And the trained network doesn’t matter as much as the training pipeline, which will include hardware and software external to the cars.
A neural net that you can’t update is less useful, and I highly doubt that the cars themselves are doing any learning.
It was about the best AI chip in general not based on some arbitrary efficiency number.
No one cares how many TOPS your 500watt non-redundant monster can run, because it’s not being put in an EV.
Because self driving cars are a multi-year journey and those platforms will likely become more efficient.
Remember we’re talking about systems made of multiple chips. It’s like asking “what’s the best Bitcoin mining rig?” The question is one of hashrate per joule. If someone asked if you should buy a 1000watt box that did 10TH/s versus a 200watt box that did 5TH/s, which is better?
They maxed out their available power envelope (~70 watts) and the resulting performance is about 20x what they were getting from their prior nVidia platform. In other words, they will always make the chip big enough to pull ~70 watts, at the highest efficiency possible.
My limited understanding of the hardware design is that once you have figured out the specific architecture you can scale up and down the power consumption almost linearly with the die size. Obviously plus or minus various hard limits (e.g. oversizing compute for the available memory bandwidth)
Tesla has already been working on their next chip for over a year. This chip they just started shipping finished design 1.5 years ago. This will not be the last AP hardware they ever ship.
I fully expect that as we delve further into “FSD” there will be functionality on the fringes that will need even more horsepower.
It’s easy to think in the present that there’s a logical “end” where development will be “complete” but that’s almost never actually the case. So there will be a Gen4/5/6, specifically what features they will unlock is very hard for me to predict. I think this is actually the type of thing Elon sees right through like it’s obvious.
Like how he sees a path to colonizing Mars which includes launching a global satellite internet company.
2. Musk has investors and the price of his cash financing goes up when people short his stock and there is negative sentiment. It was a major strategic weakness when the viability of tesla depended on short-term cashflow financing and he did what he had to save the company that he poured his life savings into. Not so much now that he's built a system where every additional vehicle sold adds additional value and long-term investors can see that. Musk thinks long-term the markets think short-term but if you run out of cash, there is no more planning and he hates the markets lack of vision and people profiting from negative sentiment effectively killing optimum solutions. The market has a lot of long-term faith in Amazon and Google and Microsoft because of their dominant networks and economies of scale and profit from complex software with zero marginal cost.
3. Solving problems in sub optimal ways isn't solving them it's compromising on them. He solves them optimally with the least capital but admits his mistakes, one of which was not judging the benefit of humans and teamwork on production lines versus robotic manufacturing technology correctly. If you are generating negative externalities you aren't reducing entropy in the system and Tesla learnt this painfully and won't forget it.
4. I'm completely out of my depth on the data scientists employer preference but if I had the choice of solving problems from a constantly growing ocean or from an artificial fishpond and I had a desire to contribute majorly to solving the autonomous driving problem and I had to factor in the probability of earning enough money to buy my time freedom as quickly as possible then the data is suggesting that Tesla at this point in time is a reasonable bet.
The question is whether he can compete with Toyota on mass scale while battery tech comes down in price but he's quite lucky Toyota misbet on fuel cells and don't readily admit their mistakes, it appears he's built a 10 year lead on the autonomous driving and can compete in the high end of the electric market profitably. The first question anyone would ask a driver of an electric BMW is why they didn't choose a Tesla? That's a fairly strong position, I wouldn't be shorting that stock.
The entrenched car lobby have only have two lines of defense left. The first which was to short him so he runs out of access to cash from negative sentiment is virtually broken on Tesla's current revenue and IP acceleration. The last line will be a delaying argument over Safety but he has a much larger dataset.
Geico falls when Tesla proves safe autonomy. There is a lot at stake here and Musk has focused primarily on the physics which is the right thing to focus on for humanity.
Does that make it the most advanced AI chip in the world? No! In fact, frankly, you're trying to have a technical discussion about a bullshit term. Tesla isn't producing an AI chip, they're producing a scalar product chip. It does a 96x96 Mult-add and that's basically it.
How does it do on any of the standard AI benchmarks? Oh it can't run any of them because it's not got support for any of them because it lacks many of the basic features of what any normal person would consider a chip capable of doing AI work.
It is the best chip to run the convolutions and pooling of 1 neural net that Tesla thinks it will want to run. It's the best 'AI' chip in the same way that the chip Nokia produces for it's mobile backhaul is the best 'neworking' chip.
The point is that the chip they're trying to compare their custom ASIC to is capable of running several AI frameworks none of which the ASIC can. Hell it can't even run single precision floating point operations.
Tesla has the best chip in the world for the one neural network they want to run. I bet you good money their custom ASIC sucks at running Waymo's AI workload.
"Tesla has the best chip in the world for the one neural network they want to run" is what I wanted to convey but don't actually have the technical background to do it.
"Frankly you're trying to have a technical discussion about a bullshit term"
You are right. I apologise for diluting the discussion and will go back to reading hacker news not creating it.
I love this site and don't want to dilute it.
2) I can't remember a CEO who has complained more about the stock price in particular those shorting the stock. And worst of all then go on to illegally manipulate the market to target them.
3) You have that completely backwards. Musk is the worst at solving problems with the least capital. Look at the way his manufacturing processes work or the decision to build out the Supercharger network/Gigafactory. There are definitely cheaper ways to do those. Better probably not. Cheaper yes.
4) I have worked with more Data Scientists than most and I assure you that they are just like everyone else. They care most about: company reputation, work environment, money, challenging problems etc. It's not just whether there is a great dataset or not.