Yeah it's interesting hearing their engineering logic, that fewer sensor types means less sensor collision and faster iteration, where iteration speed is really what matters. I also think people overhyped lidar because they don't understand it, and human behavior is to associate things we don't understand to magic. It's not magic, it performs poorly in inclination weather and can have issues with resolution over range and data processing (although lidar does do a lot of things well).
All of this said, once Karpathy left they have slowly looked at adding new sensors (recently radar), so who knows what the future for Tesla's sensor suite holds.
> I also think people overhyped lidar because they don't understand it
Speaking as a person who understands it extremely well and who has an advanced degree in computer vision, I'm sure that internet randos did, but I promise the people who actually know about the failure modes of the different modalities did not. I don't really expect you to take my word for it, but maybe this will spark an interest in investigating the failure scenarios of 3D reconstruction using cameras in computer vision. Just know that Google is an absolute top tier juggernaut in the CV/ML/AI research world, and they don't use lidar out of ignorance.
> less sensor collision
This isn't a real thing for anyone doing a good job. A sensor can be good for a scenario or it can be bad for a scenario. More sensors feeding input only gives you gradations of accuracy instead of binary accuracy. Having gradations of accuracy is an unambiguously good thing. When you only have one sensor, you have no way to know whether in the moment it is feeding you an optical illusion. That's what it means for something to be an optical illusion. But when you have multiple sensors of different modalities, then you have meaningful information about whether local disagreement between the different modalities means that one is better or worse than the other, because you can contextually characterize the failure scenarios of each.
> It's not magic, it performs poorly in inclination weather and can have issues with resolution over range and data processing (although lidar does do a lot of things well).
Inclement, not inclination. And I hate to be the bearer of bad news, but cameras also do poorly in inclement weather and have issues with resolution over range, and the solutions are identical for both (superresolution, temporal blending, alternate wavelengths, stereo correspondence, etc).
Tesla people always say (said?) things like "Well humans only drive with their eyes, so cars should be able to as well," but that's not a true statement about what humans have in relation to what Teslas have. Humans have many more different sensor modalities than what Tesla's cameras give. Teslas have single-view fixed-focus cameras that, for much of the FOV, can only reconstruct structure from shape assumptions (object detection and classification) and inter-frame changes (optical flow) coupled with sensation of the vehicle's motion. That's all they get. It's not bad at all, especially coupled with advanced machine learning, but you do have more than that coupled with even more advanced machine learning. When you as a human drive, in addition to what Teslas have (you do also have them), you also have binocular stereopsis cues, autofocus lens convergence cues, vehicle-independent motion parallax cues, and the ability to manipulate shade cover so you don't get blinded. Are all those extra cues necessary for every scenario? No, obviously not. Do they help though? Yes. Try driving with only one eye open and without moving your body or head at all. You can absolutely do it, but you won't be as good as you would with both eyes open and free movement.
They lied about the horizon battery life as well, reviewers put it at ~3 hours down from I think an "estimated" 12. Really nice laptops, I might still get one, but this sort of lying irks me.
Yeah starlabs uses a lot of glass trackpads in their products and are known for good builds; certainly this will be better than a thinkpad or something. The common complaints for their laptops are usually battery life (I know the horizon battery life was famously abysmal, roughly 3 hours of use), although I'm not sure how long this battery will last.
It's funny how Paul is recommending people use PR firms, while in more recent videos michael seibel and others have strongly recommended against using them. It's interesting how things shift in ~20 years
This is my thought too. The eggheads in accounting set budgets, and we produce products within that budget. I could be twice as productive with twice as many people, and maybe 50% more productive with good AI, but if it's not budgeted for it's an issue (especially short-term before the product is released).
I'm not sure why you're being downvoted, you're right. We were large enough that we could find the talent, and the country was free enough so that private industry could drive innovation. Low taxes let companies reinvest. We know this is what happened because the success of free markets isn't a mystery, it's well studied and documented.
I feel like floor mattresses, trash, and peeling paint were also at play. They're all sort of unsafe rooms people wouldn't want to go to unless they felt like they had to (i.e. doing drugs)
I would not blame this on republicans; they don't hold a majority in the state senate, house, both senators and most house reps are democrats, and there isn't anywhere they hold meaningful power. Further they're opposed to doubling payroll taxes, the taxes are not raised yet.
Oregon, and Portland in particular, suffered a lot economically after covid due to overprotective laws banning operations. A lot of companies went out of business, people moved, and tax revenue plummeted. Growth since has been slow due to hostile laws. TriMet cuts are due to poor city and state management, which frankly doubling payroll tax would exacerbate.
I will say, to their credit, there has been a ~25% yoy commit increase since the introduction of AI. That's a pretty significant jump on an already popular site, at the same time they're supposed to be training models for search and other features. I think most sites that see that sort of increase will experience increased downtime
All of this said, once Karpathy left they have slowly looked at adding new sensors (recently radar), so who knows what the future for Tesla's sensor suite holds.
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