Brett Larson

speaker

455 appearances 2 recordings 1 series first heard Dec 2024 last heard Feb 2025

Brett Larson’s voice in public audio — every appearance, attributed to the second.

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So traditional rules-based vision is great for a lot of things, but not for things very subtle or nuanced tasks with a great deal of variation.

Those sorts of tasks, you still usually have a human performing them because frankly, it's just hard to quantify them to then program them.

Maybe an example of that would be inspecting a phone case for very subtle defects.

There's obviously a wide variety of colors and there's just an endless list of potential defects.

So scratches, dents, blemishes in the paint.

And they're very small, very nuanced.

And then there's also usually a scale of what's acceptable and what's not, where a human would be able to look at it and pretty quickly discern that.

But it's very hard to program a machine to be able to do that, especially at obviously high speeds.

But with deep learning, instead of programming it,

You teach it with very large data sets and very large image sets.

These are good phone images, these are defects, these are acceptable defects.

And the machine learns what is acceptable and what is not and is able to accomplish that task.

Just to quantify this a little bit.

So there's currently still 30 million people in the world doing visual inspection.

And that's something that humans actually

Aren't great at, they can do it quickly, but they get fatigued and they miss things.

That's a big opportunity.

Another example would be something like deboning chickens, where every chicken's different.

It comes down the line in a different orientation.

The wings are somewhere different.

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