00:39:14,624 Yes, it is going to hyper-charge productivity. 609 00:39:14,634 --> 00:39:19,494 It is already hyper-charging productivity in for a lot of people with access to 610 00:39:19,494 --> 00:39:21,384 a lot of kind of, skills in the past. 611 00:39:21,744 --> 00:39:28,094 I think what we are now barreling towards a future where I worry that people who've 612 00:39:28,094 --> 00:39:32,204 not had that opportunity to build that taste in the kind of problems, build 613 00:39:32,214 --> 00:39:36,414 the kind of skills on how to use these tools effectively, how not to become 614 00:39:36,434 --> 00:39:42,714 too over-reliant on these tools, how to understand these tools as not as as 615 00:39:42,714 --> 00:39:47,424 black boxes or as- magical instruments, but as technological tools which are 616 00:39:47,424 --> 00:39:49,254 very capable but have limitations. 617 00:39:49,534 --> 00:39:54,204 W- when people don't understand those things, I think they then use AI to, 618 00:39:54,234 --> 00:40:01,234 to generate either, glitchy products that people will not use or to generate 619 00:40:01,414 --> 00:40:05,554 either, what people call AI slop, which is something that people just not, 620 00:40:06,404 --> 00:40:08,834 going to find joy or interest in using. 621 00:40:09,194 --> 00:40:11,094 And so I think that's something that I really worry about. 622 00:40:11,104 --> 00:40:15,784 Like, how do we build the infrastructure to building or how do we build an 623 00:40:15,784 --> 00:40:21,064 infrastructure to cultivating good taste in problems, deeper understanding 624 00:40:21,064 --> 00:40:25,104 in problems, making sure that people don't become too cognitively dependent 625 00:40:25,104 --> 00:40:30,404 on these tools as opposed to using these tools for irresponsible and 626 00:40:30,404 --> 00:40:32,964 effective ways to solve harder problems. 627 00:40:34,564 --> 00:40:39,334 Now switching to mentorship, leadership, and positive culture. 628 00:40:40,610 --> 00:40:46,690 How can I become a truly effective mentor, i.e., what are the 629 00:40:46,760 --> 00:40:49,100 characteristics of a good mentor? 630 00:40:49,100 --> 00:40:54,170 Someone inspiring, someone with long-lasting impact on young people. 631 00:40:55,790 --> 00:41:00,620 So to, to answer this question I think if I have to think back to my, to the 632 00:41:00,630 --> 00:41:06,470 mentors who have influenced me the most the mentors who have really shaped me have 633 00:41:06,470 --> 00:41:13,270 been the ones who came to me and believed in me before I saw anything in myself. 634 00:41:13,320 --> 00:41:18,330 So oftentimes mentors are the ones who are going to their mentees at moments of 635 00:41:18,340 --> 00:41:22,960 doubt, at moments where mentees feel like, "Oh, I'm not good enough to apply for this 636 00:41:22,960 --> 00:41:26,930 fellowship," or, "I'm not good enough to apply for this particular program," a-and 637 00:41:26,930 --> 00:41:31,220 say, "No, actually you can." You, you want that push, and the mentor can really 638 00:41:31,250 --> 00:41:36,860 p-provide that push to a mentee to, to take bigger risks, to try bigger things. 639 00:41:36,930 --> 00:41:41,660 A-and that I think ends up being a really profound sort of impact. 640 00:41:41,670 --> 00:41:45,460 That definitely was a profound impact that I had in my life, where mentors 641 00:41:45,540 --> 00:41:49,680 at almost every single career stage that I've had have spoken to me and 642 00:41:49,680 --> 00:41:51,500 said you should be aiming bigger." 643 00:41:51,540 --> 00:41:55,840 And and their confidence in me gave me the courage to try things out. 644 00:41:55,880 --> 00:41:59,860 And so when I am mentoring students I'm always asking, is 645 00:41:59,860 --> 00:42:04,000 this person selling themselves short by not believing themselves? 