1 00:00:02,680 --> 00:00:05,560 Speaker 1: Welcome to the Business of Tech powered by two Degrees Business, 2 00:00:05,600 --> 00:00:09,080 Speaker 1: where we dig into the forces shaping the future of technology, 3 00:00:09,240 --> 00:00:13,880 Speaker 1: innovation and the digital economy. If you missed last week's episode, 4 00:00:13,880 --> 00:00:16,280 Speaker 1: boy it was a good one. One of our best 5 00:00:16,320 --> 00:00:20,280 Speaker 1: grating episodes to date. It's all about the AWS debarcle 6 00:00:20,400 --> 00:00:24,560 Speaker 1: around the launch of their data center region in Auckland. 7 00:00:24,720 --> 00:00:26,600 Speaker 1: I'll put a link to it in the show notes. 8 00:00:27,160 --> 00:00:30,320 Speaker 1: Definitely worth the listen anyway. I'm Peter Griffin and today 9 00:00:30,520 --> 00:00:33,839 Speaker 1: I'm talking to a leading figure from Australia science sector 10 00:00:33,960 --> 00:00:37,640 Speaker 1: about how the country is reshaping its science and innovation 11 00:00:37,840 --> 00:00:43,480 Speaker 1: efforts based around advanced technologies like quantum computing, artificial intelligence, 12 00:00:43,960 --> 00:00:48,839 Speaker 1: clean tech and advance manufacturing. Doctor Kathy Foley has a 13 00:00:48,880 --> 00:00:54,600 Speaker 1: career spanning over forty years at CSIRO, the Commonwealth Scientific 14 00:00:54,680 --> 00:00:59,520 Speaker 1: and Industrial Research Organization. She started as a research scientist 15 00:00:59,640 --> 00:01:03,840 Speaker 1: and a board member of CSIRO. Along the way, she 16 00:01:04,000 --> 00:01:07,560 Speaker 1: helped come up with quantum based technology that allowed the 17 00:01:07,600 --> 00:01:12,680 Speaker 1: mining industry to identify mineral deposits deep underground. That was 18 00:01:12,720 --> 00:01:15,920 Speaker 1: a real game changer for the mining sector. Kathy also 19 00:01:16,000 --> 00:01:20,040 Speaker 1: served as Australia's Chief Scientists during the Scott Morrison government 20 00:01:20,480 --> 00:01:23,639 Speaker 1: and then part of the Anthony Albanesi government as well. 21 00:01:24,200 --> 00:01:27,760 Speaker 1: She's seen as a central figure in bringing some cohesion 22 00:01:27,840 --> 00:01:32,240 Speaker 1: to Australia's fragmented efforts in quantum computing, to the extent 23 00:01:32,280 --> 00:01:35,160 Speaker 1: that Australia is now a significant player in that area 24 00:01:35,200 --> 00:01:39,400 Speaker 1: of tech, with around fifty spin off companies, including PSI Quantum, 25 00:01:39,480 --> 00:01:43,080 Speaker 1: which has received state and federal investment to the tune 26 00:01:43,080 --> 00:01:46,360 Speaker 1: of around a billion dollars. It's setting out to build 27 00:01:46,440 --> 00:01:50,480 Speaker 1: a functional quantum computer in quite a short time frame. 28 00:01:51,000 --> 00:01:55,080 Speaker 1: Kathy offered some unique insights into how Australia turned scientific 29 00:01:55,120 --> 00:01:59,960 Speaker 1: breakthroughs like the technology underpinning Wi Fi in quantum sense, 30 00:02:00,360 --> 00:02:05,880 Speaker 1: into multi billion dollar industries, leveraging government strategy, standards and 31 00:02:06,120 --> 00:02:10,000 Speaker 1: entrepreneurial thinking. There are some hard won lessons from Australia 32 00:02:10,040 --> 00:02:13,120 Speaker 1: for US as we grapple with scaling up our own 33 00:02:13,400 --> 00:02:17,560 Speaker 1: tech sector, breaking down silos and research, and unlocking the 34 00:02:17,680 --> 00:02:21,320 Speaker 1: value in innovation. Kathy shares what worked across the Tasman 35 00:02:21,440 --> 00:02:25,480 Speaker 1: from building global supply chain niches to evolving the culture 36 00:02:25,480 --> 00:02:29,639 Speaker 1: between academia and industry, and addresses the roadmap New Zealand 37 00:02:29,639 --> 00:02:33,280 Speaker 1: can use to punch above its weight and feels like 38 00:02:33,400 --> 00:02:36,840 Speaker 1: quantum AI and clean tech. So here's Kathy Foley, who 39 00:02:36,880 --> 00:02:39,120 Speaker 1: I caught up with recently when she paid a visit 40 00:02:39,240 --> 00:02:47,800 Speaker 1: to Wellington. Kathy Foley, Welcome to the Business of Tech. 41 00:02:47,880 --> 00:02:50,040 Speaker 1: Thanks so much for coming on. Great to see you 42 00:02:50,240 --> 00:02:51,320 Speaker 1: in New Zealand. 43 00:02:51,440 --> 00:02:54,720 Speaker 2: It's wonderful to be here. Actually really enjoyed just flying 44 00:02:54,720 --> 00:02:55,359 Speaker 2: in last night. 45 00:02:55,480 --> 00:03:00,680 Speaker 1: You're visiting DoD Wall's people here. Robinson Research Institution also 46 00:03:01,040 --> 00:03:04,600 Speaker 1: involved in you were the Chief Science Advisor for four 47 00:03:04,720 --> 00:03:08,480 Speaker 1: years and spanned two Australian governments Scott Morrison and then 48 00:03:08,800 --> 00:03:13,079 Speaker 1: Anthony Albanesi administration. So that would be interesting to the 49 00:03:13,120 --> 00:03:16,240 Speaker 1: political elements of science funding and that, so maybe we 50 00:03:16,280 --> 00:03:19,440 Speaker 1: can touch on that. But really, Keen, nineteen eighty five 51 00:03:19,480 --> 00:03:23,320 Speaker 1: you joined CSIROS. That's a forty year career at CSIRO, 52 00:03:23,520 --> 00:03:27,440 Speaker 1: this incredible organization at the center of science in Australia, 53 00:03:28,320 --> 00:03:31,080 Speaker 1: and you were a researcher before that as well, have 54 00:03:31,200 --> 00:03:34,359 Speaker 1: done everything from fundamental research through to you were a 55 00:03:34,400 --> 00:03:38,440 Speaker 1: chief scientist off CSIRO and now on the board off IT. 56 00:03:38,520 --> 00:03:41,440 Speaker 1: It take us back to your early days of science. 57 00:03:41,440 --> 00:03:44,040 Speaker 1: What got you into science and the sort of area 58 00:03:44,040 --> 00:03:46,480 Speaker 1: that you sort of specialized in early on. 59 00:03:46,680 --> 00:03:48,960 Speaker 2: Well, I guess I've always been interested in science, so 60 00:03:49,800 --> 00:03:52,520 Speaker 2: just personally, I'm not good at spelling in English and 61 00:03:52,520 --> 00:03:55,120 Speaker 2: all the sorts of things that young girls are meant 62 00:03:55,160 --> 00:03:57,520 Speaker 2: to be, especially coming from a Catholic comment school. So 63 00:03:58,040 --> 00:04:02,360 Speaker 2: science was my happy place, along with math, and I 64 00:04:02,400 --> 00:04:05,400 Speaker 2: just found it. I was encouraged by teachers at school 65 00:04:05,600 --> 00:04:07,640 Speaker 2: and always thought it'd be great to be a scientist, 66 00:04:07,760 --> 00:04:11,440 Speaker 2: but not knowing any because I come from a middle 67 00:04:11,440 --> 00:04:14,400 Speaker 2: class professional family. My dad was an accountant, my mum 68 00:04:14,440 --> 00:04:17,679 Speaker 2: was an architect, so back in the sixties and seventies 69 00:04:17,720 --> 00:04:21,320 Speaker 2: that was pretty unusual. So came from a pretty privileged background, 70 00:04:21,360 --> 00:04:24,560 Speaker 2: but I didn't know science. They all thought I was 71 00:04:24,600 --> 00:04:26,920 Speaker 2: a bit weird and I was going to be a 72 00:04:26,920 --> 00:04:29,000 Speaker 2: school teacher. But when I was at university, I was 73 00:04:29,080 --> 00:04:33,000 Speaker 2: really encouraged and ended up doing this sorts of things 74 00:04:33,040 --> 00:04:35,800 Speaker 2: to do honors year, won a scholarship, did a PhD. 75 00:04:36,200 --> 00:04:38,680 Speaker 2: I applied for a job in the newspaper and got 76 00:04:38,720 --> 00:04:41,000 Speaker 2: one at CSIRO. Was what would be called a post doc, 77 00:04:41,120 --> 00:04:44,279 Speaker 2: was called research fellow. It was a three year job 78 00:04:44,320 --> 00:04:46,880 Speaker 2: and then eventually it was extended, and then I applied 79 00:04:46,920 --> 00:04:49,720 Speaker 2: for an indefinite appointment in CSIRO, which by the way, 80 00:04:49,760 --> 00:04:51,720 Speaker 2: I got when I was seven months pregnant back in 81 00:04:51,800 --> 00:04:54,760 Speaker 2: nineteen eighty nine, which is unheard of, and that having 82 00:04:54,800 --> 00:04:56,760 Speaker 2: a secure job meant that I was able to really 83 00:04:56,800 --> 00:04:57,520 Speaker 2: pursue a career. 84 00:04:57,920 --> 00:05:01,000 Speaker 1: And what was your main research focus you joined CSRO. 85 00:05:01,360 --> 00:05:03,920 Speaker 2: So when I started CSRO is actually working on amorphous 86 00:05:03,960 --> 00:05:08,440 Speaker 2: metals and magnetism. I had done my PhD in night 87 00:05:08,480 --> 00:05:13,360 Speaker 2: Tried semiconductors. Now night tried semiconductors are the materials that 88 00:05:13,400 --> 00:05:15,359 Speaker 2: are in white light emitting diodes. And when I was 89 00:05:15,400 --> 00:05:17,200 Speaker 2: doing that work, I was one of the first researchers 90 00:05:17,240 --> 00:05:20,680 Speaker 2: working on it, doing very early fundamental work, and that 91 00:05:20,760 --> 00:05:23,320 Speaker 2: eventually led to other people published papers. 