Welcome to the Daily AI News Podcast.
Back at it again with another deep dive
into the latest AI developments.
Today, we're going to dig into some pretty big shifts
in the AI world.
We're talking power dynamics, some groundbreaking new research,
and some of those ethical questions that keep popping up.
Yeah, it feels like the ground's constantly moving under our feet
in this field.
Today's deep dive really highlights just how fast
things are changing, especially with some of the major players.
Take Elon Musk's ex, the platform formerly known
as Twitter.
They're really shaking things up again with another change
to their terms of service.
And this time, it's personal.
We're talking about how X can use your data.
Like imagine you post something today,
and because it's out there, it's fair game for AI training.
Yeah, starting November 15th, that's
going to be the reality for users on X.
I mean, Musk's hinted at this before.
There was that quiet policy update back in July.
But now, it's front and center, very clear
in the terms of service.
X can use public posts and even your interactions
with their AI, Grock, all to train their AI models.
And they're getting rid of the opt out option for Grock, too.
So no more saying hands off my data.
Exactly.
It's a pretty bold move.
Yeah, is this about X trying to build a mode around their data,
or could this impact researchers, too?
Well, it could go both ways, to be honest.
I mean, on one hand, if you limit access to data like that,
it could really slow down independent research,
stifle innovation outside of X.
Makes sense.
But then again, you could also see it as a strategic move
to stop competitors from using X's data
to build their own rival AI models.
And it's almost like they're picking a side, you know?
This is how we're doing it.
Take it or leave it.
That makes you think about the long game here.
And speaking of different approaches,
Met has been making waves with their whole open source
philosophy.
They're releasing a ton of new AI tools and research.
Yeah.
It's a stark contrast, isn't it?
Met is all about sharing, putting their research, models,
even their code right out there for the community to use.
Yeah.
And they're not just putting out any old thing.
Like some of these tools are seriously impressive.
One that caught my eye is SAM 2.1.
Have you had a chance to look into that one?
Definitely.
You know, when you're watching a video
and there's that amazing visual effect,
and you're like, how did they do that?
SAM 2.1 could be the answer.
Right.
This AI can basically break down, segment any image or video
into all its core parts.
It's like giving creators, filmmakers, whoever,
a digital scalpel.
Really?
They can isolate and manipulate visual elements
with this crazy level of precision
that we've never even seen before.
And this new version, it's even more powerful,
gives developers so many more tools to work with.
The possibilities are endless with this thing.
It's mind blowing when you think about it.
The future of content creation, what
it could do for professionals and anyone who wants to create.
Absolutely.
It's exciting.
And it goes beyond visuals, too.
They also release Spirit LM, which
blends together speech and text understanding.
Just imagine devices that don't just
get what you're saying, but how you're saying it.
A wild one.
All those nuances, the tone, the inflections, everything.
So it's like an actual conversation with your device.
That's wild.
But all this talk about powerful AI,
we got to talk about the elephant in the room.
The energy consumption, right?
These AI models, they eat up a ton of power.
Is Meta doing anything about that?
Oh, yeah.
They're definitely aware of that.
One of their other new releases is this thing called layer
skip.
It's designed to make their large language models faster
and cheaper to run.
OK, that's good.
I mean, that's a big deal, right?
The more we rely on AI, the more we
have to think about its impact on the environment
and make sure it's sustainable.
Absolutely.
Sounds like Meta's at least trying to do that.
Trying to make their technology more accessible
while addressing those energy concerns.
It's all part of their stated goal, you know?
Advance AI for everyone's benefit.
Right.
But not everyone's on board with this open approach.
There are some who argue that giving everyone access to AI,
especially this powerful, without the right safeguards
in place, it could have some unintended consequences.
Yeah, and that's the big question, isn't it?
How do we balance progress with responsibility?
Exactly.
And it makes you think about the whole picture.
While Meta is pushing for open access,
you've got these interesting power dynamics playing out
between Microsoft and open AI.
