All right, so get this, imagine like you're trying to build software, but the tools you're
using are like constantly changing, like while you're using them.
Yeah.
That's kind of the world that OpenAI is working in right now.
Yeah, definitely.
And we dove into, you know, the stack of articles and research you gave us, even that transcript
from the tech conference.
And it feels like the future of AI is a lot like that quote we found.
Okay.
The technology floor is not fixed.
It is a fascinating time to be a part of the AI world.
It really is like building on shifting sand.
Oh, wow.
Because what's possible is changing so rapidly, it's kind of hard to wrap your head around.
Really?
Yeah.
Okay, so we have this transcript from Peter Dang, right?
Yeah.
And he's worked at some pretty big companies, right?
Twitter, Instagram.
He's got quite a resume.
And now OpenAI, talking about a career trajectory.
I know, right?
But he actually says that OpenAI doesn't always know what their AI can do until like…
Until it's ready, yeah.
…until the model's fully baked.
Is that…
Baked, yeah.
…is that normal?
It feels like baking a cake and you don't know if it's chocolate or vanilla until you
take a bite.
Yeah.
It's more common than you might think in the AI world these days.
Really?
Especially with these newer models that are coming out.
Okay.
Yeah.
And Dang really highlights that traditional tech usually has, you know, a relatively stable
base to build on.
Right.
And with OpenAI, that base is constantly evolving, always changing.
Okay.
Yeah.
And so he even says it can feel like a guessing game sometimes.
So it's less about having like a detailed roadmap and more about…
Exploration.
…exploration and experimentation.
Hey.
So it's…
That's gotta see what sticks.
Yeah.
And that kind of feeds into another point that Dang makes about the speed at which AI
is becoming, you know, both cheaper and more powerful at the same time.
Okay.
And he uses the example of GPT-3 versus GPT-4.
And he was saying that in under two years, GPT-4 became significantly more capable.
Wow.
And the cost to run it dropped by like 99%.
Seriously?
Yeah.
That's the kind of exponential progress that we're talking about here.
That's like saying that your monthly software subscription just got practically free.
Right.
But it also does 10 times what it used to.
Exactly.
What does that kind of leap even mean for developers who are using this?
I mean, it's a game changer.
It unlocks so many possibilities.
Dang was talking about how AI is becoming more accessible to, you know, a wider range
of developers and applications.
And it's impacting fields like education and healthcare.
Wow.
Even travel in ways that we could only dream of a few years ago.
Yeah.
And it's not just theoretical anymore either.
Right.
Because Dang mentions using ChatGPT as a real-time translator while he was traveling in Seoul
and Tokyo.
Oh, wow.
That's real-world impact right there.
That's incredible.
Yeah.
And he says that's just the start.
Really?
Yeah.
He says we're moving towards AI that goes beyond just answering questions to actually
completing complex tasks.
Like what?
Think like, you know, AI personal assistants that can handle multi-step projects.
So like booking a whole trip for you?
Yeah.
Or like writing a podcast script?
Maybe Dang emphasizes this shift from AI as a tool to AI as a collaborator.
Collaborator.
Yeah.
Imagine interacting with AI the same way you brainstorm with a colleague, right?
That natural back and forth.
That's what he says we need to be aiming for.
So are we talking about like designing the personality of AI?
Kind of.
That's a little spooky, isn't it?
It's interesting.
He talks about user experience and how it's not just about making AI smarter.
Yeah.
But it's also about making it more human-like in its interactions.
So meaning what?
Like response times?
Yeah.
How it thinks through problems, even its tone?
All of that.
Okay.
So he does make AI more like us in how it interacts and how it problem solves.
But Dang also worked at companies like Twitter and Instagram, which are much more like established
tech companies.
And he talks about the difference in pace of development between those companies and
OpenAI.
He does.
Yeah.
He says that the biggest contrast he's seen is this constant state of flux at OpenAI.
Yeah.
Like changing all the time, you know?
So imagine being an engineer and the ground rules of your work are changing every few
months.
Oh, wow.
That's wild.
Yeah.
That's like trying to build a house while the blueprints are still being drawn.
It really is.
How do you even begin to create a product roadmap in that kind of environment?
That's a great question.
Yeah.
And it's something that Dang really grapples with.
He says that often OpenAI doesn't have like this crystal clear roadmap because they're
discovering new capabilities of their models all the time.
Oh, wow.
Even during the development process.
So it's less about let's build feature X and it's more about like...
It's like let's see what this thing can do and then figure out what to build.
And see what it can do.
Okay.
He uses the term iterative to describe how they approach building products.
They release a model.
They see how people use it, see what works, what doesn't work.
Okay.
And then they refine it.
So they're constantly like adapting and iterating based on real world feedback.
Yes.
