Dyson AI Toothbrush Defeated by Water

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Stage Zero (1:30)

Dyson recently pulled its new $499 CameraJet AI-powered toothbrush from major retailers like Best Buy because water leaked into the jet tubes. Right.

SPEAKER_7 (1:41)

It got defeated by water.

Stage Zero (1:43)

Yeah, water in a bathroom sink.

SPEAKER_7 (1:45)

Which is, I mean, it is just difficult to invent a purer piece of irony.

Stage Zero (1:48)

It really is.

SPEAKER_7 (1:49)

You have a device whose entire operational existence occurs inside a bathroom sink, and it fails because it gets wet.

Stage Zero (1:56)

And we are not talking about a standard plastic stick with some nylon bristles here.

SPEAKER_7 (2:01)

No, definitely not.

Stage Zero (2:02)

This is a highly complex, computationally heavy machine.

SPEAKER_7 (2:05)

It's essentially a computer you put in your mouth.

Stage Zero (2:07)

Exactly. I look at the engineering effort required to build this and the volume of resources poured into a single consumer product, and it forces a question for you to consider as we look at this entire category of devices.

SPEAKER_7 (2:20)

Right, the broader category.

Stage Zero (2:22)

How does a company invest endless resources into engineering a product only to be defeated by the most predictable element of its environment?

SPEAKER_7 (2:32)

Yeah. A toothbrush getting wet is not an anomaly.

Stage Zero (2:36)

It is the absolute baseline assumption of the product category.

SPEAKER_3 (2:39)

It will get wet.

Stage Zero (2:41)

Right.

SPEAKER_7 (2:41)

It will get dropped. It will be handled with slippery hands.

Stage Zero (2:44)

Constantly.

SPEAKER_7 (2:45)

But when you introduce high-level electronics into something that simple, the environment stops being a passive backdrop.

Stage Zero (2:51)

It becomes an active threat.

SPEAKER_7 (2:53)

Exactly. It becomes a hostile threat to the hardware.

Stage Zero (2:56)

The raw numbers on the development give you a sense of the effort involved here. There were 661 engineers assigned to the CameraJet project.

SPEAKER_7 (3:04)

Over 600

Stage Zero (3:05)

Yeah. And they filed 38 separate patents for this specific device.

SPEAKER_7 (3:09)

38 patents.

Stage Zero (3:10)

But the software side is where the numbers stop making sense to me. The toothbrush runs on 16 million lines of code.

SPEAKER_7 (3:17)

Which is just, I mean, that is staggering.

Stage Zero (3:19)

Right. And for the features, there is a 100,000 pixel camera built directly into the brush head.

SPEAKER_7 (3:25)

A literal camera.

Stage Zero (3:26)

A camera. You have Wi-Fi connectivity, you have Bluetooth, there is a dedicated app, of course.

SPEAKER_7 (3:32)

Naturally.

Stage Zero (3:32)

And there is a local machine learning model designed to spot the microscopic gaps between your teeth, which then coordinates with precision through the pumps to shoot mouthwash into those exact gaps.

SPEAKER_7 (3:44)

16 million lines of code for dental hygiene.

Stage Zero (3:47)

Yeah.

SPEAKER_7 (3:47)

I struggle to accept that human brushing requires an operating system of that size.

Stage Zero (3:51)

It sounds like overkill.

SPEAKER_2 (3:52)

It is.

SPEAKER_7 (3:53)

The manual toothbrush has functioned perfectly well since the Ming Dynasty.

Stage Zero (3:57)

Right.

SPEAKER_7 (3:57)

It is a mechanical solution to a mechanical problem. You have plaque, you apply friction, the plaque is removed.