I'm interested if you could expand a little bit on the community of coders online, because I know like
through in my my research in AI and everything, you know, I'm discovering really how there's 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 subset of humanity that seems like it's like.
Working really well and being really kind and supporting each other and like and like putting their
time into investing serious time.
And, you know, my, my projection of coders is always like people that, you know, can 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, 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, where do you think some of the hubs for this community is and, and what what is kind of
the, 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 onramp to 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 you might ask ChatGPT, 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, in the class.
Um.
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
going to write some tools for myself that that establish a little framework that I can use quickly and
whatever.
I'm going to throw it out on GitHub and open source it because 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 what we've seen over the long development of the open source
community is that as soon as you do that, someone else 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 use Kivy and weirdly sped me up.
There's a couple of features that it doesn't have, but it may help you, 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 to do.
And I understand the language that was written in.
How about I add like the next 10% to get what I need to what I needed 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 going to keep that benefit to myself.
I'm going to 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 going to give back to the community and I'm
going to make it that much better because I needed it.
And so someone else will too.
And that's that's this this altruistic kind of spirit that that I've really enjoyed about about contributing
to open source and interacting with that community.
And once you can once you can write the code, you can do it.
You know, there's no 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 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 a, you know.
Thousands, tens of thousands of people worldwide.
Uh, 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 to it or a lot.
It's all improvement.
It all helps.
So it's just it's great to watch.
It's even better to be a part of.
That's so cool.
Um, I.
I've heard a little bit about, um, you know, because 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
and the news there.
And I keep reading that there's, you know, there's the big corporations that are all going to have
their, their language models and everyone, everyone's doing their own thing.
And then there's the open source language models.
And I think Meta has opened, um, has released one model to be adaptable and, and, and modified by,
by the open source community.
And a lot of people were saying, oh well open source is for sure going to overtake Google and the corporations
etcetera because there's the, the amount of work that will go in is more than money can buy.
And I, I find myself like I'm I'm not sure about that.
Like I like to believe that I mean like that sounds cool that it's like, okay the 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 model's like stable diffusion?
They do have a serious chance as far as that community essentially outpacing OpenAI and 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 world.
It's changing 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 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 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 the 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 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 that I think is is worth mentioning at this point is the idea of AI security.
And 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 it's just the interface, the information that you're getting in and 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 that's something that it's really worth mentioning and giving a little thought
to because this is.
As we as as people.
Give up a little bit of the control of how we're filtering that information, how we access pieces,
you know, datasets 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 our sense of autonomy.
So being able to really look at that and say, Well, I know the community of developers that worked
on this, I know.
How they are 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 it's it makes sense.