Extended Intelligences

FACULTY: Ramón Sangüesa/ Lucas Lorenzo Peña/ Pau Artigas

CALENDAR:28/11/2023 - 05/12/2023

TRACK: Exploration

11/29/2023

Surroundings

It was a long-long day.

graph LR
Madrid --> Barcelona

graph LR
Cold --> Warm

graph LR
Cloudy/Rainy --> Sunshine

Who are we helping?

An AI of a remarkable Artist that already passed away … : ( …

• During the class time, I had an idea, but this idea was in my heart for a long-long-long-time. Which is to deeply study or deeply collective informations about Modernisme (Catalan pronunciation: [muðərˈnizmə], Catalan for “modernism”), also known as Catalan modernism and Catalan art nouveau

• “The reason I wrote ‘failure’ is that because no AI machine can replace a legendary artist. Creativity is the main differences between gente and machines.” (12/01/2023)

What is Catalan modernism?

The History of Modernism in Catalan modernisme refers to not just an artistic style, but a cultural movement that spanned across architecture, art, music, literature, and society as a whole.

Quote

“Modernisme has many faces and echoes a certain ambiguity,”

Mariàngels Fondevila, curator at Museu Nacional d’Art de Catalunya

1. Guadi

Conversation

By having a conversation with Albert, which he is a Catalan man.

I asked Albert: “Do you like Guadi?”

ALbert answered: “I used to like it, but nowdays, La Sagrada Familia being changed =A Lot=”

I started to questioning myself, why people starts to hate it? Is that because Guadi? or people who building/designing/constructing it NOWdays? People keep saying that they are pasing Guadi’s art pieces to complish it. But is that a real opinion done by Guadi? I mean, he is in the heaven. Or maybe he had a code that later people can/needs to be followed? Also, for designing a architecture is not only designing 1/one/uno building, it should including the surroundings, to combining together and make a best decision.

Example

• what if we collected all the data of Guadi’s art work then move it to AI to help us do the best calculating and fair desicions.

https://www.instagram.com/gaudism.ai/?img_index=1

References

https://www.instagram.com/gaudism.ai/?img_index=1 https://www.veranda.com/home-decorators/a35075545/what-is-catalan-modernisme/ https://www.youtube.com/watch?v=z7OzWUjqkms https://www.bilibili.com/video/BV1ox411e77P/?spm_id_from=333.337.search-card.all.click&vd_source=266489d5e7b5d644812bbc8116e63a6c

Who are we helping?

The /flat/ earth

The first living robot that collects microplastics in the ocean

PNAS- Xenobot

Xenobots, named after the African clawed frog (Xenopus laevis), are synthetic lifeforms that are designed by computers to perform some desired function and built by combining together different biological tissues. Whether xenobots are robots, organisms, or something else entirely remains a subject of debate among scientists.

References

https://en.wikipedia.org/wiki/Xenobot

https://www.pnas.org/doi/10.1073/pnas.1910837117

https://www.pnas.org/post/podcast/designing-synthetic-organisms

https://www.the-scientist.com/news-opinion/xenobot-living-robots-can-reproduce-69477

https://www.britannica.com/video/179811/debris-Pacific-Ocean

https://theoceancleanup.com/ (introduced by Carlotta Alberta Hylkema)

Who are we helping?

The Children

Megan

• M3GAN is a marvel of artificial intelligence, a lifelike doll that’s programmed to be a child’s greatest companion and a parent’s greatest ally. Designed by Gemma, a brilliant roboticist, M3GAN can listen, watch and learn as it plays the role of friend and teacher, playmate and protector. When Gemma becomes the unexpected caretaker of her 8-year-old niece, she decides to give the girl an M3GAN prototype, a decision that leads to unimaginable consequences.

• M3GAN (pronounced “Megan”) is a 2022 American science fiction horror film directed by Gerard Johnstone. It was written by Akela Cooper from a story by Cooper and James Wan (who also produced with Jason Blum). Allison Williams and Violet McGraw star, Amie Donald physically portrays M3GAN, and Jenna Davis voices the character.

