Hi, and welcome to the Neil Ashton Podcast.
In each episode, we explained some of the fascinating ways
that science and engineering are changing the world around us.
We talked to leading engineers from elite level sports like
cycling and Formula One to some of the world's top academics to
understand how fluid dynamics, machine learning and
supercomputing are bringing in a new era of discovery.
We also hear some of their life stories, their career advice,
the lessons they've learned on the way that I hope will be
helpful to you too. So sit back and enjoy this
episode. Hi, and welcome back to the Neil
Ashton Podcast. I'm mainly here to say sorry
that I haven't put out an episode in quite some time.
I've been a bit busy, to be completely honest, and that's
because I actually changed jobs.
I left Amazon Web Services, AWS after being there nearly five
years and I joined NVIDIA about six weeks ago.
And yeah, I've been, I've been pretty busy.
It's been a super exciting though past sort of six weeks.
Probably anybody who changes jobs will say it's, you know,
stressful time, but I actually found it a a really good time.
Maybe I'll just briefly say what I'm what I'm doing, just, you
know, I guess if people are interested.
So I'm I've joined NVIDIA as a Distinguished CAE
(Computer-Aided Engineering) Architect, which I joined on
the sort of product engineering side of of the business.
So the side of the company that builds the builds, designs the,
the, the, the GPUs and CPUs and also looks after the, the sort
of software side of things to the CAE platform.
And so that's the team that I'm joining, but I'll have a
reasonably broad remit of trying to help, you know, the product
teams, the marketing, the sales and be, I guess, the subject
matter expert or domain specialist for, for, for CAE,
which is super exciting because, you know, NVIDIA's doing a lot
in many different areas. And it's a chance for me
hopefully to contribute to them.
You know, the things that I've learnt over my career and some
of the projects that I'm engaged with and, and, you know, help
them to deliver things, but also the other way around.
It's really great for me to expand my knowledge,
particularly obviously as GPUs are becoming more and more
frequently used and, and also on the software stack.
So I kind of like to challenge myself.
And certainly getting more into the the computer science side of
things, I guess is particularly appealing to me.
But also it's no secret that I've been doing a lot of work in
the AI side. And you know, for obvious
reasons, NVIDIA is pretty good at the AI stuff and is used by
many people for the AI side of things.
So it's been great to, yeah, to expand myself there.
I was lucky enough to go out to the headquarters in Santa Clara
a couple of weeks ago. So it's kind of funny actually,
to go back to the Bay Area. The Bay Area, by the way, being
the place, the Bay to the South of San Francisco.
I guess all of it's technically the Bay Area.
But when, whenever I say the Bay Area, it's Silicon Valley,
although I sort of feel a bit weird saying Silicon Valley
sounds a bit odd to say it, but they're based there.
And it's great to go back actually, because, you know, I
was there 10 years ago, living there for a short time when I
was at NASA Ames. And I, I remember that was for a
British person going out to California and going to Silicon
Valley. I saw all these, you know, tech
companies and I often did wonder, you know, would I ever
join a company like that? At that time, it didn't seem
like my path would ever lead me there.
So it's funny to be back 10 years and now be working for one
of the big companies in that area and be going there, I guess
more towards the middle of my career.
It was kind of a funny feeling going, you know, driving around
that area and walking around. And of course, it's nice to get
a bit of sun in January because it's been very gloomy in the UK.
So I went over there and yeah,
everyone's been great. It's a fantastic company, lots
of super talented people and a really nice culture.
This is not a sales for them. This is just my honest opinion.
It's, it's genuinely, it's been great.
Met loads of nice people, you know, engaged in customer
meetings and things like that. So that's why I've been a bit
preoccupied. And there's quite a big event
coming up. It's called GTC.
So it's NVIDIA's main conference.
I guess a bit like AWS has re:Invent and Microsoft has
Ignite or something. I can't remember what it's
called. Every company, you know, Siemens
has Siemens Realize LIVE. Ansys has something else.
So this is the NVIDIA thing and it's in March.
And so it's always a bit crazy leading up to it.
I'm actually going to be going out there again for that.
So if anybody listens to this, watches this and is going to be
at GTC, then please come and say hello.
It'd be great to, to, to speak to people.
But yeah, that's why I've been a bit busy.
But the good news is I will be continuing the podcast and I
have already some really interesting guests lined up to
finish off this season. And and I'm going to take a
little bit of a break then to sort of get re-energised and get
some stuff recorded and prepared for the third season and to
make sure that I don't have this embarrassing gap of time when
I basically was just a bit manic to go and record and and
interview people. So I just, yeah, had to take a
bit of a break. But I thought I should come on
here and at least tell you that I'm sorry for not putting out
any new episodes. And at least, you know that I'm,
you know, still around and still working.
I'm still, you know, going to be as engaged with all the
community projects that I've been really, you know, proud of
doing, like AutoCFD, like the high lift workshops, like some
of the AI dataset stuff. These are all activities that I
will be continuing at NVIDIA and have even more of a remit to,
you know, go out there and hopefully do some really good
things for the community. But also very keen to to hear
what people think are the next topics and engage and try and
look what's around the corner. That always interests me.
That's obviously why I've done so many episodes around the AI
side and there'll be some more stuff around the quantum side of
things as well that I'll be talking to some guests on and,
and really the rest is down to you.
I'd love to actually hear what episodes and what topics and
what sort of things you would like to hear.
Yeah, Let me know either on LinkedIn or YouTube or whatever
mechanism you want. Yeah.
Tell me what sort of stuff interests you, what you've
liked, what you didn't like, and I'll try to make these
episodes as interesting as possible.
But for now, yeah, Please be patient and and thank you.
If you are listening to this and you haven't completely stopped
listening to these podcasts, there are quite a few episodes
maybe to go back and listen to. I mean that's probably anybody
who's watched or listened to this will know most of them are
in the one hour to two hour mark.
So if you whilst maybe if you're waiting for new episodes to
come, I'd encourage you to go in the back catalogue and maybe try
and listen more of those episodes if you didn't get to
listen to the whole thing because, yeah, I left them
long-form so you could really get the full story.
But I appreciate that they're sometimes a bit difficult to
listen to all in one go. So maybe this is a good
opportunity to do it. And like I said this now, there
will be some more episodes coming soon.
But in the meantime, yeah, thanks for thanks for listening
to this and following this podcast.
I really do appreciate the the fact that you're doing it and
any, you know, the nice feedback I've had from people.
But yeah, sorry for not being so good at putting them out, but
there will be more in the future.
So with that, hope you had a good start to the year.
And yeah, speak to you all soon.