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 in Formula One to some of the world's top academics to
understand how fluid dynamics, machine learning, supercomputing
are bringing in a new era 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 the video as
a distinguished CAE. So computer, computer aided
engineering architect, which enjoyed 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 GP US 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 BI 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, the videos are 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 see 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 Reinvent and Microsoft has RE
ignition or something. I can't remember what it's
called. Every company, you know, Siemens
has Siemens realise 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 it's 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 in a
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 the auto CFDS, like the high lift workshops, like
some of the AI data set 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 at 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 array 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'd 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 is 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 listened to the whole thing
because yeah, I left them long forms so you could really get
the full story. But I appreciate that there are
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.