All right, so get this, we're diving into Google's AI
co-scientist today.
And it's not just about number crunching.
This AI is straight up collaborating
on some big time scientific breakthroughs.
It's wild.
We're talking potential game changers,
even if you don't have a science degree.
We've got research papers, articles, all that jazz.
Yeah, what's really mind blowing about AI co-scientist
is that it tackles a huge problem in science right now.
Researchers are just drowning in information.
Oh, absolutely.
I mean, just look at leukemia research,
a quick Google scholar search pops up over 2.6 million results.
I mean, come on, how could anyone even
begin to make sense of all that?
Exactly.
It's totally overwhelming.
So while there are tools out there,
like deep research from OpenAI to help summarize all this stuff,
they don't actually come up with new ideas on their own.
And that's where AI co-scientist steps in.
So it's not just about analyzing what we already know.
It's about generating completely new hypotheses,
new paths for research.
That's pretty incredible.
It really is.
And it does this through what's called a multi-agent system.
OK, so break that down for me.
Basically, imagine a bunch of AI specialists,
each with their own specific role, all working together.
So like, what a virtual scientific dream team.
Exactly.
Some are all about generating ideas.
Others are evaluating and ranking them
and even refining the best ones.
Then you've got an agent dedicated to making sure
there's no redundancy, no repeated suggestions.
So it's got checks and balances built right in.
Right on.
There's even a meta review agent that
analyzes the patterns and insights from all the data.
And here's the kicker the whole system learns and improves
constantly, even incorporates feedback from us,
human scientists.
Wow, so it's a truly dynamic process,
a real collaboration between AI and humans.
Pretty amazing.
But you know what really blew my mind?
The actual results.
So let's talk about that leukemia research I read,
that AI co-scientist was tasked with finding existing drugs
that could be repurposed to treat leukemia.
Yeah, and it did.
The AI identified several promising drug candidates.
And what's really wild is that these were then
tested in a real lab.
And did they work?
Like actually work?
They did.
Scientists found that the drugs identified by AI co-scientists
actually inhibited leukemia cell activity.
Think about that traditional drug discovery
can take years, even decades, AI co-scientists
spit up the process big time.
That's huge, especially for patients and their families
waiting for new treatments.
It gives me chills.
But it doesn't stop there, right?
There's the liver fibrosis story too, isn't there?
Oh, absolutely.
Liver fibrosis is a really serious condition,
could eventually lead to liver failure.
And even cancer AI co-scientists was
tasked with finding new targets for treatment.
And did it succeed?
It did.
It really did.
It pinpointed several totally new targets.
And when those were tested using human liver cells,
they were effective in reducing fibrosis.
Wow.
So another potential game changer for tackling
a really tough disease.
OK, but this next one, this is where
it gets really interesting for me.
The whole antibiotic resistance thing
that AI co-scientists just figured out on its own.
This one really shows the power of thinking AI.
You see, for over a decade, scientists
have been researching this key factor in antibiotic resistance
called CFIIs.
They were getting close to some big conclusions,
but hadn't published anything yet.
And AI co-scientists cracked it independently.
It did.
And here's the crazy part.
It reached the same conclusions in just two days
compared to like a decade of human research.
Two days?
Seriously, that's just, I don't even know what to say.
It's like having a research assistant that never sleeps
and processes information at warp speed.
It is pretty incredible.
It really makes you wonder, though,
about this whole idea of thinking AI.
It sounds like something straight out of, I don't know,
Star Trek.
Can you break that down a little?
Sure.
It all comes down to what's called test time compute.
So traditional AI models, like, say, GPT-4,
they give you an answer almost instantly,
super fast at processing, but they don't really
like think things through.
So they're all reacting, then contemplating.
Exactly.
Reasoning AI models, like AI co-scientists,
they actually take their time to think before giving an answer.
And the more compute power you give them,
the longer they can think and the better their results.
So like giving them more brain power.
Exactly.
