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> Teams at the San Mateo office were tasked with evaluating customer vehicle data related to the Autopilot driver-assistance features and performing so-called data labeling. My sympathies with the folks laid off, but do American firms still do data labeling in-house? I assume most of it is out-sourced via Scale or other vendors to eventually India, Vietnam etc.
Does anyone know why Tesla is laying off so agressively? While they are likely overvalued post-pandemic... their financial position appears solid even if the stock fell by 50x. I doubt any cuts could yield the type of profitability that wall street expects at the current valuation.
That's the reason.
Earlier quoted context omitted.
If I recall correctly, Karpathy during one of the Tesla AI talks addresses this and said that keeping data labeling in-house was an advantage because it could be integrated more tightly into their processes with better customization & turnaround etc. Firing most of their data-cleaning & labeling capacity isn't going to be good for their car efforts, but I suppose if things are that bad at Tesla now, it's better to fi…
The Tesla bull will say that Tesla’s ML has gotten so good that these top-shelf human curators are now unnecessary, and can be outsourced or dispensed with entirely. The Tesla bear will counter that this is merely to keep up appearances; it looks a hell of a lot better to fire data curators over machine learning engineers, even if the former are still just as (if not more!) necessary as the latter.
I would be very surprised if Tesla optimized for optics here.
Does anyone know why Tesla is laying off so agressively? While they are likely overvalued post-pandemic... their financial position appears solid even if the stock fell by 50x. I doubt any cuts could yield the type of profitability that wall street expects at the current valuation.
The interest rates will likely reach 3% by the end of the year, and may need to go all the way to 8% to have a meaningful effect on the inflation.
Every measurable economic metric suggests we are rolling full speed into a recession. And driving your old car for another year or two instead of upgrading to that nice luxury EV is one of the first things many people would do.
So, their sales will likely plummet. Taking on more debt will become quite expensive, and the share prices will very likely correct by a lot. They are doing everything well, if you ask me.
Does anyone know why Tesla is laying off so agressively? While they are likely overvalued post-pandemic... their financial position appears solid even if the stock fell by 50x. I doubt any cuts could yield the type of profitability that wall street expects at the current valuation.
Does anyone know why Tesla is laying off so agressively? While they are likely overvalued post-pandemic... their financial position appears solid even if the stock fell by 50x. I doubt any cuts could yield the type of profitability that wall street expects at the current valuation.
These are not the kind of cuts you make because you have a bad feeling. These are the kinds of cuts you make because you're seeing orders fall off a cliff. I suspect that in particular Tesla is seeing erosion in their Cybertruck pre-orders given that Ford and Rivian have beaten them to market and both those products are drawing rave reviews.
And why do you think that orders are falling off of a cliff exactly?
Tesla has grown incredibly fast, they have 100k employees, they have a terrific balance sheet and are at no risk of bankruptcy.
For the last 10 years people seem to always lay out this awful scenario for Tesla, meanwhile they are growing in sales incredibly quickly, literally the quickest ever.
> Teams at the San Mateo office were tasked with evaluating customer vehicle data related to the Autopilot driver-assistance features and performing so-called data labeling. My sympathies with the folks laid off, but do American firms still do data labeling in-house? I assume most of it is out-sourced via Scale or other vendors to eventually India, Vietnam etc.
Recently NY state sold off all the solar panel equipment, and Panasonic pulled out of the partnership. Tesla hired minimum wage data taggers to avoid fines under the job creation agreement.
One of the worst public subsidy scams in state history if you ask me, alongside Scott Walker's Foxconn giveaway in Wisconsin. I wish state governments would collectively agree to stop falling for this.
https://www.investigativepost.org/2021/12/28/tesla-reaches-i...
Does anyone know why Tesla is laying off so agressively? While they are likely overvalued post-pandemic... their financial position appears solid even if the stock fell by 50x. I doubt any cuts could yield the type of profitability that wall street expects at the current valuation.
Tesla P/E is at 94, Ford is at 4, so they are overvalued by quite a lot. The interest rates will likely reach 3% by the end of the year, and may need to go all the way to 8% to have a meaningful effect on the inflation. Every measurable economic metric suggests we are rolling full speed into a recession. And driving your old car for another year or two instead of upgrading to that nice luxury EV is one of the first t…
You don't even know what you are saying about Tesla. Take on more debt? Why would they do that? They have 17 billion dollars in cash on hand, and paid off a lot of their pre existing debt.
Even if they want to build a new gigafactory they don't need any more funding. They smartly sold more shares when the stock was insanely high and got a huge infusion.
Earlier quoted context omitted.
The Tesla bull will say that Tesla’s ML has gotten so good that these top-shelf human curators are now unnecessary, and can be outsourced or dispensed with entirely. The Tesla bear will counter that this is merely to keep up appearances; it looks a hell of a lot better to fire data curators over machine learning engineers, even if the former are still just as (if not more!) necessary as the latter.
They still have a lot of human curators (Elon said they have over 1500 in a recent interview). I imagine that these cuts are for some category of labeling that has become redundant.