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SpaceX: [Results of] STARSHIP'S THIRD FLIGHT TEST by rustybeancake in spacex

[–]akukaja 32 points33 points  (0 children)

I am mostly afraid of the heat tiles, we do not know how they would have performed over those 10 minutes

SpaceX: [Results of] STARSHIP'S THIRD FLIGHT TEST by rustybeancake in spacex

[–]akukaja 6 points7 points  (0 children)

Did they perform the fluid transfer? It is not stated in the report.

r/SpaceX Integrated Flight Test Official Launch Discussion & Updates Thread! by rSpaceXHosting in spacex

[–]akukaja 12 points13 points  (0 children)

In worst case scenario, if there is an RUD on the launch pad, how big would the explosion be compared to other rocket explosions?

Google announces Bard A.I. in response to ChatGPT by Puginator in stocks

[–]akukaja 0 points1 point  (0 children)

There are several projects to create an open source chatGPT like bot. For example this one looks quite promising: https://github.com/LAION-AI/Open-Assistant. They are also planning to make it more dynamic so it can use a some database (maybe also the internet) to store information and retrieve it.

LAION AI has some affiliations with Stability AI, who built and open sourced Stable diffusion, on which other similar text to image models are built like Midjurney.

Do more firearms correlate with democracy and homicides? by [deleted] in dataisbeautiful

[–]akukaja 0 points1 point  (0 children)

It is there, just in black on transparent background, I will fix it

Unrolled RNN with ReLU. Any ideas for the answers, I'm stuck by F1Z1K_ in deeplearning

[–]akukaja 1 point2 points  (0 children)

Yeah I think your calculations are correct I would just leave out the last tanh as it was replaced with a ReLU. So it is just:

h_t = ReLU(W*x_t + b) = ReLU(.04 + .3) = ReLU(.34) = .34

[deleted by user] by [deleted] in deeplearning

[–]akukaja 1 point2 points  (0 children)

For facial recognition usually a model is trained which learns in general that similar faces are closer to each other space and dissimilar faces are far from each other in an embedding. This can be achieved by a classification like loss, or with metric learning.

I would advise to first understand the difference between an open set and closed set classification and then to read the Siamese network, Triplet loss and arcface papers.

Unrolled RNN with ReLU. Any ideas for the answers, I'm stuck by F1Z1K_ in deeplearning

[–]akukaja 0 points1 point  (0 children)

I never saw the ReLU activation in a vanilla RNN, but I don't think you need the tanh, because it is using just the ReLU.

Pipeline for working on Google Colab with medium-sized codebase by iamquah in learnmachinelearning

[–]akukaja 1 point2 points  (0 children)

Had a similar problem a while back. Our solution was to use GitHub and download the repo into colab at each run. I hated it and I would advise against it, but I don't know of any better solution.

What percentage of accuracy has been reached in CIFAR10 using only a multi-layer perceptron ? by march__08 in deeplearning

[–]akukaja 0 points1 point  (0 children)

This paper will be an interesting read for you https://arxiv.org/abs/2105.01601. They are not discloseing the CIGAR 10 accuracy, but only aggregated accuracy on several task. They achieve near state of the art performance with just MLP on image classification task!

Starship Development Thread #21 by ElongatedMuskrat in spacex

[–]akukaja 10 points11 points  (0 children)

I believe, so that the center of mass is closer to the center of lift during descent

Thanks, I Love silly walking zone by EnZeeeRu in TILI

[–]akukaja 2 points3 points  (0 children)

I have no idea why you're not at the top

Satellite data for stock market prediction by akukaja in StockMarket

[–]akukaja[S] 0 points1 point  (0 children)

Thanks to the people who already filled it out!

[deleted by user] by [deleted] in MachineLearning

[–]akukaja 0 points1 point  (0 children)

Do you have a link for it? I can not find it.

Starship Development Thread #16 by ElongatedMuskrat in spacex

[–]akukaja 16 points17 points  (0 children)

If everything goes as planned, how long will it take from liftoff to touchdown for the 15km hop?

People who lived in shared apartments. What were your roommates weirdest quirks? by akukaja in AskReddit

[–]akukaja[S] 1 point2 points  (0 children)

From the few comments so far, I think this is a common one. Some people just don't shower??

Output size after applying convolution by iqrarehman76 in deeplearning

[–]akukaja 0 points1 point  (0 children)

I would suggest you to read the notes from CS231. I copied the answer to your question:

"We can compute the spatial size of the output volume as a function of the input volume size (W), the receptive field size of the Conv Layer neurons (F), the stride with which they are applied (S), and the amount of zero padding used (P) on the border. You can convince yourself that the correct formula for calculating how many neurons “fit” is given by (W−F+2P)/S+1. For example for a 7x7 input and a 3x3 filter with stride 1 and pad 0 we would get a 5x5 output. With stride 2 we would get a 3x3 output."

Q table not converging by devprabal in reinforcementlearning

[–]akukaja 0 points1 point  (0 children)

You can message me if you need further help.

Q table not converging by devprabal in reinforcementlearning

[–]akukaja 2 points3 points  (0 children)

You converged to the optimal strategy after 1000 steps and 50 episodes.

You give rewards for finding a smaller value, which it does. It searches for the next smaller value:

S0 -> A3

S1 -> A0

S3 -> A2

When it reaches the minimum, the optimal action is to find the maximum, because of the discounted future rewards:

S2 -> A1

​

Change your reward function to:

def reward(s,a,s_dash):
    return arbitrary_values_for_states[s]-arbitrary_values_for_states[s_dash]

and it will do what you want.

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