And get this AI co-scientist has actually
been shown to outperform even Google's own top models,
like Gemini 2.0 Pro and Gemini 2.0 Flash Thinking,
at least in certain tasks.
Wait, hold on.
It's outperforming Google's own AI.
Come on, that's insane.
It's pretty remarkable.
And in some cases, it's actually surpassing human experts,
too.
Wow, so they measured the novelty of the ideas, right?
And the actual impact.
And AI co-scientists is consistently coming out on top.
That's right.
I mean, that's mind-blowing.
We're at a point where AI can actually
exceed human's capabilities in scientific discovery.
That's incredible.
If this is what's possible today,
what does the future even look like?
It really makes you think.
It really does.
And that's exactly what we'll be exploring
in the next part of our deep dive.
We'll talk about what this thinking AI could
mean for the future of scientific discovery and beyond.
I can't wait.
OK, so we just finished talking about how AI co-scientists
is even beating human experts in some areas.
It's really kind of crazy to think about what
this whole thinking AI thing could
mean for the future of scientific discovery.
I mean, where do you even begin to imagine the possibilities?
Oh, right.
It's a total game changer.
We could be talking about speeding up breakthroughs
in pretty much every field, from medicine to materials
to climate change research.
It makes you wonder, right?
Like, if AI co-scientists is doing this much already,
what's it'll be capable of in like five, 10, 20 years?
The potential is, I mean, it's mind blowing.
Imagine a world where AI is working with scientists
to cure diseases like Alzheimer's or Parkinson's,
or even figure out how to slow down aging.
Think about that.
Whoa.
OK, yeah, it's almost like we're about to enter
this whole new era of science and AI is leading the way.
But hold on a sec.
This kind of rapid progress, it kind of raises some questions
too, doesn't it?
Like, what happens to the role of scientists
if AI can do some things better than they can?
Right.
And that's something we definitely
need to think about carefully.
But you know what?
I think AI, just like all the other big tech
revolutions before it, it's going to create more opportunities
than it eliminates.
So instead of replacing scientists,
AI will become like a really powerful tool that
helps them do even more.
Exactly.
Think of it as like a shift in skill sets.
You know, the scientists of the future,
they're going to need to know how to work with AI,
understand its strengths and weaknesses,
and guide its research in the right direction.
Gotcha.
So it's not AI versus humans.
It's AI and humans teaming up to achieve
like crazy, amazing things.
Exactly.
And who knows what breakthroughs this partnership could
lead to, like personalized medicine based
on your unique DNA or totally sustainable energy solutions
that change how we power the whole planet?
OK.
Yeah, those are some seriously exciting possibilities.
Seems like AI could help us tackle some of humanity's
biggest problems.
But let's get back to AI co-scientists for a minute.
We talked about drug discovery and antibiotic resistance.
But is it showing promise anywhere else?
Oh, totally.
Researchers are exploring its potential in material science.
OK, how so?
Imagine AI designing brand new materials
with crazy properties, like way lighter, way
stronger, more sustainable than anything we've got now.
Oh, I see.
That would change everything from buildings to cars
to like everyday stuff.
Right.
And that's just one area AI co-scientists
is also being used to explore new avenues in renewable energy,
environmental science, even space exploration.
Wow, the possibilities are kind of endless, aren't they?
Feels like we're on the edge of a scientific revolution.
We are.
And it's a revolution driven by collaboration, humans
and machines working together, different scientific fields
coming together, researchers all over the world sharing ideas.
It's this collaborative spirit that's
going to allow us to really unlock the potential of AI
to benefit everyone.
It's pretty exciting to think about all that.
But we can't forget that any new tech comes
with responsibility, right?
Like, how can we be sure that something like AI co-scientists
gets used for good and not for bad stuff?
That's a million dollar question and one
that's being debated right now.
We need clear ethical guidelines for developing and using AI.
Make sure it's transparent, accountable, and fair.
So it's not just about pushing boundaries.
It's about making sure those possibilities are actually
good for society.
Exactly.
And that takes a careful and thoughtful approach,
one that involves scientists, ethicists, policymakers,
and everyday people all working together.