Which makes sense given what we talked about earlier, right?
About how the technology floor is always shifting.
Always.
But that also must be a challenge when it comes to like monetizing these products.
Yeah.
Right.
Huge question.
If you're constantly iterating, the landscape is changing so rapidly, how do you build a
sustainable business model around that?
That's what everybody's trying to figure out.
And Dang even admits that OpenAI doesn't have all the answers yet.
He says that traditional approaches like advertising premium subscriptions might not translate very
well to the world of AI.
Especially if the goal is to make AI more accessible.
Exactly.
It's hard to imagine charging a hefty subscription fee for something that's supposed to be as
ubiquitous as like email.
The internet.
Yeah.
Exactly.
So it raises some really interesting questions about the future of AI, how it's going to
be funded and governed.
Yeah.
If AI is going to be this transformative force, we can't just leave it up to market forces
to decide how it's developed and who benefits from it.
Dang seems to agree.
He stresses that we need to start thinking now about the economic and social structures
that will shape the future of AI.
He says it's not just a technological challenge, it's a societal one as well.
Okay.
So big picture stuff aside, let's get back to like the tech for a second.
Dang talks about a new open AI model called O1.
Yes.
What's so special about it?
It's really fascinating.
Okay.
It gives us a glimpse into the future of AI.
Dang describes O1 as a completely different kind of model.
Really?
Yeah.
He says it goes beyond just retrieving information.
It actually reasons through problems almost like a human would.
Wait, hold on.
Is O1 actually like thinking on its own?
Thinking.
Is there just enough sci-fi movies to know how that usually ends?
Yeah.
Not well.
Yeah, not quite like in the movies, at least not yet.
Okay.
But Dang says O1 operates more like a detective solving a case, you know?
Okay.
It forms hypotheses, tests them against its knowledge base.
Wow.
And then kind of refines its thinking based on the results.
So it's like...
Imagine doing that.
And constantly going back to the drawing board?
Exactly.
But at lightning speed.
Wow.
On a massive scale.
Okay.
And a little intimidating at the same time.
Right.
How do you even build something that can reason like that?
I mean, it's incredibly complex.
Yeah.
But Dang explains that one of the key breakthroughs with O1 is its ability to handle those like
multi-step reasoning tasks.
Multi-step, okay.
Yeah.
He gives this example of a senior lawyer who used O1 to draft a legal brief.
Right.
Something that would usually take hours.
Right.
O1 was able to do it in minutes.
Whoa.
Yeah.
So it's huge.
It's a big deal.
And not just for lawyers.
Right.
But for like anyone who works with complex information.
Yeah.
Anybody who has to, you know, analyze data, look for patterns, make decisions.
It has huge implications.
Okay.
So Dang sees O1 as like a glimpse into this future.
Yeah.
Where AI isn't just answering our question.
It's like actively collaborating with us.
Working alongside us.
On these really complex projects.
Yeah.
So we're talking like...
AI partners.
Okay.
So does that mean that robots are taking our jobs?
Well...
Like seriously, what does this kind of AI mean for the average person?
I mean that's the big question, right?
Dang acknowledges that there is the potential for disruption in the workforce.
Okay.
But he's optimistic overall.
Okay.
He believes that AI will ultimately create new opportunities.
Okay.
You know, free us up from these tedious tasks.
Right.
And focus on the things that require, you know, creativity and critical thinking.
Things that AI isn't quite ready for.
Okay.
I can get behind that, but it also sounds like we've all got some learning and adapting
to do.
For sure.
Like to stay ahead of the curve, so to speak.
Lifelong learning is going to be more important than ever.
But Dang's advice is really interesting.
He says instead of, you know, being afraid of what AI can do, focus on what it can't
do yet.
Okay.
Because those are the areas where humans will continue to add unique value.
So like find the gaps and then build your expertise there.
Yeah.
So I like that.
And remember what we talked about earlier, that technology floor.
Yeah.
Constantly shifting.
Right.
So what AI can't do today, it might be able to do tomorrow.
Wow.
Yeah.
So just staying curious, adapting to new tools and ways of thinking, that's going to be key.
This entire deep dive has been a wild ride, let me tell you.
I know, right?
We've gone from AI that translates languages in real time to AI that can draft legal documents
in minutes.
It's incredible.
My head is spinning.
Mine too.
And we've just scratched the surface.
Just the beginning.
The future of AI is full of possibility.
Endless possibility.
It's going to be fascinating to see how it all unfolds.
It really is.
And if this conversation is any indication, it's definitely not going to be boring.
I agree.
So for our listeners out there, keep exploring those what if questions because the future
of AI is being written right now.
And who knows?
Maybe you hold the key to the next breakthrough.
You never know.
Until next time, happy exploring.