Let's talk about open source versus closed source AI.
Is one better than the other?
Is there a specific direction we should push towards to create AGI and ASI that benefits
humanity? Well, let's talk about it.
Welcome to the rabbit hole.
My name is Julia McCoy and I explore everything around AI, AGI, robotics, and the
future of automation.
I believe that we're living in an AI age.
We're headed towards a future that is hard to imagine, one we've never lived in before.
We are literally living in future as it unfolds.
Technology is ten axing every six months, and we're going to finally have the ability
to live more meaningful lives with robotics, AI and automation.
Doing 98 to 100% of the work we didn't really want to do anyway.
And we can get back to being humans.
We aren't human doings, we are human beings and AI, and the rise of technology to support
a breakthrough towards AGI will present humanity with the opportunity to not have to
be tied to work for a living.
So again, welcome to the rabbit hole.
As we get into today's topic, open source versus closed source AI is one better than
the other? Can we function with both?
What should the direction be?
Let's talk about what I'm reading.
The better question is what am I watching?
I don't really watch a lot of TV unless it's a classic movie.
Something to do with technology, sci fi, the future, the history of or a spotlight on a
great person in history.
I just find much of TV a waste of brain space.
So I'm not on Netflix.
Instead, I'm usually on YouTube learning from a playlist like Peter Diamandis
moonshots, hearing interviews with leading technologists, reading books by these people
instead of picking up a movie or a show.
But the exception to that rule was with the new Netflix show Three-body problem.
And oh my God, this is probably one of my top five favorite TV shows.
Three Body Problem is based on an award winning Chinese novel called the same title,
The Three Body Problem.
I finished watching all eight episodes a few days ago.
This show had a ton of my favorite things all in it strong characters that pursued
opportunities to change the world for the better.
Even when there was a 0% chance of success.
Supercomputers in the size of protons.
Quantum entanglement VR worlds created so incredibly lifelike you could see, smell,
taste, feel everything that happened in that world.
I mean, these are incredible pieces of imaginative storytelling, and they were all
found in this story.
But like most fiction tales, guess where the supercomputer in the size of a proton came
from? I'll give you a second.
You might have guessed it.
Aliens. The scientist an alien race in outer space that made contact with Earth through a
Chinese scientist who went through horrific trauma as a young adult, witnessing her
father's death and then being dragged away to a Chinese prison camp.
She became full of hate for all of humanity and knowingly made contact with a hostile
alien race, inviting them down to invade Earth.
Some of my favorite characters in the show were Thomas Wade and Jen Chang.
Thomas Wade is this old, brazen, uncouth British intelligence superior who just says
it like it is throws in a few offensive words.
I really like him.
Jen Chang is a young Chinese scientist who is incredibly brilliant and basically hacks
science to come up with a project she calls Project Staircase, where for the first time
in humanity, she gets a moving shuttle almost to the point of traveling at 1% of
light speed. The show, much like the book, doesn't really end on a high note.
The book is actually a more negative and paints the picture of the death of humanity
thanks to the alien supercomputers and technology.
What I love that the show did is it actually ended on a high note.
Jen, Chang and Saul are sitting around a pool.
Their project completely failed.
They're looking at the Santee alien race invading Earth in the next 400 years.
Knowing this, they feel pretty down.
Clarence, one of the British intelligence officers, says, come on, I've got something
to show you. And he takes them to a swamp where they see the proliferation of hundreds
of thousands of locusts.
And he says, while these bugs swarm all around them, you know, the aliens called us
bugs, which they did.
Santee took over everyone's phone billboards, and they named the human race
bugs. The Clarence says as he looks at that swamp full of locusts.
We have sprayed these things with pesticides.
We've covered the ground with poison.
We've stomped on them.
But look, they have managed to not just survive, but thrive.
There is hope for us after all.
This is a good perspective to have with what's coming with AI and AGI, which, by the
way, did not come from an alien race.
It's the result of multiple breakthroughs in technology and computing.
On the sky from some alien ship.
When Lama three, an open source AI, was released by meta this month, April 2024,
here's what Mark Zuckerberg said on Daksh Patel's podcast when he was asked about the
dangers and risks of open source versus closed source.
