Ethan B. Holland

Over 51,300 manually organized AI links and counting

AI Technical/Dev Links: Week Ending 01/12/2024

January 12, 2024

This week’s corresponding executive summary and top links are here:
https://ethanbholland.com/2024/01/27/ai-news-15-week-ending-01-012-2024-with-executive-summary-and-top-13-stories/

Below are the more technical and dev oriented links from the week. The links descriptions are often pulled directly from tweets or articles, so it’s not always my voice. Pause when you see something that interests you. Reach out to me any time. I enjoy sharing and discussing these items.

Major New Update: You can now draw on Trace and turn your drawings into real apps in minutes.

Major New Update: You can now draw on Trace and turn your drawings into real apps in minutes. 🎨 pic.twitter.com/1ftkbeujKH
— trace (@trace_ai) January 9, 2024

Artificial intelligence may benefit from talking to itself

An inner monologue can help a machine learn to perform complex tasks more reliably

Artificial intelligence may benefit from talking to itself.

My latest for @ScienceMagazine @NewsfromScience, on work at @NeurIPSConf #NeurIPS2023, by @shengranhu and @jeffclune at @UBC_CS. Thanks also @ShunyuYao12 and @annaborghi8. https://t.co/YsaA7yZHoU
— Matthew Hutson (@SilverJacket) January 9, 2024

https://www.science.org/content/article/artificial-intelligence-may-benefit-talking-itself

How to Create Gaussian Splats with Nerfstudio

The Four Wars of the AI Stack

https://www.latent.space/p/dec-2023

I’ve created a step-by-step guide to fine-tuning an LLM on your Apple silicon Mac. I’ll walk you through the entire process, and it won’t cost you a penny because we’re going to do it all on your own hardware using Apple’s MLX framework.

A simple guide to local LLM fine-tuning on a Mac with MLX

A comprehensive RAG ecosystem survey has just been published, and it’s a must-read for anyone interested in the future of the industry.

It covers all advanced techniques in retrieval and evaluation

A comprehensive RAG ecosystem survey has just been published, and it's a must-read for anyone interested in the future of the industry.
It covers all advanced techniques in retrieval and evaluationhttps://t.co/sS5lIeAvu8 #llm #rag #retrieval #ai pic.twitter.com/VrvNnPS2pv
— Simonas Jakubonis (@sijak5) January 8, 2024

Ever wonder why well-trained Vision Transformers still exhibit noises? We introduce Denoising Vision Transformers (DVT)

Ever wonder why well-trained Vision Transformers still exhibit noises? We introduce Denoising Vision Transformers (DVT), led by amazing @JiaweiYang118 @katielulula @jiefengli_jeff, and with long-term collaborators @YonglongT @KilianQW.

Website: https://t.co/ub4Nlc9YWq
Code:… pic.twitter.com/TKJoKG2kCU
— Yue Wang (@yuewang314) January 8, 2024

https://jiawei-yang.github.io/DenoisingViT/

We just increased the GPT-4 Turbo with Vision rate limits for our highest usage customers to 3,000 requests per minute and 50,000 requests per day—that’s 5x the previous limit.

https://platform.openai.com/docs/guides/rate-limits/usage-tiers?context=tier-five

Phixtral on an M2 Ultra is impressive. Runs pretty quick in MLX.

Phixtral on an M2 Ultra is impressive. Runs pretty quick in MLX.

Thanks to @mrclbschff for adding to MLX and @maximelabonne for making the model!

Code: https://t.co/qy8XUmQKdN
Demo (real time): pic.twitter.com/0DwEZ6RqCm
— Awni Hannun (@awnihannun) January 13, 2024

Transformers From Scratch

https://blog.matdmiller.com/posts/2023-06-10_transformers/notebook.html

V*: Guided Visual Search as a Core Mechanism in Multimodal LLMs

https://vstar-seal.github.io/

Your private AI can have eyes. Ollama with the LLaVA model

https://benyoung.blog/your-private-ai-can-have-eyes-ollama-with-the-llava-model/

Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior

https://benhenryl.github.io/SharpNeRF/?utm_source=tldrai

Be Sure To Read “This Week in AI“

This is an extension of my weekly newsletter, This Week In AI, an executive summary of the top things to know in AI. Each week, I create an accessible overview for laypeople to feel confident they are conversant with the week’s AI developments. I include a curated list of must-click links of the week, to offer everyone a hands-on opportunity to explore the most intriguing updates in artificial intelligence across various categories, including robotics, imagery, video, AR/VR, science, ethics, and more. Beyond the overview, I post these topic-based deeper dives (below). If you haven’t read this week’s overview, I recommend starting there.