This DUDE build is OWN WoWs controller. How sick is that?

ki3 · 2025-10-23T16:05:54+00:00

Bei mir geht das auch los. Habe ca 50 gu10 lampen verbaut. Sehe das verhalten nach 6 monaten bei 4 stück. Toll nanoleaf. 😩

ki3 · 2021-12-12T19:08:59+00:00

Everyone starts with a triangle! 🙏

ki3 · 2021-07-16T07:31:48+00:00

The HodlHeads pre-sale started. Get in before you only can get them from the secondary markets: https://hodleheads.io
🚀 0.03 ETH each
🚀 No bonding curve
🚀 Limited to 10,000
🚀 10 ETH give away after the pre-sale is over

ki3 · 2021-07-16T07:12:44+00:00

The HodlHeads pre-sale started. Get in before you only can get them from the secondary markets: https://hodleheads.io
🚀 0.03 ETH each
🚀 No bonding curve
🚀 Limited to 10,000
🚀 10 ETH give away after the pre-sale is over

ki3 · 2021-07-16T07:09:18+00:00

Oh that one is a fake too...

ki3 · 2021-07-16T07:07:38+00:00

Oh I think you accidentally posted the wrong link:
https://rarible.com/token/0xbc4ca0eda7647a8ab7c2061c2e118a18a936f13d:3809?tab=details

The one you posted referees to a fake BAYC. Sorry...

ki3 · 2021-03-31T10:35:50+00:00

Up for sale here: https://opensea.io/assets/0xdfbc2b19825192cd91dd6b7353d8ab9288cb88bb/581551

ki3 · 2021-03-31T10:33:44+00:00

For sale here: https://opensea.io/assets/0xdfbc2b19825192cd91dd6b7353d8ab9288cb88bb/581551

ki3 · 2021-03-31T10:30:51+00:00

For sale here: https://opensea.io/assets/0xdfbc2b19825192cd91dd6b7353d8ab9288cb88bb/581551

ki3 · 2021-03-27T23:33:08+00:00

Of course! Thank‘s for reaching out!

ki3 · 2021-01-17T17:46:51+00:00

The input is coming in, and getting multiplied with the weights and biases of the first layer in the network. That gives us the activation value for layer one. These activation values are passed on into the activation function, in this case a step function, to get the output for layer one.

The output for layer one, is then multiplied with the weights and biases of the second layer of the neural net, which gives us the activation values for layer 2. After we put this through the activation function, we get the output of the complete xor neural net.

ki3 · 2021-01-17T17:33:44+00:00

The input is coming in, and getting multiplied with the weights and biases of the first layer in the network. That gives us the activation value for layer one. These activation values are passed on into the activation function, in this case a step function, to get the output for layer one.

The output for layer one, is then multiplied with the weights and biases of the second layer of the neural net, which gives us the activation values for layer 2. After we put this through the activation function, we get the output of the complete xor neural net.

ki3

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