646 00:42:04,300 --> 00:42:08,640 And can I convince them that, "Hey even if you fail, just try this"? 647 00:42:08,640 --> 00:42:11,580 Because oftentimes what happens is that when they actually try they 648 00:42:11,580 --> 00:42:13,950 go and are exceedingly successful. 649 00:42:13,950 --> 00:42:18,230 And and so yeah, I, I think the best parts of mentorship is to 650 00:42:18,240 --> 00:42:24,220 help people see in themselves what they don't see for themselves. 651 00:42:25,870 --> 00:42:32,130 If you could redesign one aspect of how universities and research institutions 652 00:42:32,230 --> 00:42:37,040 support the students and early career researchers, what would it be? 653 00:42:39,016 --> 00:42:42,766 I think that it is a rewarding the kind of work that you are doing, 654 00:42:42,776 --> 00:42:47,036 Hashem, where you're trying to supporting… you're trying to support 655 00:42:47,046 --> 00:42:48,716 innovators from around the world. 656 00:42:48,726 --> 00:42:52,816 You are doing this I'm sure when you're doing this pre-tenure, your 657 00:42:52,816 --> 00:42:57,746 tenure packet wasn't considering this as as part of your promotion. 658 00:42:57,976 --> 00:43:01,646 It's something that you are doing as a service to the community and and I think 659 00:43:01,646 --> 00:43:07,446 we I think universities need to recognize this as not just, unpaid service to 660 00:43:07,446 --> 00:43:11,206 the community, but this is the things that they should be rewarding, whether 661 00:43:11,206 --> 00:43:15,881 that is something that they reward by making sure this is included or given 662 00:43:15,881 --> 00:43:18,891 the same prestige as as research papers. 663 00:43:18,941 --> 00:43:22,081 I think that, that is one direction that they should really look at. 664 00:43:22,111 --> 00:43:29,091 Increasingly, I think the fact that research is starting to become relatively 665 00:43:29,091 --> 00:43:31,331 democratized using a lot of AI tools. 666 00:43:31,331 --> 00:43:36,251 I think the real value for universities is going to be the kind of mentoring 667 00:43:36,251 --> 00:43:37,631 opportunities that they provide. 668 00:43:37,631 --> 00:43:42,361 So universities, if they want to, continue to to justify their existence, 669 00:43:42,361 --> 00:43:47,031 they need to reward faculty to be better teachers, to be better mentors and 670 00:43:47,031 --> 00:43:52,311 not just be individuals who can write papers or publish very fast and, and 671 00:43:52,311 --> 00:43:53,951 get all the citations that they can. 672 00:43:53,951 --> 00:43:57,991 Because I think that, that bar that metric has really been 673 00:43:57,991 --> 00:43:59,751 disrupted because of AI right now. 674 00:44:00,101 --> 00:44:03,511 And like universities really need to reimagine what kind of incentive 675 00:44:03,511 --> 00:44:09,461 structures we provide because then that's also going to, invite people who 676 00:44:09,471 --> 00:44:14,291 have that dedication to come into that academy and make the academic enterprise 677 00:44:14,391 --> 00:44:17,251 richer more diverse and more impactful. 678 00:44:18,021 --> 00:44:23,151 And so I think, yeah, universities should really look beyond narrow citation metrics 679 00:44:23,191 --> 00:44:26,941 when they are rewarding all kinds of things, whether they're rewarding, faculty 680 00:44:26,941 --> 00:44:30,641 tenure or who they are hiring and who they are giving awards to and so forth. 