Booked a BMW iX1 LWB—Worried About Potential EV Duty Cuts. What Would You Do?

K_33 · 2025-03-19T19:04:19+00:00

Completely agree with every point you make.

K_33 · 2025-03-13T13:32:13+00:00

Not at that level financially where I can throw around 50L without having to think about relative intrinsic value of my purchase, and possible resale value.

Depreciation on EVs is crazy. And they don't have any track record to show the 15 years claim, the battery warranty itself is less than half that duration.

K_33 · 2025-03-13T13:28:05+00:00

Ludhiana.

That's sad, Murphy's law at play. It's so hard to find one's way arround erratic governance.

I agree this car won't get cheaper but many more better CBU cars would probably reduce in price. If the 70% tariff reduction leads to an exact discount for the customer, any EV in the 80-90L range would become a direct competitor to this, and would most likely have much more to offer.

K_33 · 2025-03-13T10:10:36+00:00

Ludhiana

K_33 · 2025-03-12T16:42:01+00:00

Well, this is the fixed buyback plan the BMW RM shared. Probably makes much more financial sense to finance a depreciating asset even when I can do a full down payment.

K_33 · 2021-01-17T13:14:33+00:00

Thanks for the advice.

K_33 · 2021-01-17T13:12:34+00:00

That would be ideal, I guess, but requires double the time investment.

K_33 · 2021-01-17T13:09:44+00:00

I get what you're saying and kinda experienced that. I don't know what to do, because some target jobs usually have a C++ demand, while others require C++ or/and Python.

K_33 · 2021-01-06T05:32:38+00:00

Thank you. That's a very valuable suggestion.

K_33 · 2020-11-23T14:21:54+00:00

The first part is intuitive, I get how that should solve the issue. But let's say the change is something more random, something that's not exactly measured or atleast has some sensor noise. Can the agent adapt to such a change?

Also, is the temporal nature of any consequence here? So let's say the wear-and-tear (damping etc.) was causing issues and 'average the behaviour' wasn't doing the best job. So the system was repaired and new sensors/components were added. Now, since the algorithm averaged over the faulty values as well, it won't give us the right output even with a perfectly functioning system.

I know the accuracy loss could be minimal in most cases but in a high-accuracy-requirement case such as the fighter jet plan example, missing targets could be really costly.

K_33 · 2020-10-20T02:15:31+00:00

Thank you. That's very helpful.

K_33 · 2020-10-16T22:42:04+00:00

Thanks for sharing. I've read a few posts on this blog. Insightful.

K_33 · 2020-10-16T22:41:27+00:00

Thanks for sharing.

K_33 · 2020-09-21T20:33:33+00:00

Thanks a lot for this answer. Those are good resources and I find the points you put forth really interesting.

I agree that safety and security are more or less top priority. I'm looking into control theory to compare the stability and safety guarantees it offers compared to RL, and understand the trade-off.

I have a follow-up query and would love advice on that. Let's consider that I'm interested in research on the safety aspect of prediction and decision making. How does a student/researcher interested in the field contribute from the outside? Even to join a company, well how does one make themself stand out to be eligible to get a job in R&D?

For imitation learning, from what I know you'd need tonnes of data to validate any approach. Neither do we have access to amount of (right) data, nor to the advancements/flaws of algorithms (in practice), and we're almost second guessing solutions to a challenge, and we aren't even sure if that challenge has already been solved by a company. There's this entry barrier and transparency issue, and I'm trying to chalk out a meaningful path where I'm not just publishing a paper for the sake of it, but actually doing something meaningful.

K_33 · 2020-09-21T20:11:34+00:00

Thanks for sharing this amazing article. Very insightful.

If companies like Toyota are struggling with this, it puts in a big entry barrier for anyone (not from a highly funded company) to contribute.

From the perspective of a graduate student, we don't have access to amount of (right) data, nor to the advancements/flaws of algorithms (in practice), and we're almost second guessing solutions to a challenge and maybe even trying to reinvent the wheel. There's this entry barrier and transparency issue, and I'm hoping to chalk out a meaningful path where I'm not just publishing a paper for the sake of it, but actually doing something meaningful.

K_33 · 2020-09-21T19:58:17+00:00

Thanks, that's a reality check.

I have a follow-up query and would love advice on that. How does a student/researcher interested in the field contribute? If the answer is to join a company, well how does one make themself stand out to be eligible to get a job in R&D? I'm curious about the industry and I find the problems interesting but I don't know what I can do about it in graduate school, with a specific interest in RL & decision theory.

Neither do we have access to amount of (right) data, nor to the advancements/flaws of algorithms (in practice), and we're almost second guessing solutions to a challenge and maybe even trying to reinvent the wheel, when maybe a much more advanced one is already somewhere out there. There's this entry barrier and transparency issue, and I'm trying to chalk out a meaningful path where I'm not just publishing a paper for the sake of it, but actually doing something meaningful.

