1 00:00:00,280 --> 00:00:02,400 Hi, and welcome to the Neil Ashton Podcast. 2 00:00:03,080 --> 00:00:05,920 In each episode, we explained some of the fascinating ways 3 00:00:05,920 --> 00:00:09,080 that science and engineering are changing the world around us. 4 00:00:09,800 --> 00:00:12,760 We talked to leading engineers from elite level sports like 5 00:00:12,840 --> 00:00:16,880 cycling and Formula One to some of the world's top academics to 6 00:00:16,880 --> 00:00:20,450 understand how fluid dynamics, machine learning and 7 00:00:20,450 --> 00:00:23,000 supercomputing are bringing in a new era of discovery. 8 00:00:23,960 --> 00:00:27,080 We also hear some of their life stories, their career advice, 9 00:00:27,640 --> 00:00:30,080 the lessons they've learned on the way that I hope will be 10 00:00:30,080 --> 00:00:33,840 helpful to you too. So sit back and enjoy this 11 00:00:33,840 --> 00:00:40,840 episode. Hi, and welcome back to the Neil 12 00:00:40,840 --> 00:00:44,440 Ashton Podcast. I'm mainly here to say sorry 13 00:00:44,440 --> 00:00:47,400 that I haven't put out an episode in quite some time. 14 00:00:48,000 --> 00:00:51,840 I've been a bit busy, to be completely honest, and that's 15 00:00:51,840 --> 00:00:54,240 because I actually changed jobs. 16 00:00:54,248 --> 00:00:59,050 I left Amazon Web Services, AWS after being there nearly five 17 00:00:59,058 --> 00:01:02,467 years and I joined NVIDIA about six weeks ago. 18 00:01:02,475 --> 00:01:05,640 And yeah, I've been, I've been pretty busy. 19 00:01:05,648 --> 00:01:10,224 It's been a super exciting though past sort of six weeks. 20 00:01:10,232 --> 00:01:13,666 Probably anybody who changes jobs will say it's, you know, 21 00:01:13,674 --> 00:01:19,478 stressful time, but I actually found it a a really good time. 22 00:01:19,486 --> 00:01:24,142 Maybe I'll just briefly say what I'm what I'm doing, just, you 23 00:01:24,150 --> 00:01:25,715 know, I guess if people are interested. 24 00:01:25,723 --> 00:01:31,290 So I'm I've joined NVIDIA as a Distinguished CAE 25 00:01:31,298 --> 00:01:35,320 (Computer-Aided Engineering) Architect, which I joined on 26 00:01:35,320 --> 00:01:39,480 the sort of product engineering side of of the business. 27 00:01:39,480 --> 00:01:44,880 So the side of the company that builds the builds, designs the, 28 00:01:45,040 --> 00:01:49,880 the, the, the GPUs and CPUs and also looks after the, the sort 29 00:01:49,880 --> 00:01:52,600 of software side of things to the CAE platform. 30 00:01:52,600 --> 00:01:56,000 And so that's the team that I'm joining, but I'll have a 31 00:01:56,000 --> 00:02:01,240 reasonably broad remit of trying to help, you know, the product 32 00:02:01,240 --> 00:02:06,740 teams, the marketing, the sales and be, I guess, the subject 33 00:02:06,740 --> 00:02:10,818 matter expert or domain specialist for, for, for CAE, 34 00:02:10,818 --> 00:02:15,904 which is super exciting because, you know, NVIDIA's doing a lot 35 00:02:15,904 --> 00:02:19,080 in many different areas. And it's a chance for me 36 00:02:19,080 --> 00:02:20,664 hopefully to contribute to them. 37 00:02:20,672 --> 00:02:24,822 You know, the things that I've learnt over my career and some 38 00:02:24,830 --> 00:02:29,322 of the projects that I'm engaged with and, and, you know, help 39 00:02:29,330 --> 00:02:32,328 them to deliver things, but also the other way around. 40 00:02:32,336 --> 00:02:34,972 It's really great for me to expand my knowledge, 41 00:02:34,980 --> 00:02:39,144 particularly obviously as GPUs are becoming more and more 42 00:02:39,152 --> 00:02:42,672 frequently used and, and also on the software stack. 43 00:02:42,680 --> 00:02:45,147 So I kind of like to challenge myself. 44 00:02:45,155 --> 00:02:50,000 And certainly getting more into the the computer science side of 45 00:02:50,000 --> 00:02:53,734 things, I guess is particularly appealing to me. 46 00:02:53,742 --> 00:02:57,718 But also it's no secret that I've been doing a lot of work in 47 00:02:57,718 --> 00:03:01,220 the AI side. And you know, for obvious 48 00:03:01,228 --> 00:03:04,992 reasons, NVIDIA is pretty good at the AI stuff and is used by 49 00:03:04,992 --> 00:03:06,774 many people for the AI side of things. 