92 00:05:23,360 --> 00:05:24,800 Speaker 3: Other people in Japan. 93 00:05:24,600 --> 00:05:27,040 Speaker 2: Took it up, and thank goodness, we've got white light 94 00:05:27,080 --> 00:05:29,440 Speaker 2: emitting diodes now because they're big energy save us. 95 00:05:29,480 --> 00:05:33,200 Speaker 1: In the eighties here those opto electronics. You're working on 96 00:05:33,360 --> 00:05:37,000 Speaker 1: things that go into bicodes, your blu ray players. 97 00:05:37,320 --> 00:05:39,159 Speaker 3: So well that they were things where that. 98 00:05:41,120 --> 00:05:44,320 Speaker 2: The applications of something like a white a light emitting 99 00:05:44,360 --> 00:05:48,000 Speaker 2: diode and the whole photonics that was really critical. And 100 00:05:48,040 --> 00:05:50,480 Speaker 2: I suppose the thing which was interesting was I was 101 00:05:50,520 --> 00:05:54,200 Speaker 2: interested in solid state and then when I went to CSRO, 102 00:05:54,400 --> 00:05:57,720 Speaker 2: I worked in in magnetism and then in eighty six 103 00:05:57,839 --> 00:06:01,920 Speaker 2: eighty seven there was a discovery ofhigh temperature superconductive so 104 00:06:02,000 --> 00:06:04,840 Speaker 2: I was selected to join a team to work on 105 00:06:04,960 --> 00:06:09,920 Speaker 2: developing the material making devices and from that took very 106 00:06:09,960 --> 00:06:12,680 Speaker 2: new discovery which was done of course in other countries, 107 00:06:13,080 --> 00:06:15,359 Speaker 2: but got the Australian version of it. We got to 108 00:06:15,400 --> 00:06:18,400 Speaker 2: a point where we developed a device that can detect 109 00:06:18,560 --> 00:06:21,440 Speaker 2: very small magnetic fields and that can be used from 110 00:06:21,480 --> 00:06:24,839 Speaker 2: anything from measuring your heart or your brain through to 111 00:06:25,480 --> 00:06:28,680 Speaker 2: eventually mineral expiration, which is where we commercialize the system. 112 00:06:28,760 --> 00:06:33,560 Speaker 1: Oh yeah, and obviously Australia's ground zero for that sort 113 00:06:33,600 --> 00:06:35,919 Speaker 1: of stuff. So Kathy, take us through that. How you 114 00:06:35,960 --> 00:06:37,800 Speaker 1: do that? How you can sort of basically see through 115 00:06:37,800 --> 00:06:41,599 Speaker 1: the Earth's crust using these super conducting sensors. 116 00:06:41,760 --> 00:06:45,560 Speaker 2: So a superconducting sensor just measures magnetic fields, and we 117 00:06:45,600 --> 00:06:48,320 Speaker 2: forget we liven on a big bar magnet the earth. 118 00:06:48,480 --> 00:06:51,400 Speaker 2: So North and South Pole, which everyone's familiar with. What 119 00:06:51,880 --> 00:06:54,120 Speaker 2: we were doing was at that time to working with 120 00:06:54,160 --> 00:06:59,440 Speaker 2: PHP and originally we were developing a device to detect 121 00:06:59,560 --> 00:07:01,839 Speaker 2: defect in steel because at that stage It was also 122 00:07:01,920 --> 00:07:06,080 Speaker 2: still manufactured before they spun it out to bloscope, and 123 00:07:06,120 --> 00:07:10,360 Speaker 2: we detected with a very preliminary device. It was pretty 124 00:07:10,600 --> 00:07:13,360 Speaker 2: one of the first squid devices made using this high 125 00:07:13,360 --> 00:07:16,280 Speaker 2: temperature material. And high temperature I should say it means 126 00:07:16,320 --> 00:07:19,560 Speaker 2: it was cool with liquid nitrogen, not liquid helium, so 127 00:07:19,680 --> 00:07:23,480 Speaker 2: minus two hundred degrees it operatesor BHP got us to 128 00:07:23,720 --> 00:07:26,720 Speaker 2: present that to their annual review of all their research 129 00:07:26,800 --> 00:07:29,400 Speaker 2: they did within the company back then in the late 130 00:07:29,680 --> 00:07:33,880 Speaker 2: late nineteen eighties, and they said, oh, this is really interesting. 131 00:07:33,920 --> 00:07:35,840 Speaker 2: We've been trying to get one of these devices to 132 00:07:35,880 --> 00:07:39,720 Speaker 2: work for mineral expiration. And the idea being that if 133 00:07:39,760 --> 00:07:42,840 Speaker 2: you put a big loop of wire on the top 134 00:07:42,880 --> 00:07:45,640 Speaker 2: of the surface of the earth, pulse a current, and 135 00:07:45,640 --> 00:07:48,560 Speaker 2: when you pulse the current through a wire, it creates 136 00:07:48,800 --> 00:07:53,320 Speaker 2: Eddy currents in everything, and then those Eddie currents have 137 00:07:53,400 --> 00:07:58,440 Speaker 2: their own magnetic field, and when you turn their current 138 00:07:59,120 --> 00:08:02,960 Speaker 2: pulse it the current happens in the Eddy current happens, 139 00:08:02,960 --> 00:08:05,320 Speaker 2: and if there's a conductor or all body, and then 140 00:08:05,360 --> 00:08:07,520 Speaker 2: it dies away. And what we were able to do 141 00:08:07,760 --> 00:08:11,240 Speaker 2: was use the magnetic sensor to detect that dying Eddy 142 00:08:11,280 --> 00:08:15,560 Speaker 2: current in an all body and how slowly it died away, 143 00:08:15,640 --> 00:08:18,200 Speaker 2: gave you an idea of how deep it was and 144 00:08:18,320 --> 00:08:21,360 Speaker 2: also what the quality of it was, and you could 145 00:08:21,520 --> 00:08:23,440 Speaker 2: move this across the top of the Earth and be 146 00:08:23,480 --> 00:08:26,280 Speaker 2: able to map out up to two kilometers below the 147 00:08:26,280 --> 00:08:28,080 Speaker 2: earth in some cases not always. 148 00:08:28,440 --> 00:08:29,920 Speaker 3: But the other thing that's really important is. 149 00:08:29,840 --> 00:08:33,720 Speaker 2: Australia got that old red soil, which everyone knows that is. 150 00:08:33,800 --> 00:08:36,600 Speaker 3: Terrible for mineral expiration from the surface. 151 00:08:36,280 --> 00:08:39,480 Speaker 2: Because it's like having an RS screen there, so you 152 00:08:39,520 --> 00:08:43,319 Speaker 2: can't it's very conducting. They call it a conducting overburden, 153 00:08:44,080 --> 00:08:47,040 Speaker 2: and so these systems could see through that because of 154 00:08:47,080 --> 00:08:51,800 Speaker 2: the we were measuring the magnetic field directly, as opposed 155 00:08:51,840 --> 00:08:55,640 Speaker 2: to other techniques which measured the variation of the magnetic 156 00:08:55,640 --> 00:08:58,440 Speaker 2: field with time, and they just screwed up with everything 157 00:08:58,440 --> 00:09:01,079 Speaker 2: that was in the environment. And as a consequence, we're 158 00:09:01,120 --> 00:09:03,240 Speaker 2: able to see things which couldn't be seen previously. 159 00:09:03,480 --> 00:09:07,520 Speaker 1: And you know that led to the mining companies having 160 00:09:07,520 --> 00:09:11,160 Speaker 1: the ability to much more easily see, Okay, there are deposits, 161 00:09:11,160 --> 00:09:12,920 Speaker 1: they might be quite deep, and there's a lot of 162 00:09:12,920 --> 00:09:16,480 Speaker 1: really deep deep mining in Australia, but they could actually 163 00:09:16,559 --> 00:09:19,800 Speaker 1: identify it, and so in terms of speeding up the 164 00:09:19,840 --> 00:09:23,800 Speaker 1: discovery of mineral resources and there I mean that created 165 00:09:23,840 --> 00:09:25,120 Speaker 1: billions of dollars in value. 166 00:09:25,360 --> 00:09:28,719 Speaker 2: Yeah, So to be honest, some of our work, you 167 00:09:28,760 --> 00:09:31,040 Speaker 2: know how a mining industry, like any industry, has its 168 00:09:31,080 --> 00:09:33,200 Speaker 2: high as and lone and when it was in a 169 00:09:33,280 --> 00:09:35,480 Speaker 2: low we actually started doing some of our research with 170 00:09:35,840 --> 00:09:40,960 Speaker 2: Canadian mining companies. And there's a company back then which 171 00:09:41,000 --> 00:09:43,240 Speaker 2: has changed its name multiple times. It probably doesn't even 172 00:09:43,280 --> 00:09:48,240 Speaker 2: exist anymore. But up in the Raglan in the Polar region, 173 00:09:49,320 --> 00:09:51,880 Speaker 2: they got to a point where they're looking for nickel 174 00:09:51,920 --> 00:09:56,720 Speaker 2: sulphides and they reduced their exploration costs by about thirty 175 00:09:56,720 --> 00:10:01,280 Speaker 2: percent because they could go through and get the shape 176 00:10:01,480 --> 00:10:04,400 Speaker 2: and the depth and then be able to drill holes 177 00:10:04,440 --> 00:10:06,839 Speaker 2: to get know where it was. Because usually go through 178 00:10:06,840 --> 00:10:09,480 Speaker 2: into a map, then you go through and do drilling, 179 00:10:10,040 --> 00:10:12,240 Speaker 2: and the drilling is very expensive and quite often the 180 00:10:12,320 --> 00:10:15,280 Speaker 2: drill holes tell you nothing. But they were able to 181 00:10:15,320 --> 00:10:17,280 Speaker 2: every time get it right in the center of where 182 00:10:17,280 --> 00:10:19,560 Speaker 2: they needed to find the order posit, and it meant 183 00:10:19,559 --> 00:10:21,320 Speaker 2: they could get into mines much faster. 