1/ Another FSD thread.

@karpathy points out that $TSLA& #39;s FSD competitors use high-definition maps to plot out all drivable space

These cars don& #39;t need to see Stop Signs because they& #39;ve already programmed/baked in all the stop signs

Let& #39;s discuss, $TSLAQ https://twitter.com/ElectrekCo/status/1273764197126504449">https://twitter.com/ElectrekC...
2/ A robot car doesn& #39;t need to "see" stop signs if it knows ahead of time where all the stop signs are.

Similar, but the car doesn& #39;t need to decipher lanes or any signs. It& #39;s been pre-programmed that "this lane is the left-turn only lane." Or "this is where I have right of way"
3/ And @karpathy is right that this isn& #39;t ideal

No one can map out all drivable space and keep it 100% up-to-date all the time.

It would be ideal for cars to be able to see the signs and infer their meaning.

Stop sign --> stop here

Left turn only --> leave lane to go straight
4/ So why do these companies do it?

Because it& #39;s the critical path to getting to market.

Driving on ordinary streets is already a monumental challenge. Without the map, you& #39;re introducing another layer of complexity: inferring the world around you.
5/ So these companies have all arrived at a similar conclusion:

Step #1: Get the car to drive perfectly with a 100% perfect map

Step #2: Get the car to drive perfectly with no map

The progression here is obvious.
6/ The second benefit of this approach is that it enables FSD companies to get to market much faster. You can launch as soon as you& #39;ve solved step #1.

There& #39;s billions up for grabs in just a few major US cities. Establishing your brand in major cities helps the broader rollout.
7/ So while @karpathy is correct that pre-mapping in FSD isn& #39;t ideal...

... he& #39;s very wrong to imply that it& #39;s a poor decision.

Mapping is a relatively cheap solution that will enable these FSD companies to start seizing transportation market share in major cities. Lots of $$$
8/ And it may even be technically a better approach.

With the map, the FSD companies can stay very focused on discreet ML problems.

Once they& #39;ve solved a very safe FSD car, they can then try to go to the next level and drop the map.
9/ Similar point can be made with LIDAR:

If LiDAR is not necessary, then these companies will eventually be able to drop it. No reason they can& #39;t just say "ok, we& #39;re training just off the cameras now."
10/

Point is this:

Once you have solved a safe FSD vehicle that can pick up and drop off passengers...

Once you have SOLVED the world& #39;s greatest AI challenge...

Your company moves from "solving" to "optimizing." All other AI challenges get vastly easier.
11/

But $TSLA will never solve this, because the FSD challenge is one of the hardest challenges of our time, with some of our brightest minds trying to solve it.

and $TSLA can& #39;t retain talent

$TSLAQ
12/ $TSLA& #39;s brightest minds realize Elon& #39;s constrains create an unsolvable problem. And they leave.

FSD isn& #39;t a one-man show. No one person put a man on the Moon.

These achievements come from organizations committed to unconstrained innovation. Elon is antithetical to that.
13/ To say that Elon Musk and @karpathy, in all their genius glory, are going to solve FSD cheapens the work of the hundreds of researchers that are actually solving the problem.

And it begs the question...

Why aren& #39;t their test $TSLA cars on the road testing FSD today?
14/14

All $TSLA needs to do is deploy 100 FSD cars with test drivers

Stock price would skyrocket. Kathy would have infinite pump ammo. Tesla get a wave of talent applying to join

But a fraud of that scale is too hard to pull off.

The reality is... $TSLA has nothing

$TSLAQ
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