681 00:44:31,425 --> 00:44:31,615 Yeah. 682 00:44:31,615 --> 00:44:32,355 Thank you so much. 683 00:44:32,835 --> 00:44:36,725 I usually don't talk about my own work, but because you just brought 684 00:44:36,725 --> 00:44:41,045 it up and it's what you said perhaps for some listeners they might not 685 00:44:41,085 --> 00:44:42,965 know what you are referring to. 686 00:44:43,985 --> 00:44:49,135 Like yourself, I grow up … I was born and grow up in a very rural 687 00:44:49,135 --> 00:44:53,485 and poor area in Iran, and I have had a very difficult career path. 688 00:44:54,495 --> 00:44:59,065 And I have seen quite a lot of inequalities, disparities in education 689 00:44:59,105 --> 00:45:03,865 and talented people not becoming successful, as I said, not because 690 00:45:03,935 --> 00:45:09,595 they weren't talented, but because they had no access to education or 691 00:45:09,595 --> 00:45:11,935 opportunities as we have here in European. 692 00:45:11,995 --> 00:45:14,745 And for that reason, I have set up all these things. 693 00:45:14,795 --> 00:45:16,285 There are webinars. 694 00:45:16,285 --> 00:45:19,485 I ask very renowned scientists around the world, and these are freely 695 00:45:19,564 --> 00:45:24,208 accessable to scientists and students in particular from around the world. 696 00:45:24,408 --> 00:45:29,428 We have a mentoring and coaching scheme that we offer free of charge, 697 00:45:29,578 --> 00:45:34,568 a CV or cover letter evaluation or mock interviews, and again, just to 698 00:45:34,578 --> 00:45:36,218 help them to reach what they deserve. 699 00:45:36,268 --> 00:45:37,588 So thank you for that. 700 00:45:38,228 --> 00:45:43,328 Now for the last section, Avilash I would like to just talk a little bit 701 00:45:43,328 --> 00:45:45,138 about, looking ahead to the future. 702 00:45:45,198 --> 00:45:50,238 Which achievements makes you most proud because it convince you that 703 00:45:50,298 --> 00:45:52,808 real impact was being created? 704 00:45:54,950 --> 00:45:55,380 Yeah. 705 00:45:55,430 --> 00:45:59,710 If you let me again talk about a story that, that connected us actually. 706 00:45:59,750 --> 00:46:04,270 One of our Equitech scholars, Kexin Xu was an undergraduate at 707 00:46:04,360 --> 00:46:06,250 Imperial College when she joined us. 708 00:46:06,260 --> 00:46:10,380 And Kexin did not have a background in programming and coding 709 00:46:10,740 --> 00:46:12,030 when she joined the program. 710 00:46:12,030 --> 00:46:15,350 And when she went through our program, she was able to learn about AI. 711 00:46:15,380 --> 00:46:19,090 She was a biologist by training, and she was able to learn a bunch of these 712 00:46:19,090 --> 00:46:22,510 tools and could see the application of these these tools in biology. 713 00:46:22,510 --> 00:46:26,130 And then after she finished the program with us, we hired her as an 714 00:46:26,140 --> 00:46:31,210 Equitech research fellow, where she worked on application of AI tools to 715 00:46:31,480 --> 00:46:35,770 breast cancer research from a massive dataset called the Nightingale dataset. 716 00:46:35,840 --> 00:46:40,820 And I could see the process of someone going from saying, "Oh, maybe I'm 717 00:46:40,820 --> 00:46:46,430 not a AI scientist, maybe I'm not a machine learning person," into 718 00:46:46,450 --> 00:46:50,400 really embracing themselves as an AI scientist and a machine learning person. 719 00:46:50,680 --> 00:46:54,980 And then going and working with you now as a PhD student in really 720 00:46:55,020 --> 00:46:58,230 embracing their identity as an interdisciplinary scientist. 721 00:46:58,550 --> 00:47:01,550 And I think seeing those kinds of successes, and there are many, we 722 00:47:01,550 --> 00:47:04,420 cover a lot of these stories on our on our newsroom on Equitech 723 00:47:04,420 --> 00:47:07,880 Futures, and I encourage people to go look up these examples. 724 00:47:07,880 --> 00:47:11,440 And the reason we also showcase these stories is because I think it's important 725 00:47:11,450 --> 00:47:16,660 for people to see that, that the kind of career trajectories or the skills 726 00:47:16,660 --> 00:47:21,110 that they think are inevitable in them just because they chose biology, 727 00:47:21,750 --> 00:47:25,630 that they cannot do AI in biology, or just because they chose physics, 728 00:47:25,630 --> 00:47:26,940 they cannot study something else. 729 00:47:27,200 --> 00:47:28,940 That, that's just a false narrative, right? 