184 00:10:21,720 --> 00:10:22,839 Speaker 3: An example happening. 185 00:10:22,559 --> 00:10:27,080 Speaker 2: With BHP with a silver mine up in Cannington in Queensland, 186 00:10:27,200 --> 00:10:30,000 Speaker 2: and they again they had this was We didn't discover 187 00:10:30,080 --> 00:10:32,120 Speaker 2: that mine, but we were just used as a trial 188 00:10:32,200 --> 00:10:35,720 Speaker 2: and they thought it was too that it was two 189 00:10:35,840 --> 00:10:40,040 Speaker 2: separate loads or all bodies next to each other, and 190 00:10:40,320 --> 00:10:43,240 Speaker 2: they were about to drill in between them. No, sorry, 191 00:10:43,240 --> 00:10:44,960 Speaker 2: they thought it was a single load. I'm not going 192 00:10:45,000 --> 00:10:46,880 Speaker 2: to drill down the middle. But we showed it was 193 00:10:46,920 --> 00:10:49,439 Speaker 2: two loads, and if they drilled, they would have gone 194 00:10:49,520 --> 00:10:52,839 Speaker 2: right through the middle of it and that would have missed. 195 00:10:52,600 --> 00:10:53,160 Speaker 3: Both of them. 196 00:10:53,440 --> 00:10:56,440 Speaker 2: And because they said let's just move it a certain distance, 197 00:10:56,520 --> 00:10:59,400 Speaker 2: I went through the middle of the of the silver deposit. 198 00:11:00,000 --> 00:11:01,560 Speaker 2: It meant that they found it was a really good 199 00:11:01,600 --> 00:11:04,800 Speaker 2: silver deposit. They're able to delineate it really carefully just 200 00:11:04,880 --> 00:11:08,680 Speaker 2: with that system, and it brought the mine on site 201 00:11:09,080 --> 00:11:13,280 Speaker 2: eighteen months early. And back in their nineties everyone forgets about. 202 00:11:13,280 --> 00:11:16,720 Speaker 2: The mining companies had difficulties. They invested a lot into 203 00:11:16,800 --> 00:11:20,680 Speaker 2: copper in Chile and BHP wasn't doing very well. The 204 00:11:20,720 --> 00:11:24,000 Speaker 2: first shipment of Cannington silver from that mine, which we 205 00:11:24,040 --> 00:11:28,240 Speaker 2: help bring online eighteen months early, I paid their salary 206 00:11:28,240 --> 00:11:28,920 Speaker 2: bill one month. 207 00:11:29,240 --> 00:11:32,480 Speaker 3: So you know, these things have a flow on effect. 208 00:11:32,520 --> 00:11:35,559 Speaker 2: Where a technology that started with me playing around with 209 00:11:35,600 --> 00:11:38,800 Speaker 2: single grain boundary doing fundamental work led to know, really 210 00:11:39,480 --> 00:11:43,800 Speaker 2: supporting a company to be financially viable in a downtime, 211 00:11:43,880 --> 00:11:46,520 Speaker 2: helping things come online fast. Now got a life of 212 00:11:46,520 --> 00:11:50,320 Speaker 2: its own. There's about thirteen land M systems and they're 213 00:11:50,760 --> 00:11:55,000 Speaker 2: used commercially, even though it's old technology and now looking 214 00:11:55,000 --> 00:11:57,800 Speaker 2: to be upgraded with a whole lot of new, up 215 00:11:57,800 --> 00:12:01,199 Speaker 2: to date quantum stuff. It is a quantum device. It's 216 00:12:01,280 --> 00:12:04,319 Speaker 2: one where we really need to upgrade the electronics. And 217 00:12:04,360 --> 00:12:06,439 Speaker 2: I know I'm not part of my old team are 218 00:12:06,440 --> 00:12:09,880 Speaker 2: now working on upgrading that. But what we've seen is 219 00:12:09,920 --> 00:12:13,440 Speaker 2: it's delineated or discovered billions of dollars worth of minds. 220 00:12:13,600 --> 00:12:16,920 Speaker 1: That's incredible and sort of around the same time, some 221 00:12:17,000 --> 00:12:20,040 Speaker 1: of your colleagues and another part of CSIRO were working 222 00:12:20,240 --> 00:12:25,000 Speaker 1: on radio telescopes and some of the technologies they came 223 00:12:25,080 --> 00:12:28,480 Speaker 1: up with to facilitate their research underpins what we use 224 00:12:28,480 --> 00:12:29,360 Speaker 1: as Wi Fi. 225 00:12:29,480 --> 00:12:33,319 Speaker 2: Now, that's a really interesting story because it goes back 226 00:12:33,360 --> 00:12:37,720 Speaker 2: to nineteen eighties, late eighties where CCRO used to be 227 00:12:38,040 --> 00:12:40,960 Speaker 2: in the early eighties a university without students. You could 228 00:12:41,000 --> 00:12:44,920 Speaker 2: describe it as McKinsey's consulting company came through at the 229 00:12:44,920 --> 00:12:47,000 Speaker 2: request of the government to do a review and they said, 230 00:12:47,000 --> 00:12:49,200 Speaker 2: look to be more engaged with industry. 231 00:12:49,240 --> 00:12:50,760 Speaker 3: You need to pull thirty percent of. 232 00:12:50,720 --> 00:12:53,400 Speaker 2: It's finding a way and make it earn that money 233 00:12:53,440 --> 00:12:56,320 Speaker 2: by engaging with industries. So you can imagine doing it 234 00:12:56,400 --> 00:12:59,719 Speaker 2: overnight in a budget cycle was catastrophic for the organization. 235 00:13:00,160 --> 00:13:03,839 Speaker 2: But over a twenty year period we finally learned how 236 00:13:03,880 --> 00:13:08,120 Speaker 2: to do that and engage. Because csro's purpose is to 237 00:13:08,160 --> 00:13:11,079 Speaker 2: solve the greatest challenges to help Australia this successful country. 238 00:13:11,280 --> 00:13:14,480 Speaker 2: But we've always had a strong astronomy aspect in it, 239 00:13:14,559 --> 00:13:18,840 Speaker 2: even though it's seen as fundamental work. Australia's in a 240 00:13:18,880 --> 00:13:24,320 Speaker 2: really good place on the Southern Hemisphere. It's quite electromagnetically. 241 00:13:24,920 --> 00:13:27,480 Speaker 2: It's radio astronomy that it's involved with, so it's got 242 00:13:27,559 --> 00:13:30,480 Speaker 2: really good and ability to design antennas and all the 243 00:13:30,559 --> 00:13:34,640 Speaker 2: electronics and signal processing that goes with that. And that 244 00:13:34,720 --> 00:13:38,600 Speaker 2: was a consequence of the During World War II CSRO 245 00:13:38,720 --> 00:13:41,480 Speaker 2: there wasn't a defense research organization and and CSRO did 246 00:13:41,559 --> 00:13:44,480 Speaker 2: the government's defense research and they developed a version of 247 00:13:44,559 --> 00:13:47,880 Speaker 2: radar and when well the warfare, he said said, what 248 00:13:47,920 --> 00:13:49,480 Speaker 2: do we do with is now? Let's point at the 249 00:13:49,520 --> 00:13:52,200 Speaker 2: sky and that was radio astronomy being discovered by Ruby 250 00:13:52,200 --> 00:13:54,280 Speaker 2: Payne Scott. You know, the team there said what can 251 00:13:54,320 --> 00:13:55,880 Speaker 2: we do. We've going to earn some money, let's do 252 00:13:55,960 --> 00:13:58,240 Speaker 2: some solve one really big problem. Wouldn't it be great 253 00:13:58,320 --> 00:14:01,600 Speaker 2: if you could actually work out how you can separate 254 00:14:01,640 --> 00:14:03,680 Speaker 2: out signals so that you didn't have to have wires 255 00:14:03,720 --> 00:14:07,160 Speaker 2: and have a wireless communication. And so they did that 256 00:14:07,320 --> 00:14:11,040 Speaker 2: saying well, we've got this background of fundamental work and experience, 257 00:14:11,480 --> 00:14:14,360 Speaker 2: how do we actually turn that to solve this particular problem. 258 00:14:14,440 --> 00:14:16,800 Speaker 2: So it wasn't a Eurecam moment. It was actually a 259 00:14:16,840 --> 00:14:18,959 Speaker 2: project which over a very long period of time. These 260 00:14:18,960 --> 00:14:22,400 Speaker 2: things don't happen straight away. And there's a great picture 261 00:14:22,440 --> 00:14:25,920 Speaker 2: which Bob Freighter puts he called it's a cosmic geneology. 262 00:14:25,920 --> 00:14:29,360 Speaker 2: He's got things going everywhere, were educating people with PhDs, 263 00:14:29,920 --> 00:14:33,120 Speaker 2: having different different research projects that sort of built up 264 00:14:33,120 --> 00:14:36,440 Speaker 2: the capability and eventually they came up with a solution. 265 00:14:36,560 --> 00:14:37,359 Speaker 3: It was patented. 266 00:14:37,600 --> 00:14:40,640 Speaker 2: But the thing was really important was engaging with international standards. 267 00:14:40,680 --> 00:14:44,680 Speaker 2: So Dave Skillen, who was a mcquarie University professor in 268 00:14:44,760 --> 00:14:47,200 Speaker 2: electronics who was collaborating with this team because he was 269 00:14:47,240 --> 00:14:49,880 Speaker 2: part of the team that educated some of the researchers 270 00:14:49,880 --> 00:14:53,800 Speaker 2: that developed the technology, and he's spun out a company 271 00:14:54,200 --> 00:14:57,000 Speaker 2: called Radiata. It was brought up by Cisco Systems and 272 00:14:57,040 --> 00:15:01,680 Speaker 2: then it commercialized Wi Fi in the USA. And the 273 00:15:01,720 --> 00:15:04,040 Speaker 2: thing was really critical was they really pushed hard for 274 00:15:04,080 --> 00:15:06,680 Speaker 2: it to be accepted as the Tripoli standard. Thank goodness 275 00:15:06,680 --> 00:15:10,360 Speaker 2: he did, because it's a high quality capability, which meant 276 00:15:10,360 --> 00:15:12,400 Speaker 2: that you know, when you go overseas and you've got 277 00:15:12,440 --> 00:15:15,840 Speaker 2: to have different powerpoints for plugs for different things, or 278 00:15:15,880 --> 00:15:18,200 Speaker 2: even with our mobile phones, you've got to use different jacks. 