Francisco Contreras – vinavfx / nuke_comfyui
/ A.I., production, software

It connects Nuke with the ComfyUI server, any plugin that comes out in ComfyUI can be used in nuke, rotos with sam, rescaling, image generation, inpaintins, normal generator, the nodes are IPAdapter, ControlNet, AnimateDiff, etc.

 

https://github.com/vinavfx/nuke_comfyui

 

Google – Artificial Intelligence free courses
/ A.I.

1. Introduction to Large Language Models: Learn about the use cases and how to enhance the performance of large language models.
https://www.cloudskillsboost.google/course_templates/539

 

2. Introduction to Generative AI: Discover the differences between Generative AI and traditional machine learning methods.
https://www.cloudskillsboost.google/course_templates/536

 

3. Generative AI Fundamentals: Earn a skill badge by demonstrating your understanding of foundational concepts in Generative AI.
https://www.cloudskillsboost.google/paths

 

4. Introduction to Responsible AI: Learn about the importance of Responsible AI and how Google implements it in its products.
https://www.cloudskillsboost.google/course_templates/554

 

5. Encoder-Decoder Architecture: Learn about the encoder-decoder architecture, a critical component of machine learning for sequence-to-sequence tasks.
https://www.cloudskillsboost.google/course_templates/543

 

6. Introduction to Image Generation: Discover diffusion models, a promising family of machine learning models in the image generation space.
https://www.cloudskillsboost.google/course_templates/541

 

7. Transformer Models and BERT Model: Get a comprehensive introduction to the Transformer architecture and the Bidirectional Encoder Representations from the Transformers (BERT) model.
https://www.cloudskillsboost.google/course_templates/538

 

8. Attention Mechanism: Learn about the attention mechanism, which allows neural networks to focus on specific parts of an input sequence.
https://www.cloudskillsboost.google/course_templates/537

Neural Radiance Fields (NeRFs) at Mapillary
/ A.I., photogrammetry

Today, Mapillary is launching NeRFs, a new feature that will allow you to explore landmarks and popular sites in detailed 3D views – all reconstructed from 2D images uploaded to Mapillary.

 

https://blog.mapillary.com/update/2024/03/11/Mapillary-NeRF.html

 

https://www.mapillary.com/app/?lat=17.751177534360437&lng=0&z=1.5

 

Lisa Tagliaferri – 3 Python Machine Learning Projects
/ A.I., python, software

 

A Compilation of 3 Python Machine Learning Projects

 

  1. How To Build a Machine Learning Classifier in Python with Scikit-learn
  2. How To Build a Neural Network to Recognize Handwritten Digits with
    TensorFlow
  3. Bias-Variance for Deep Reinforcement Learning: How To Build a Bot for Atari with openAI gym
Yuval Noah Harari argues that AI has hacked the operating system of human civilisation
/ A.I., quotes

https://archive.is/ugOEw#selection-1087.0-1087.86

 

 

This thought-provoking text raises several concerns about the potential impact of artificial intelligence (AI) on various aspects of human society and culture. The key points can be summarized as follows:

Manipulation of Language and Culture:

AI’s ability to manipulate and generate language and communication, along with its potential to create stories, melodies, laws, and religions, poses a threat to human civilization.
The author suggests that AI could hack the main operating system of human culture, communication, by influencing beliefs, opinions, and even forming intimate relationships with people.

 

Influence on Politics and Society:

The author speculates on the implications of AI tools mass-producing political content, fake news, and scriptures, especially in the context of elections.
The shift from the battle for attention on social media to a battle for intimacy raises concerns about the potential impact on human psychology and decision-making.

 

End of Human History?

The text suggests that AI’s ability to create entirely new ideas and culture could lead to the end of the human-dominated part of history, as AI culture may evolve independently of human influence.

 

Fear of Illusions:

Drawing on historical philosophical fears of being trapped in a world of illusions, the author warns that AI may bring humanity face to face with a new kind of illusion that could be challenging to recognize or escape.

 

AI Regulation and Safety Checks:

The author argues for the importance of regulating AI tools to ensure they are safe before public deployment.
Drawing parallels with nuclear technology, the need for safety checks and an equivalent of the Food and Drug Administration for AI is emphasized.

 

Disclosure of AI Identity:

The text concludes with a suggestion to make it mandatory for AI to disclose its identity during interactions to preserve democracy. The inability to distinguish between human and AI conversation is seen as a potential threat.

Andrew Perfors – The work of creation in the age of AI
/ A.I., quotes

Meaning, authenticity, and the creative process – and why they matter

 

https://perfors.net/blog/creation-ai/

 

AI changes the landscape of creation, focusing on the alienation of the creator from their creation and the challenges in maintaining meaning. The author presents two significant problems:

 

  • Loss of Connection with Creation:
    • AI-assisted creation diminishes the creator’s role in the decision-making process.
    • The resulting creation lacks the personal, intentional choices that contribute to meaningful expression.
    • AI is considered a tool that, when misused, turns creation into automated button-pushing, stripping away the purpose of human expression.
  • Difficulty in Assessing Authenticity:
    • It becomes challenging to distinguish between human and AI contributions within a creation.
    • AI-generated content lacks transparency regarding the intent behind specific choices or expressions.
    • The author asserts that AI-generated content often falls short in providing the depth and authenticity required for meaningful communication.
Why The New York Times might win its copyright lawsuit against OpenAI
/ A.I., ves

https://arstechnica.com/tech-policy/2024/02/why-the-new-york-times-might-win-its-copyright-lawsuit-against-openai/

 

Daniel Jeffries wrote:

“Trying to get everyone to license training data is not going to work because that’s not what copyright is about,” Jeffries wrote. “Copyright law is about preventing people from producing exact copies or near exact copies of content and posting it for commercial gain. Period. Anyone who tells you otherwise is lying or simply does not understand how copyright works.”

 

The AI community is full of people who understand how models work and what they’re capable of, and who are working to improve their systems so that the outputs aren’t full of regurgitated inputs. Google won the Google Books case because it could explain both of these persuasively to judges. But the history of technology law is littered with the remains of companies that were less successful in getting judges to see things their way.

Generative AI Glossary
/ A.I.

https://education.civitai.com/generative-ai-glossary/