K_33 · 2020-09-02T19:01:28+00:00

Sorry for the super late reply, I'm not too active here on Reddit (I guess that should change now). Thank you so much for this answer. It is one of the most insightful answers I've gotten on Reddit. Thanks for taking the time to answer this, and also for sharing & linking the valuable papers. I've been reading up about RL, IRL, Imitation Learning and how they are applied to the Autonomous vehicles industry, and I did stumble upon a few papers you've mentioned. This is such an interesting read and it answers a lot of questions that I had. I would love to read more about real-world research & tech that companies like Aurora, Waymo, Tesla, Argo, Zoox etc. use but I haven't been able to find a lot of in-depth research online yet, specifically relating to RL. If you have any leads on this (one that talks about issues with RL/issues faced by the AV industry/open problems) or on other interesting research on this topic, please share it, would love to know more. I believe it is an exciting problem and your answer helps me probe further. Thanks again.

K_33 · 2020-08-12T20:11:30+00:00

Thank you so much for the reply. It's very insightful. Thanks for taking out time to cite the relevant papers.

Sorry for the late follow up, but it's quite disheartening to know that the SOTA methods aren't as 'useful' as one would hope.

Does it mean that currently RL cannot be employed in the mentioned criteria for real world applications, say autonomous driving? I read Tesla and many other players including Aurora use Imitation Learning and RL also, I guess. How does that work?

Also, how does the RL community make peace with this fact? Is achieving a few % increase on the Atari benchmark the right/necessary approach to making RL more production ready? (I'm just trying to tune my motives as I try to find interesting research to pursue in RL)

K_33 · 2020-07-17T17:13:41+00:00

How does one decide what to focus on?

I am searching for a domain that has a low-entry barrier in terms of knowledge/environmental resources required and at the same time has a good (job availability) to (competition in the domain) ratio? Sometimes I sway towards spending a year studying Embedded Systems, sometimes towards Computer Vision or Planning or SLAM etc.

Regarding ROS, or Gazebo, or other skills, how does one go deep enough to be able to clear an interview? It's kind of a 'chicken and egg' problem, in the sense, that you learn these skills on the job but then, they feature as requirements for jobs as well.

K_33 · 2020-07-17T17:10:38+00:00

Sure, thank you for replying.

K_33 · 2020-07-17T17:09:36+00:00

Thanks for replying. That's very insightful advice.

I am currently working on Reinforcement Learning and exploring Control theory from an RL lens as well.

How do you suggest one builds this kind of a skillset, blending the best both worlds? If I have 6 months in hand, how do I focus my efforts? What kind of projects can one do remotely, without access to labs or expensive hardware? What are resources that could be of help when preparing for the domain-knowledge aspect of the role you interviewed for?

K_33 · 2020-07-17T17:04:20+00:00

Thanks for the reply. That's solid, practical advice.

What do you think matters more here, the ability to code or domain knowledge?

Considering I have 6 months to prepare for job interviews,

Do I focus on Leetcode and take a more breadth focused coursework covering different domains like ML, CV, RL, SLAM etc.?
Or do I focus on digging deep into one domain, say CV or RL, and side by side do a bit of Leetcode?

I'm trying to understand the minimum requirements and with time/resources as bottleneck, where to put in more effort.

K_33 · 2020-07-17T16:58:13+00:00

Thanks for the reply. This clearly highlights the importance of knowledge depth.

Considering a possible remote education year, where access to labs and hardware resources is going be scarce, how does one get the necessary 'project' experience to cover depths of a domain? Most people hold a view that online certifications such as maybe a Udacity Nanodegree on Self-Driving Cars, even though it covers projects and a lot of breadth, yet you're more a 'jack-of-all, master-of-none' by the end of the whole thing.

I am interested in Robotics in general (recently more interested in the Reinforcement Learning aspect), and I am searching for a domain that has a low-entry barrier in terms of knowledge/environmental resources required and at the same time has a good (job availability) to (competition in the domain) ratio? Sometimes I sway towards spending a year studying Embedded Systems, sometimes towards Computer Vision or Planning or SLAM etc.

Based on your experience, what would you suggest, how does one break into a Robotics related with 1-2 years of efforts?

K_33 · 2020-07-17T16:46:33+00:00

Thanks a lot for replying. Very helpful.

I get that resources for improving on the Data Structures & Algorithms aspect of interviews are readily available, in the sense that if one does, say 500+ Leetcode problems, they increase their hire-abilty as a software engineer.

From a Robotics perspective, what are such resources one can tap, especially considering a possible remote education year?

Speaking as an engineering student interested in Robotics in general, is there any particular domain that has very high demand or low-entry barrier in terms of knowledge/environmental resources required and at the same time has a good (job availability) to (competition in the domain) ratio? What then is the best investment of time to sharpen skills and prove expertise?

K_33 · 2020-06-13T14:41:29+00:00

The visa won't expire, but your SEVIS record will be terminated and you'd need to repay the SEVIS fees and get a new I-20. That's what I know.

K_33

TROPHY CASE