279 00:15:18,560 --> 00:15:21,160 Speaker 2: Imagine if we'd had different Wi Fi systems everywhere and 280 00:15:21,200 --> 00:15:22,680 Speaker 2: every time you get to a different place, you'd have 281 00:15:22,760 --> 00:15:25,600 Speaker 2: to use a different Wi Fi, I'd be unworkable. By 282 00:15:25,640 --> 00:15:29,400 Speaker 2: getting that international standard right with the best quality thing 283 00:15:29,960 --> 00:15:34,360 Speaker 2: our process or technology means that it's been ubiquitously used. 284 00:15:34,560 --> 00:15:36,320 Speaker 1: And the great thing about that, you know, that is 285 00:15:36,360 --> 00:15:39,240 Speaker 1: the ultimate example. And what you did with squid Off 286 00:15:39,520 --> 00:15:42,080 Speaker 1: the whole point of CSIRO. And we had at the 287 00:15:42,080 --> 00:15:46,680 Speaker 1: time the DSII, the Department of Scientific and Industrial Research, 288 00:15:46,720 --> 00:15:49,000 Speaker 1: which then split in the early nineties into these Crown 289 00:15:49,040 --> 00:15:55,560 Speaker 1: Research organizations. It was the commercialization of fundamental research. And 290 00:15:55,800 --> 00:15:58,120 Speaker 1: the great thing about that, you know, for CSIRO is 291 00:15:58,120 --> 00:15:59,840 Speaker 1: probably still getting royalties from. 292 00:15:59,600 --> 00:16:02,200 Speaker 3: Not because the patterns run out, but. 293 00:16:02,120 --> 00:16:04,000 Speaker 1: For probably twenty or thirty years it would have been 294 00:16:04,240 --> 00:16:08,080 Speaker 1: a lucrative stream back to the country. 295 00:16:08,200 --> 00:16:12,080 Speaker 2: We had to fight legal battles, so CESRO actually went 296 00:16:12,120 --> 00:16:14,680 Speaker 2: to court in the US. It was quite controversial at 297 00:16:14,680 --> 00:16:17,480 Speaker 2: the time to protect the IP and the reason that 298 00:16:17,560 --> 00:16:21,760 Speaker 2: was important was to show that the rule of law 299 00:16:21,840 --> 00:16:27,600 Speaker 2: with patenting internationally can be upheld and therefore patents are 300 00:16:27,640 --> 00:16:30,880 Speaker 2: worth it because they're really only licensed to sue really, 301 00:16:31,360 --> 00:16:33,160 Speaker 2: so that was really important. But it took a lot 302 00:16:33,200 --> 00:16:36,320 Speaker 2: of guts, I think to do that, and as a consequence, 303 00:16:36,360 --> 00:16:38,480 Speaker 2: they went through a whole lot of the different companies 304 00:16:38,480 --> 00:16:41,200 Speaker 2: who were using that White Fi technology while it was 305 00:16:41,200 --> 00:16:45,800 Speaker 2: still under patent to therefore get royalties in response, and 306 00:16:45,840 --> 00:16:47,920 Speaker 2: with that it allowed us to set up a whole 307 00:16:47,960 --> 00:16:51,680 Speaker 2: lot of different programs across the country. Those funds were 308 00:16:51,880 --> 00:16:54,280 Speaker 2: followed back into government revenue. What they did were put 309 00:16:54,280 --> 00:16:58,360 Speaker 2: into a special funding pool, which led to for example, 310 00:16:58,720 --> 00:17:02,080 Speaker 2: setting up main Sequences, which is a venture capital which 311 00:17:02,120 --> 00:17:05,480 Speaker 2: is funded by well start off with Wi Fi funds, 312 00:17:05,480 --> 00:17:10,400 Speaker 2: some federal government money and it's a very successful venture capital, 313 00:17:10,640 --> 00:17:13,040 Speaker 2: which is a little bit like what Israel did in 314 00:17:13,040 --> 00:17:17,840 Speaker 2: the seventies. We're invest very early with patient capital. Also 315 00:17:17,880 --> 00:17:21,760 Speaker 2: bring in a whole lot of entrepreneurialism into the research 316 00:17:21,800 --> 00:17:24,719 Speaker 2: sector so that you can help commercialize and translate stuff 317 00:17:25,040 --> 00:17:29,200 Speaker 2: that was set up by Malcolm Turnbull government. And it's 318 00:17:29,280 --> 00:17:34,040 Speaker 2: been they've had multiple funding rounds. Now it's a very successful, 319 00:17:34,359 --> 00:17:38,160 Speaker 2: very successful venture capital and it's now the government doesn't 320 00:17:38,200 --> 00:17:40,720 Speaker 2: put money in because people put money in because it's 321 00:17:40,720 --> 00:17:44,000 Speaker 2: so successful and it raises it's funding independently, so. 322 00:17:43,920 --> 00:17:48,479 Speaker 1: That model has been really successful. CSIRO is seen as 323 00:17:49,200 --> 00:17:53,760 Speaker 1: a really important part of the research landscape in Australia. 324 00:17:53,960 --> 00:17:56,119 Speaker 1: What was it like over sort of forty years of 325 00:17:56,119 --> 00:18:00,360 Speaker 1: being involved in the organization the ev and flow of polot. 326 00:18:00,400 --> 00:18:04,040 Speaker 1: It seems that there was always a commitment to fundamental 327 00:18:04,080 --> 00:18:07,680 Speaker 1: research and spending a decent amount of money. I think 328 00:18:07,880 --> 00:18:10,040 Speaker 1: Australia spends more on R and D than the New 329 00:18:10,119 --> 00:18:13,119 Speaker 1: Zealanders as a percentage of GDP, It's probably low compared 330 00:18:13,160 --> 00:18:17,040 Speaker 1: to Israel in the US, but there's always been that commitment, 331 00:18:17,040 --> 00:18:20,040 Speaker 1: whether it's been a left leaning or a right leaning government. 332 00:18:20,160 --> 00:18:23,720 Speaker 2: Some people would question that at the moment, the government's 333 00:18:23,800 --> 00:18:27,639 Speaker 2: undertaking a strategic examination of research and development, and what 334 00:18:27,680 --> 00:18:31,760 Speaker 2: we've found is that Australia has the highest investment in 335 00:18:31,920 --> 00:18:35,640 Speaker 2: research from the university sector because of their international students. 336 00:18:36,480 --> 00:18:37,680 Speaker 3: It's the highest in the OECD. 337 00:18:38,320 --> 00:18:41,320 Speaker 2: The government investment is about a little bit below average. 338 00:18:42,040 --> 00:18:44,040 Speaker 2: It has dropped a bit in recent times in real 339 00:18:44,119 --> 00:18:48,840 Speaker 2: terms a bit under two percent, and someone might even 340 00:18:48,880 --> 00:18:49,680 Speaker 2: have dropped even. 341 00:18:49,520 --> 00:18:50,000 Speaker 3: More than that. 342 00:18:50,080 --> 00:18:54,480 Speaker 2: But there's the biggest problem for us is the industry 343 00:18:54,560 --> 00:18:58,040 Speaker 2: investment in research development or business expenditure and research development 344 00:18:58,160 --> 00:18:59,280 Speaker 2: is the lowest in the OECIT. 345 00:18:59,440 --> 00:19:02,119 Speaker 3: So that is a huge problems for Australia. Lovet yes, 346 00:19:02,200 --> 00:19:02,560 Speaker 3: where a. 347 00:19:02,520 --> 00:19:07,880 Speaker 2: Country of small medium enterprises like ninety nine percent most 348 00:19:07,920 --> 00:19:10,480 Speaker 2: of them have got like seventy percent have lessened to twenty people. 349 00:19:10,560 --> 00:19:13,760 Speaker 2: So you can imagine their investment in innovation is not 350 00:19:13,800 --> 00:19:15,639 Speaker 2: where it needs to be and that's a focus on 351 00:19:15,680 --> 00:19:16,879 Speaker 2: the government at the moment. 352 00:19:17,480 --> 00:19:19,359 Speaker 3: A lot of it is because of it's a service. 