Hey everyone, welcome back.
Ready for another deep dive?
Definitely.
Today we're gonna tackle something
that's been making headlines
and frankly, causing a bit of a stir.
We're talking deep-seek R1.
Ah, yeah, the AI that's got everybody talking.
And the market's reeling too.
You know, it really feels like
we're in the middle of a Sputnik moment right now.
You know, it's funny you say that.
I was just thinking the same thing.
With China launching this AI bombshell,
it feels like the US-China tech race
just went into overdrive.
Oh, absolutely.
I mean, look at what happened.
The US stock market lost like over a trillion dollars
in value the day deep-seek R1 dropped.
January 28th, to be exact.
Yeah, that kind of shock wave, you know?
That tells you we're dealing with something way bigger
than just another cool piece of tech.
It's not just a cool toy, is it?
I mean, let's break it down.
Deep-seek R1 is free, it's open source,
anyone can just tinker with the code.
It's performing as well as, if not better than,
the top US models, but here's the real kicker.
It was developed for a fraction of the cost.
Yeah, like less than 3% of what it took to build,
let's say, chat GPT.
Yeah, 3%.
I'm still trying to wrap my head around that.
Well, it's not just about the number itself, right?
It's what it signals.
Right.
It's a potential disruption of the whole AI landscape.
Imagine the implications.
Access to these really powerful AI tools
could become like totally democratized.
That could shake up the power dynamics
of the whole industry.
Right, so we're not just talking about one company
or one product, this is.
This is much bigger.
Yeah, this is a paradigm shift, maybe.
So who is this mastermind behind Deep-seek?
So that would be Liang Wenfang.
He's a former, get this, hedge fund manager,
who kind of embarked on this whole AI journey
back in 2021.
But here's the really fascinating part.
He stocked up, get this, on NVIDIA GPUs.
You know those high-powered chips, right?
Yeah, yeah.
He stocked up on those right before the US
imposed those export restrictions.
Like he knew, right?
Talk about being in the right place at the right time.
Almost like he had a crystal ball or something.
OK, but two months, two months to build Deep-seek R1
on a reported budget of like $5.6 million.
That's unheard of, isn't it?
Pretty much.
And that speed and efficiency, that's
what's really got everyone scratching their heads,
even among AI experts.
And it really comes down to a few key things.
You know, one of them being this mixture of experts approach
they've used.
Mixed of experts.
OK, break that down for me.
Sure.
So does Deep-seek have like a whole team of like,
you know, Brainiacs huddled in a room somewhere?
Not quite a room full of Brainiacs,
but you know, the analogy kind of works.
OK.
Instead of creating this one massive AI model,
they've designed Deep-seek with all these specialized modules.
Think of it like a university, right?
With different departments dedicated to specific subjects.
Got it.
You wouldn't go to your history professor
to try to solve a complex physics problem.
Right, right.
So Deep-seek is only activating the modules that
are relevant to a specific task.
Exactly.
Hence the efficiency.
Clever.
Right.
This targeted activation conserves energy, processing
power, and it ultimately reduces cost.
But they don't stop there.
They're also using something called distillation.
Distillation.
Like what you do with whiskey.
Well, in the AI world, distillation
is more about knowledge transfer.
Not so much about making spirits.
OK, all right.
Think of it like an apprenticeship
where a larger, more mature AI model helps train
these smaller, more specialized modules.
OK.
It's like a master craftsman passing down their skills
to the next generation.
I like that.
OK, so instead of starting from scratch,
they're leveraging this existing knowledge
to train these modules more efficiently.
Exactly.
And it's one of the reasons why they've
been able to achieve these really impressive results
with relatively limited resources.
Plus, they're very transparent about their chain of thought
reasoning, basically how the AI arrived at its conclusions.
Wait, hold on.
Transparent chain of thought reasoning?
That's a stark contrast to how some US companies are
approaching AI development, right?
It is.
Where they keep everything very hush, hush, very secret.
Very much so.
DeepSeek's open approach is really shaking things up.
It lets developers understand how the AI is making its decisions.
And that potentially could lead to more trust,
maybe faster improvements.
It's a gamble, but it seems to be paying off.
It's definitely sending shockwaves through Silicon Valley
from what I've been hearing.
Oh, absolutely.
Imagine you're a major player in the AI space, right?
And suddenly this competitor comes out of nowhere,
offering comparable performance for a fraction of the cost.
I mean, no wonder there's a bit of panic mixed with a scramble
to adapt.
I bet.
I read that OpenAI quickly made their GPT-3 mini-model free.
And there are even rumors that Meta is having some serious
internal discussions about their whole AI strategy.
Is this a turning point for the industry, do you think?
It could very well be.
That old playbook of building bigger, more expensive models,
that might not be the winning strategy anymore.
Interesting.
This can be the beginning of an era where the real value isn't
in the AI model itself, but in the applications built
on top of them.
