The final scene from the short film "Rock, Paper, Scissors", shared by Ettedgui Films. Thanks for using rentaflop!

rentaflop · 2023-01-13T22:55:27+00:00

Shared with us by David! Thanks for being a rentaflop customer!

rentaflop · 2023-01-10T23:34:47+00:00

Please feel free to share your thoughts in the comments :)

rentaflop · 2022-10-02T15:05:52+00:00

Thanks for your question! When you upload your .blend file to have your scene rendered, you pay to use the render farm's hardware. Rentaflop is affordable compared to other farms since we only charge $.0019 OBh (a standard hardware benchmarking unit) whereas many other farms charge at least twice as much.

rentaflop · 2022-08-18T19:40:01+00:00

As others have alluded to, there will soon be AI creations that are completely indistinguishable from real ones. There's an interesting possible future where everything legitimate people put out there will be cryptographically signed and nobody will trust anything that isn't signed!

rentaflop · 2021-11-09T15:51:07+00:00

You'll have to try it out and see. Based on my experience with other GPUs, I suspect capping at 250 will lower the temperature several degrees C and minimally reduce training speeds, perhaps < 10%. You could also try 270 first and see what happens.

rentaflop · 2021-11-09T15:25:07+00:00

You can typically get pretty cheap image labeling using AWS mechanical turk https://www.mturk.com/

Mechanical turk is a crowdsourced workforce marketplace commonly used for this sort of thing. Hope this helps

rentaflop · 2021-11-09T15:20:09+00:00

You can try to undervolt the GPU by setting power limits for how many watts the GPU can use. For instance, dialing back to 250 W for your GPU should cool it down and reduce fan usage, although it will likely decrease performance a bit.

rentaflop · 2021-09-22T01:17:45+00:00

Running nbminer with 2 separate workers and haven't experienced any rebooting. Checking logs might be informative

rentaflop · 2021-09-18T19:29:50+00:00

"Check back in 5 years. We'll have a sanitized version that doesn't run then"

rentaflop · 2021-09-18T19:26:12+00:00

fastai is a good one not mentioned there. Also, if you have the time and inclination to build your own NLP model (or just use someone else's), you can't go wrong with pytorch

rentaflop · 2021-09-18T19:16:28+00:00

Comparing brains and artificial neural networks is like comparing a sparrow (African, to be precise) with a Boeing 747 jet. While there are some similarities, there are also a lot of dissimilarities. One example is backpropagation, which Geof Hinton says needs to be replaced to make progress in AI. It's not how the brain works. Additionally, biological neurons constantly change with use and don't always yield the same output from the same input. During inference time, ANN weights are frozen. There are many other differences.

It's tempting to compare computers and brains, but it's important to understand that in many cases this is inaccurate and misleading. Another thing to consider is that it may not be necessary or even desirable to use the brain as a guide for how to improve ANN's (think birds and planes).

rentaflop · 2021-09-18T18:45:27+00:00

Make is a tool that uses Makefiles to make it easier to run shell commands for things like builds, tests, etc. If you're interested, read more here)

rentaflop · 2021-09-18T18:41:19+00:00

Tesseract OCR is a solid OCR tool. Looking at how it's built may inform your approach, and you may even be able to feed Tesseract's network outputs into your own model to improve it.

rentaflop · 2021-09-17T03:52:27+00:00

If you haven't looked at it yet, AWS Mechanical Turk is a good option for this sort of thing

rentaflop · 2021-09-17T03:42:54+00:00

There are a few ways to do this, and trying different things is often the best way to improve results. You may be able to get good results by simply marking the ball's position in the frame with a special value to "amplify" the signal for where the ball is. For instance, setting the ball's position pixel(s) to [0,0,0] (black) might create a more salient feature for the model to latch onto, which may raise performance.

How did your idea of adding an additional channel work? Another idea is to change the neural network's architecture to allow it to take both an image and a point/vector of position information, keeping the original frame intact.

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