353 00:19:19,560 --> 00:19:22,520 Speaker 2: A lot of those small medium enterprises a service, you know, 354 00:19:22,640 --> 00:19:24,879 Speaker 2: our bars, coffee shops, that sort of stuff. But the 355 00:19:24,880 --> 00:19:29,280 Speaker 2: innovative companies are beginning to grow and that's why things 356 00:19:29,320 --> 00:19:33,120 Speaker 2: like quantum has been really important AI deep tech and 357 00:19:33,119 --> 00:19:36,000 Speaker 2: the recognition that we've had a bit of a bifurcation 358 00:19:36,080 --> 00:19:39,240 Speaker 2: where you've got amazing research. Australa has always done really well. 359 00:19:39,320 --> 00:19:41,640 Speaker 2: Everyone talks about hitting you know what is it hitting 360 00:19:41,680 --> 00:19:45,480 Speaker 2: above its way? That's it punching above its way and 361 00:19:46,560 --> 00:19:49,240 Speaker 2: it has, but that's where it stayed. And we haven't 362 00:19:49,240 --> 00:19:52,720 Speaker 2: been so good at transitioning things out of the university 363 00:19:52,800 --> 00:19:57,639 Speaker 2: sector into turning it into industry. University people being universities 364 00:19:58,080 --> 00:20:01,360 Speaker 2: industry people in the universe. He even public funded agencies 365 00:20:01,400 --> 00:20:05,560 Speaker 2: like CESO, there's not much movement between them. And so 366 00:20:06,160 --> 00:20:08,199 Speaker 2: one of the things that the Turnbull government did in 367 00:20:08,240 --> 00:20:11,359 Speaker 2: twenty sixteen, and this wasn't popular, He almost lost the 368 00:20:11,400 --> 00:20:12,040 Speaker 2: election over it. 369 00:20:12,040 --> 00:20:14,440 Speaker 3: He set up in December twenty sixteen the. 370 00:20:16,160 --> 00:20:21,200 Speaker 2: National Innovation and Science Agenda, and he set up main 371 00:20:21,240 --> 00:20:26,639 Speaker 2: Sequence Ventures investment into Michelle Simmons's quantum computer, setting up 372 00:20:26,720 --> 00:20:29,840 Speaker 2: the on program, which is an entrepreneurial program which Larry Marshall, 373 00:20:29,840 --> 00:20:32,560 Speaker 2: who is the CEO of CSR at the time, to 374 00:20:32,600 --> 00:20:36,639 Speaker 2: try and create entrepreneurialism within scientists and that's been hugely successful. 375 00:20:37,600 --> 00:20:39,000 Speaker 3: And there were some other things as well. 376 00:20:39,040 --> 00:20:41,359 Speaker 2: But the thing that was interesting was the electorate hated 377 00:20:41,400 --> 00:20:43,920 Speaker 2: it and he almost lost the next election because people 378 00:20:43,960 --> 00:20:46,959 Speaker 2: saw innovation was going to take their jobs. But holding 379 00:20:47,000 --> 00:20:49,560 Speaker 2: in there we've seen as a real shift so that 380 00:20:50,240 --> 00:20:53,080 Speaker 2: we're beginning to see and it's been painful and we're 381 00:20:53,200 --> 00:20:57,080 Speaker 2: not there yet, but at university professors thinking that where 382 00:20:57,359 --> 00:21:00,600 Speaker 2: instead of having just an academic perspective, you see, how 383 00:21:00,600 --> 00:21:03,440 Speaker 2: can they spin out companies, how can they turn their 384 00:21:03,440 --> 00:21:08,480 Speaker 2: great research into opportunities for creating new businesses. So we've 385 00:21:08,480 --> 00:21:11,120 Speaker 2: got a remarkable number of startups and the quantum area 386 00:21:11,200 --> 00:21:12,480 Speaker 2: is the one we're focusing on. 387 00:21:12,400 --> 00:21:15,119 Speaker 1: It Well, that's from the outside has been incredible to 388 00:21:15,160 --> 00:21:18,520 Speaker 1: watch sort of from the Turnbull government and actually before 389 00:21:18,640 --> 00:21:21,760 Speaker 1: you know there was significant investments into quantum, but that's 390 00:21:21,760 --> 00:21:25,320 Speaker 1: really accelerated to the extent that we've had Psygh Quantum, 391 00:21:25,359 --> 00:21:29,080 Speaker 1: a huge government investment into this one really promising startup 392 00:21:29,119 --> 00:21:34,240 Speaker 1: that is looking to build quantum computers artificial intelligence as well. 393 00:21:34,320 --> 00:21:37,760 Speaker 1: And now we've got in the wake of COVID, a 394 00:21:37,800 --> 00:21:43,320 Speaker 1: big push on advanced manufacturing, clean tech in Australia and 395 00:21:43,400 --> 00:21:45,800 Speaker 1: cyber a lot of money relative to New Zealand's going 396 00:21:45,800 --> 00:21:50,560 Speaker 1: into cyber and so you were there as Chief Science 397 00:21:50,600 --> 00:21:53,680 Speaker 1: Advisor in the Scott Morrison government towards the end of 398 00:21:54,200 --> 00:21:59,280 Speaker 1: his tenure Albanisi government as well. From your perspective, what 399 00:21:59,400 --> 00:22:02,040 Speaker 1: explained this sort of ongoing commitment was it that fact 400 00:22:02,040 --> 00:22:05,840 Speaker 1: that politicians across the aisle realize we've got a problem 401 00:22:05,840 --> 00:22:08,439 Speaker 1: with our small and medium sized businesses here. They're not 402 00:22:08,560 --> 00:22:12,119 Speaker 1: spending enough, they're not commercializing science to enough of a 403 00:22:12,280 --> 00:22:14,480 Speaker 1: degree to shift the needle for the economy. We need 404 00:22:14,520 --> 00:22:16,040 Speaker 1: to resource this properly. 405 00:22:16,560 --> 00:22:16,720 Speaker 3: Well. 406 00:22:16,720 --> 00:22:21,719 Speaker 2: Look, successive governments have been worried about that, and especially 407 00:22:21,720 --> 00:22:23,520 Speaker 2: when you're a science advisor, your role is to just 408 00:22:23,560 --> 00:22:27,000 Speaker 2: provide the evidence, and the evidence is stuck. You know, 409 00:22:27,160 --> 00:22:29,960 Speaker 2: Australia didn't have much new to the world innovation in 410 00:22:30,000 --> 00:22:34,359 Speaker 2: its products that it's exporting. If you look at Australia's 411 00:22:36,040 --> 00:22:41,679 Speaker 2: economic complexity, we are sort of one hundred somewhere between ninety 412 00:22:41,680 --> 00:22:44,320 Speaker 2: seventh and one hundred and second. It's a Harvard measure 413 00:22:44,359 --> 00:22:47,520 Speaker 2: saying how complex is your economy? And because we're so 414 00:22:47,600 --> 00:22:54,160 Speaker 2: dependent on agriculture and on mining, and it means that 415 00:22:54,320 --> 00:22:58,719 Speaker 2: although we've got deep complexity in our ability to extract 416 00:22:58,760 --> 00:23:01,320 Speaker 2: them and be globally competitive. What we're not doing is 417 00:23:01,359 --> 00:23:04,040 Speaker 2: adding value to them, so that we're not realizing it's 418 00:23:04,080 --> 00:23:06,879 Speaker 2: almost like producing the materials but then shipping it off 419 00:23:06,920 --> 00:23:09,920 Speaker 2: somewhere else for someone else to get the value from it. 420 00:23:10,080 --> 00:23:15,000 Speaker 2: And as we see the energy transition, Australia is very 421 00:23:15,000 --> 00:23:18,560 Speaker 2: dependent on fossil fuels, so we have to transition oury economy. 422 00:23:19,080 --> 00:23:20,919 Speaker 2: I mean, just to give you an idea of what 423 00:23:21,400 --> 00:23:25,320 Speaker 2: being one hundred and second is, Yemen, Bikina. 424 00:23:24,960 --> 00:23:27,399 Speaker 3: Faso, Bangladesh. 425 00:23:27,600 --> 00:23:32,320 Speaker 2: Okay, So it sounds ridiculous that Australia should be ranked there, 426 00:23:32,960 --> 00:23:35,200 Speaker 2: but that's because we've got huge volumes. 427 00:23:35,240 --> 00:23:36,520 Speaker 3: We've been a prostrous nation. 428 00:23:36,640 --> 00:23:40,280 Speaker 2: We've not really had a technical recession for decades. I'm 429 00:23:40,359 --> 00:23:42,880 Speaker 2: getting on to forty years now, and that's because we've 430 00:23:42,880 --> 00:23:45,479 Speaker 2: been so lucky that we've been able to use our 431 00:23:45,480 --> 00:23:51,240 Speaker 2: mineral deposits and basically ship them to mostly China and 432 00:23:52,680 --> 00:23:56,040 Speaker 2: wreck the benefit from that. So that's possibly made us 433 00:23:56,040 --> 00:23:59,080 Speaker 2: a little bit lazy as well, and as a consequence, 434 00:23:59,119 --> 00:24:02,960 Speaker 2: we haven't really had the desperate need to turn our 435 00:24:03,040 --> 00:24:04,280 Speaker 2: research into dollars. 436 00:24:04,359 --> 00:24:07,240 Speaker 3: But that's changing. We have to really get to. 437 00:24:07,200 --> 00:24:09,280 Speaker 2: A point where if we're going to be a prosperous 438 00:24:09,359 --> 00:24:12,080 Speaker 2: nation in twenty fifty where we lose at least sixteen percent, 439 00:24:12,119 --> 00:24:14,880 Speaker 2: which is about between one hundred and fifty and three 440 00:24:15,000 --> 00:24:17,880 Speaker 2: hundred billion dollars of our exports because of no one's 441 00:24:17,880 --> 00:24:21,639 Speaker 2: going to buy our coal, our thermal coal, oil gas. 442 00:24:22,119 --> 00:24:25,879 Speaker 2: We're going to reduce circular economy, econom iron ore, that 443 00:24:25,960 --> 00:24:28,560 Speaker 2: sort of thing. Even some of the critical minerals used 444 00:24:28,600 --> 00:24:31,200 Speaker 2: for batteries will be recycled. 445 00:24:31,480 --> 00:24:32,840 Speaker 3: We've got a bit of a runway. 446 00:24:32,960 --> 00:24:35,720 Speaker 2: So how can we make that great research turn into 447 00:24:35,760 --> 00:24:39,600 Speaker 2: prosperity we like in Australia. Look, if you go through 448 00:24:39,640 --> 00:24:42,480 Speaker 2: looking at successive governments have recognized this. How they've gone 449 00:24:42,520 --> 00:24:45,439 Speaker 2: about it has been slightly different, and there's always tweaking 450 00:24:45,480 --> 00:24:48,960 Speaker 2: around the edges, but saying the quantum areas in some 451 00:24:49,080 --> 00:24:50,400 Speaker 2: here this week for quantum. 