OK, so less about the raw power and more about what you can
actually de-know with it.
Precisely.
That's a pretty interesting shift.
It is a fascinating development.
It's like the app store all over again.
Remember when Apple launched the iPhone?
The device itself, you know, cool.
But the real revolution was all the apps.
Oh, yeah, great parallel.
And just like with the app store, we
could see an explosion of creativity and innovation
in this new AI landscape.
AI-powered tools for everything.
Oh, yeah.
Education, health care, entertainment, productivity
even.
And these tools could be cheaper and more accessible
than ever before thanks to platforms like DeepSeek.
Exactly.
This is huge, especially for smaller businesses, startups,
even individual developers who just couldn't afford
to get into the AI game before.
Yeah, it's amazing.
But with all this talk about open source and accessibility,
there's a part of me that wonders,
what about the potential downsides?
What about the possibility of this technology being misused?
I mean, anyone can access and modify DeepSeek's code, right?
Yeah, no, that's a valid concern.
And it's something we need to be having some really serious
discussion about.
Open source AI has this incredible potential for good.
But like any powerful technology,
it can also be used for not so good things.
For sure.
And DeepSeek sends user data to China, right?
Some folks are raising some real concerns
about privacy and security.
I mean, we're not just talking about your favorite coffee
order here.
This could be some pretty sensitive personal data.
Oh, absolutely.
It's a really complex issue.
And it raises all these important questions about data
sovereignty, transparency, and ultimately, who
controls these powerful AI systems.
It's a balancing act, for sure, between harnessing
the potential of AI while safeguarding individual rights.
It's like we're at a crossroads.
Do we embrace all the potential benefits of open source AI,
even with the risks?
Or do we try to put the genie back in the bottle,
try to regulate it heavily?
I don't think there's an easy answer.
This is a conversation that needs to involve everybody,
policymakers, industry leaders, ethicists, the public,
everybody.
We need to really consider the potential consequences
of our decisions and work together
to create a framework that encourages innovation
while protecting our values.
You mentioned ethicists, which reminds me of something
I've been hearing more and more about,
the Thucydides trap.
What is that exactly?
And how does it relate to all of this?
Right.
So the Thucydides trap is a term.
It was actually coined by a political scientist
named Graham Allison.
OK.
And it refers to this historical pattern
where a rising power, like China, in this case,
challenges an established power, like the US.
OK.
And that rivalry often leads to conflict.
So are we saying that deep seek is the catalyst
for some real world conflict between the US and China?
That sounds a little dramatic, doesn't it?
I don't think it's about deep seek itself being a weapon
or anything.
But it's more of a symbol of this larger power dynamic.
Right.
The rapid advancements in AI, particularly from China,
are changing the global landscape.
Right.
And that shift, that could lead to more attention
in increased competition, for sure.
It's like a modern day space race.
But instead of rockets and satellites, it's AI.
Yeah.
Just like with the space race, you've got this competition
that can drive incredible innovation,
but it also carries this risk of escalation,
maybe even conflict.
Yeah, absolutely.
And that's why it's so important to encourage
dialogue, collaboration, and a sense of shared responsibility.
We need to figure out how to use AI for good, for everyone,
rather than letting it become a source of division or conflict.
For sure.
OK.
So we've talked about the big picture stuff,
the potential risks, the rewards.
But what about some specific ways
that deep seeks arrival is already
impacting industries and companies?
What are you seeing?
We're seeing a really wide range of responses.
Everything from cautious optimism to straight up panic.
Some companies are scrambling, investing heavily
in their own AI research and development.
Others are trying to figure out ways to integrate deep seek
into their existing workflows.
And then there are some who are just trying
to wrap their heads around it all.
What does it all mean for their business?
It's a lot to process, for sure.
I read an article about how some investors are starting
to question the valuations of some of these AI companies,
the ones that have been pouring billions of dollars
into developing their own large language models.
If deep seek can achieve similar results for pennies on the dollar,
what does that mean for the industry, right?
Yeah, it's a really good question.
We might see a shift away from this bigger is better mentality,
which has kind of dominated the AI landscape for a while now.
Efficiency, accessibility, those could
become the new buzzwords.
That's a pretty significant shift.
It is.
I'm sure some companies are feeling a little threatened
right now.
Oh, there's definitely a sense of disruption.
Yeah.
But disruption isn't always bad.
Competition can lead to innovation, right?
And ultimately, it's the consumers
who benefit from better, cheaper, more accessible products
and services.
OK, that's a good point.
I've also been hearing a lot about how
deep seek could really democratize access to these AI tools,
making them available to smaller businesses, startups,
individuals.
Yeah.
What are your thoughts on that?
Honestly, I think that's one of the most exciting aspects
of all of this.
Imagine anyone with a laptop and a good idea
can harness the power of AI.
They can create something amazing.
Yeah.
It reminds me of the early days of the internet.
Suddenly, anybody could build a website and share their ideas.
