AI/ML

...but the other 10% are worth 1000x

These are key elements of diagnostic decision-making, elements that ought not to be casually discarded.

Voicemod is launching initially as a beta for macOS

Google has to make some big decisions about fair use, YouTube, and building AI tools of its own.

RedPajama is “a project to create leading open-source models, starts by reproducing LLaMA training dataset of over 1.2 trillion tokens”. It’s a collaboration between Together, Ontocord.ai, ETH DS3Lab, Stanford CRFM, …

A curated collection of interesting applications, repos, and tutorials using large language models (LLM) like GPT-3 - mallahyari/llm-hub: A curated collection of interesting applications, repos, an...

Over the last three weeks or so I’ve been following the crazy rate of development around locally run large language models (LLMs), starting with llama.cpp, then alpaca and most recently (?!) …

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

RedPajama is a project to create a set of leading, fully open-source models. Today, we are excited to announce the completion of the first step of this project: the reproduction of the LLaMA training dataset of over 1.2 trillion tokens.

An artist is refusing his prize after his AI-generated image controversially won first place at one of the most prestigious photo contests.

In this post, we walk through my entire workflow/process for bringing Stable Diffusion to life as a high-quality framed art print. We’ll touch on making art with Dreambooth, Stable Diffusion, Outpainting, Inpainting, Upscaling, preparing for print with Photoshop, and finally printing on fine-art paper with an Epson XP-15000 printer.

Neural Radiance Field training can be accelerated through the use of grid-based representations in NeRF's learned mapping from spatial coordinates to colors and volumetric density. However, these grid-based approaches lack an explicit understanding of scale and therefore often introduce aliasing, usually in the form of jaggies or missing scene content. Anti-aliasing has previously been addressed by mip-NeRF 360, which reasons about sub-volumes along a cone rather than points along a ray, but this approach is not natively compatible with current grid-based techniques. We show how ideas from rendering and signal processing can be used to construct a technique that combines mip-NeRF 360 and grid-based models such as Instant NGP to yield error rates that are 8%-76% lower than either prior technique, and that trains 22x faster than mip-NeRF 360.

Activity around building sophisticated applications on top of LLMs (Large Language Models) such as GPT-3/4/ChatGPT/etc is growing like wildfire right now. Many of these applications are potentially vulnerable to prompt …

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

A comprehensive guide into using NLP for Machine Learning

In this LangChain Crash Course you will learn how to build applications powered by large language models.

Learn how to use Microsoft JARVIS aka HuggingGPT for free right now. You can achieve multiple tasks with a single query using JARVIS.

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf - microsoft/JARVIS: JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/...

An exploration into customizing LLMs for personal use

Prepare your M1, M1 Pro, M1 Max, M1 Ultra or M2 Mac for data science and machine learning with accelerated PyTorch for Mac.

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 -...

archived 31 Mar 2023 11:16:52 UTC

Advanced playground tools for GPT-3

Supabase hired me to build ClippyGPT - their next generation doc search. We can ask our old friend Clippy anything you want about Supabase, and it will answer it using natural language. Powered by OpenAI + prompt engineering. In this video I will be showing you exactly how I did this, and how you can do the same in your projects. We'll be covering: - Prompt engineering and best practices - Working with a custom knowledge base via context injection + OpenAI embeddings - How to store embeddings in Postgres using pgvector Supabase blog post: https://supabase.com/blog/chatgpt-supabase-docs pgvector extension: https://github.com/pgvector/pgvector Generate embeddings implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/apps/docs/scripts/generate-embeddings.ts Clippy edge function implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/supabase/functions/clippy-search/index.ts Clippy frontend implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/packages/ui/src/components/Command/AiCommand.tsx Prompt engineering: https://prmpts.ai/blog/what-is-prompt-engineering 00:00 Why? 01:40 Let's get started 03:15 Custom knowledge base 04:49 Context injection 06:13 Pre-process MDX files 13:40 Embeddings 15:40 Storing in Postgres + pgvector 22:21 API endpoint (edge function) 23:44 Calculating similarity in pgvector 27:55 Prompt engineering 33:15 Prompt best practices 38:37 Demo time! 41:32 Thanks for watching!

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In the journal Nature today, my colleagues and I published an article on the future directions of generative A.I. (aka Large Language or Foundation models) for the practice of medicine. These new AI models have generated a multitude of new and exciting opportunities in healthcare that we didn’t have before, along with many challenges and liabilities. I’ll briefly explain how we got here and what’s in store.

The historians of tomorrow are using computer science to analyze the past.

archived 10 Apr 2023 23:28:28 UTC