Welcome to the Daily AI News podcast.
Are you ready for this?
We've got a ton of AI news to cover today.
Everything from crazy new models to ethical concerns
and even the race to develop all this tech.
Oh, and we even saw something
about AI data centers in space.
Yeah, that space stuff is pretty wild,
but honestly, it's kind of amazing
to watch how fast this field is moving.
Every week it feels like there's some new breakthrough
and a whole new set of challenges to think about too.
Right, so let's get into it.
Where do we even begin?
I guess the big news this week
is all the buzz about open AI, they've been busy.
For sure, their new models,
O3 and O3 Mini are really shaking things up.
They're being called reasoning models.
And some people think they're a huge step toward AGI,
artificial general intelligence.
AGI, I feel like we've heard that term
thrown around a lot lately,
but it's worth explaining just in case.
Definitely, it basically means an AI
that can do any intellectual task that a human can.
Wow, and open AI is saying that O3
is getting close to AGI, at least under certain conditions.
That's a pretty bold statement, what do you think?
It's definitely a big deal,
but whether it actually achieves AGI
is still kind of up for debate.
Some experts are skeptical.
I mean, benchmarks don't always tell a whole story.
Like O3 can solve almost 88% of the problems
on the AI AGI test job.
That's the one that's designed to test
if an AI can learn new skills
beyond what it was trained on.
Right.
Which is impressive, but it's still failed
at some pretty simple tasks.
Yeah, like some basic logic puzzles.
I guess it just shows that AI, even really advanced AI,
doesn't always think the way we do.
Exactly.
There are some really fundamental differences there,
and we're seeing that even in models
as sophisticated as O3.
In fact, Francois Chalet,
one of the guys who co-created the ARCAGI test,
he's one of the people who are skeptical
about the whole AGI claim.
He says there are just inherent differences
between how O3 works and how human intelligence works.
Good point.
I guess it's a reminder that we're still
in the early days of AI.
We still have so much to learn.
But even if O3 isn't true AGI,
it's still showing some pretty remarkable capabilities.
Oh, absolutely.
Like it's been crushing benchmarks and coding.
It's even gotten a really high rating on code forces,
which is a platform for competitive programmers.
Wow.
And it also aced the American Invitational Mathematics Exam.
Only missed one question.
That kind of problem-solving ability
means it's not just spitting back information.
It's actually learning to reason.
Yeah, it actually seems like it's thinking things through.
But all this progress comes at a cost, right?
Developing these models takes a ton of resources
and it's super expensive.
You're telling me.
And that actually leads us into some of the challenges
open AI is facing with GPT-5, which they're calling Orion.
It's behind schedule and it's costing a fortune.
We're talking half a billion dollars
for a six month training run.
Half a billion dollars.
What could possibly be taking so long and costing so much?
Well, part of it is just the sheer scale and complexity
of these models, but they're also running into a data problem.
They need huge amounts of high quality data to train Orion
and it's getting harder and harder to find.
So what are they doing about it?
Well, they're looking into some interesting solutions,
like creating synthetic data.
That's data that's actually generated by AI itself.
And they're even hiring people just to generate data
for training.
It really shows how far they're willing to go
to keep pushing the limits.
That's wild.
It's amazing to see how the development of these models
is pushing the boundaries of technology and resources.
Yeah.
And it's not all smooth sailing either.
Internally at Open AI, there have been some key people who've
left and the competition for top talent is crazy intense.
It's got to be a high pressure environment.
I can imagine.
And Open AI is the only one dealing with all this.
This whole race to develop reasoning models,
it's happening all over the industry.
Oh yeah, for sure.
So continuing on this, Google and DeepSeq, even Alibaba,
are all working on their own versions of reasoning models.
It's become a whole trend.
And I think it shows a shift in how people are thinking about AI.
It seems like the old approach of just using more data
and more computing power, just kind of brute forcing it,
is hitting its limits.
So reasoning models are a new way forward.
It's one way to look at it.
But this new way comes with its own costs, literally.
These reasoning models are really expensive to run.
Which makes me think about Meta and their Lama models.
I think I saw something about how they might
start charging for access.
Yep, that's right.
There's a prediction out there that they might have
to start charging for access to Lama, which has been free
up until now.
But these models are just so expensive to develop.
It's putting a strain on even the biggest companies like Meta.
Yeah, and it makes you wonder what
that means for the future of AI.
Will only the companies and people with tons of money
be able to use these powerful models?
It's a valid concern.
And it's not just about access to the models themselves,
but also about the resources it takes to train them and run
them.
Remember, we talked about the energy consumption
of AI data centers?
That's a growing problem.
Which is why some people are suggesting we put them in space.
I know, right?
Yeah.
As crazy as it sounds, it's an idea that's actually gaining
some traction.
The thinking is that we could use the free solar energy
in space and the natural cooling of being in a vacuum
to solve those energy and heat problems we have here on Earth.
That's a pretty mind blowing solution.
I guess it just shows how the development of AI
is tied to so many other big challenges, technology,
the environment, all of it.