Right, right.
Exactly.
And just like the internet, the democratization of AI
could lead to this incredible explosion
of creativity and innovation.
Yeah.
New applications and solutions emerging
from all corners of the globe.
That's an inspiring thought, but let's not get too carried away.
Yeah.
It's important to acknowledge that there are also
potential downsides to this rapid democratization of AI.
Oh, totally.
I mean, we need to be mindful of the misuse, the bias,
the unintended consequences.
It's crucial that we develop ethical frameworks and safeguards,
especially as this technology gets
more powerful and ubiquitous.
For sure.
And speaking of unintended consequences,
one of the biggest concerns I keep hearing about
is AI's impact on jobs.
If machines can do more and more of the work that humays do,
what does that mean for the future of employment?
I mean, that's a big one.
That's the question that's been on everybody's mind
since the dawn of the Industrial Revolution, right?
Yeah.
That's a really complex issue, no easy answers.
So is this time different?
I mean, is AI going to lead to mass unemployment?
Or are we just going to see a shift in the types of jobs
that are in demand?
It's probably going to be a bit of both.
Some jobs are going to be automated.
That's inevitable.
But new jobs will also be created,
especially in areas that require creativity,
critical thinking, emotional intelligence,
those skills that are hard for machines to replicate.
So the key is to adapt, to learn new skills.
Absolutely.
We all need to embrace lifelong learning,
develop the skills that are going
to be needed in this new, rapidly evolving landscape.
So the future of work is going to be
about staying agile, adaptable, constantly learning
and evolving.
Precisely.
The folks who can embrace that mindset,
they're the ones who will thrive in the age of AI.
OK.
So we've covered a lot here.
The big picture, the risks and rewards,
the impacts on industries, on individuals.
But there's one more piece of this puzzle
that I think we need to explore.
The ethical considerations surrounding deep seek.
And really, the future of AI as a whole.
It feels like we're in uncharted territory here, you know?
Yeah.
With AI becoming so powerful, so accessible.
I mean, we've got to be asking some tough questions.
How do we make sure it's used ethically, responsibly?
It's not even just about preventing it from being
used for bad things.
We have to think about the unintended consequences too.
Even when AI is designed with the best intentions.
OK, give me an example.
What kind of unintended consequences?
Let's say AI-powered hiring tools.
OK.
They're supposed to make hiring more efficient,
remove human bias.
Right?
Right.
But what if the data that's used to train these systems,
what if that data is biased itself?
Ah, I see you're saying.
So the AI could end up perpetuating those biases,
maybe even amplifying them without us even realizing it.
Exactly.
And that's just one example.
We've got to be really careful about the data
that we're using to train these AI systems.
Right.
We need to be constantly monitoring
for any signs of bias, any unintended consequences.
It sounds like a whole new level of responsibility here.
Like, it's not just about writing the code anymore.
It's about understanding the impact of that code on society.
It's a whole new way of thinking for sure.
And it needs to be a team effort.
You know, the developers, the ethicists, the policymakers,
even the public.
We need to create guidelines, frameworks, you know,
for developing and deploying AI ethically.
So this isn't just a tech issue.
It's a societal issue.
And we need to have these conversations now
before it's too late to course correct.
Absolutely.
We're at this, like, pivotal point.
The decisions we make today about AI,
they're going to echo for generations.
OK.
So let's say we get it right.
We manage to steer AI in the right direction.
What does that future look like?
Paint me a picture.
Imagine a world where AI helps us,
where it augments our abilities, helps us solve problems
we could never solve before, helps us make better decisions.
I like it.
Give me some specifics.
What kind of changes?
Think about health care.
AI could help us develop personalized medicine,
you know, to take diseases early, maybe even
discover new cures faster.
That would be incredible.
What about other fields?
Education.
AI could give every student a truly personalized learning
experience tailored to their needs.
Wow.
That's a game changer.
And what about, like, the environment?
AI could help us optimize our energy consumption,
cut down on waste, you know, develop more sustainable solutions
to climate change.
The possibilities are endless.
It's almost like a little overwhelming to think about.
It is.
But it's important to remember, AI is a tool, right?
Right.
It ends up to us how we use it, how we shape it,
how we make sure it's working for humanity, not against it.
This deep-seek moment, it's a wake-up call.
It's telling us that the future isn't set in stone.
We're creating it right now.
That's a great way to put it.
And AI is going to play a huge role.
It is.
This is a call to action for everybody, you know?
Engage the conversation, stay informed,
make your voices heard.
The future of AI, it's in our hands.
So if deep-seek is our sputnik moment,
the big question now is what will be our space race?
What kind of future will we choose to build
with this incredible technology?
It's something for all of us to think about.
I hope this deep-dyes gave everyone a better understanding
of just how complex this all is.
You know, deep-seek, the future of AI,
it's changing so fast.
It is, it is.
So keep those brain gears turning.
And join us again next time for another deep dive.