452 00:24:50,720 --> 00:24:51,399 Speaker 3: One of the things is. 453 00:24:51,480 --> 00:24:54,919 Speaker 2: Interesting was when I became true scientists, I raised the 454 00:24:55,000 --> 00:24:58,800 Speaker 2: issue that with the Prime Minister saying quantum is a 455 00:24:58,800 --> 00:25:01,600 Speaker 2: really big opportunity. The AI was just sort of beginning 456 00:25:01,720 --> 00:25:05,240 Speaker 2: and said, well, quantum is. We've got strength in that 457 00:25:05,480 --> 00:25:08,720 Speaker 2: we've been investing in fundamental research for twenty five years 458 00:25:08,760 --> 00:25:12,520 Speaker 2: for the istering research Council through numerous centers of excellence, 459 00:25:12,680 --> 00:25:17,120 Speaker 2: we've funded about a billion dollars worth of fundamental research 460 00:25:17,800 --> 00:25:20,919 Speaker 2: since about two thousand and we're beginning to see the 461 00:25:20,960 --> 00:25:24,000 Speaker 2: odd spinout company. There's a real opportunity for us to 462 00:25:24,080 --> 00:25:25,919 Speaker 2: have an industry. We're one of the best in the 463 00:25:25,920 --> 00:25:29,560 Speaker 2: world in the research. Let's turn that into an industry. 464 00:25:29,600 --> 00:25:32,000 Speaker 2: And to be honest, in the four years I was 465 00:25:32,080 --> 00:25:35,080 Speaker 2: chief signed as we turned it into an industry and 466 00:25:35,119 --> 00:25:36,560 Speaker 2: there were a couple of things that we needed. First 467 00:25:36,600 --> 00:25:38,879 Speaker 2: of all, when I was in CSORROW, we did a 468 00:25:38,960 --> 00:25:42,479 Speaker 2: roadmap to show the value proposition. So Larry Marshall, who 469 00:25:42,520 --> 00:25:45,840 Speaker 2: is the Chief executive at the time, funded a roadmap 470 00:25:45,880 --> 00:25:48,920 Speaker 2: being done through an ability to do these sort of 471 00:25:48,960 --> 00:25:52,920 Speaker 2: roadmaps within CSRO the technoeconomic stuff which is very important. 472 00:25:52,920 --> 00:25:55,280 Speaker 2: So we're able to get the value proposition and you know, 473 00:25:55,480 --> 00:25:58,720 Speaker 2: sixteen thousand jobs, billions of dollars worth of increased at 474 00:25:58,720 --> 00:26:03,720 Speaker 2: GDP is pretty easy. Well, the Morrilton government said let's 475 00:26:03,720 --> 00:26:06,320 Speaker 2: start doing a strategy and then they lost the election. 476 00:26:06,400 --> 00:26:09,160 Speaker 2: We got an Albanesi government and then Minister Husick, who 477 00:26:09,160 --> 00:26:11,880 Speaker 2: was the Minister at the time, said I'm all in 478 00:26:13,240 --> 00:26:16,120 Speaker 2: and so we had a National Committee Quantum Committee. We 479 00:26:16,160 --> 00:26:20,520 Speaker 2: developed a strategy and then the Government Department of Industry, 480 00:26:20,560 --> 00:26:24,080 Speaker 2: Science and Resources had the whole branch of that implementing 481 00:26:24,080 --> 00:26:27,040 Speaker 2: that quantum strategy. And I guess you had a lunatic 482 00:26:27,200 --> 00:26:30,240 Speaker 2: chief science like me running around the country sprooking out 483 00:26:30,280 --> 00:26:31,680 Speaker 2: saying this is really important. 484 00:26:31,880 --> 00:26:35,920 Speaker 3: And if I go back to twenty ten, when I was. 485 00:26:35,880 --> 00:26:39,880 Speaker 2: In the austrain Institute of Physics was saying we're doing 486 00:26:39,880 --> 00:26:43,200 Speaker 2: their decaybal plants and there's no industry for physics in Australia. 487 00:26:43,240 --> 00:26:44,199 Speaker 3: That was just so wrong. 488 00:26:44,640 --> 00:26:47,200 Speaker 2: What we didn't realize was what it means to take 489 00:26:47,359 --> 00:26:50,520 Speaker 2: our research. And we've seen a lot of Australia's physics 490 00:26:50,560 --> 00:26:53,080 Speaker 2: research line up behind quantum. 491 00:26:53,720 --> 00:26:55,000 Speaker 3: Quantum is quite a horizontal. 492 00:26:55,040 --> 00:26:59,560 Speaker 2: It's got photonics, it's got semiconductors, it's got classic quantum 493 00:26:59,560 --> 00:27:02,560 Speaker 2: computing sensing and things. And so what we've seen is 494 00:27:02,560 --> 00:27:06,960 Speaker 2: a real focusing down on as a research community saying 495 00:27:06,960 --> 00:27:12,119 Speaker 2: this is important. People now doing PhDs saying I'm spinning 496 00:27:12,119 --> 00:27:13,639 Speaker 2: out a company, and some of those companies have been 497 00:27:13,720 --> 00:27:17,040 Speaker 2: very successful. There's one which came out of University Queensland 498 00:27:17,080 --> 00:27:19,600 Speaker 2: and these PhD students sold the company for forty million 499 00:27:19,640 --> 00:27:20,520 Speaker 2: dollars recently. 500 00:27:20,680 --> 00:27:22,359 Speaker 1: So credible is that one? 501 00:27:22,680 --> 00:27:22,840 Speaker 3: Is it? 502 00:27:22,880 --> 00:27:24,640 Speaker 1: Control? Are is another wall? 503 00:27:24,720 --> 00:27:27,639 Speaker 3: No? No, that's some Key Control Control. 504 00:27:28,040 --> 00:27:31,240 Speaker 2: So Key controls another big company. It's it's come out 505 00:27:31,240 --> 00:27:35,160 Speaker 2: of Sydney University. There's been I think about fifty startup companies, 506 00:27:35,240 --> 00:27:37,280 Speaker 2: been forty and fifty happening all the time. 507 00:27:37,280 --> 00:27:41,720 Speaker 3: I've lost count credible and so kids are doing their PhDs. 508 00:27:40,960 --> 00:27:43,200 Speaker 2: Knowing where I'm going to spin out a company when 509 00:27:43,240 --> 00:27:47,359 Speaker 2: I finish this and then partner because it's not like 510 00:27:47,400 --> 00:27:50,280 Speaker 2: they're building a whole quantum computer. I've got some quantum 511 00:27:50,280 --> 00:27:52,359 Speaker 2: computers being built, but they realize they're part of the 512 00:27:52,359 --> 00:27:56,320 Speaker 2: supply chain because there's a big global, big global effort, 513 00:27:56,440 --> 00:27:59,360 Speaker 2: and so there's there's a need for so many different bids. 514 00:27:59,640 --> 00:28:01,200 Speaker 3: No one place is going to do it all, no 515 00:28:01,320 --> 00:28:01,960 Speaker 3: one country. 516 00:28:02,000 --> 00:28:05,560 Speaker 1: And I think that's the opportunity for New Zealand. Interested 517 00:28:05,560 --> 00:28:08,720 Speaker 1: in your view what our relative strengths are both in 518 00:28:08,800 --> 00:28:11,560 Speaker 1: quantum man and in the superconducting space as well. But 519 00:28:12,320 --> 00:28:16,000 Speaker 1: we have to remember we're very small. But as you say, 520 00:28:16,000 --> 00:28:18,720 Speaker 1: there's going to be a big supply chain for quantum computers, 521 00:28:18,800 --> 00:28:24,440 Speaker 1: quantum sense and quantum communications, So if we can specialize 522 00:28:24,480 --> 00:28:27,280 Speaker 1: in particular niches that aren't being filled overseas, and I 523 00:28:27,280 --> 00:28:30,040 Speaker 1: think what you said that works so well in Australia. 524 00:28:30,080 --> 00:28:32,439 Speaker 1: You know that mapping of what the opportunities are, and 525 00:28:32,480 --> 00:28:34,760 Speaker 1: I feel in some of these areas we haven't. For instance, 526 00:28:34,760 --> 00:28:38,480 Speaker 1: in artificial intelligence, we just had a national strategy put 527 00:28:38,520 --> 00:28:41,560 Speaker 1: out there, but it was sort of criticized because I 528 00:28:41,600 --> 00:28:44,520 Speaker 1: think there wasn't much depth to it where you were 529 00:28:44,560 --> 00:28:48,239 Speaker 1: actually saying this is the opportunity for New Zealand. It 530 00:28:48,360 --> 00:28:52,320 Speaker 1: was they want adoption of artificial intelligence, but they've sort 531 00:28:52,320 --> 00:28:54,760 Speaker 1: of said we're not necessarily going to be developers of AI, 532 00:28:54,840 --> 00:28:57,040 Speaker 1: which seems to be a lost opportunity. 533 00:28:57,200 --> 00:28:58,400 Speaker 3: So there's a couple of things there. 534 00:28:58,840 --> 00:29:03,120 Speaker 2: The first one is developing software is really cheap in anyways, 535 00:29:03,160 --> 00:29:05,600 Speaker 2: so it's an easy way in. But the other is 536 00:29:05,600 --> 00:29:08,720 Speaker 2: also AI is dependent on training and algorithms and stuff 537 00:29:08,720 --> 00:29:12,320 Speaker 2: which are very culturally based. Really every country needs to 538 00:29:12,360 --> 00:29:15,000 Speaker 2: have a version of AI just so. 539 00:29:14,960 --> 00:29:17,560 Speaker 3: It's got its cultural stuff that's in there. 540 00:29:17,840 --> 00:29:21,800 Speaker 2: You've got a strong sort of First Nations culture here 541 00:29:21,840 --> 00:29:23,640 Speaker 2: as well, So how do you get make sure that's 542 00:29:23,720 --> 00:29:26,960 Speaker 2: part of your AI training that it means that, and 543 00:29:27,000 --> 00:29:30,960 Speaker 2: then you've got the whole issues of IP and ownership 544 00:29:31,280 --> 00:29:33,840 Speaker 2: and that which is a very different cultural perspective. So 545 00:29:34,400 --> 00:29:39,080 Speaker 2: that New Zealand has been such a leader in Mari 546 00:29:39,280 --> 00:29:42,200 Speaker 2: culture and adoption and being able to bring knowledge systems 547 00:29:42,240 --> 00:29:47,480 Speaker 2: alongside more Western approaches, there's something really huge opportunity there 548 00:29:47,480 --> 00:29:47,960 Speaker 2: to lead the. 549 00:29:47,880 --> 00:29:48,560 Speaker 3: World on that. 550 00:29:49,960 --> 00:29:51,800 Speaker 2: As well as you know just what it is to 551 00:29:51,840 --> 00:29:53,760 Speaker 2: be in New Zealand, just like it is what it 552 00:29:53,840 --> 00:29:55,520 Speaker 2: is to be in Australian is very different to what 553 00:29:55,560 --> 00:29:57,000 Speaker 2: it is to be a Silicon valley. 