730 00:47:28,940 --> 00:47:34,030 The idea that you can grow and that you can be interdisciplinary 731 00:47:34,030 --> 00:47:35,220 and that you can take risks. 732 00:47:35,250 --> 00:47:38,720 And I think the thing that I'm proudest of most in, in Equitech Futures is 733 00:47:38,960 --> 00:47:41,860 seeing the number of students who go through our programs and are able to 734 00:47:41,860 --> 00:47:46,590 make that pivot, and it gives them that confidence to go try new things 735 00:47:46,640 --> 00:47:49,410 to try, building careers where… 736 00:47:49,670 --> 00:47:53,160 which are slightly riskier, which are in the fringes in some ways. 737 00:47:53,450 --> 00:47:55,590 But that's how the frontier gets pushed, right? 738 00:47:55,620 --> 00:47:57,910 That's how new discoveries come. 739 00:47:57,990 --> 00:48:01,690 New discoveries always come from the boundaries between fields. 740 00:48:01,730 --> 00:48:05,680 And so that really convinced me when I saw lots of students from our programs 741 00:48:05,980 --> 00:48:10,360 discover that that interdisciplinary lens of thinking, and then moving 742 00:48:10,360 --> 00:48:13,930 forward and taking the risks to, to applying those things in their lives. 743 00:48:14,760 --> 00:48:15,110 Thank you. 744 00:48:15,150 --> 00:48:18,410 I must say Keshan is really a pleasure to work with. 745 00:48:18,420 --> 00:48:23,530 She's very talented and yeah I'm sure about her great work in the future. 746 00:48:23,530 --> 00:48:24,980 So she's a rising star for sure, yeah. 747 00:48:24,980 --> 00:48:27,600 What gives you optimism about next generation? 748 00:48:29,230 --> 00:48:34,690 I just think that they're fearless in a way that I I don't think that 749 00:48:34,800 --> 00:48:39,890 that o- our generation, my generation particularly I graduated college in 2008. 750 00:48:39,940 --> 00:48:44,640 I think there was there was the kind of, looking at a linear pathway, right? 751 00:48:44,670 --> 00:48:47,820 As an academic, the linear pathway that, that I was looking at was 752 00:48:48,080 --> 00:48:51,520 you finish your PhD, you get a, faculty position, so on and so forth. 753 00:48:51,930 --> 00:48:55,600 I think this new generation is so much more willing to take risks 754 00:48:55,650 --> 00:49:00,190 and trying to experiment with different career trajectories. 755 00:49:00,540 --> 00:49:06,980 They really care about not just, having a career path, but figuring out how their 756 00:49:06,980 --> 00:49:08,870 careers have an impact in the world. 757 00:49:08,920 --> 00:49:15,600 And they're truly driven by genuine, sincere desire to make the lives of 758 00:49:15,690 --> 00:49:20,230 their peers, their communities better, and that really gives me hope, right? 759 00:49:20,230 --> 00:49:24,090 If you just look at the news all the time, you might get the impression 760 00:49:24,090 --> 00:49:25,390 that the future is very bleak. 761 00:49:25,390 --> 00:49:29,260 Everyone is very depressed and and anxious about the future. 762 00:49:29,560 --> 00:49:33,530 But I think when you talk to a lot of young people, yes, the anxiety exists, 763 00:49:33,550 --> 00:49:39,820 but there also is a kind of unbending optimism a kind of desire to say the world 764 00:49:39,820 --> 00:49:44,530 doesn't have to be a particular way and that we can shape it in the, in, in the 765 00:49:44,530 --> 00:49:46,590 shape of what we want to see in the world. 