-: I'm interested if you could expand a little bit
on the community of coders online,
because I know like through, in my research in AI
and everything, you know, I'm discovering really how
there's this like open source network of people,
who are all chipping in helping each other,
which is so cool because it's like this subsect of humanity
that seems like it's like working really well,
and being really kind and supporting each other,
and like putting their time into investing serious time.
And you know, my projection of coders is always like,
is people that you know, can make a lot of money.
You know, it's a pretty valuable skill.
So it's like in a sense, it's a valuable,
in a sense, it's like valuable time is being spent for free,
just for the betterment of society one could say,
or at least experimenting in different things.
And I'd be curious if you could touch on that aspect
a little bit. Like where do you think some of the hubs
for this community is, and what is kind of the mentality
as an insider for the open source thing?
Because it's wild to me and it's sad that it's wild,
but it's wild to me that so many people are willing
to just chip in kind of for free,
for no like, conceivable gain that they get
except for like making something cool,
which like one would hope that that's all
that humans cared about, but it doesn't seem
to be that way all the time.
-: Well that's one of the wonderful things that this whole,
you know, learning to code and learning to think about code
is such an on-ramp too. Because when you can do that,
we've seen already in the course material that, you know,
when as you're working, you often use libraries or modules
or packages that come in from outside,
and you're saying you might ask chat GPT,
oh, I need, is there a Python package that, for example,
gives me a framework for developing little desktop apps?
Like Kivy, which is one of the ones we used in the class.
Things like that, so often are maintained
by the open source community, and it happens
because somebody somewhere or maybe a couple of people
had to solve that problem, and they thought,
well, I've been writing all these little apps,
I'm duplicating a lot of code.
I'm gonna write some tools for myself
that establish a little framework
that I can use quickly and whatever.
I'm gonna throw it out on GitHub and open source it.
'Cause I don't, that's not what I'm making my money off of.
I'm making the money building the apps.
So I'll just throw that framework out there
so that people can use it. And the gain is enormous
because what we've seen over the long development
of the open source community is that as soon as you do that,
someone else that comes along and says,
oh, well that's a problem I've been trying to solve
for a while. And they Google around.
They maybe see some forum posts that say,
hey, I used kivy and it worldly sped me up.
There's a couple of features that it doesn't have,
but it may, you know, help you out.
So you then as the next coder in line, you think,
well that's great. Kivy does 80% of what I want it it to do.
And I understand the language it was written in.
How about I add like the next 10%
to get what I need it to do. And I'll just contribute it
so that other people can use it.
Because again, that's not what I set out to do.
It's just the tool that I'm using
to get from point A to point B.
And so as people use the tools
and take a little time to improve them
for their own benefit, all they're doing is saying,
well, I'm not gonna keep that benefit to myself.
I'm gonna share that out because the things I'm using
to build it with are mine, but this tool
that I got from the community,
well I'm gonna give back to the community,
and I'm gonna make it that much better because I needed it.
And so someone else will too.
And that's this altruistic kind of spirit
that I've really enjoyed about contributing to open source
and interacting with that community.
And once you can write the code, you can do it.
You know, there's no barrier to entry there,
other than knowing how to make something better
and deciding to go do it. So it's just,
it's such an entry point learning to do this.
You can start participating in this very,
very large community and taking some code where you need it,
giving back some code when you think
it would help somebody else. It's, you know,
thousands, tens of thousands of people worldwide
are doing this every day. And so many more of them
are just contributing here and there,
using a project once in a blue moon, you know,
and whether you have a little time
to give it to it or a lot, it's all improvement.
It all helps. So it's just, it's great to watch
and it's even better to be a part of.
-: That's so cool. I've heard a little bit about, you know,
'cause I'm deep, I'm deeply invested in the AI space,
and you know, I'm always reading
and just figuring out like, what's coming,
what's happening in the news there.
And I keep reading that there's, you know,
there's the big corporations that are all gonna have
their language models and everyone's doing their own thing.
And then there's the open source language models.
And I think Meta has opened, has released one model
to be adaptable and modified by the open source community.
And a lot of people were saying,
oh, well open source is for sure gonna overtake Google
and the corporations, et cetera,
because there's the amount of work that will go in
is more than money can buy. And I find myself
like I'm not sure about that.
Like, I'd like to believe that, I mean like,
that sounds cool, that it's like, okay,
that open source there will be more innovation quicker
because more people are working on it all the time.
And I'm like, is that, I'd be curious
to know what you think. Do you think the open source models
like Stable diffusion, they do have a serious chance
as far as that community essentially outpacing open AI
and Google, and some of the larger corporations out there?
-: I think it's very possible, especially with the kind
of moment that AI is having,
where so many people are attending to it,
and really, really wanting to invest
in the way it's going to change the world
because it is already demonstrably changing the world.
It's changing in the way we relate to information.
It's making tremendous data sets human accessible again,
where the growth of data has outpaced our ability
to actually, you know, be a person and understand
all of the ramifications of it. But this as an intelligent,
aggregation tool, is something that brings that back
into the realm of comprehensibility.
You know, it makes it accessible again.
There's such a lot of really valid
and really well motivated interest in that
from all quarters. And I think the really interesting thing
about letting open source communities get their hands
on it, there are two things.
One is that the variety of use cases,
the broad number of things that people are going to want
to have this do for them will automatically, organically,
vastly outpace the number and the diversity
of use cases that are going to happen
when these models sit in a sort of walled garden,
and are used by single organizations,
and trained by those single organizations.
So that's one place where we're going to see
open source bring a very, very different track
of development to it. And the other thing
that I think is worth mentioning at this point,
is the idea of AI security and AI safety.
Where these open models, where you can see the code,
provides a layer of community accountability
that won't be there in situations where the code is private,
and it's just the interface, the information
that you're getting in, that you're putting in
and getting out, that is visible to the community.
And because of that, I think there will be a preference
when it's available to use these open tools
simply because you can see what you're getting,
you know, what's in there. And I think that that's something
that it's really worth mentioning
and giving a little thought too, because this is.
As we, as people give up a little bit of the control
of how we're filtering that information,
how we access pieces, you know, data sets, and a world
that is too large for us to confront on our own,
how we relate to those tools as intermediaries,
and how we expect them to behave and how we can validate
that those expectations are realistic,
becomes incredibly important to our own sense of agency,
and to their sense of autonomy.
So being able to really look at that
and say, oh, I know the community developers
that worked on this, I know how they're keeping themselves
accountable and more than that, I know that I can see
the code that's out there, that we're looking at.
And, you know, it makes sense.