Exploring the Deep Dream Generator an Art-Making Generative AI PPT

There are many AI animation software and applications developed by big techies like Google, Adobe that are making complex and time-consuming tasks simpler for animators of all categories either beginner or experienced. Some of the examples are Google Deepdream, Adobe Sensei, Adobe Animate, and many more. A Bayesian two-factorial repeated measures ANOVA consisting of the factors interval production [1 s, 2 s, 4 s] and video type (control/Hallucination Machine) was used to investigate the effect of video type on interval production.

In this paper I present one approach of incorporating machine learning into the animator’s toolset. Animation production has often been a leader in the adoption of technology in the motion picture industry, so exploring the emerging technology of machine and deep learning seems a good fit. Machine learning, defined by the IEEE as “the study of computer algorithms that improve automatically through experience,” opens up the possibilities for computing devices to become adept at skills difficult or impossible to specify in traditional computer code.

What are other types of digital art?

Embracing these tools can help you optimize your animation process, deliver high-quality projects faster, and expand your business operations. But to fully harness the potential of AI in animation, it’s equally important to grasp the business side of the animation industry. This is where the Animation Business Accelerator program can offer invaluable assistance.

To do this, I am committed to doing my research, engaging with diverse perspectives, and being thoughtful and intentional in my approach. I think that art created by humans will become even more valuable, and precious. We all want to see and hear real human stories, so that we feel seen and connected. I think the novelty of AI generated stories and pictures will lose its shine. For example, there was a project where we were working on a fabric that was supposed to be laying on top of an actor, but didn’t feel right on the shoot. We pulled references of hellenic statues for the drapery and the look of wet robes, and then basically fed our references and conversation surrounding the shot into DALL-E to produce some images.

Embracing the Future: AI Animation Tools and Beyond

“orison” is a work by Nettrice R. Gaskins, an African American digital artist, academic, cultural critic and advocate of STEAM fields. In her practice, she explores how to generate art pieces through the wide use of algorithms and coding. The combination of technologically advanced tools used as media and the final effect with its vintage character offers an interesting contrast. The lace as a material does not seem to belong to the sphere of the virtual, as it refers to the culture of the handmade, yet the two worlds are brought together in a delicate and poetic dialogue. Another key feature of the Hallucination Machine is the use of highly immersive panoramic video of natural scenes presented in virtual reality (VR). Conventional CGI-based VR applications have been developed for analysis or simulation of atypical conscious states including psychosis, sensory hypersensitivity, and visual hallucinations28,29,33–35.

While sitting on a stool they could explore the video footage with 3-degrees of freedom rotational movement. While the video footage is spherical, there is a bind spot of approximately 33-degrees located at the bottom of the sphere due to the field of view of the camera. After each video, participants were asked to rate their experiences for each question via an ASC questionnaire which used a visual analog scale for each question (see Fig. 2c for questions used). We used a modified version of an ASC questionnaire, which was previously developed to assess the subjective effects of intravenous psilocybin in fifteen healthy human participants31. This can be used for visualizations to understand the emergent structure of the neural network better, and is the basis for the DeepDream concept. The optimization resembles backpropagation; however, instead of adjusting the network weights, the weights are held fixed and the input is adjusted.

Boris Johnson, bins, and coffee in bumholes: Joe Lycett on his array of creative inspirations

We have described a method for simulating altered visual phenomenology similar to visual hallucinations reported in the psychedelic state. Our Hallucination Machine combines panoramic video and audio presented within a head-mounted display, with a modified version of ‘Deep Dream’ algorithm, which is used to visualize the activity and selectivity of layers within DCNNs trained for complex visual classification tasks. In two experiments we found that the subjective experiences induced by the Hallucination Machine differed significantly from control (non-‘hallucinogenic’) videos, while bearing phenomenological similarities to the psychedelic state (following administration of psilocybin). In addition, the method carries promise for isolating the network basis of specific altered visual phenomenological states, such as the differences between simple and complex visual hallucinations. Overall, the Hallucination Machine provides a powerful new tool to complement the resurgence of research into altered states of consciousness. Using Deep Learning algorithms to explore and develop new ways of doing animation is currently both a technical and aesthetic challenge.

• Our fundamental philosophy is that it’s scary and it’s new and there are a lot of unknowns, but it’s also the future.
• The many exciting graphic and animation trends promise to make 2023 an even more exciting year for animators worldwide.
• It’s genuinely fascinating and something no ordinary designers, artists, and creators could ever dream of recreating on their own.
• In the current study, we chose a relatively higher layer and arbitrary category types (i.e. a category which appeared most similar to the input image was automatically chosen) in order to maximize the chances of creating dramatic, vivid, and complex simulated hallucinations.
• Staying abreast of industry standards and trends, our curriculums, taught one-on-one or in small classes (max. 4 students), are designed to prepare you for the dynamic film, game, and publishing industries and to be able to face any challenges head-on.
• After reading this message from Chat GPT I decided to shift my focus to creating images of healing and joy.

In fact, a computer program is sometimes the only way to duplicate newsprint colors with any fidelity. After reading this message from Chat GPT I decided to shift my focus to creating images of healing and joy. My thought process wandered over to a memory of a TikTok trend I used to see with the hashtag #blackboyjoy. It was the sweetest thing ever that this trend went off, and you would see videos of dudes being like “Oh we frolicking now?! Many individuals have been voicing their concerns over the potential harm and destruction caused by AI.

The 6 fundamentals of art every good artist must learn

Confusion is essential to DHMIS’ s unique brand of colourful, chaotic and occasionally distressing content. Launching on YouTube in 2011 as a web short, after the creators had just finished art school, the show was born as a comment on “being taught creativity between occasionally narrow margins,” says Baker. Over a decade has passed since its first episode – which showed its central characters Duck, Red Guy and Yellow Guy receiving a lesson in creativity – and the series is now coming to Channel 4 as a full-length TV show (launching today on 23 September 2022).

Due to its flexibility, artistic flair, and impressive visual effects, 2D and 3D mixed animation quickly became one of the most popular forms. Head of Digital Painting, Brandon Reimchen, thinks that AI art in its current form shouldn’t be seen as a hindrance to artists but as a tool they can use to help speed up creative workflows and generate new ideas. Below are some of the common AI art-generating tools used to create digital imagery. Sensei also has features like Capture Mobile that help in font recognition and text recognition for a video.

However, these previous applications all use of CGI imagery, which while sometimes impressively realistic, is always noticeably distinct from real-world visual input and is therefore suboptimal for investigations of altered visual phenomenology. Our setup, by contrast, utilises panoramic recording of real world environments thereby providing a more immersive naturalistic visual experience enabling a much closer approximation to altered states of visual phenomenology. In the present study, these advantages outweigh the drawbacks of current VR systems that utilise real world environments, notably the inability to freely move around or interact with the environment (except via head-movements). The algorithms (a list of rules laid out in code) used to generate AI artwork can range from simple ones that use randomness or chaos theory-based approaches to more complex methods such as neural networks, deep learning, and natural language processing. Trained DCNNs are highly complex, with many parameters and nodes, such that their analysis requires innovative visualisation methods.

Our fundamental philosophy is that it’s scary and it’s new and there are a lot of unknowns, but it’s also the future. As professionals and people moving into the future, the question becomes, how do we harness this technology and make use of it? We can influence the use of AI within the industry with how we use it responsibly in a way that makes sense. However, people are the drivers and catalysts behind creating visual stories, and we need to assert ourselves in that regard. AI should be viewed as an aid, a supplemental team member where suited, and one driven by people.

Recent Images

Read more about https://www.metadialog.com/ here.