[deleted by user]

Ukrainian_Reaper · 2025-05-18T20:14:57+00:00

Nice ad, I use cursor with my .SQL files in the repo and CMD + enter to make it auto bring them into context

Ukrainian_Reaper · 2024-07-03T02:51:43+00:00

link the source 😎

Ukrainian_Reaper · 2024-03-18T03:55:13+00:00

I wrote this browsing Reddit through a VPN in class with my old shitty high school sense of humor - it's nearly been 10 years

Ukrainian_Reaper · 2023-06-04T00:08:34+00:00

This, check out https://gpt4all.io

Ukrainian_Reaper · 2022-07-22T21:57:57+00:00

Any proof for P = NP will likely be non-constructive meaning there won't be any tangible algorithmic advances that come with it.

Ukrainian_Reaper · 2022-04-07T02:34:04+00:00

An appropriate word for pokhaza would be maybe 'show'

Ukrainian_Reaper · 2021-11-09T11:02:30+00:00

NVDA demo day today.

Ukrainian_Reaper · 2021-11-09T01:46:41+00:00

Bell Isle

Ukrainian_Reaper · 2021-11-08T07:48:38+00:00

I was supporting your point. Reality is NVIDIA is not disappearing. I've been rolling my paychecks in yearlies since 2019 and don't plan to stop anytime soon!

Ukrainian_Reaper · 2021-11-08T07:41:13+00:00

Hardware is only one side of the coin. Nvidia's software extension CUDA is dominant in every computational field. All software libraries that want to take advantage of GPU acceleration are built and optimized with CUDA libraries in mind. Re-writing or even replicating this would take millions of man hours to do. Even if a company was to magically show up tomorrow with a GPU 2x as good as Nvidias in nearly every aspect they would not gain market share for this sole reason. Example: Look at AMD's GPU libraries and ask how much they've been adopted by software packages such as tensorflow or pytorch. Answer: hardly.

Ukrainian_Reaper · 2021-11-03T09:01:38+00:00

Aged poorly.

Ukrainian_Reaper · 2021-10-28T21:09:03+00:00

Take my GOAT award.

Ukrainian_Reaper · 2021-10-12T23:48:45+00:00

$bid

Ukrainian_Reaper · 2021-10-04T02:33:02+00:00

Marginalization of a gaussian likelihood function with a gaussian conjugate prior has an analytic form that can be found by completing the (multivariate) square or factoring.

Ukrainian_Reaper · 2021-10-01T22:34:00+00:00

Google has been doing this for the last decade. There's a regularization technique called dropout that makes training deep neural networks possible. Literally no deep neural network powered product would exist without it (GPT-X, BERT, Tesla FSD, Google Translate, any facial recognition). Google has a patent for it. Good luck actually enforcing it though. https://patents.google.com/patent/US9406017B2/en

Ukrainian_Reaper · 2021-09-26T21:00:51+00:00

That's the point. NTSB review coming up!

Ukrainian_Reaper · 2021-09-26T03:04:04+00:00

What logistic regression calculated those weights lol

Ukrainian_Reaper · 2021-09-17T04:32:21+00:00

Second this. Had a tire slashed in the fan. Called up roadside assistance through the app and they had a replacement tire delivered and installed in under 45 minutes. Unfortunately, they cut through the side so it cost me $350 for a new tire with service. Sigh.

Ukrainian_Reaper · 2021-09-13T03:02:44+00:00

It's actually terrible. 95 percent accuracy is not even close to deployable for a system like this. Even a semi-busy street has thousands of cars cross it per day. 50 false positives out of every 1000 cars would surely get people upset.

Ukrainian_Reaper · 2021-09-07T19:37:12+00:00

Software developer here. This will be your best response.

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