AI/ML

You can install PyTorch for GPU support with a Mac M1/M2 using CONDA. It is very important that you install an ARM version of Python. In this video I walk you through all the steps necessary to prepare an Apple Metal Mac for my deep learning course in PyTorch. 0:27 Overview 1:00 Install Miniconda 1:49 Uninstall Anaconda (optional) 3:33 Install Miniconda 5:03 Install Jupyter 5:24 Install PyTorch 7:07 Create Jupyter Kernel Code for This Video: https://github.com/jeffheaton/t81_558_deep_learning/blob/pytorch/install/pytorch-install-aug-2022.ipynb ~~~~~~~~~~~~~~~ COURSE MATERIAL ~~~~~~~~~~~~~~~ 📖 Textbook - coming soon 😸🐙 GitHub - https://github.com/jeffheaton/t81_558_deep_learning/tree/pytorch ▶️ Play List - https://www.youtube.com/playlist?list=PLjy4p-07OYzuy_lHcRW8lPTLPTTOmUpmi 🏫 WUSTL Course Site - https://sites.wustl.edu/jeffheaton/t81-558/ ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.heatonresearch.com/ 🐦 Twitter - https://twitter.com/jeffheaton 😸🐙 GitHub - https://github.com/jeffheaton 📸 Instagram - https://www.instagram.com/jeffheatondotcom/ 🦾 Discord: https://discord.gg/3bjthYv ▶️ Subscribe: https://www.youtube.com/c/heatonresearch?sub_confirmation=1 ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/jeffheaton 🙏 Other Ways to Support (some free) - https://www.heatonresearch.com/support.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #Python #Tensorflow #Keras

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks - GitHub - jeffheaton/t81_558_deep_learning: Washington University (in St. Louis) Course T81-558: Applicati...

How I run Anaconda and Miniforge side-by-side on my Mac M1 with TensorFlow and Keras.Install Locations* https://developer.apple.com/metal/tensorflow-plugin/*...

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks - t81_558_deep_learning/tensorflow-install-mac-metal-jan-2023.ipynb at master · jeffheaton/t81_558_deep_lea...

Many NLP applications require manual data annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd-workers on platforms such as MTurk as well as trained annotators, such as research assistants. Using a sample of 2,382 tweets, we demonstrate that ChatGPT outperforms crowd-workers for several annotation tasks, including relevance, stance, topics, and frames detection. Specifically, the zero-shot accuracy of ChatGPT exceeds that of crowd-workers for four out of five tasks, while ChatGPT's intercoder agreement exceeds that of both crowd-workers and trained annotators for all tasks. Moreover, the per-annotation cost of ChatGPT is less than $0.003 -- about twenty times cheaper than MTurk. These results show the potential of large language models to drastically increase the efficiency of text classification.

Contribute to thomas0809/MolScribe development by creating an account on GitHub.

People often ask me how to use AI. Here's an overview with lots of links.

What challenges can GPT overcome when combined with human laziness?

The risks inherent in the technology, plus the speed of its take-up, demonstrate why it’s so vital that we keep track of it, writes the Guardian’s head of editorial innovation, Chris Moran

Your gateway to dynamic, interactive, and intelligent conversations with any PDF document

This is a conversation I had with Chat GPT trying to simulate an interaction with an non existing anonymous FTP server that would be made available for Disney fans

We’ve released our new course with over 30 hours of video content.

It’s the inaugural week of the second annual edition of Automation April, and to celebrate the occasion, I’ve been working on something special: today, I’m introducing S-GPT, an advanced conversational shortcut for ChatGPT that bridges OpenAI’s assistant to native system features of iOS, iPadOS, macOS, and watchOS. S-GPT (which stands for Shortcuts-GPT) is free to

Why generative AI tools can be so difficult to use and how we might improve them

Bring ideas to life in seconds using video, interactivity, and live data.

We are an interdisciplinary and globally distributed AI research institute.

An LLM playground you can run on your laptop. Contribute to nat/openplayground development by creating an account on GitHub.

Contribute to yoheinakajima/babyagi development by creating an account on GitHub.

PAL generates a Python program to solve a task from its natural language description.

ChatGPT has written passable law school essays, and GPT-4 has aced the bar exam. But what if, instead of asking AI to take our tests, we asked it about the future of legal education and licensing? …

For over two decades, many people, including me , have been writing programs attempting to replicate "medicinal chemistry intuition".   This...

[Natalie](https://www.instagram.com/natbat.art/) has been experimenting with using a microwave as a kiln for pottery, specifically for [Raku](https://en.wikipedia.org/wiki/Raku_ware). She wanted to u

I wanted to stream the results from the ChatGPT API as they were generated, rather than waiting for the entire thing to complete before displaying anything. Here's how to do that with the [openai Pyt

Stable Diffusion with Core ML on Apple Silicon. Contribute to apple/ml-stable-diffusion development by creating an account on GitHub.

An experimental open-source attempt to make GPT-4 fully autonomous. - GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.

This bot is trained on over 200k comments and posts from BuyItForLife subreddits to embody the collective knowledge of the Reddit BuyItForLife community.

Stanford researchers asked GPT-4 questions about real-life medical situations. The AI didn't fare as well as it did on the medical boards.

So as an exercise, let’s grant his premise for a moment. Let’s treat him as an expert witness. What would it mean if he was right? What can we learn about the shape of AI’s path based on the analogies of previous epochs?

LLM Introduction: Learn Language Models. GitHub Gist: instantly share code, notes, and snippets.