Dr. Fei-Fei Li

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372 appearances 1 recordings 1 series first heard Nov 2025 last heard 7 Nov

Dr. Fei-Fei Li’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Nov 2025 with 1.

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Young and Profiting (YAP) with Hala Taha: Entrepreneurship and Self-Improvement Podcast · Dr. Fei-Fei Li: Turn AI Into Humanity's Greatest Ally, Not Its Biggest Threat | Artificial Intelligence | AI Vault · 7 Nov 2025 podcast

I would call it a gray box.

And depending on your understanding of the AI technology, it's either darker gray or lighter gray.

So the things we know is that it is

It's a neural network algorithm that is behind, say, a chat GPT model or a large language model.

Of course, you hear the names of transformer models, sequence-to-sequence, and all that.

At the end of the day, these models take data, like document data, and it learns how the words and sometimes even sub-words, parts of words,

are connected with each other.

There are patterns to see, right?

If you see the word how, it tends to be followed by are, and then it tends to be followed by you.

So how are you is a frequently occurring sequence.

So that pattern is learned.

And once you learn enough in a big, huge neural network, your ability to predict

the next word when you're given a word is really, really quite amazing, amazingly high to the point that it can converse more or less like a human.

And because in the training data, it has so much knowledge, whether it's chemistry or movie reviews or geopolitical facts, it has memorized all of them.

and so it can give out very very good answers so those are the things we know we know how the algorithm works we know it needs training we know that it's learning and predicting pattern what we don't know is that because these models are huge there are billions and billions hundreds of billions of parameters and then

inside these models there are these little nodes, each one of them have a little mathematical function that connects to each other.

So how do we know exactly how these billions and billions of parameters learn the pattern and where is the pattern stored and why sometimes it hallucinates a pattern versus

it gives out a correct answer.

There is no not yet precise mathematical explanation.

We don't know at the level of, there's no equation that can tell us, oh, I know exactly why at this moment the chat GPT gives you the word, how are you versus how is he?

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