Waymo self-driving cars -- progress

[mostlylong]

A few quick points.

@Goofyhoofy

I get what he’s saying. Totally. So do you, I think.

First,
Did you read my post?

It feels like no, because I wrote:

@mostlylong

I get your gist, but I think we really have no idea on these statements you are making. Without definitions of key terms (such as “dumber” in a discussion of intelligence), we really have no idea.

Second,
My main question upthread is asking for a basis (supporting evidence) for the claims that are made. We ask each other for supporting evidence all the time.

And, I’m thinking, often, definitions are an important part of communicating supporting evidence, so I asked for definitions to make sure we are talking about apples and apples.

You can bet when people benchmark these systems, they will have, you know, “definitions” of the metrics used to benchmark.

And if there existed public data measuring “smartness” of competing AIs and “quality/nature” of sensor data as part of benchmarking “AV functionality” per unit data and brain power, we would be citing that information here.

Third,
I also provided two counterarguments, using non-technical language.

I’d be interested in specific responses to these specific counterarguments.

Finally, while I enjoy to speculate, forecast and guess about the future, I am not wed to any particular view.

When such information exists, I want to see data, evidence, valid logic, etc and that will guide my view.

Maybe some information new to me will surface here, I don’t follow the AV world as closely as others here.

[Goofyhoofy]

@mostlylong

I’d be interested in specific responses to these specific counterarguments.

[1]Finally, while I enjoy to speculate, forecast and guess about the future, I am not wed to any particular view.

[2]When such information exists, I want to see data, evidence, valid logic, etc and that will guide my view.

[3]Maybe some information new to me will surface here, I don’t follow the AV world as closely as others here.

1. OK.
2. OK.
3. OK.

Anything else? Meanwhile since such data is not forthcoming, not from Waymo and certainly not from Tesla, all we can do is speculate. You think we shouldn’t do that?

[Tamhas]

@albaby1

But if they do expand to California, then we’ll have more of an answer.

Given how little we really know about what Waymo is doing in CA, let me be skeptical …

[mostlylong]

@Goofyhoofy

Anything else?

These are the examples I provided upthread, quoted again below.

The first example is a question about how to measure (define) “extra/more information,” driven by a realistic, but non-technical example.

The second example illustrates that having “extra/more information” might require more (not less) analytical processing (more or smarter or “less dumb” brain power).

I don’t know the answers, but I believe these are very legit examples that counter or maybe deepen the discussion on the claims made upthread.

@mostlylong

Two basic counterarguments.

First:
System 1 could be very high resolution camera data, high spatial and temporal resolution. System 2 could be lower resolution camera with LIDAR data. Does S1 or S2 have more “information” with respect to AVs?

I would say you and I don’t really know this, and can’t even make a statement about this (unless maybe you want to define terms more precisely).

Second:
Processing sensory inputs (including synchronizing the data in space and time, and also calculating correlated, interacting features) from multiple sensor types (camera + lidar) might require more analytical processing (somehow appropriately defined) relative to processing from a single sensor type (camera only).

One can imagine additional neurons and connections and specialized features (in artificial and/or biological intelligence) to process vision plus sound, versus either alone.

I would say you and I just don’t know.

[dividends20]

It is ALL about real world data. The debate about vision only or vision + multiple sensors is over.

Tesla’s has automated data annotation with video feeds coming in from millions of cars all over the world every day and is using for model training.

On the other hand, Waymo is paying drivers to drive around and collect data and hdmaps. You cannot generate the data synthetically. The fleet is very small and expensive even when compared with Uber. This is a dead end.