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Re:Comma.ai: Refactoring for Growth by sashank_1509 on Monday August 12, 2024 @12:57AM (#41221266)
I will try to be objective here and give them a bit of a reality check, they tried to reinvent the “VC”, tried to reinvent the vibe of SV company but at some point they seem to have lost the ball.

They pioneered the idea of end to end learning for self driving, they were talking about it seriously earlier than most and yet Tesla got a hang of it and within a year Tesla has released a fantastic e2e model miles ahead of whatever comma released. Tesla’s model is that good, I can see it becoming a robo taxi.

I can’t help but think that if they weren’t fixated on bootstrapping, shippable intermediaries etc etc, they could have been what Tesla is now. What if they actually tried to scale? It would have been off the vibe they are going for, but if they went the standard route and raised say 500M+ which is reasonable in this space, bought a ton of GPU’s, hired a bunch of ML superstars, hired a bunch of drivers to collect data, they could have already been leading against FSD. Of course whether they actually could have raised enough capital to do all this, is a hypothetical but it would have given them a fighting chance.

Then they tried to reinvent hiring, create good PR’s, solve challenges, they said which sounds like a good idea only if you’ve never tried to scale a company. When you’re a small startup, this may be a good way to sift through candidates but if you want to play in the big leagues this is a naive no go.

First off, most superstar candidates probably have not heard of you or even if they did wouldn’t be bothered to do your challenges, PR’s (god forbid microinternship etc). You need recruiters and head hunter to go after them, go to their universities, actively seek them out. Then you also need a reason for them to join when Anthropic is offering 600k to new hires, no one will choose comma ai in comparison. (Which is why you really need to scale, scale, scale to be able to afford them). Even if you offered them higher salaries, it’s still hard to hire them, you need a nexus of existing talent, a few well known names initially which will convince them to join. This will inevitably lead to some bad hires, some over hiring since you won’t be literally vetting them to a micro internship etc, but you can let them go quickly once you identify them. This will also lead to some redundancy. Having just 21 engineers is not a good thing, when the competition is literally running away with your product. There is a tendency to become too big like say cruise with 800+, but aim to at least have a 100+ , your organization speed will ramp up, and the product can defend against competition much more quickly.

TLDR; Comma for some reason acted allergic to scaling, when a traditional scaling route could have done them wonders. Now it might be too late. I also find it ironic that the best car on the streets right now is a Waymo, I took it through China Town SF no issues and this was the company Comma spent so much time shitting on. Apparently you could just scale up traditional robotics and solve robotaxis (whether it will ever become a profitable business, jury is still out)

Re:Comma.ai: Refactoring for Growth by levocardia on Monday August 12, 2024 @01:50AM (#41221438)
Or they could have been one of the dozens upon dozens of failed self-driving startups that promised the moon and never shipped a product. Sheesh, if only they'd hired a bunch of headhunters to find money-hungry Ivy League CS grads, they could have joined the party of smoldering VC scams!

As for Waymo...is it really the best? It won't even drive on highways! Plus, it's not like you can "buy" a Waymo car. Nor will you ever be able to, I suspect.

Tesla is still the leader, but with Cruise in a death spiral and Waymo burning through so much cash their balance sheet is on the verge of spawning a gravitational singularity, I would not be so quick to dismiss Comma's strategy. Unlike anyone but Tesla, they ship a product you can actually buy, and actually use.

Re:Comma.ai: Refactoring for Growth by mft_ on Monday August 12, 2024 @08:26AM (#41223613)
Agree totally; what Comma has achieved is noteworthy precisely because they've not gone the obvious SV route.

They've delivered a meaningfully functional product that you can actually buy for a very reasonable price and retrofit to all manner of cars, while raising very little and now being profitable.

Re:Comma.ai: Refactoring for Growth by olive247 on Monday August 12, 2024 @01:43AM (#41221413)
I've also been confused why they stay so small. It seems like such a good idea, why not scale faster and larger. My guess is they are so bound to the hacker ethos and culture. Also the regulatory gray area the product sits in, scaling too large would put a target on them.
Re:Comma.ai: Refactoring for Growth by kennyloginz on Monday August 12, 2024 @01:40AM (#41221400)
Wait, what is Tesla’s “e2e” model? And you “can see robotaxis”?

Tesla is counting on “humanoid “ robots. Which , uhh, yah, good luck undercutting minimum wage workers.

Re:Comma.ai: Refactoring for Growth by azinman2 on Monday August 12, 2024 @01:49AM (#41221432)
“FSD (Supervised) v12 upgrades the city-streets driving stack to a single end-to-end neural network trained on millions of video clips, replacing over 300K lines of explicit C++ code”

This was the changelog message lately.

https://www.teslaoracle.com/2024/07/13/tesla-fsd-v12-5-highw....

Re:Comma.ai: Refactoring for Growth by ericlewis on Monday August 12, 2024 @01:53AM (#41221448)
I have one of these. It’s not there.
Re:Comma.ai: Refactoring for Growth by stavros on Monday August 12, 2024 @04:58AM (#41222512)
> It's not there.

It probably drove away on its own.

Re:Comma.ai: Refactoring for Growth by AlotOfReading on Monday August 12, 2024 @01:55AM (#41221452)
It's not clear what Tesla actually means when they say "E2E". The expectation most people have is that there's a single NN between sensor data and steering wheel/pedals out. Based on the limited technical detail available from "AI day" and such, what they're actually doing is more along the lines of a bunch of ML models glued together in a pipeline.

Now you might ask why people talk about Tesla E2E all the time if it's not clear exactly what it is. I don't know either. Let me know if you figure out a charitable rationale.