Bob Ross Lives: Difference between revisions

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In the context of the latest development in deep learning and specifically in Generative Adversarial Networks (GANs), we read a lot about the negative side of these tools being widely accessible. The media focus on harmful deep fakes and their consequences on politics or privacy. The creative potential of visual generative power of the AI is left behind.
In the context of the latest development in deep learning and specifically in Generative Adversarial Networks (GANs), we read a lot about the negative side of these tools being widely accessible. The media focus on harmful deep fakes and their consequences on politics or privacy. The creative potential of visual generative power of the AI is left behind.
Let’s embrace the positive side of the neural networks' ability to generate synthetic imagery and explore the potential of these tools with a diverse group of curious makers. Before large companies take over and colonize this creative space, or it gets distilled into simple entertaining Snapchat filters, we want to invite hackers and designers to get their hands dirty and experiment with the deep learning models that would have been Bob Ross' wet dream!


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We embraced the positive side of the neural networks' ability to generate synthetic imagery and explored the potential of these tools with a diverse group of curious makers. Before large companies take over and colonize this creative space, or it gets distilled into simple entertaining Snapchat filters, we wanted to invite hackers and designers to get their hands dirty and experiment with the deep learning models that would have been Bob Ross' wet dream!
 
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The future brings a massive challenge for fast adaptation of our senses to the new visual reality as well as the necessary adaptation of our work methodologies. Formerly impossible is now possible - artificial intelligence can generate photorealistic sceneries, objects, animals and humans that are not part of this physical world. Despite its worrying nature, that it might lead to the state of confusion in communication (distinguishing between what’s real and what’s fake), this technological progress also means unforeseeable advancements in the work of visual makers. It’s a new territory that deserves exploration right now, while it’s still evolving. Especially for creative professionals, this evolution means necessary reimagining of their practice, discovering new methodologies and appropriating unexpected new tools. Video might have killed the radio star - GANs might as well kill a lot of creative visual jobs, but will definitely liberate many from laborious visualising in favor for more conceptual and valuable work!
The future brings a massive challenge for fast adaptation of our senses to the new visual reality as well as the necessary adaptation of our work methodologies. Formerly impossible is now possible - artificial intelligence can generate photorealistic sceneries, objects, animals and humans that are not part of this physical world. Despite its worrying nature, that it might lead to the state of confusion in communication (distinguishing between what’s real and what’s fake), this technological progress also means unforeseeable advancements in the work of visual makers. It’s a new territory that deserves exploration right now, while it’s still evolving. Especially for creative professionals, this evolution means necessary reimagining of their practice, discovering new methodologies and appropriating unexpected new tools. Video might have killed the radio star - GANs might as well kill a lot of creative visual jobs, but will definitely liberate many from laborious visualising in favor for more conceptual and valuable work!


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Latest revision as of 08:58, 30 January 2024

Bob Ross Lives
Name Bob Ross Lives
Location NDSM
Date 2019/07/23
Time 9:30-16:30
PeopleOrganisations Lenka Hamosova, Pavol Rusnak
Type HDSA2019
Web Yes
Print No


Antigerda43.jpg

In the context of the latest development in deep learning and specifically in Generative Adversarial Networks (GANs), we read a lot about the negative side of these tools being widely accessible. The media focus on harmful deep fakes and their consequences on politics or privacy. The creative potential of visual generative power of the AI is left behind.

SoyunGan.png

We embraced the positive side of the neural networks' ability to generate synthetic imagery and explored the potential of these tools with a diverse group of curious makers. Before large companies take over and colonize this creative space, or it gets distilled into simple entertaining Snapchat filters, we wanted to invite hackers and designers to get their hands dirty and experiment with the deep learning models that would have been Bob Ross' wet dream!

JonasBae2babe.gif

The future brings a massive challenge for fast adaptation of our senses to the new visual reality as well as the necessary adaptation of our work methodologies. Formerly impossible is now possible - artificial intelligence can generate photorealistic sceneries, objects, animals and humans that are not part of this physical world. Despite its worrying nature, that it might lead to the state of confusion in communication (distinguishing between what’s real and what’s fake), this technological progress also means unforeseeable advancements in the work of visual makers. It’s a new territory that deserves exploration right now, while it’s still evolving. Especially for creative professionals, this evolution means necessary reimagining of their practice, discovering new methodologies and appropriating unexpected new tools. Video might have killed the radio star - GANs might as well kill a lot of creative visual jobs, but will definitely liberate many from laborious visualising in favor for more conceptual and valuable work!

Technical requirements