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American Vigilante

What is Artificial Intelligence? | Introducing SystemShift

American Vigilante

Crowd Network

Society & Culture, Documentary, True Crime

4.2879 Ratings

🗓️ 27 February 2025

⏱️ 8 minutes

🧾️ Download transcript

Summary

Do you love American Vigilante? Then you'll love this new podcast.   Perfect for question-askers and curious minds, welcome to SystemShift! Have a listen, and if you love it, hit one of the links below to see and hear more. Enjoy!   https://podfollow.com/1683278976 https://www.youtube.com/watch?v=ENvqNLnE8js Learn more about your ad choices. Visit megaphone.fm/adchoices

Transcript

Click on a timestamp to play from that location

0:00.0

Hello listeners, it is Tom here. I hope you are well. Now, I'm here because I thought I would

0:05.1

recommend you another podcast. I think you'll love this one. It's called System Shift, and it's all

0:10.8

about the change we can expect to see in our lifetime. I'm about to play you a short clip from the

0:16.8

episode about AI. You'll find out what AI truly is and how it can affect elections,

0:23.0

which is particularly relevant given the current news cycle. Give it a listen and if you enjoy it,

0:28.6

search for System Shift, that's all one word, in your favourite podcast app to listen to the

0:34.2

whole episode. We'll also leave you a little cheeky link in the episode description.

0:41.6

People attach AI to so many things today where it's not the right term to use. Could you explain

0:47.8

a little bit the difference between a normal computer program and what AI is? Yes, so artificial

0:53.6

intelligence and even machine learning models are making a prediction.

0:57.0

And these are probabilistic predictions.

0:59.0

So when we think of, let's say, a machine learning model, these are very sophisticated

1:04.0

statistical predictions.

1:05.0

So for someone like myself, I was a statistician by background, the way these models work

1:10.0

is not particularly

1:11.5

magical. It's just mathematically dense. And the same holds true for generative AI models,

1:18.0

neural networks, other kinds of AI models. They just get more and more and more mathematically

1:22.6

complex, which also makes them more and more fragile. So a traditional software, let's say a computer program,

1:30.3

just relies on input output.

1:32.3

So you give it some sort of input,

1:34.3

and then you can predict with basically 100% certainty what the output will be.

1:40.3

If it deviates from that, then there is something wrong with the model.

...

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