Sounds like the conversation about AI is just getting started.
And it's a conversation we all need to be a part of.
We've covered a lot of ground today.
The inner workings of AI co-scientists,
its accomplishments, its potential.
Is there anything else you want to add before we wrap up
this deep dive?
I think the big takeaway here is
that we're living in a truly amazing time.
AI isn't science fiction anymore.
It's here.
It's now.
It's already changing things.
And as AI keeps evolving, it's crew you
that we're both enthusiastic and responsible about how
we develop and use it.
Well said.
This has been an incredible look at AI co-scientists
and all its implications.
It feels like we're just scratching the surface
of what's possible.
And the future, well, it's full of incredible potential
and big challenges.
It sure is.
Thanks for being with us on this journey.
We hope you've enjoyed this deep dive
into the world of AI co-scientists.
But before we go, I want to leave our listeners
with a little something to think about.
If AI can help us figure out diseases, aging, even
the universe itself, what role are we as humans going
to play in shaping this future?
What kind of world do we want to create
with this awesome power in our hands?
Yeah, those are some big questions we're thinking about.
Because at the end of the day, the future of AI is up to us.
We've spent a lot of time talking about the amazing things
AI can do for science.
And it's obvious that AI co-scientists is already
making big changes.
But as we wrap up our deep dive, I
kind of want to switch gears a bit
and talk about what all this means for us, for society,
the big picture.
Yeah, I think that's important to AI like this.
It's not just a tool for scientists, right?
It has the potential to change the world in some really big
ways.
OK, I'm listening.
Just think about health care.
Imagine AI helping doctors diagnose diseases way earlier
or coming up with better treatments that actually work,
or even personalizing health care based
on each person's needs.
That would be huge for so many people.
But wouldn't something like that make health care even more
expensive?
I mean, we're already struggling with access
and affordability.
That's a good point.
And it's something we definitely need to think about.
As AI gets better and better at health care,
we've got to make sure everyone can benefit, not just
the wealthy.
It's got to be accessible and affordable for everybody.
Makes sense.
But it's not just health care that could be disrupted, right?
What about all the jobs that might be lost because of AI?
I mean, lots of people are worried about AI taking over tasks
that humans do now.
Yeah, I get that.
It's a natural worry.
Think about this way.
Every time there's a big technological shift,
the job market changes too.
But instead of seeing AI as this job killing monster,
maybe we should think of it as a chance
to rethink what work even means and create new jobs that
use our creativity and problem solving skills.
So instead of replacing jobs, AI will change what those jobs
look like and lead to new jobs that we can't even
imagine right now.
You got it.
Look at the internet, for example.
Changed everything, right?
Lots of industries were disrupted,
but a ton of new ones popped up.
And a whole bunch of new jobs were created too.
We might see the same thing happen with AI.
As AI takes over the boring and repetitive stuff,
it frees us up to do the things that
require real human thinking and innovation.
I like that way of looking at it
instead of being afraid of AI, we
should be figuring out how to adapt and evolve with it.
It's about preparing for the future
and making sure everyone benefits
from all this new technology.
Absolutely.
We need to focus on education and training,
give people the skills they need to thrive in a world where
AI is everywhere.
And we also need to have some real, honest conversations
about the ethics of it all.
Make sure it's developed and used in a way that
aligns with human values.
So it's not just about the tech itself.
It's about how we use it and what kind of future
we want to build.
Couldn't have said it better myself.
AI has this incredible potential to do so much good in the world,
help us solve problems, make things more sustainable
and equitable.
But it's up to us to steer it in the right direction.
Well said.
This deep dive has been amazing.
It's been fascinating to explore AI coscientists
and all the possibilities and challenges that come with it.
We're just starting to understand what AI can really do.
And the future is looking pretty exciting.
For sure.
Thanks for joining us on this journey.
We hope you enjoyed this deep dive
into the world of AI coscientists.
And until next time, keep exploring, keep asking questions,
and keep imagining what's possible.