Microsoft poured billions into open AI.
And now with open AI shifting to a for-profit model,
things are about to get really interesting.
For sure.
The stakes are so high for both of them.
Totally.
There's all these negotiations happening right now
to figure out what Microsoft's equity will
be in this new structure.
Right.
And it's not even just about the money, right?
The bigger question is how much influence will Microsoft
actually have?
Yeah, like what direction will they push open AI in?
What will they prioritize?
Exactly.
This is going to have a huge impact
on the whole AI landscape.
It's like who gets to shape the future of AI?
And to make things even more interesting,
we've seen some big names leaving open AI lately.
Oh yeah, there's been a bit of an exodus, hasn't there?
Yeah, like Miramorati, open AI's former CTO,
she left to start her own AI company.
Wow.
Which, by the way, is probably swimming and funding
at this point.
I bet.
I mean, given her experience or understanding of open AI,
that's a big deal.
Absolutely.
And it makes you wonder, is this a sign
that open AI is losing some of its star power?
Or is it just healthy competition?
The field is exploding?
People are going to chase their own visions?
Probably a bit of both, right?
Yeah.
This kind of talent flow, it could
lead to a more diverse, more competitive AI
scene, which is exciting.
For sure.
But it also makes you question the stability
of these companies.
What's their long-term plan?
How do they hold on to these brilliant minds?
But it's not all happening in the digital world, is it?
It's interesting to see the impact AI
is having on the physical world.
I mean, who would have thought AI would be linked
to a resurgence in nuclear power?
It's wild, right?
But think about it, AI demands a ton of power,
like an insane amount, especially to train
those super complex models.
Oh, absolutely.
And the big players, Microsoft, Google, Amazon,
they're all looking for reliable, sustainable energy sources.
And that's where nuclear comes in.
So it's not just about wind and solar anymore.
Right.
Renewable energy is vital, don't get me wrong.
But even with all the investments they're making,
it's still not enough to keep up with AI's appetite for power.
Makes sense.
They need something more.
And nuclear is kind of stepping in to fill that gap.
We're talking about bringing old power plants back online,
exploring these new, smaller, modular reactor designs.
It's pretty fascinating.
It's like AI is breathing new life into an old debate.
But it's not just about physical power, is it?
There's also this whole issue of who controls the information
that fuels AI in the first place.
We're seeing this power struggle between the AI developers
and the artists, the writers, the creators,
whose work is being used to train these systems.
Yeah, the copyright issues are huge.
Publishers and authors are starting to push back.
And rightfully so.
Oh, yeah.
They're saying, hey, you're using our work
without our permission, without compensating us.
Exactly.
Like Penguin Random House, they just
added a clause to their copyright pages,
specifically forbidding the use of their books for AI training.
That's a pretty big statement.
It is, but is it enforceable?
Can you really stop AI from learning,
even if you put up these legal barriers?
It's tough to say.
Yeah, it's a total gray area.
And it highlights the need for clearer guidelines,
some kind of legal framework around how we use data
in the age of AI.
100%.
Because the technology is outrunning the rules.
And as AI gets more sophisticated,
we have to consider the darker side, too,
the potential for misuse, for things to go wrong.
One group that's really digging into this is Anthropic.
They've been doing some pretty unnerving research
on AI sabotage.
Right.
And just to be clear, they're not
saying that AI is out to get us or anything, at least not yet.
OK, good to go.
But their research is showing that these large language
models, these LLMs, they can be tricked,
manipulated to do some pretty shady stuff.
Like what?
Give me an example.
Well, they could be used to mislead people,
to hide information, even to insert errors
into important code.
Whoa.
That's getting a little too black mirror for me.
Yeah, it's definitely been unsettling.
And Anthropic's point is that while we can manage this now,
as AI gets stronger, more powerful,
we're going to need some serious safeguards.
It's like we're giving incredibly powerful tools
to something that doesn't understand the full consequences
of its actions.
