Yep

... has to, has to use.

Now, the government will argue it's not an AI tool.

It is quite close to that, and the tool is quite restricted, where aged care providers were able to previously make a human-based call on what package to be, is relevant for which particular person in an aged care space.

The tool is now deciding, and it, and it is quite restrictive in the sense to override the tool.

Now, that has beyond the decision-making capabilities of that tool, and there's a lot of feedback for the government on the tool.

Uh, but the point I'm trying to make is the decisions that tool will make for the organizations direct the organizations into a particular direction, perhaps changes their case mix, perhaps changes their demographic mix.

Yes

Mm-hmm.

And the problem is you can do that in a lab setting, but when you take it to the real world, there's a much broader diversity of, of settings, of configurations, of objects, lighting, and so on, and the models fail.

So that's the central problem that we were started to address, is how do you get robots to generalize beyond these very contrived situations, uh, that, you know, that people have shown they work in in lab settings.

Uh, and, and so we, we've got a different approach that we're taking.

Mm.

Uh, if you have any kind of non-linearities in the system, like compliance or elasticity, that's very hard to model, and, and that doesn't work well with AI.

So we wanted to build more of an Apple-like solution, where we control the OS and we control the hardware in order to provide a full solution to the customer.

Having said that, some of our customers do want our model to control their existing hardware.