Welcome to Tesla Motors Club
Discuss Tesla's Model S, Model 3, Model X, Model Y, Cybertruck, Roadster and More.
Register

Model 3 - LR AWD Waiting Room

This site may earn commission on affiliate links.
Received my wall charger today thinking I would need it soon. Silly me thinking the EDD dates are somewhat accurate. 😂
Btw I hope my car doesn’t come in like the charger did, little banged up….
View attachment 801027
I also don’t like how they have Tesla marked all over the boxes they ship. If I didn’t work from home now I wouldn’t feel comfortable with the boxes they send sitting in my front porch.
 
  • Like
Reactions: jpaychek
If your SA doesn’t know what the Matrix Lights are, they are also referred to as the “Global lights”! Excited for you congrats!!!!
mine has been swearing up and down that they are matrix. Have talked to 3 people and all said yes. Have gotten the part number looked up for my vin and they said yes. They even went as much as saying that they dont see description in the part number, but only the part number itself, but upon looking up the part number description it was matrix lights.
But I aint falling for any of that, until I have the vehicle infront of me.
 
I also don’t like how they have Tesla marked all over the boxes they ship. If I didn’t work from home now I wouldn’t feel comfortable with the boxes they send sitting in my front porch.

I haven't purchased the wall charger but on 5 different boxes from Tesla, it's just a typical brown box with very small letters on the shipping label that says Tesla Parts or something to that effect. Couldn't tell it was a Tesla product unless you picked up the box and looked for it. Boxes were floor mats, trunk mats, 2 different adapter cables, and console trays.
 
I initially had mine set for finance, but that just expired. So i'll probably change it cash and try to lock in a rate with my credit union rather than have another hard pull on my credit from Tesla. I was holding strong with my original EDD up until April 20, but at least now it's moving back towards the right direction.
Cool. Just taking a pulse for the variables. I am cash since day one but I did a paint color change about a month ago. Still no changes though. Good luck!
 
If your SA doesn’t know what the Matrix Lights are, they are also referred to as the “Global lights”! Excited for you congrats!!!!
I looked up why they're called "global". It's because they're designed to be able to adapt to the headlamp requirements of various countries around the globe. That may have been obvious to others, but it was not to me.
 
sigmoid works. But typical raw scores and probabilities should be kept separate. Probabilities are usually for binary task i.e will I get my car on 25th or not. Raw numbers are for ordinal (either numeric or discrete) things, e.g will I get my car 10 days from now or 12 days from now or 15 days from now.
Makes sense. What if the model’s output is an ordinal number? Say 12 days from now. How do you convert that to a range as Tesla provides to us? Running many optimizations under different assumptions?
 
I also don’t like how they have Tesla marked all over the boxes they ship. If I didn’t work from home now I wouldn’t feel comfortable with the boxes they send sitting in my front porch.
I said the same thing. I had a $4k item delivered about six months ago and not only did it clearly show in pictures what was inside, but the FedEx guy also left it in the middle of the driveway. Amazon and other companies do it as well. The good news is if a company doesn't insist on you signing for it the claim will work out in your favor.
 
  • Like
Reactions: jpaychek
Makes sense. What if the model’s output is an ordinal number? Say 12 days from now. How do you convert that to a range as Tesla provides to us? Running many optimizations under different assumptions?
1) dont think Tesla uses a complex ML algorithm to make predictions as from what I have gathered, they use some variant of (your num minus current num) divide by daily production, type models.
2) If they were to use an ML model with an ordinal output, they can either sum all the days together and provide a range based on the 95% confidence intervals derived from standard errors, or run a bunch of simulations and provide a range based on the 95% confidence interval of the simulation outputs. Again, if it were me, I would not use an ML model for this problem. Maybe for some tiny component, but definitely not for the main part of the algorithm as the EDD is still largely dependent on how far back a person is in the queue divided by the daily production counts.
 
1) dont think Tesla uses a complex ML algorithm to make predictions as from what I have gathered, they use some variant of (your num minus current num) divide by daily production, type models.
2) If they were to use an ML model with an ordinal output, they can either sum all the days together and provide a range based on the 95% confidence intervals derived from standard errors, or run a bunch of simulations and provide a range based on the 95% confidence interval of the simulation outputs. Again, if it were me, I would not use an ML model for this problem. Maybe for some tiny component, but definitely not for the main part of the algorithm as the EDD is still largely dependent on how far back a person is in the queue divided by the daily production counts.
"Changing Random Stuff until your program works is hacky and bad coding practice. But if you do it fast enough it is Machine Learning and pays 4x your current salary"
 
"Changing Random Stuff until your program works is hacky and bad coding practice. But if you do it fast enough it is Machine Learning and pays 4x your current salary"
I can agree to some of the sentiment as the proportion of people who actually know how to use ML properly, out of the total who claim to know ML or are employed to do ML related work, is pretty low. With the whole 'data science' boom in the past few years, every random person who has ever used an ML package in R or Python, claims to be an expert in ML.
I have been working in the field for 12 years now, and still learn something new whenever I work with a new dataset, or am asked to solve a new problem.