I part of the reason why you make this open source is that there are a lot of other
people who study this too.
So yeah, we want to see what other people are observing, what we're observing, what we
can mitigate, and then we'll make our assessment on whether we can make it open
source. But I think for the foreseeable future, I'm optimistic we will be able to.
And in the near term, I don't want to take our eye off the ball of what our actual bad
things that people are trying to use the models for today, even if they're not
existential, but they're like, they're like pretty bad kind of day to day harms that
we're familiar with and running our services.
That's actually a lot of what we have to, I think, spend our time on.
And here's what Ilya Sutskever, the chief scientist of OpenAI, said when he was asked
the same question should we focus on open source versus closed source?
But there is another Longer-Term argument against open sourcing as well, which is if
one believes that eventually AI is going to be unbelievably powerful.
If we get to a point where your AI is so powerful, where you can just tell it, hey,
can you autonomously create, I don't know, a biological research lab, autonomously do all
the paperwork, rent the space, hire the technicians, aggregate the experiments, do
all this autonomously.
Like that starts to get like mind bendingly powerful.
Should this be open sourced also?
So my position on the open source question is that I think that there is a maybe a level
of capability you can think about these neural networks in terms of capability, how
capable they are, how smart they are, how much can they do when the capability is on
the lower end?
I think open sourcing is a great thing.
But at some point, and you know, there can be debate about where the point is.
But I would say that at some point the capability will become so vast that it will
be obviously irresponsible to open source models.
The points that both Ilya and Mark make are completely valid.
Mark makes a great point that with open source, we have the ability to take in the
input of more humans and create a more diverse AI mind, so to speak.
But the risks are what people will do with this technology.
Ilya makes a great point that the more powerful the AI is, the more we actually need
closed source systems.
If we look at the definition of open versus closed source AI, OpenAI is when the source
code, algorithms and data are openly available to the public.
Openai ChatGPT itself is one example.
Closed source refers to AI systems where algorithms and data are proprietary and
they're not openly shared with the public.
These are commercial products built for use, potentially even inside of another product
like Siri. Inside of an iPhone.
Open source AI fosters innovation and collaboration.
Closed AI gives the opportunity for more security around these systems, quality
control over development and maintenance, and a consistent, reliable user experience.
I think that's something David Shapiro said when he talked about this on his YouTube
video is 100% true.
We should be optimizing for research, much like that scene in episode six where Thomas
Wade brings Jen Chang into a room full of old, archaic thinking scientists, and she
hacks science right in front of them and gets a ton of doubt.
She says it's our job to worry about the goal, someone else's job to worry about the
money. Basically, what that means is let's achieve innovation at all costs.
Let's accelerate and hit massive breakthroughs that we've never hit before as
a human race. And so if we optimize for research, well, we need both.
We need both open source, allowing for a ton of collaboration between bright minds, not
necessarily just big commercial players like Microsoft, meta, Google, but the
entrepreneur, the coder, the programmer at home that has innovative ideas.
But we also need closed source AI.
I work at continental scale.
It's a proprietary AI SEO writer built to generate content that ranks, well, original,
deeply researched, fact based content.
It's an incredible product with thousands of users.
We don't allow anyone to jump in that code and tamper with it, because then it would
mess with the quality of that product.
We have dedicated engineers, our own founder, our AI director work on this
technology themselves, and we keep the quality deliverable high, something our
founder, Justin McGill, said when I asked him this question is open source or closed
source better?
Is there one that is better?
He pointed out the need for closed source.
If we allow every Joe Schmo to mess with AI, there's a lot of danger in that.
Let me know what you think in the comments.
I'd love to hear your perspective on this.
I think as we rapidly.
Accelerate towards AGI and ASI.
Automating human labor.
We're gonna need resources and innovation and breakthroughs in both directions.
Open and closed source AI.
And if you've watched Three-body problem, let me know in the comments.
You're my people.
That was an incredible show.
Subscribe to my channel Julie McCoy.
For more videos like this where we explore the rabbit hole of AI.
I'll see you back here.