Defining AI and Machine Learning – Technical Terms, Simplified | Alicia Klinefelter

We sit down with Alicia Klinefelter, a research scientist for NVIDIA, and ask her to help define AI and the different types of AI that we often hear about. Alicia is an expert in her field.

She has a PhD in electrical engineering from the University of Virginia. Since joining NVIDIA, her focus has turned more towards high-performance hardware, including machine learning circuits and systems.

What’s AI?

When talking about AI, Alicia says that as hardware engineer she can see it more from a practical side, rather who is more on the algorithms or kind of theoretic side.

“For me, I see it more as a revolution of finally having enough computing power”, she adds.

It’s from the mid-2000s to late-2000s that we see the implementation of these algorithms at a larger scale. So AI it’s all about having those resources now available, that weren’t there before so.

For Alicia “Machine learning is the power of machines to learn through iterative training, the same way that a child might learn.”

Interested to learn more?

Be sure to check out part two of our conversation with Alicia, in which she offers some important insights on AI.



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