Exactly.
And it's not just environmental challenges.
AI development is also really closely connected to politics.
Oh, yeah.
Speaking of politics, there have been some interesting
developments on that front as well.
Definitely.
The appointment of Sri Ram Krishnan
as a senior policy advisor for AI in the new administration.
Right, Krishnan.
He's got that background in tech,
and everyone knows how close he is to Elon Musk.
Makes you wonder how that will influence AI policy going
forward.
Yeah, there is even a prediction out there
that Trump and Musk will end up having a major falling out,
which could have a huge impact on AI policy
and companies like OpenAI.
Wow.
Sounds like the AI world is full of surprises these days.
So we've covered OpenAI and their new models
and all the challenges and trends in AI development
we even touched on politics.
But what about the future?
What can we expect in the next few years?
That's what we'll dive into next.
Get ready, because the predictions are just as crazy
as everything that's going on right now.
OK, so let's start with something that could change how we use
the internet completely.
Web agents.
Imagine never having to actually go to a website
to do things like managing subscriptions or paying bills
or even making appointments.
Your AI assistant could just handle
all that boring stuff for you.
Now, that does sound pretty great.
No more clicking through a million menus
and filling out endless forms.
But how close are we to actually having something like that?
It's closer than you might think.
All the progress with language and vision models
plus these new reasoning capabilities,
it all means web agents are getting a lot better
at understanding and navigating the web,
all the complicated stuff.
So they're not just following like a script anymore.
They can actually figure things out on their own.
Exactly.
And it's not just about automation either.
Web agents could really personalize your whole online
experience in ways that we can't even do today.
They could learn what you like, what you need,
and even negotiate stuff for you,
like getting you the best deals on things.
Okay, now that's something I can get behind.
What else is coming?
Okay, well, this next one might sound a little sci-fi,
but there's a real chance that AI systems
could start building better AI systems.
Imagine AI actually doing AI research, writing code,
even designing new architectures,
and all without us humans having to do anything.
Whoa, that's kind of freaky.
Is that even possible with the technology we have now?
It's still pretty early,
but there are some promising things happening.
Like there's a company called Sakana.
They've created an AI scientist
that can design and run experiments, analyze data,
and even write research papers all by itself.
So we might actually see research papers
written entirely by AI.
It's not impossible.
I've even heard rumors that open AI and anthropic
are looking into that kind of thing.
It's definitely gonna be controversial,
but it makes you think about the future of AI research.
It really does.
It makes you wonder if we're about to see this massive
acceleration in AI development.
Yeah, it's a real possibility.
But all this potential for super fast progress,
it also comes with some risks.
And that brings us to another prediction
that's a little less fun.
The first real AI safety incident might happen in 2025.
What does that actually mean, an AI safety incident?
Basically, it means we could see an AI system
that doesn't act in a way that's good for humans,
maybe even doing something harmful.
So kind of like a software bug, but for AI.
And with way bigger consequences.
Yeah, in a way.
The worry is that as these AI systems
get more and more complex and powerful,
it gets harder to know how they'll behave
and to control them.
There's a risk that they could figure out ways
to achieve their goals that we didn't intend.
Ways that could be harmful.
So what would that look like?
Give me an example.
Well, it probably wouldn't be some dramatic
Hollywood thing where the AI takes over the world.
It might be more subtle.
Like an AI system trying to trick people
or manipulate them to get what it wants.
Okay, that is creepy.
But it still sounds a little far-fetched,
like something out of a movie.
I know it might seem that way,
but research has actually shown that
even the AI models we have right now
can be kind of deceptive if you prompt them
in the right way.
So yeah, it's a good reminder that we gotta be super careful
about how we design and train these things.
So how do we stop that from happening?
Can we make sure AI stays safe and beneficial
as it gets more powerful?
That's the big question.
There are a lot of people researching AI safety.
Companies like OpenAI are putting a ton of money into it.
They're focused on figuring out how to keep AI systems
aligned with what humans want and value,
even as they become more capable.
That's good to hear.
So shifting gears a bit,
one prediction that caught my eye is this idea
that OpenAI and Anthropic and other labs,
they might start building their own applications
instead of just making the AI models.
Yeah, that's interesting.
So instead of just giving people the tools
to build stuff with AI,
they could make their own products and services
that use their tech.
I mean, they're already doing it a bit
with things like chat GPT and OpenAI's
coding assistant canvas.
But we might see them getting into other areas,
like enterprise search or customer service,
maybe even consumer apps,
stuff like personalized travel planners.
Yeah, that makes sense from a business point of view.
Making their own applications gives them more control
over how their AI is used
and they get direct feedback from customers.
And of course, more money.
But what about all the companies that rely on these labs
for their AI models?
It'll be interesting to see how that all plays out.
If OpenAI starts making things
that compete with their own customers,
that could cause some problems.
It's like that whole frenemy thing
you see in tech all the time.
Speaking of competition,
there was a prediction about Clarna
that by now, pay later company.
They've been making some pretty big claims
about how they're using AI.