50 00:03:06,782 --> 00:03:09,896 So it's been great to, yeah, to expand myself there. 51 00:03:09,904 --> 00:03:14,860 I was lucky enough to go out to the headquarters in Santa Clara 52 00:03:14,860 --> 00:03:19,230 a couple of weeks ago. So it's kind of funny actually, 53 00:03:19,230 --> 00:03:24,062 to go back to the Bay Area. The Bay Area, by the way, being 54 00:03:24,062 --> 00:03:26,974 the place, the Bay to the South of San Francisco. 55 00:03:26,982 --> 00:03:29,072 I guess all of it's technically the Bay Area. 56 00:03:29,080 --> 00:03:31,612 But when, whenever I say the Bay Area, it's Silicon Valley, 57 00:03:31,620 --> 00:03:35,216 although I sort of feel a bit weird saying Silicon Valley 58 00:03:35,224 --> 00:03:38,667 sounds a bit odd to say it, but they're based there. 59 00:03:38,675 --> 00:03:42,995 And it's great to go back actually, because, you know, I 60 00:03:43,003 --> 00:03:48,031 was there 10 years ago, living there for a short time when I 61 00:03:48,039 --> 00:03:51,568 was at NASA Ames. And I, I remember that was for a 62 00:03:51,568 --> 00:03:54,520 British person going out to California and going to Silicon 63 00:03:54,520 --> 00:03:56,820 Valley. I saw all these, you know, tech 64 00:03:56,820 --> 00:03:59,798 companies and I often did wonder, you know, would I ever 65 00:03:59,806 --> 00:04:02,937 join a company like that? At that time, it didn't seem 66 00:04:02,937 --> 00:04:05,170 like my path would ever lead me there. 67 00:04:05,178 --> 00:04:10,518 So it's funny to be back 10 years and now be working for one 68 00:04:10,518 --> 00:04:15,026 of the big companies in that area and be going there, I guess 69 00:04:15,026 --> 00:04:17,820 more towards the middle of my career. 70 00:04:17,827 --> 00:04:21,500 It was kind of a funny feeling going, you know, driving around 71 00:04:21,500 --> 00:04:25,282 that area and walking around. And of course, it's nice to get 72 00:04:25,282 --> 00:04:29,943 a bit of sun in January because it's been very gloomy in the UK. 73 00:04:29,943 --> 00:04:32,120 So I went over there and yeah, 74 00:04:32,120 --> 00:04:35,640 everyone's been great. It's a fantastic company, lots 75 00:04:35,640 --> 00:04:39,000 of super talented people and a really nice culture. 76 00:04:39,000 --> 00:04:41,760 This is not a sales for them. This is just my honest opinion. 77 00:04:41,800 --> 00:04:44,280 It's, it's genuinely, it's been great. 78 00:04:44,400 --> 00:04:48,080 Met loads of nice people, you know, engaged in customer 79 00:04:48,080 --> 00:04:50,880 meetings and things like that. So that's why I've been a bit 80 00:04:50,880 --> 00:04:55,360 preoccupied. And there's quite a big event 81 00:04:55,720 --> 00:04:57,560 coming up. It's called GTC. 82 00:04:57,560 --> 00:04:59,600 So it's NVIDIA's main conference. 83 00:04:59,920 --> 00:05:04,640 I guess a bit like AWS has re:Invent and Microsoft has 84 00:05:05,560 --> 00:05:07,320 Ignite or something. I can't remember what it's 85 00:05:07,440 --> 00:05:08,960 called. Every company, you know, Siemens 86 00:05:08,960 --> 00:05:11,400 has Siemens Realize LIVE. Ansys has something else. 87 00:05:11,800 --> 00:05:13,880 So this is the NVIDIA thing and it's in March. 88 00:05:13,880 --> 00:05:15,960 And so it's always a bit crazy leading up to it. 89 00:05:16,600 --> 00:05:19,000 I'm actually going to be going out there again for that. 90 00:05:19,000 --> 00:05:23,120 So if anybody listens to this, watches this and is going to be 91 00:05:23,120 --> 00:05:25,040 at GTC, then please come and say hello. 92 00:05:25,400 --> 00:05:27,600 It'd be great to, to, to speak to people. 93 00:05:28,440 --> 00:05:30,040 But yeah, that's why I've been a bit busy. 94 00:05:30,680 --> 00:05:34,440 But the good news is I will be continuing the podcast and I 95 00:05:34,440 --> 00:05:37,760 have already some really interesting guests lined up to 96 00:05:37,760 --> 00:05:42,600 finish off this season. And and I'm going to take a 97 00:05:42,600 --> 00:05:47,720 little bit of a break then to sort of get re-energised and get 98 00:05:47,720 --> 00:05:51,790 some stuff recorded and prepared for the third season and to 99 00:05:51,790 --> 00:05:55,570 make sure that I don't have this embarrassing gap of time when 100 00:05:55,570 --> 00:05:59,640 I basically was just a bit manic to go and record and and 101 00:05:59,640 --> 00:06:01,960 interview people. So I just, yeah, had to take a 102 00:06:01,960 --> 00:06:03,720 bit of a break. But I thought I should come on 103 00:06:03,720 --> 00:06:07,249 here and at least tell you that I'm sorry for not putting out 104 00:06:07,249 --> 00:06:09,280 any new episodes. And at least, you know that I'm, 105 00:06:09,480 --> 00:06:11,880 you know, still around and still working. 