All right, everyone, so let me introduce our next speaker, my fellow Devroom, co-organized
and actually, a company's co-founder Tatiana Dada Shiva, who will be talking about some of
the interesting projects between hardware, software, and AI, so take it away, thank you.
So this is actually an AI application talk, which will not technically allow them this
Devroom, so since it's applied to AI Plum, and I guess it works, so if anybody wants
to do, then use the same LiveHard next time, you welcome.
So I haven't wanted to talk about load in the better fountains in different kind of hardware
development, and if you ask, how well, actually, I'd say as low as it gets, because I'm
not even an engineer, so I'm even worse, I'm CEO of hardware company, and if anybody
asks me, can I have a design hardware, now that it doesn't know, so how did I do that?
Well, in this particular case, and for the purpose of this discussion, I'll talk about how
to use AI to be helpful to your company when you know nothing, and what I do know, I do
know how to manage people, I do know how to kind of know when somebody's bullshit in
the company, and I wanted to use it all in the AI, and I absolutely am not here to produce
the best code ever, or be the smartest person in the room, I'm usually just for the result.
So what does it mean?
It means that I use code code, and absolutely shoots which double-nercarnities, but again,
for me, the model doesn't matter, usually don't even pay attention, which one clue chooses,
I'm not writing code myself, so it's not about being a copilot, and again, safety
matters, so especially if you're not in professional engineer, don't allow cloth mess up
your stuff, and it did start it to kind of motivate people in the company to use more
AI, but then, again, I figure out that there are so many ways that how people use AI,
so here are some questions that I suggest people to ask themselves, so I do use it in just
one instance of AI, and since we are, like as we discussed today, in the edge of open
core, I guess you should think twice if you use it on the one.
Do give the AI tasks like a bigger than junior developer can handle?
I know people who ask AI to just create a core and validate it, and do the whole design,
I don't believe in that, you should absolutely not do that.
Again, personal opinion, but pretty strongly hold, and I suggest, like, you think about
these questions, not going to focus on each one of them, but it's always good for lots of things,
but not for everything, so what do they do in my company?
So I think one of the good first examples is we got this novel, I accelerated a card, and then I said
in all, I mean, there was no documentation, and I didn't want to have the source code.
I mentioned years in the company, we are trying to figure out what is there, how to use it,
that is a win-work, and they have been trying to understand it all for a few weeks, and then
another insure of it works, and we've got code in about three hours and made it work, and again,
some ideas of how to use it, is asked to run just about every model you can, and you
can make conclusions as, like, what work, what dawn, what is the difference?
You can bring us that of human being, like, they would think about the structures, and this,
and that, and again, you can slow a lot of things and ask it to compare, to experiment.
It's basically we call it software at a college now, so when you have something you don't understand,
but you want to make it work. So that's one example, some important D files.
Another one, so we're doing a lot of open source efforts, and since again,
all the engineers in the company actually doing useful stuff, and I want an open source code to be nice,
and people be able to use it. So one of the ideas was, let's make it applicable.
So how do we do that? I got the cheapest of PGA as I could, so this, for example, was
a sprinkler, it cost, like, 80 bucks. I got a few others. So my knowledge of PGA actually
is very limited. It's limited to one hour talk. I've heard that the RISC file sent it,
and I've been able to port a couple of cores that are open already, and well documented,
and again, by comparing and contrasting, asking the I to basically figure out how to do it
for the next one that I happen to have. So that's another application. By the way,
I'm not the only one doing all of this. So this is our friend who basically
tweeted recently about exactly the same. So while some people are afraid to use the I,
others are asking them to figure out the path and put easy complicated tasks. So why and how does it work?
Actually, I'll quickly jump to this one. It's basically asking to find the solution,
experimenting a lot, comparing things, and treating everything as a system. So there are lots of
tools that appear actually, I didn't find any open source ones. But there are lots of tools
that allow you to kind of throw documentation with the white papers, whatever you have the
data sheets at the AI system like to and program the system. So if your system is open and
it's a system on the chip, you can do it a similar thing. So again, if you know any open ones,
that's another really interesting way to work with it all. But again, I'm not touching platform
blocks that would be other people talking about it. But if you have enough platform blocks,
yeah, it's a really good way to kind of free combine them, experiment with them, and basically
allow us people who have never done hardware developments that are doing that. Thank you.