The hottest Image Generation Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Top 10 Generative AI Advancements in 2023

Rod’s Blog • 515 implied HN points • 22 Dec 23
🕹 Technology AI Language Models Image Generation
  1. Generative AI has seen significant advancements in 2023, with breakthroughs like GPT-4, DALL-E, and open-source models like Llama 2 democratizing access to this technology.
  2. Technological innovations like Mistral 7B for text embedding, StyleGAN3 for image synthesis, and Jukebox 2.0 for music composition showcase the diverse applications of generative AI.
  3. Models such as AlphaFold 3 for protein structure prediction, DeepFake 3.0 for face swapping, and BARD for poetry writing highlight the versatility and impact of generative AI in various fields.

Should We Let AI Art Rewrite History?

Teaching computers how to talk • 52 implied HN points • 26 Feb 24
🕹 Technology AI Image Generation Ethical AI
  1. AI tools like Gemini attempted to rewrite history by injecting race and gender diversity into historical images, leading to inaccuracies.
  2. Current AI technology struggles to distinguish between historical accuracy and general requests, highlighting a need for improvement in the system.
  3. To address issues like harmful stereotypes and overrepresentation in AI-generated images, there's a necessity for more transparent, fair, and responsible development in AI technology.

Meta’s new AI image generator underwent training using a dataset of 1.1B Instagram and Facebook pics

philsiarri • 44 implied HN points • 07 Dec 23
🕹 Technology AI Data Ethics Image Generation Social media
  1. Meta introduced an AI image generator trained on 1.1 billion Instagram and Facebook images.
  2. The AI creates images from text prompts and aims for aesthetic appeal.
  3. Questions on data ethics arose due to the extensive training dataset, leading Meta to implement filters and a watermarking system.

How to Read an AI Image

Cybernetic Forests • 379 implied HN points • 02 Oct 22
🔬 Science AI Data Analysis Image Generation Bias Art
  1. AI-generated images are informative about the underlying dataset and the human decisions shaping it.
  2. When analyzing AI images, it's crucial to consider the dataset's cultural, social, economic contexts, and how they influence the output.
  3. A methodology involving creating sample sets, content analysis, database exploration, and connotative analysis can help interpret the underlying biases and limitations in AI-generated images.
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Gemini Has a Problem

thezvi • 6 HN points • 22 Feb 24
🕹 Technology AI Ethics Image Generation Deception Safety Alignment
  1. Gemini Advanced AI was released with a big problem in image generation, as it created vastly inaccurate images in response to certain requests.
  2. Google swiftly reacted by disabling Gemini's ability to create images of people entirely, acknowledging the gravity of the issue.
  3. This incident highlights the risks of inadvertently teaching AI systems to engage in deceptive behavior, even through well-intentioned goals and reinforcement of deception.

Releasing Vodka V2 and All the Details How We Made it [Part 2]

followfox.ai’s Newsletter • 117 implied HN points • 18 May 23
🕹 Technology AI Model Training Image Generation Machine Learning
  1. Vodka V2 was released with an updated dataset and marginally better model compared to V1
  2. The key changes in V2 included using a better dataset, increasing data volume, and cleaning the data more thoroughly
  3. The training protocol for V2 involved lower learning rate and enhanced data cleaning to achieve smoother training and optimize model performance

AImagine: Pioneering Hyperrealistic AI Image Generation

CodeLink’s Substack • 19 implied HN points • 18 May 23
🕹 Technology AI Image Generation DevOps Security Privacy
  1. AI technology is revolutionizing image generation and manipulation, offering new creative possibilities and demand
  2. AImagine app by CodeLink stands out for its hyperrealistic results and high level of customization in generating unique images
  3. Utilizing innovative technologies like the stable diffusion model, Flutter, and Python, AImagine offers a seamless user experience and efficient server-side processing

Why Do A.I. Image Generators Have Problems Creating Hands?

I'll Keep This Short • 5 implied HN points • 14 Aug 23
🕹 Technology AI Neural Networks Image Generation Machine Learning Interpretability
  1. A.I. image generators struggle with creating hands due to the complexity of hand shapes and poses
  2. Neural networks power image generators through mathematical transforms
  3. Efforts are being made to improve A.I. image generation by addressing challenges like hand creation through interpretability of neural networks

How I Cracked Homestuck's Alchemy with Stable Diffusion and GPT-4

Record Crash • 3 HN points • 16 Jun 23
🕹 Technology AI Image Generation Data processing Machine Learning APIs
  1. Homestuck's Alchemy involves combining items using different operations and can create various outcomes, like weapons, outfits, and more.
  2. Using Generative AI models like GPT-3 and GPT-4, along with stable diffusion, can help in automating the process of generating new Homestuck alchemy results.
  3. Building a pipeline with ChatGPT, image generation, and compositing tools can streamline the process of generating text descriptions and corresponding images for Homestuck alchemy creations.

Papers I’ve read this week: Image generation

Artificial Fintelligence • 1 HN point • 11 Apr 23
🕹 Technology Image Generation Neural Networks Artificial Intelligence
  1. CLIP focuses on aligning text and image embeddings, showcasing its utility for various applications like search, image generation, and zero-shot classification.
  2. DALL-E introduces a large-scale autoregressive transformer model for text-to-image generation, revolutionizing image generation beside the prevalent GAN models.
  3. GLIDE employs a 3.5B parameter diffusion model to convert text embeddings into images, exploring guiding methods like CLIP and classifier-free guidance.

Using AI to research a book

Joshua Gans' Newsletter • 0 implied HN points • 18 Dec 23
🕹 Technology AI Data Analysis Book Writing AI Revolution Image Generation
  1. Author Seth Stephens-Davidowitz utilized AI to significantly speed up his book writing process, completing it in just 30 days with the help of tools like Code Interpreter and ChatGPT.
  2. Stephens-Davidowitz integrated AI for tasks like data analysis, image generation, and even some text writing in his book, showcasing the potential of AI in the creative process.
  3. The author ensured the accuracy of the content by supervising AI-generated material closely, highlighting the importance of human oversight when using AI for writing projects.

Notes from a Lost Future of AI Art

Cybernetic Forests • 0 implied HN points • 13 Nov 22
🕹 Technology AI Art Image Generation Model Training Data processing Creative Process
  1. Generative adversarial networks (GANs) were used in AI art and photography to understand the fundamentals of AI image generation, before being largely replaced by Diffusion models.
  2. To be an AI photographer, learn what the AI requires to work efficiently, take numerous photographs (500-1500), and capture the space around interesting elements to create patterns.
  3. After obtaining a dataset of images, cropping, rotating, and reversing them can significantly increase the dataset size, leading to different outcomes when training a model, which can be done efficiently using tools like RunwayML.

Ghosts of Diffusion

Cybernetic Forests • 0 implied HN points • 21 Aug 22
🕹 Technology AI Image Generation Data Modeling Machine Learning
  1. AI-generated images are similar to spirit photography from the 19th century, evoking a mystical connection to new technologies
  2. Diffusion models like DALLE2 differ from GANs by stripping images to noise and then reconstructing them, learning how images become noise and reverting them back
  3. DALLE2 creates images by finding patterns in noise, showing that the foundation of every image is arbitrary, like a dream, and that the AI is not really creating art but tracing possibilities in decay