106 00:06:13,000 --> 00:06:15,320 I'm still, you know, going to be as engaged with all the 107 00:06:15,320 --> 00:06:20,000 community projects that I've been really, you know, proud of 108 00:06:20,000 --> 00:06:23,914 doing, like AutoCFD, like the high lift workshops, like some 109 00:06:23,914 --> 00:06:27,360 of the AI dataset stuff. These are all activities that I 110 00:06:27,360 --> 00:06:32,200 will be continuing at NVIDIA and have even more of a remit to, 111 00:06:32,240 --> 00:06:34,800 you know, go out there and hopefully do some really good 112 00:06:34,800 --> 00:06:39,080 things for the community. But also very keen to to hear 113 00:06:39,800 --> 00:06:42,920 what people think are the next topics and engage and try and 114 00:06:42,920 --> 00:06:45,440 look what's around the corner. That always interests me. 115 00:06:45,920 --> 00:06:49,534 That's obviously why I've done so many episodes around the AI 116 00:06:49,534 --> 00:06:53,324 side and there'll be some more stuff around the quantum side of 117 00:06:53,324 --> 00:06:57,232 things as well that I'll be talking to some guests on and, 118 00:06:57,232 --> 00:06:59,080 and really the rest is down to you. 119 00:06:59,120 --> 00:07:03,240 I'd love to actually hear what episodes and what topics and 120 00:07:03,240 --> 00:07:05,680 what sort of things you would like to hear. 121 00:07:06,560 --> 00:07:09,760 Yeah, Let me know either on LinkedIn or YouTube or whatever 122 00:07:09,760 --> 00:07:12,160 mechanism you want. Yeah. 123 00:07:12,160 --> 00:07:14,451 Tell me what sort of stuff interests you, what you've 124 00:07:14,451 --> 00:07:17,980 liked, what you didn't like, and I'll try to make these 125 00:07:17,980 --> 00:07:19,960 episodes as interesting as possible. 126 00:07:19,968 --> 00:07:23,669 But for now, yeah, Please be patient and and thank you. 127 00:07:23,677 --> 00:07:26,520 If you are listening to this and you haven't completely stopped 128 00:07:26,528 --> 00:07:29,920 listening to these podcasts, there are quite a few episodes 129 00:07:29,928 --> 00:07:32,980 maybe to go back and listen to. I mean that's probably anybody 130 00:07:32,988 --> 00:07:35,862 who's watched or listened to this will know most of them are 131 00:07:35,862 --> 00:07:38,080 in the one hour to two hour mark. 132 00:07:38,088 --> 00:07:42,310 So if you whilst maybe if you're waiting for new episodes to 133 00:07:42,318 --> 00:07:45,755 come, I'd encourage you to go in the back catalogue and maybe try 134 00:07:45,755 --> 00:07:48,480 and listen more of those episodes if you didn't get to 135 00:07:48,480 --> 00:07:51,610 listen to the whole thing because, yeah, I left them 136 00:07:51,618 --> 00:07:54,415 long-form so you could really get the full story. 137 00:07:54,423 --> 00:07:56,624 But I appreciate that they're sometimes a bit difficult to 138 00:07:56,632 --> 00:07:59,424 listen to all in one go. So maybe this is a good 139 00:07:59,432 --> 00:08:02,439 opportunity to do it. And like I said this now, there 140 00:08:02,439 --> 00:08:04,372 will be some more episodes coming soon. 141 00:08:04,380 --> 00:08:07,720 But in the meantime, yeah, thanks for thanks for listening 142 00:08:07,720 --> 00:08:10,012 to this and following this podcast. 143 00:08:10,020 --> 00:08:14,562 I really do appreciate the the fact that you're doing it and 144 00:08:14,570 --> 00:08:17,224 any, you know, the nice feedback I've had from people. 145 00:08:17,232 --> 00:08:20,880 But yeah, sorry for not being so good at putting them out, but 146 00:08:20,888 --> 00:08:22,100 there will be more in the future. 147 00:08:22,108 --> 00:08:25,730 So with that, hope you had a good start to the year. 148 00:08:25,738 --> 00:08:28,040 And yeah, speak to you all soon.