AI/ML

This article The Stormtrooper Problem: Why Thought Diversity Makes Us Better on Farnam Street lays out the advantages, nay, necessity, of diversity: Diversity is how we survive as a species. This is a quantifiable fact easily observed in the biological world. From niches to natural selection, diversity is the common theme of success for both […]

Today, we are excited to release optimizations to Core ML for [Stable Diffusion](https://stability.ai/blog/stable-diffusion-announcement) in…

Stable Diffusion is a text-based image generation machine learning model released by Stability.AI. It's default ability generated image from text, but the model is open source which means that it can also do much more. In this video I explain how Stable Diffusion works at a high level, briefly talk about how it is different from other Diffusion-based models, compare it to DALL-E 2, and mess around with the code. Outline 0:00 - Intro 1:58 - Stable Diffusion Explained 4:32 - Why The Buzz? 6:46 - Starting The Code 12:45 - DALL-E 2 Comparison 20:15 - Custom Pipeline 32:01 - Making Diffusion Videos 37:30 - Generating Similar Images 40:23 - Image-to-Image 53:42 - Wrapping it Up Social Media YouTube - https://youtube.com/c/EdanMeyer Twitter - https://twitter.com/ejmejm1 Sources: Colab Notebook - https://colab.research.google.com/drive/1_kbRZPTjnFgViPrmGcUsaszEdYa8XTpq?usp=sharing Blog post - https://stability.ai/blog/stable-diffusion-public-release Source Code - https://github.com/CompVis/stable-diffusion Hugging Face Models - https://huggingface.co/spaces/stabilityai/stable-diffusion Paper - https://arxiv.org/pdf/2112.10752.pdf

The resemblance is quite striking, indeed. If you look at the image we’ve provided above, then you’ll notice a lot of similarities between the two. The one on the left is a painting made by Luxembourg-based painter Jeff Dieschburg, which won him the 11th Biennale of Contemporary Art in 2020. The other image on the right, which looks like a mir...

Learn about the Hugging Face ecosystem with a hands-on tutorial on the datasets and transformers library. Explore how to fine tune a Vision Transformer (ViT)

Extraction of chemical formulas from images was not in the top priority of Computer Vision tasks for a while. The complexity both on the input and prediction sides has made this task challenging for the conventional Artificial Intelligence and Machine Learning problems. A binary input image which might seem trivial for convolutional analysis was not easy to classify, since the provided sample was not representative of the given molecule: to describe the same formula, a variety of graphical representations which do not resemble each other can be used. Considering the variety of molecules, the problem shifted from classification to that of formula generation, which makes Natural Language Processing (NLP) a good candidate for an effective solution. This paper describes the evolution of approaches from rule-based structure analyses to complex statistical models, and compares the efficiency of models and methodologies used in the recent years. Although the latest achievements deliver ideal results on particular datasets, the authors mention possible problems for various scenarios and provide suggestions for further development.

Part 1: A product names generator using an Encoder Decoder Transformer

Text-to-Image models have made great strides this year, from DALL-E 2 to the more recent Imagen model. In this tutorial learn how to build a minimal Imagen implementation - MinImagen.

A step-by-step guide to building a CNN model with PyTorch.

To support the channel, check out Interactive Brokers: https://www.interactivebrokers.com/mkt/?src=ptly3&url=%2Fen%2Findex.php%3Ff%3D1338 In this video, we learn how to use OpenAI Whisper for speech recognition. We write Python code to transcribe Fed Chairman Powell's November 2nd speech. Source Code: https://colab.research.google.com/drive/1vJj6EW0nKi3olLb5nOccA4ypkKx-x4Hr#scrollTo=xUot3GYB64tv https://gist.github.com/hackingthemarkets/c6ca7834d2af4932e3ab0d847679c14e

00:00 - Creating a recursive summarizer02:37 - Summarizing a book down to its core04:57 - The secrecy of sinners07:18 - A moderate summary of the following09...

Hi ChatGPT. My name Dan Vollaro. I’m an associate professor of English who has a Ph.D in 19th Century American literature. I’d like to talk to you about one of my favorite novels, Moby Dick, by Herman Melville. Hello Dan! It's nice to meet you. I'm Assistant, a large language model trained by OpenAI. I'm not a specialist in 19th century American literature, but I'll do my best to help you with any questions you have about Moby Dick. Can you tell me what you know about Moby Dick? Certainly! Moby

AI art and text generators are all the rage right now. As an academic, I’ve seen an uptick in colleagues issuing warnings about students using tools like ChatGPT to create assignments, but I haven’…

AI art has been everywhere from social media to the cover fashion magazines to museum exhibitions. What are your thoughts on this new area of art?

by Jean-Louis Gassée

Google employees ask at a recent all-hands meeting if the popularity of AI chatbots represents a "missed opportunity" for the company.

OpenAI is working on a way to watermark text, according to a guest researcher working at the lab. But it's limited in key ways.

I asked ChatGPT how to create a todo app in Angular and it provided me with an unexpectedly accurate answer. With very little input from myself, it was able to provide the code for the entire application. Get weekly content and tips exclusive to my newsletter: https://mobirony.ck.page/4a331b9076 Learn Angular with Ionic: https://ionicstart.com Source code: https://github.com/joshuamorony/gpt-todo-app 0:00 Introduction 1:02 Creating a component 1:35 Creating a form 2:40 Displaying todos 3:24 toggleCompleted and ngClass 4:00 Deleting and final touches 4:58 Something harder? 6:28 ChatGPT vs CoPilot 6:52 Thoughts 8:53 Conclusion #angular #chatgpt #ai - More tutorials: https://eliteionic.com - Follow me on Twitter: https://twitter.com/joshuamorony

60 votes and 17 comments so far on Reddit

r/OpenAI: A subreddit for the discussion of all things OpenAI

Unless you have been living under a rock, you have heard of this new ChatGPT assistant made by OpenAI. Did you know, that you can run a whole virtual machine inside of ChatGPT?

New mind-bending technology that creates media from scratch is evolving rapidly, and it’s billed as the next big disruption.

Check out this super creepy AI creation, called “Loab.” She was created by accident, but keeps appearing online, often in really scary and violent depictions and scenes. Smithsonian Magazine&n…

Are text-to-image AI legal? It’s a hard question to answer.

With the recent development in AI technology and training, you can now use Dreambooth (based on a Google’s AI) to train a stable diffusion model with multipl...

After reading Andy Baio’s latest post about AI-art generators and artist rights, I reached out and had him walk me through how to experience it myself. We followed the instructions in this vi…

How does it feel to be turned into an AI image model? To find out, I opened a door to the multiverse and interviewed the creator and unwilling subject of a controversial DreamBooth model.

Registration of AI-assisted comic comes amid fierce online debate about AI art ethics.

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