Helen Hastie

So this is AI that will do actions in the real world like make a booking for you.

It's been fascinating.

It's changing so rapidly that it's quite hard to keep up.

And universities, I think we have to find a way to advance the technology and the science within our means.

And so we're looking at things like how we can train models on less data more efficiently.

So there are areas that we can research, but the adoption of AI has just been blown away.

So there are different research directions that we can go in that are going to be important for the future.

It's true we don't have access to hundreds of millions of pounds for training really large models running on very large systems.

But we do, for example, at Edinburgh University, we have the UK's national computer.

And we do have access to data.

But what's going to be important going forward is changing the paradigm of AI.

So, for example, learning how to learn rather than just throwing more data and more compute at these models.

There's a general definition of trust being the willingness to be vulnerable to another entity's actions.

And this is particularly important for robots, increasing so if you can't actually see the robot.

So an example of this is underwater robotics.

They're very expensive robots.

They go very deep.

They don't.

communicates very well.

So this idea that you have to trust the robot to be autonomous and to complete its task.