References

https://www.imdb.com/title/tt8760708/ https://en.wikipedia.org/wiki/M3GAN

Klara and the Sun- Novel by Kazuo Ishiguro

• One of my favorite fiction :)
• From her place in the store, Klara, an Artificial Friend with outstanding observational qualities, watches carefully the behavior of those who come in to browse, and of those who pass on the street outside. She remains hopeful that a customer will soon choose her, but when the possibility emerges that her circumstances may change forever, Klara is warned not to invest too much in the promises of humans.

References

https://www.goodreads.com/book/show/54120408-klara-and-the-sun https://en.wikipedia.org/wiki/Klara_and_the_Sun https://www.newyorker.com/magazine/2021/03/08/kazuo-ishiguro-uses-artificial-intelligence-to-reveal-the-limits-of-our-own

Datasets

Dataset name	WikiArt Dataset
Dataset URL	https://datasets.activeloop.ai/docs/ml/datasets/wiki-art-dataset/
	https://paperswithcode.com/dataset/wikiart/
	https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN
Description	The WikiArt dataset contains paintings from 195 different artists. The dataset has 42129 images for training and 10628 images for testing. Because WikiArt is available to the public, it has a well-developed structure, WikiArt is often used in the field of machine learning. Namely, it is used to train AI on WikiArt data to discover its ability to recognize, classify, and generate art.
Interest	During my undergraduate studies, I pursued a double major in Interior Architecture and Art History. However, my particular passion lies in Art History. I am intrigued by the origins of each art movement, the underlying logic and philosophical aspects, and the reasons leading to their eventual manifestations.
	Throughout my exploration of Art History, I actively traced the roots of each art movement, delving deep into their ideologies and philosophical foundations. I gained a profound understanding of how societal, cultural, and historical factors influence art movements. I sought to comprehend the origins and development of these movements from an artistic perspective, considering the unique environments and social contexts of each period.
	Each art movement is like a canvas saturated with the thoughts and reflections of artists of that time. I am excited by the unique creativity and ideas that emerge within these movements. Through artworks spanning different eras, I aim to understand how artists serve as cultural commentators of their times by expressing their viewpoints and emotions.
	While pursuing a profound understanding of art movements, my interest extends to the evolution of their ultimate forms. I believe that interpreting artworks from logical and philosophical perspectives not only aids in appreciating their aesthetics but also reveals deeper layers of thoughts and emotions embedded in these creations.
	In summary, my academic background fuels my deep curiosity about the origins and development of art movements. I look forward to further exploring and understanding the cultural and philosophical implications of different art movements and how they have influenced the evolution and presentation of art.

Quote

“The famous pipe. How people reproached me for it! And yet, could you stuff my pipe? No, it’s just a representation, is it not? So if I had written on my picture “This is a pipe”, I’d have been lying!”

— wrote René Magritte about his brilliant concept and artwork “The Treachery of Images”.

This quote is from René Magritte, a famous surrealist artist, and it refers to his painting “The Treachery of Images” (“La trahison des images” in French). The painting features a pipe, accompanied by the text “Ceci n’est pas une pipe” (This is not a pipe) below it.

Magritte’s statement reflects the philosophical idea that an image or representation is not the same as the real object it represents. The pipe in the painting is just an image of a pipe, not a functional pipe that one could smoke. The text challenges the viewer to consider the distinction between representation and reality.

Magritte’s work often explored the relationship between words and images, and “The Treachery of Images” is a prime example of his fascination with the nature of perception and language in art. The painting invites viewers to question their assumptions about representation and prompts philosophical reflections on the nature of reality in art.

For further FUTURE

1. Social and Historical Background:

   Examine the societal, political, and cultural environment of specific periods, understanding the social upheavals and intellectual trends that often influence the development of art.

2. Artists and Thinkers:

   Study the major artists and thinkers within specific art movements, gaining insights into their perspectives, ideologies, creative motivations, and how they propelled the movement forward.

