Zoe Kleinman

I'm good, thank you. This is such a good topic, I think, because as someone who lives in a particularly cold and wet part of the world, weather prediction is very important to me in terms of where I go, what I wear and what I take with me when I go out.

I'm good, thank you. This is such a good topic, I think, because as someone who lives in a particularly cold and wet part of the world, weather prediction is very important to me in terms of where I go, what I wear and what I take with me when I go out.

I'm good, thank you. This is such a good topic, I think, because as someone who lives in a particularly cold and wet part of the world, weather prediction is very important to me in terms of where I go, what I wear and what I take with me when I go out.

I think weather prediction is getting more accurate and it's going to increasingly get easier. And the reason for that, it might not surprise you to hear, is artificial intelligence. I want to tell you about a really interesting tool that we've just had some new research on published last month. It's called GenCast and it was made by Google DeepMind in the UK.

I think weather prediction is getting more accurate and it's going to increasingly get easier. And the reason for that, it might not surprise you to hear, is artificial intelligence. I want to tell you about a really interesting tool that we've just had some new research on published last month. It's called GenCast and it was made by Google DeepMind in the UK.

I think weather prediction is getting more accurate and it's going to increasingly get easier. And the reason for that, it might not surprise you to hear, is artificial intelligence. I want to tell you about a really interesting tool that we've just had some new research on published last month. It's called GenCast and it was made by Google DeepMind in the UK.

And it's basically an AI program that does weather predictions. And it performed 20 percent better in tests than the current world leader. And what's really interesting about it, not only was it better and more accurate on day to day forecasts, it was also more accurate on extreme event prediction up to 15 days in advance.

And it's basically an AI program that does weather predictions. And it performed 20 percent better in tests than the current world leader. And what's really interesting about it, not only was it better and more accurate on day to day forecasts, it was also more accurate on extreme event prediction up to 15 days in advance.

And it's basically an AI program that does weather predictions. And it performed 20 percent better in tests than the current world leader. And what's really interesting about it, not only was it better and more accurate on day to day forecasts, it was also more accurate on extreme event prediction up to 15 days in advance.

And it was better at predicting the paths of hurricanes, which, as we know, can change. change quite dramatically at very short notice. It was trained on 40 years of weather data, which is an awful lot of data and also contained an awful lot of variables. And it used that data to make its own predictions.

And it was better at predicting the paths of hurricanes, which, as we know, can change. change quite dramatically at very short notice. It was trained on 40 years of weather data, which is an awful lot of data and also contained an awful lot of variables. And it used that data to make its own predictions.

And it was better at predicting the paths of hurricanes, which, as we know, can change. change quite dramatically at very short notice. It was trained on 40 years of weather data, which is an awful lot of data and also contained an awful lot of variables. And it used that data to make its own predictions.

It does the same as traditional predictions, by the way, which is called ensemble forecasting, where you get a range of them. But it was calculating which one was the most probable and it was very good at it. Traditionally, forecast tools involve basically solving enormous amounts of equations and they use supercomputers to do it because they have to. But it still takes a long time.

It does the same as traditional predictions, by the way, which is called ensemble forecasting, where you get a range of them. But it was calculating which one was the most probable and it was very good at it. Traditionally, forecast tools involve basically solving enormous amounts of equations and they use supercomputers to do it because they have to. But it still takes a long time.

It does the same as traditional predictions, by the way, which is called ensemble forecasting, where you get a range of them. But it was calculating which one was the most probable and it was very good at it. Traditionally, forecast tools involve basically solving enormous amounts of equations and they use supercomputers to do it because they have to. But it still takes a long time.

And Gencast managed to process its forecasts in eight minutes, which is considerably faster, isn't it? But, of course, the data it was using had been gathered and processed in all of our old school ways that we've been doing for the last 40 plus years.

And Gencast managed to process its forecasts in eight minutes, which is considerably faster, isn't it? But, of course, the data it was using had been gathered and processed in all of our old school ways that we've been doing for the last 40 plus years.

And Gencast managed to process its forecasts in eight minutes, which is considerably faster, isn't it? But, of course, the data it was using had been gathered and processed in all of our old school ways that we've been doing for the last 40 plus years.

And so what we don't know is whether going forward, if we were to just rely on AI generated data, because that would become, wouldn't it, our data set, whether it would be as reliable.

And so what we don't know is whether going forward, if we were to just rely on AI generated data, because that would become, wouldn't it, our data set, whether it would be as reliable.