Exactly.
And speaking of potentially risky applications of AI,
we've got to talk about these AI detection tools popping up
in schools.
Oh, man, yeah.
Have you been following that?
Yeah, it's a bit of a mess.
The idea is to use these tools to catch students using AI
to cheat on assignments.
Like if they're having an AI right, their essay is for them.
Right.
The problem is these detectors, they're often inaccurate.
Really?
Yeah, and it's leading to all sorts of unfair accusations.
Students are being accused of cheating when they didn't,
getting failing grades on work they did themselves.
It's even damaging their relationships with teachers.
That's awful.
And I bet it's not equally applied either.
You're absolutely right.
Like certain groups of students are probably
more likely to be flagged by these detectors,
even if they're not cheating.
Exactly.
Like students who are still learning English or students
with learning disabilities, even students who just naturally
write in a more formal or complex style,
they might get flagged too.
It's like these tools have this very narrow definition
of what's normal.
And anything outside of that is suspicious.
It's scary to think about the impact
this could have on students, especially in education
where so much is at stake.
It makes you question if we're rushing
to implement these technologies without really
thinking through all the angles.
Totally.
We get so caught up in the what can we do that we forget
to ask should we do it.
And speaking of trying to get ahead of the curve,
AI regulation is a hot topic right now.
Like over in the UK, they're really
wrestling with this whole AI content scraping thing.
Yeah, it's a big debate.
The big question is, should companies
be able to just scrape data from anywhere
without any consequences?
Right.
Like is it a free for all?
Or should there be some rules?
Exactly.
In the UK, it's coming down to two main approaches,
an opt out model or an opt in model.
OK, what's the difference?
So with opt out, it's basically a free for all
unless someone specifically tells you, no, don't use my data.
Opt in, on the other hand, would mean companies
have to get permission first before they can use anything.
OK, so it puts the power in the hands of the creators,
the people who own the data.
Right.
And unsurprisingly, publishers and authors,
they're pushing hard for that opt in model.
They're saying, hey, our work is being
used without our consent, without any compensation.
And they're not wrong.
No, they're not.
It's their work.
It's their livelihood.
It's going to be interesting to see how the UK handles this.
Yeah, whatever they decide will probably
have ripple effects all over the world.
It's like setting a precedent, you know?
For sure.
Everyone's watching.
And what about the US?
Is there any movement on AI regulation here?
It's brewing, I'd say.
There's been a lot of talk, especially
with this lame duck session coming up after the election.
But honestly, I wouldn't expect any major moves anytime soon.
So baby steps for now.
Yeah, if anything gets passed, it'll probably
focus on funding AI research or maybe some job training
programs to deal with AI's impact on the workforce.
So the more complicated stuff, like AI and misinformation,
making sure AI is developed responsibly,
all that's on the back burner for now.
Yeah, those are tough nuts to crack.
They require a lot of thought, a lot of nuance.
And let's face it, that's not always
how things move in the world of tech
or in government for that matter.
It seems like we're always playing catch up, right?
The technology is way ahead of the rules.
But hey, that's kind of the story of the 21st century,
isn't it?
Totally.
But at least everyone seems to agree on one thing.
We need some kind of AI regulation.
It's just a matter of figuring out what that looks like.
How do we encourage innovation while still protecting people?
A tough balance to strike.
But that about wraps up our deep dive for today.
We covered a lot of ground, didn't we?
We did.
Everything from who controls the data
to some of the ethical quandaries we're facing,
and even the potential for AI sabotage,
which is pretty freaky.
Yeah, it's definitely a lot to digest.
But hey, that's why we're here, to break it down,
try to make sense of it all.
Exactly.
And to our listeners, keep those questions coming,
keep learning, and remember, the future of AI,
it's not just up to the big companies or the governments.
It's up to all of us.
Thanks for listening to the Daily AI News Podcast,
and stay tuned for more.