554 00:29:57,320 --> 00:30:00,760 Speaker 3: Dude, Yeah, that's right. 555 00:30:00,880 --> 00:30:04,200 Speaker 2: Doing their algorithm development, So these sorts of things really 556 00:30:04,400 --> 00:30:10,040 Speaker 2: are very culturally based because you AI is basically a 557 00:30:10,080 --> 00:30:13,400 Speaker 2: big statistical model that trains and uses the whole stuff 558 00:30:13,440 --> 00:30:15,560 Speaker 2: that they can access, which they choose because of the 559 00:30:15,600 --> 00:30:19,880 Speaker 2: algorithms that they develop to be able to pull out 560 00:30:19,960 --> 00:30:24,520 Speaker 2: information and from that get a statistical approximation based on 561 00:30:24,600 --> 00:30:26,600 Speaker 2: what's been going before. So, I mean, when you think 562 00:30:26,640 --> 00:30:29,360 Speaker 2: about it as extraordinary how humans have been able to 563 00:30:29,400 --> 00:30:33,080 Speaker 2: create that something, AI has the ability to really have 564 00:30:33,200 --> 00:30:37,520 Speaker 2: a huge uptick in productivity in so many ways, just 565 00:30:37,600 --> 00:30:40,880 Speaker 2: even just from able to synthesize information. Here's a whole 566 00:30:40,920 --> 00:30:42,880 Speaker 2: lot of information. Can you bring it together? And that's 567 00:30:42,880 --> 00:30:45,240 Speaker 2: where AI can be great. If you're asking you to 568 00:30:45,360 --> 00:30:48,720 Speaker 2: questions which sort of says how I'm trying to find 569 00:30:48,760 --> 00:30:51,600 Speaker 2: something new or pull together information if you look at 570 00:30:51,640 --> 00:30:54,480 Speaker 2: where it pulls it from. It doesn't necessarily pull it 571 00:30:54,560 --> 00:30:57,800 Speaker 2: from your own area. You can ask it to and 572 00:30:57,880 --> 00:31:00,160 Speaker 2: there's all different models that you have to learn how 573 00:31:00,160 --> 00:31:03,080 Speaker 2: to engage with them, and that and itself will be 574 00:31:04,200 --> 00:31:07,280 Speaker 2: I think a high level professional role is how to 575 00:31:07,280 --> 00:31:10,680 Speaker 2: actually talk to an AI and put the prompt sense 576 00:31:10,720 --> 00:31:13,400 Speaker 2: so that you're able to get the best out out 577 00:31:13,440 --> 00:31:16,400 Speaker 2: of an AI system. That in itself will become a 578 00:31:16,600 --> 00:31:19,640 Speaker 2: very highly sought after professional role. 579 00:31:20,200 --> 00:31:23,719 Speaker 1: Absolutely, and you've got the national AIC into in Australia, 580 00:31:23,880 --> 00:31:27,560 Speaker 1: quite a bit of investment going into AI available for startups. 581 00:31:27,600 --> 00:31:31,120 Speaker 1: The different dynamic you have in Australia is the States 582 00:31:31,640 --> 00:31:34,640 Speaker 1: and they're all quite competitive as well, so they will 583 00:31:34,680 --> 00:31:38,040 Speaker 1: put on their own R and D tax incentives and 584 00:31:38,080 --> 00:31:40,960 Speaker 1: that they're all competing with each other to host labs 585 00:31:40,960 --> 00:31:43,480 Speaker 1: and that sort of thing. Has that as a chief 586 00:31:43,520 --> 00:31:46,080 Speaker 1: science advisor because they all have their own chief science 587 00:31:46,080 --> 00:31:48,840 Speaker 1: advisors as well. Does that complicate things or does that 588 00:31:48,880 --> 00:31:49,960 Speaker 1: actually improve things. 589 00:31:50,120 --> 00:31:51,960 Speaker 3: Oh, look, it complicates and improves. 590 00:31:52,040 --> 00:31:56,120 Speaker 2: So each state and territory's got a different demographics, different environment, 591 00:31:56,360 --> 00:32:01,080 Speaker 2: different weather, different industry focus. So even though it looks 592 00:32:01,120 --> 00:32:03,440 Speaker 2: like you've got a bit of everything everywhere, what you'll 593 00:32:03,440 --> 00:32:05,440 Speaker 2: find is each state and territory has got their own 594 00:32:05,520 --> 00:32:09,520 Speaker 2: thing which is appropriate for their area. The Chief Scientists 595 00:32:09,560 --> 00:32:11,880 Speaker 2: of the States and Territories, along with the New Zealand 596 00:32:11,920 --> 00:32:15,760 Speaker 2: Chief Scientists or Science Advisor get together regularly the Forum 597 00:32:15,880 --> 00:32:18,120 Speaker 2: of Australian Chief Scientists, we should say in New Zealand 598 00:32:18,160 --> 00:32:20,480 Speaker 2: and in fact I believe their meeting in Sydney next 599 00:32:20,480 --> 00:32:25,000 Speaker 2: week and we became a really close cohort and we're 600 00:32:25,040 --> 00:32:27,800 Speaker 2: able to share information. But the other is also showing 601 00:32:27,880 --> 00:32:28,800 Speaker 2: how it works. 602 00:32:28,560 --> 00:32:30,640 Speaker 3: Together and quite. 603 00:32:30,360 --> 00:32:33,440 Speaker 2: Often you can do an awful lot without investment by 604 00:32:33,480 --> 00:32:38,200 Speaker 2: just making sure you've got coordination, planning and optimizing and 605 00:32:38,640 --> 00:32:41,440 Speaker 2: where your focus should be so that you're able to 606 00:32:41,480 --> 00:32:44,280 Speaker 2: turn You know, when you've got a small envelope of money, 607 00:32:44,320 --> 00:32:45,520 Speaker 2: you've got to work out how do I use it 608 00:32:45,560 --> 00:32:48,040 Speaker 2: well and get a big leverage from it. And that's 609 00:32:48,040 --> 00:32:50,600 Speaker 2: always the challenges, saying how can I take this dollar 610 00:32:50,800 --> 00:32:54,640 Speaker 2: and turn it into five dollars by partnering, by getting 611 00:32:54,640 --> 00:32:57,400 Speaker 2: others to put money in. And that's probably the biggest 612 00:32:57,480 --> 00:32:59,560 Speaker 2: challenge for New Zealand is to say, well, how can 613 00:32:59,560 --> 00:33:00,840 Speaker 2: we levery your investment? 614 00:33:01,400 --> 00:33:02,200 Speaker 3: And quite often. 615 00:33:02,120 --> 00:33:06,400 Speaker 2: Leveraging requires you to just be constant, play the long game. 616 00:33:06,960 --> 00:33:10,840 Speaker 2: The second is that you just settle and deal with 617 00:33:10,880 --> 00:33:15,000 Speaker 2: the structures so that then you're able to navigate things 618 00:33:15,040 --> 00:33:17,520 Speaker 2: so that people aren't having every time they're out contact 619 00:33:17,520 --> 00:33:19,800 Speaker 2: with you. It's not a new face or a new organization. 620 00:33:20,160 --> 00:33:24,360 Speaker 1: Look, you're meeting our Prime Minister's Chief Science Advisor, John 621 00:33:24,440 --> 00:33:28,680 Speaker 1: Rosche's relatively new to the position. Any sort of words 622 00:33:28,680 --> 00:33:32,040 Speaker 1: of advice or thoughts about what worked well for you 623 00:33:32,160 --> 00:33:35,560 Speaker 1: as chief Science Advisor and your forty years of working 624 00:33:35,560 --> 00:33:39,440 Speaker 1: at CSIRO. You talked about turning one dollar into five dollars. 625 00:33:39,440 --> 00:33:41,400 Speaker 1: That's really the remit he has. He comes from an 626 00:33:41,400 --> 00:33:44,080 Speaker 1: agricultural background and we've done very well in that space. 627 00:33:44,120 --> 00:33:47,640 Speaker 1: But in terms of the more sort of advanced technologies 628 00:33:47,720 --> 00:33:51,160 Speaker 1: that you've specialized in, how do we get this right? 629 00:33:51,440 --> 00:33:53,440 Speaker 2: Well, I think the first thing is it's not the 630 00:33:53,520 --> 00:33:56,080 Speaker 2: role of chief scientists to tell the government what to do. 631 00:33:56,600 --> 00:33:59,880 Speaker 2: What's really important is to provide the options, evidence based 632 00:34:00,040 --> 00:34:04,480 Speaker 2: strategic thinking in terms of what if how can we coordinate, 633 00:34:04,720 --> 00:34:09,080 Speaker 2: bring things together, use a convening power to bring people 634 00:34:09,120 --> 00:34:12,439 Speaker 2: together to work together. That's what I found worked really 635 00:34:12,440 --> 00:34:15,239 Speaker 2: well because when I took over, Australia was seems very 636 00:34:15,239 --> 00:34:17,200 Speaker 2: fragmented and a bit of a mess in quantum to 637 00:34:17,239 --> 00:34:21,760 Speaker 2: be honest, and very disorganized, and people fighting amongst themselves, 638 00:34:22,239 --> 00:34:25,240 Speaker 2: and just by being there and bringing people together, working 639 00:34:25,280 --> 00:34:27,680 Speaker 2: through and saying, look, let's look at the bigger picture, 640 00:34:27,760 --> 00:34:30,839 Speaker 2: where us against the world, not us against each other 641 00:34:30,880 --> 00:34:34,759 Speaker 2: within the country, and also having good something to sell, 642 00:34:35,000 --> 00:34:37,520 Speaker 2: which is so that it's what the last thing you 643 00:34:37,560 --> 00:34:40,400 Speaker 2: ever should do with the government in my experiences, go 644 00:34:40,480 --> 00:34:41,520 Speaker 2: out and say. 645 00:34:41,320 --> 00:34:42,200 Speaker 3: I need money. 