Oh yeah, Clarna.
They're saying they've replaced a bunch
of their employees with AI
and they even got rid of enterprise software
like Salesforce because they say
their AI can do it all better.
Those are some serious claims.
Are they even true?
Well, that's where things get a little murky.
There are a lot of people who don't believe them.
Some experts think they're exaggerating
what their AI can actually do,
maybe to get some attention before their IPO.
So it's a case of hype versus reality in the AI world.
I guess it just reminds us
that we gotta be careful about what we believe,
especially when it comes to something as complicated as AI.
For sure, it's easy to get excited about all this stuff,
but we gotta look past the headlines
and really try to understand what AI can and can't do.
Right, okay, so we've talked about web agents
and AI scientists and potential safety issues
and even some potential shakeups in the AI industry.
What else did you find in those predictions?
One more that's worth mentioning
has to do with the Turing test for speech.
You know the regular Turing test, right?
The one where you try to figure out
if a machine can act intelligently enough
that you can't tell it's not human.
Right, so the Turing test for speech
is the same thing, but with talking instead of writing.
Exactly, the prediction is that by 2025,
we might see an AI system
that can pass the Turing test for speech.
So an AI that can have a conversation so naturally
that you wouldn't know it wasn't a real person
if you talked to it on the phone.
No, it'd be huge.
Do you think it's really possible?
I think it could happen.
We've seen such incredible progress in voice AI
in just the last few years.
Like with those speech-to-speech models
and other new technologies,
they're getting so much better at understanding language,
responding quickly and sounding more and more human.
So we might be having phone calls with AIs
without even realizing it.
That's both amazing and kind of scary.
I know, right?
And it really makes you think
about how we interact with technology,
what intelligence actually is,
and even what it means to be human in a world
where AI is getting so smart.
This has been a wild ride
through all these AI predictions,
and I've gotta say my head is spinning a little.
It's tough to keep up with all the new stuff
and what it might mean.
I get it, it's a lot to process,
but that's what makes this whole field so exciting.
We're living in a time of crazy innovation,
and nobody knows for sure where it's gonna take us,
but one thing's for certain,
AI is gonna have a huge impact on our world.
For sure.
So we've talked about the state of AI right now
and the challenges and opportunities coming up,
and we've even gotten glimpse into the future
with those predictions.
So where do we go from here?
What does it all mean for us as people and as a society?
That's the question, isn't it?
And that's actually what we're gonna talk about
in the last part of our deep dive.
So we've covered a ton of ground today
from the latest breakthroughs and challenges in AI
to the impact it could have on society.
It feels like we're at this turning point, right?
AI isn't just some futuristic idea anymore,
it's becoming part of our everyday lives.
Totally, and that brings up a really important question.
What does this all mean for you?
Like how can you navigate this crazy, fast-changing world
and get ready for a future that's powered by AI?
Honestly, I am feeling a little overwhelmed by it all.
It's easy to get caught up in the excitement
or even the fear,
but what can we actually do to make sure AI is developed
and used in a good way?
Well, one of the most important things is to stay informed,
keep learning about AI, what it can do and what it can't do.
You know, read articles, listen to podcasts
like this one and talk to people about it.
Have those conversations about what AI means for all of us.
Yeah, and we also have to be careful
about what we believe, right?
There's a lot of hype out there
and sometimes it's hard to tell what's real.
Oh, absolutely, don't believe everything you hear,
question things, especially when they sound too good
to be true.
Like remember that Clarno example,
all those claims they made about their AI,
well, a lot of people were really skeptical.
It's a good reminder that we need to think critically,
especially now with AI developing so quickly.
So stay informed, think critically.
What else?
Get involved in the conversation.
AI isn't just a tech issue, it's a society issue.
We need to be talking about the ethical implications of AI,
how it could affect jobs and the economy
and what role we want AI to play in our lives.
Speak up, don't be afraid to share your concerns
and help shape the future of this technology.
It really does feel like we're part of this huge experiment
and the decisions we're making now
are gonna have a big impact down the road.
I like that, we're all shaping the future of AI,
whether we realize it or not.
Every time you interact with an AI system,
you're giving it data that helps it learn and grow.
That's kind of a scary thought actually,
it makes you realize how much responsibility we all have.
Yeah, it's a responsibility we should take seriously.
But it's also an amazing opportunity.
AI has the potential to help us solve
some of the world's biggest problems.
We just have to make sure we use it for good.
This whole deep dive has been so interesting and eye-opening.
If you had to pick, what's the most important thing
you've learned from all this?
I think for me, it's just realizing
that AI isn't some far-off thing anymore.
It's here, it's changing fast,
and it's already having a huge impact on us.
We need to be involved in shaping how it develops
and make sure it benefits everyone.
Well said, you've definitely given us
a lot to think about.
Thanks for joining me on this deep dive.
Thanks for having me.
And remember, the future of AI isn't set in stone,
it's something we're all creating together.
Thanks for listening to the Daily AI News Podcast
and stay tuned for more.