3. Technological and Innovative Aspects:

   Investigate the technologies and innovations associated with art movements, including painting techniques, sculptural methods, photographic advancements, etc. Technological changes often play a significant role in the evolution of artistic forms.

4. Artistic Theory:

   Understand the theoretical foundations of particular art movements, including considerations of artistic viewpoints, aesthetic concepts, and the philosophical reflections on artistic goals.

5. Social Impact:

   Examine the societal impact of specific art movements, encompassing their influence on the public, critics, and other artists. Analyze how these movements resonate within the broader social context.

References

https://towardsdatascience.com/the-non-treachery-of-dataset-df1f6cbe577e

BINGO

Quote

From Taco 2 CoCo 2 Yolo - Albert

If for any reason the connection is broken. Just call me again- Colab

AI image created by Adobe Firefly

BINGO

Here is the process of how the AI would work inside an app called Bingo, made to help the people to throw out the trash in the correct recycled bin.

Previous info

To know”BINGO” previous info :https://33dudu.github.io/magicreator/term1/Intervention%2001/

What?

• What kind of data (images, text, world)
• What task you want to
• Different specific models of the same type of network
• its internal functioning
• deep neural network

https://github.com/simonw/laion-aesthetic-datasette

• Dataset for trash identification/ Taco,
• Train and model for Dataset for trash/ COCO/YOLO/ Colab
• Obj. classification data set
• Neural Network

Catalog of Datasets:

Floder:

• Cigarratte

• Drink Can

• Foam Cup

• Negative=none of above

Reflection

Introduction:

In an increasingly environmentally-conscious world, efficient waste management has become a global priority. This document introduces an innovative solution: an artificial intelligence (AI) specialized in trash tracking. This AI not only identifies objects as garbage but also provides valuable information to enhance waste management. Throughout this document, we will explore the fundamentals of this technology, its advanced capabilities, and the positive impact it can have on environmental sustainability and waste management efficiency.

Creation:

Data set: For selecting the information library, initially, our focus was on searching for specific datasets to recognize beverage cans and cigarettes. Even during the process, we proposed creating a small dataset with images to label the brands. Due to time constraints, we opted for a library that specializes in trash recognition called TACO.

Neural networking: We came across YOLO, a neural network for image detection and recognition that is also compatible with the chosen dataset.

Coding:

Since the dataset from TACO uses COCO format, we first need to convert it to the files needed by YOLO. The requirements to train YOLO with our custom dataset are as follows:

A: Splitting the dataset to a folder containing an “images” folder and a “labels” folder for training, another containing an “images” folder and a “labels” folder for validation and an optional folder containing an “images” folder and a “labels” folder for testing

B: A .yaml file that contains the list of classifications and paths to the mentioned folders. See appendix.

Training: the following command trains the model

!yolo task=detect mode=train model=yolov8n.pt data=/content/trash_data/trash_data.yaml epochs=25 imgsz=640

Parameters:

1. data = path to the .yaml file
2. epochs = number of iterations. More epochs means longer training.
3. imgsz = image size

This outputs 2 new models: best.pt and last.pt

Detecting: we can now use the following command to detect objects in an image we give it

!yolo task=detect mode=predict model=”/content/train/weights/best.pt” source=”/content/20231205_004350.jpg

Sample output:

Conclusions:

1 - From the dataset that recognizes objects as trash, we question what criteria define the initiation of an object to be categorized as garbage.

2 - To improve the precision of the model, the neural network should be trained with more epochs (time).

3 - On surveillance and accountability: We can combine it with a text or label detection in order to trace the origin of the product and the companies responsible for the waste.

References

YOLOv8 https://github.com/ultralytics/ultralytics

(chatgpt-cost): https://www.washingtonpost.com/technology/2023/06/05/chatgpt-hidden-cost-gpu-compute/

():https://12ft.io/

(transition from Automatization to Autonomization)https://www.youtube.com/watch?v=rL3D0cAu02U

(Voice In My Head): https://lauren-mccarthy.com/Voice-In-My-Head