766 00:49:46,860 --> 00:49:49,670 And a lot of young people want to do that. 767 00:49:49,690 --> 00:49:52,950 They want to, pick themselves up by the bootstraps and get to work. 768 00:49:52,970 --> 00:49:54,660 And that's the thing that really inspires me. 769 00:49:54,740 --> 00:49:58,800 And the more opportunities we provide, the more pathways we provide for these 770 00:49:58,800 --> 00:50:04,760 young people to then go and and have that impact in the world I think we 771 00:50:04,890 --> 00:50:08,670 as a society, and we as a scientific community will be will be richer for that. 772 00:50:10,040 --> 00:50:15,950 Where do you see or where do you like to see future of Equitech Futures or 773 00:50:15,950 --> 00:50:21,250 more broadly speaking, the movement for equitable access to science and 774 00:50:21,270 --> 00:50:25,990 technology that you started in next few years, perhaps next five years? 775 00:50:27,438 --> 00:50:31,368 For Equitech Futures, we would really like to build more tools and and 776 00:50:31,368 --> 00:50:35,888 mechanisms through which more people can participate in the process. 777 00:50:35,968 --> 00:50:38,848 As I-- the statistics are really alarming, right? 778 00:50:38,888 --> 00:50:42,048 There are going to be about one point five billion young people 779 00:50:42,048 --> 00:50:43,468 in the next five to ten years. 780 00:50:43,578 --> 00:50:47,408 The number of projected jobs are around four hundred million people. 781 00:50:47,458 --> 00:50:51,908 So there's a massive gap in in the workforce that needs to be solved. 782 00:50:51,968 --> 00:50:55,228 And that's something that, that we… I really want to figure out how to solve. 783 00:50:55,228 --> 00:50:59,818 And one way to solve that is not just access to skills, but access to networks 784 00:50:59,818 --> 00:51:03,908 and capital for entrepreneurs in different parts of the world to start 785 00:51:03,918 --> 00:51:08,238 companies where they can hire other people and activate these economies. 786 00:51:08,278 --> 00:51:08,518 Right? 787 00:51:08,518 --> 00:51:11,628 So I think what we have seen in the past fifteen years is a concentration 788 00:51:11,628 --> 00:51:16,258 of technology innovation in very small a handful of cities in the 789 00:51:16,258 --> 00:51:20,418 world, whether that is, Silicon Valley, New York, London, Bangalore. 790 00:51:20,448 --> 00:51:25,248 And, in the next five to ten years, my hope would be that this geography of 791 00:51:25,248 --> 00:51:29,578 concentration of of innovation really diversifies and that, you don't need 792 00:51:29,578 --> 00:51:33,828 to be a Silicon-- in Silicon Valley to found the next great AI company. 793 00:51:33,828 --> 00:51:38,378 You don't need to be in London to launch the next big biotech company. 794 00:51:38,428 --> 00:51:42,848 And and, the vast majority of the one point five, one point two to 795 00:51:42,848 --> 00:51:45,968 one point five b-b-billion young people are going to be in the 796 00:51:45,968 --> 00:51:47,588 African continent and in South Asia. 797 00:51:47,898 --> 00:51:51,438 Not all of them are going to be able to attend Oxfords and Cambridges 798 00:51:51,438 --> 00:51:52,098 and Stanfords of the world. 799 00:51:52,438 --> 00:51:56,318 So we would really like to figure out how can we as an institution at Equitech 800 00:51:56,318 --> 00:52:02,628 Futures help these emerging innovators from around the world to really get 801 00:52:02,628 --> 00:52:04,488 their re-realize their potential. 802 00:52:04,808 --> 00:52:07,218 And that's not just through skills or mentorship. 803 00:52:07,248 --> 00:52:10,368 That is through, supporting these networks giving them access to 804 00:52:10,368 --> 00:52:14,328 opportunities that are-- that they might not be aware of and which is why 805 00:52:14,328 --> 00:52:16,858 I'll put a pl-plug for Futures Hub. 806 00:52:16,918 --> 00:52:20,908 Go check out futureshub.com, which is a new platform we are launching 807 00:52:20,908 --> 00:52:24,808 to make these networks and learning opportunities more accessible 808 00:52:24,868 --> 00:52:26,428 to, to people around the world. 