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Print Just before DeepDream: 1000 classes #2, 2015/01
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Just before DeepDream: 1000 classes #2, 2015/01

CHF 9,000.00

by Alexander Mordvintsev

Fine Art Print on paper

Size: 60 x 60 cm

The work is also available as a unique NFT (minted upon request) for 5 ETH

Description:

The Deep Dream algorithm was created in a series of experiments that led to the generation of psychedelic images full of intricate details that swept across the globe in the summer of 2015. Slides 4-8 show images that were created on the way to the final algorithm. Scientific progress is enabled by accumulation of ideas and building on the work of others. For example, p.4 “Just before DeepDream 1000 classes” shows a few images out of 1000 that were generated by the algorithm inspired by the paper . The network was also different: these images were produced by the AlexNet , created in 2012, which is often cited as one of the main triggering points of the Deep Learning revolution. These images lack the resolution and rich details, but already show promising capabilities of deep nets for image generation. The subsequent slides show steps that Alexander Mordivntsev took to improve the fidelity of the machine generations and finally giving the network more “creative freedom” by formulating the objective for amplification patterns already perceived by the network in a particular input image.

For more information please email us on info@katevassgalerie.com

Exhibited at Untitled Miami Art Fair, Miami, Kate Vass Galerie Booth A43, December 2024

Exhibited at Automat und Mensch 2.0, Kate Vass Galerie, May 2024

Add To Cart

by Alexander Mordvintsev

Fine Art Print on paper

Size: 60 x 60 cm

The work is also available as a unique NFT (minted upon request) for 5 ETH

Description:

The Deep Dream algorithm was created in a series of experiments that led to the generation of psychedelic images full of intricate details that swept across the globe in the summer of 2015. Slides 4-8 show images that were created on the way to the final algorithm. Scientific progress is enabled by accumulation of ideas and building on the work of others. For example, p.4 “Just before DeepDream 1000 classes” shows a few images out of 1000 that were generated by the algorithm inspired by the paper . The network was also different: these images were produced by the AlexNet , created in 2012, which is often cited as one of the main triggering points of the Deep Learning revolution. These images lack the resolution and rich details, but already show promising capabilities of deep nets for image generation. The subsequent slides show steps that Alexander Mordivntsev took to improve the fidelity of the machine generations and finally giving the network more “creative freedom” by formulating the objective for amplification patterns already perceived by the network in a particular input image.

For more information please email us on info@katevassgalerie.com

Exhibited at Untitled Miami Art Fair, Miami, Kate Vass Galerie Booth A43, December 2024

Exhibited at Automat und Mensch 2.0, Kate Vass Galerie, May 2024

by Alexander Mordvintsev

Fine Art Print on paper

Size: 60 x 60 cm

The work is also available as a unique NFT (minted upon request) for 5 ETH

Description:

The Deep Dream algorithm was created in a series of experiments that led to the generation of psychedelic images full of intricate details that swept across the globe in the summer of 2015. Slides 4-8 show images that were created on the way to the final algorithm. Scientific progress is enabled by accumulation of ideas and building on the work of others. For example, p.4 “Just before DeepDream 1000 classes” shows a few images out of 1000 that were generated by the algorithm inspired by the paper . The network was also different: these images were produced by the AlexNet , created in 2012, which is often cited as one of the main triggering points of the Deep Learning revolution. These images lack the resolution and rich details, but already show promising capabilities of deep nets for image generation. The subsequent slides show steps that Alexander Mordivntsev took to improve the fidelity of the machine generations and finally giving the network more “creative freedom” by formulating the objective for amplification patterns already perceived by the network in a particular input image.

For more information please email us on info@katevassgalerie.com

Exhibited at Untitled Miami Art Fair, Miami, Kate Vass Galerie Booth A43, December 2024

Exhibited at Automat und Mensch 2.0, Kate Vass Galerie, May 2024


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