I'd, I'd go so far as to say my biggest dilemma that I remember from my last hospital job was I would be called someone at 3:00 in the morning, and the decision was, do you add fluid, which put them at risk of heart failure, or do you remove fluid, which put them at risk of kidney failure?

Exactly that.

And it's the-- it's one of the thorniest questions, isn't it? And it's vexing doctors up and down the country as we speak.

So we should put it in context first.

So patients are not in the situation or often not in a situation where they're able to regulate their fluid intake or their fluid output in the way that we evolved to do.

And whether that's because we've done some funny things to them, like we've told them not to drink before their operation, or they haven't been able to take in as much fluid 'cause of the disease that they have.

You know, maybe they're feeling sick, they're having side effects from treatment or so on.

Why is that?

And we'll talk a little bit more about that in doctor's notes.

Yeah.

But for most healthy people, thirst is actually a, a good sign.

You mentioned the socials.

There's a big amount of noise around how much we need to drink, right? And, you know, I hear everything from two to three liters a day.

There's been these big bottles full of water.

Say, you know, "Well done.

Are those things actually associated with hydration?

Tell us a little bit from an AI expert perspective, where are frontier models at and what would you use them for?

Oh, good question.

So the whole game in town over the last few years in AI has been scale.

So more data, more compute.

And there's a very healthy debate going on out there whether just focusing on scale will actually fundamentally lead to new advances in terms of new levels of intelligence.

There's some evidence to show that the intelligence levels of these frontier models is kind of plateauing.

And so, although it's still increasing, just throwing more data and more compute at it is not necessarily going to lead to a step change.

Do we see that in gen AI as well?

What are some of the interdependencies and vulnerabilities between AI and security that you wish were better understood?

So I think there's a lot of misconceptions about AI.

Um, a- and it, it probably comes down to the fact that people don't realize how much better the models are today than they were, say, a couple of years ago.

Um, so people still worry about things like hallucinations, um, at a, at a personal use level.

And, and although hallucinations definitely haven't gone away, I think things have definitely improved compared to where we were a couple of years ago.

Um, I think if you talk to CTOs and so forth in organizations, they worry a lot about, um, s- the, the security of the AI that they're running.

And again, that's...

You mentioned you advise to a lot of corporate Australia, and as an advisor to major companies, do you have insights into trends when it comes to actual productivity gains?

Has that changed at all in the past 12 months or are the same uncertainties still there? What are you seeing?

Yeah, so that research really made a distinction between personal productivity, so how we use AI tools ourselves and does that make us faster at things, versus organizational and national level productivity.

And the research found that certainly at a personal level, AI generally does tend to increase productivity, although not always.

But where we're really struggling is how do you actually translate that? How do you aggregate that up to an organizational level and then up to a national level after that? In terms of what's changed since then, certainly an awful lot has changed in AI even in the last few months.

I think the tools have got an awful lot better.

I think there's been a step change in 2026.

And so for some professions like software engineering, I think we're now seeing quite radical increases in productivity.

Can you explain in simple terms what a token is and why they matter so much when we talk about AI systems, how they work and how much they cost?

It's another to have any idea what you're getting when he's on the field.

Yeah, and those are huge questions.

And some of the same ones can be said for Dylan Stewart, too.

But, you know, Jacarius is certainly a big deal for the Gamecocks.

He was the key cog in the portal.

And what I can tell you is they've been talking about since the injury happened that they felt like he would be ready for the start of the season.

And Shane Beamer said recently that he is ahead of schedule.

Do we know anything more about what the plan is for Nefgiwa for this fall?