809 00:52:28,048 --> 00:52:33,008 And finally, if you had one message for a talented student or 810 00:52:33,348 --> 00:52:37,548 early career researcher who feels overlooked, what would it be? 811 00:52:39,762 --> 00:52:43,352 I would say do not undersell yourself. 812 00:52:43,482 --> 00:52:46,932 think that you are not enough. 813 00:52:46,982 --> 00:52:47,822 You are enough. 814 00:52:47,842 --> 00:52:52,122 You have the potential to, to try and do incredible things. 815 00:52:52,262 --> 00:52:54,502 Go find, search for that opportunity. 816 00:52:54,512 --> 00:52:55,712 Go find that mentor. 817 00:52:56,002 --> 00:52:57,372 Reach out to people. 818 00:52:57,402 --> 00:53:00,552 You'd be surprised at how much people want to help. 819 00:53:00,662 --> 00:53:04,452 When you go reach out to people for help and you're able to take that 820 00:53:04,452 --> 00:53:08,922 help I'm sure new doors will open up and new opportunities will open up. 821 00:53:08,972 --> 00:53:11,242 And it's that process that really, definitely brought me as to 822 00:53:11,242 --> 00:53:12,362 where I am, and I'm sure, Hashem, 823 00:53:14,502 --> 00:53:18,172 it's, it was reaching out to mentors and other people who made that happen. 824 00:53:18,342 --> 00:53:19,002 So reach out. 825 00:53:19,012 --> 00:53:22,262 I think reaching out you'd be surprised how many people would be willing to help 826 00:53:22,302 --> 00:53:24,232 and help you achieve your ambitions. 827 00:53:24,342 --> 00:53:26,662 So don't under, undersell yourself, and ask for help, 828 00:53:26,672 --> 00:53:27,712 are the two things I would say. 829 00:53:28,392 --> 00:53:28,742 Thank you. 830 00:53:28,742 --> 00:53:29,312 Great message. 831 00:53:29,632 --> 00:53:33,172 Abhilash, is there any other message or anything that I haven't 832 00:53:33,172 --> 00:53:35,952 covered in my questions and you would like to finish up with? 833 00:53:37,392 --> 00:53:37,702 No. 834 00:53:37,702 --> 00:53:40,532 I just want to thank you again for inviting me to 835 00:53:40,532 --> 00:53:42,402 this wonderful conversation. 836 00:53:42,412 --> 00:53:45,372 I really enjoyed this conversation, and I want to thank you for 837 00:53:45,372 --> 00:53:47,092 what you are doing, Hashem. 838 00:53:47,112 --> 00:53:51,992 And just emphasize to your listeners that this, and both … And I'm sure there 839 00:53:51,992 --> 00:53:56,252 are some academic listeners, faculty at universities who are listening to you. 840 00:53:56,302 --> 00:54:00,522 And I hope they will equally go out and be mentors to students in their 841 00:54:00,802 --> 00:54:05,432 networks and communities because this is the way in which we give back. 842 00:54:05,442 --> 00:54:06,722 A lot has been given to us. 843 00:54:06,742 --> 00:54:09,372 We we give back using this. 844 00:54:09,422 --> 00:54:13,202 And and this is not just from the generosity of our hearts, right? 845 00:54:13,222 --> 00:54:15,122 It is one of the most meaningful things I do. 846 00:54:15,372 --> 00:54:17,102 I'm extremely proud of what I do. 847 00:54:17,332 --> 00:54:21,002 But I also recognize that this is the way in which scientific progress is 848 00:54:21,022 --> 00:54:23,862 going to happen in the next 10, 20 years. 849 00:54:23,902 --> 00:54:27,702 So it's really an exciting time to be a scientist. 850 00:54:27,732 --> 00:54:32,102 And the way to, to do that is by enabling more scientists to enter the field. 851 00:54:32,422 --> 00:54:32,922 So thank you. 852 00:54:33,492 --> 00:54:34,482 Thank you so much, Abhilash. 853 00:54:34,482 --> 00:54:36,052 It was great having you on board. 854 00:54:36,052 --> 00:54:41,612 I really enjoyed talking to you, and hats off to the great work that you guys do. 855 00:54:41,662 --> 00:54:46,142 And I hope my listeners also enjoyed as much as I did. 856 00:54:46,152 --> 00:54:49,942 And I hope to see them again in next episode.