646 00:34:42,680 --> 00:34:45,480 Speaker 2: What you need to say is I've got a vision 647 00:34:46,480 --> 00:34:49,560 Speaker 2: and we've got the evidence to show how we can 648 00:34:49,600 --> 00:34:52,560 Speaker 2: get to that vision over to you, and they'll either 649 00:34:52,640 --> 00:34:55,880 Speaker 2: say that it's run with it or not. We elect governments, 650 00:34:55,960 --> 00:34:58,879 Speaker 2: I think you have to always respect, particularly liberal democracies, 651 00:34:58,880 --> 00:35:00,960 Speaker 2: that you have to respect the people have been elected, 652 00:35:01,600 --> 00:35:03,759 Speaker 2: They've been elected for a purpose, and what you're there 653 00:35:03,800 --> 00:35:06,759 Speaker 2: to try and do is to support them in what 654 00:35:06,800 --> 00:35:09,960 Speaker 2: they were elected for, but making sure that they can 655 00:35:10,000 --> 00:35:12,560 Speaker 2: see what the options are and what the consequences are. 656 00:35:12,520 --> 00:35:15,680 Speaker 1: What the consequences that are. Having something to sell bottom 657 00:35:15,760 --> 00:35:19,200 Speaker 1: line is really important. And we've had we've had great 658 00:35:19,239 --> 00:35:22,440 Speaker 1: academic outputs, lots of research papers. 659 00:35:22,840 --> 00:35:25,080 Speaker 2: New Zealand is an amazing country. When you go back 660 00:35:25,080 --> 00:35:33,320 Speaker 2: from Rutherford. Oh well dogs see you've got some amazing 661 00:35:33,400 --> 00:35:37,200 Speaker 2: work in se conducting power lines and tapes and magnets 662 00:35:37,239 --> 00:35:40,239 Speaker 2: and stuff like that. And what I always say is, 663 00:35:40,360 --> 00:35:43,120 Speaker 2: you know a fewer bigger things, focus on things where 664 00:35:43,239 --> 00:35:45,840 Speaker 2: you've got strengths. You don't it to be your things 665 00:35:45,920 --> 00:35:49,640 Speaker 2: to everybody, but identify where your strengths are and then 666 00:35:49,680 --> 00:35:52,160 Speaker 2: turn that into global market supply chains. 667 00:35:52,440 --> 00:35:55,799 Speaker 1: And that point about there is a global supply chain 668 00:35:55,960 --> 00:35:59,600 Speaker 1: in quantum, in AI, in clean tech, and particularly in 669 00:35:59,640 --> 00:36:02,880 Speaker 1: things like clean tech and manufacturing where the Australian government 670 00:36:02,880 --> 00:36:05,399 Speaker 1: has said we want to rebuild Australian manufacturing. We want 671 00:36:05,440 --> 00:36:10,279 Speaker 1: to build EV batteries in Australia, solar panels. 672 00:36:09,560 --> 00:36:12,440 Speaker 2: So not EV batteries but probably stationary batteries. 673 00:36:12,560 --> 00:36:15,360 Speaker 3: Yeah, so I think which. 674 00:36:15,400 --> 00:36:16,800 Speaker 1: Are for power plants and that's sort. 675 00:36:16,680 --> 00:36:17,399 Speaker 3: Of yeah, that's right. 676 00:36:17,440 --> 00:36:21,120 Speaker 2: Yeah, so you know, things on vanadium flow batteries are 677 00:36:21,160 --> 00:36:23,640 Speaker 2: sorts of things and making the most of some technology. 678 00:36:24,080 --> 00:36:26,560 Speaker 2: But the thing that I think that's really important is, 679 00:36:27,200 --> 00:36:30,040 Speaker 2: you know, the strain promises here over the weekend. I 680 00:36:30,560 --> 00:36:33,840 Speaker 2: suspect that there's real opportunity to for Australian New Zealand 681 00:36:33,840 --> 00:36:36,440 Speaker 2: to partner more and say let's hold hands across the 682 00:36:36,440 --> 00:36:39,319 Speaker 2: ditch and be able to see where we. 683 00:36:39,239 --> 00:36:40,520 Speaker 3: Can support each other at bit more. 684 00:36:40,520 --> 00:36:41,880 Speaker 2: And that's what I'm hoping we'll be able to do 685 00:36:42,040 --> 00:36:44,960 Speaker 2: this week too, because there's some real strengths in New 686 00:36:45,080 --> 00:36:47,440 Speaker 2: Zealand which we don't have in Australia. So I'm hoping 687 00:36:47,480 --> 00:36:51,200 Speaker 2: we can in my unofficial capacity as quantum enthusiasts, see 688 00:36:51,200 --> 00:36:53,440 Speaker 2: how we can make sure that we can link those up. 689 00:36:53,640 --> 00:36:57,520 Speaker 1: Yeah, and helping out Robinson Research Institute as an advisor. 690 00:36:57,520 --> 00:37:01,319 Speaker 1: I just had around seventy million in it into that organization. 691 00:37:01,560 --> 00:37:04,160 Speaker 1: So there is ye green shoots happening. 692 00:37:04,520 --> 00:37:05,680 Speaker 3: It's exciting times. 693 00:37:05,840 --> 00:37:08,000 Speaker 1: Thanks so much, Kathy, really appreciate you coming on the 694 00:37:08,000 --> 00:37:08,600 Speaker 1: business of Tech. 695 00:37:08,680 --> 00:37:09,279 Speaker 3: Lovely talking to you. 696 00:37:09,360 --> 00:37:17,680 Speaker 1: Thanks, thank you. So there you have it, some great 697 00:37:17,719 --> 00:37:22,640 Speaker 1: insights from Kathy Foley. Australia, as Kathy pointed out, has 698 00:37:23,080 --> 00:37:26,400 Speaker 1: a bit of runway. Thanks to its vast mineral wealth 699 00:37:26,880 --> 00:37:31,600 Speaker 1: to transition its economy away from fossil fuels, but it 700 00:37:31,680 --> 00:37:35,160 Speaker 1: faces many of the problems that we do. Most businesses 701 00:37:35,239 --> 00:37:38,400 Speaker 1: there are small and medium sized, so it's hard for 702 00:37:38,480 --> 00:37:40,920 Speaker 1: them to invest a lot in R and D and 703 00:37:40,960 --> 00:37:44,520 Speaker 1: cutting edge technologies that will define the twenty first century. 704 00:37:45,239 --> 00:37:48,080 Speaker 1: Australia is reviewing its approach to R and D to 705 00:37:48,320 --> 00:37:52,080 Speaker 1: address some of the issues holding back innovation in Australia. 706 00:37:52,640 --> 00:37:56,200 Speaker 1: That's a process we've just been through. The key takeaway 707 00:37:56,200 --> 00:37:59,600 Speaker 1: from Kathy from me is that areas like quantum tech 708 00:37:59,640 --> 00:38:05,560 Speaker 1: require a complex supply chain. No company or country can 709 00:38:05,600 --> 00:38:08,960 Speaker 1: do it all themselves, so that's an opportunity for New Zealand. 710 00:38:09,120 --> 00:38:12,040 Speaker 1: But as she said, you know, being really deliberate in 711 00:38:12,160 --> 00:38:15,120 Speaker 1: knowing where you can add value to that supply chain 712 00:38:15,680 --> 00:38:18,120 Speaker 1: and being able to articulate that to the government when 713 00:38:18,200 --> 00:38:21,600 Speaker 1: you ask for a taxpayer dollars is absolutely crucial. The 714 00:38:21,680 --> 00:38:25,560 Speaker 1: Robinson Research Institute were obviously really successful at that. Recently 715 00:38:25,600 --> 00:38:30,120 Speaker 1: they got seventy million dollars in funding for their superconducting 716 00:38:30,440 --> 00:38:34,600 Speaker 1: and magnetic research. CSIRO has been successful in making the 717 00:38:34,680 --> 00:38:38,000 Speaker 1: case for investment in the areas like quantum cybersecurity and 718 00:38:38,160 --> 00:38:41,960 Speaker 1: AI and has done a lot to improve the relationship 719 00:38:41,960 --> 00:38:45,759 Speaker 1: between the research sector and Australian businesses, so there are 720 00:38:45,800 --> 00:38:49,760 Speaker 1: some useful pointers there as our own reorganized research sector 721 00:38:49,840 --> 00:38:53,759 Speaker 1: with its new remit of supporting economic growth starts to 722 00:38:53,800 --> 00:38:56,239 Speaker 1: take shape. Thanks for listening to the Business of Tech. 723 00:38:56,239 --> 00:38:59,960 Speaker 1: If you found Cathy Foley's insights on innovation strategy, commercialized 724 00:39:00,520 --> 00:39:04,560 Speaker 1: and cross tasmin collaboration as interesting as I did, make 725 00:39:04,640 --> 00:39:08,200 Speaker 1: sure to share the episode and subscribe if you haven't, 726 00:39:08,280 --> 00:39:12,120 Speaker 1: on iHeartRadio or your favorite podcast app for more deep 727 00:39:12,160 --> 00:39:15,600 Speaker 1: dives into the business of tech. Next week, what's going 728 00:39:15,680 --> 00:39:19,000 Speaker 1: on in tech recruitment at the moment as AI becomes 729 00:39:19,120 --> 00:39:23,719 Speaker 1: pervasive in software developments, and what happens when AI is 730 00:39:23,840 --> 00:39:28,839 Speaker 1: tasked with analyzing your job application. That's next Thursday. I'll 731 00:39:28,840 --> 00:39:29,399 Speaker 1: catch you then.