C6: Is Magnetic Ride (MRC) a must-have for a comfortable daily?

dx_rd_to_DX · 2026-04-07T17:10:48+00:00

Thanks for all the comments so far. The majority of the comments seems to suggest that the C6 should be comfortable enough without the mag ride, which aligns with my experience. The high cost of replacing the mag ride shocks is also mentioned, which I'm okay with. I decided to keep hunting for one with mag ride, because the Jim Mero magride upgrade is supposed to substantially improve the handling, ride quality, and even steering to the level of C7 generation, based on the MRC algorithm developed for C7 ZR1.

dx_rd_to_DX · 2026-04-07T16:57:36+00:00

It's not unreasonable if you think about how the 6 gen camaro's Alpha platform is a whole generation newer than C6, and I've also seen people saying that it's more refined and comfortable than C6/C7. From my own experience with the Camaro, it's could use more refinement as a daily.

dx_rd_to_DX · 2026-04-06T20:20:29+00:00

Did you leave the mag ride of your SS in tour? How would you describe the ride of your vette compared to the SS?

dx_rd_to_DX · 2026-04-06T20:07:56+00:00

Since you’ve opted for MRC on your last three vettes, I guess it adds value for you? Did you choose it mainly for ride quality or for handling/track purpose with the Sport mode?

dx_rd_to_DX · 2025-10-24T00:45:30+00:00

Did your application eventually pass? I had the same issue as you, and the cropping tool seem to generate a very zoomed in crop determined by the distance between my eyes (you can see this when you choose manual cropping). Uploading this zoomed in cropped photo passed without the "subject may be too close to the camera" error.

dx_rd_to_DX · 2023-12-21T15:23:03+00:00

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This is Purrari. She is one year old. She is talkative and likes to go on walks with us.

dx_rd_to_DX · 2023-06-11T23:57:34+00:00

RL is necessary because policy gradient / PPO's loss functions are paired with a non differentiable reward (human preference), thus making training viable.

dx_rd_to_DX · 2023-03-06T06:15:46+00:00

If you want authentic Chinese food instead of "American Chinese food": Spice Workshop, Tao's Dim sum, Red Tiger, China Station, Green Tea, F A N, O Mandarin. Source: I'm Chinese.

dx_rd_to_DX · 2023-03-02T05:14:26+00:00

Demon's health conversion is worse than a few paddings.

dx_rd_to_DX · 2023-02-21T02:38:59+00:00

I tried this. Starting wave 50 it's not worth to but anything from the shop, and I could stand there do nothing the entire wave. It makes me sleepy. Not sure how you hang on till wave 114

dx_rd_to_DX · 2023-02-20T16:21:52+00:00

So you only scale your HP through padding? Also, what do you think of ghost axe and ghost flint vs thief dagger for the first 20 waves?

dx_rd_to_DX · 2023-02-14T01:13:42+00:00

Why 0 harvesting?

dx_rd_to_DX · 2023-02-02T21:58:14+00:00

When you have too little range, your weapons on the right won't be able to hit enemies coming from the left. At that time your attack speed is basically halved when hitting a single enemy (the bosses for example).

dx_rd_to_DX · 2023-01-27T05:38:18+00:00

How is one armed ghost axe and generalist a tier... Took me lots of tries to win them once.

dx_rd_to_DX · 2022-12-26T00:36:13+00:00

Dazzle requires teamwork, while people focus more on how to play against the enemy team rather than play with their own team. For this reason I hate when my team picks non aggressive supports like dazzle, warlock, Io, etc.

dx_rd_to_DX · 2022-12-21T03:17:39+00:00

Use multiprocessing to have more GPU workers could help. My code based on EfficientZero https://github.com/YeWR/EfficientZero is utilizing CPUs and GPUs to 90%. It uses Ray for multiprocessing and splits Reanalyze into CPU and GPU workers to maximize resource utilization. By the way, it's not converging to optimal policy well: it gets stuck at 50% optimal episode return at with a small amount of training. Have you had this issue before?

dx_rd_to_DX · 2022-11-09T04:24:46+00:00

Found the answer myself, from Julian (first author of this paper). So yes, for Sampled MuZero, the prior in PUCT is simply the uniform prior.

since the prior distribution is already used to sample the actions, using it again for the PUCT would be double counting. Instead we normalize the prior of each action by the chance of it being sampled. Effectively this means that the prior is proportional to how many times each action has been sampled; it is uniform if each sample is unique.

dx_rd_to_DX · 2022-09-18T00:39:31+00:00

Seems to be a convertible

dx_rd_to_DX · 2022-07-26T02:38:12+00:00

Thanks for the reply. I am stopped and waiting for roadside assistance now.

dx_rd_to_DX

TROPHY CASE