Ethan B. Holland

Over 56,600 manually organized AI links and counting

A photorealistic image of a humanoid robot coding on a laptop at a desk, surrounded by books, with complex AI models and equations on a holographic display above. The room is warmly lit, blending traditional learning with futuristic technology

AI Tech and Development News: Week Ending 03/01/2024

March 4, 2024

“Nvidia CEO Jensen Huang said he believes humans will no longer need to know how to code in the future. He also argues that kids should stop learning how to code. Don’t fully agree with this. But Jensen’s a good marketer (and this is going super viral). https://t.co/BlTWfPFLW1” / X – https://twitter.com/rowancheung/status/1762345788116459671

“Paper on how to think about how LLMs explain their answers as plausible (do they make sense) & faithful (do they accurately represent how the LLM “thought”). For some cases, like the LLM explaining how to calculate 5!, you want plausible but not faithful. https://t.co/E0fr1rXMp4 https://t.co/eRSJyE458d” / X – https://twitter.com/emollick/status/1762498945597804730

“Two needles in a haystack: Our latest study explores how LLMs perform on the same task with different lengths of context. Accuracy dips when models must not only find, but reason over two text parts. Even on just 3000 tokens! Results and analysis 👇(1/7) https://t.co/M7gkdcKZBh https://t.co/JXDrIqlw1F” / X – https://twitter.com/mosh_levy/status/1762027624434401314

“Announcing TTS Arena! 🗣️ *sound on* One place to test, rate and find the champion of current open models. A continually updated space with the greatest and the best of the current TTS landscape! ⚡ Rate once, rate twice – help us find the best out there. Starting with five… https://t.co/E1V4dEvzM5” / X – https://twitter.com/reach_vb/status/1761482861176082921

““Biggest feature: “chat with your notes.” Basically RAG built-in to Obsidian. The flagship feature uses embeddings to surface relevant notes, which is important for someone like me, with ADHD, where out-of-sight-out-of-mind can lead to problems like rework/losing progress,” from…” / X – https://twitter.com/Scobleizer/status/1761517610108395704

“Rochat AI is Novel Game style AI Character product, where on Rochat AI, you can create your own AI characters and interact with them. Next, Rochat is about to launch game mode, which means you can simply create different RPG type games for AI characters through natural language. https://t.co/96KPL3Zv8t” / X – https://twitter.com/chunyeah/status/1761762510804504886

“🎉 Today’s the day! https://t.co/sp7qzTu5mw is now live on X! 🚀 Join us for the latest in prompt versioning and collaboration. Questions? Requests? Reach out to us here or at prompteams@gmail.com. Let’s make prompt management easier together! #Prompteams #TwitterLaunch” / X – https://twitter.com/prompteams/status/1748266390837162401

“(Accepted to #CVPR2024) Are you tired of looking at weird human hands in AI-generated images? We introduce a two-stage diffusion process that leverages topological and geometric human priors to generate realistic-looking hands. #GenAI, #AI, #machinelearning, #computervision https://t.co/JZA3tL9NID” / X – https://twitter.com/nsupreeth5/status/1762290564404560347

“Interesting experiment. Diffusion can “render” algorithms. It implements maze traversal purely from pixels, even with U-Net that is far weaker than transformer. I always think of diffusion as a renderer, and transformer as the reasoning engine. It seems that the renderer itself…” / X – https://twitter.com/DrJimFan/status/1762888644933902681

GeneOH Diffusion – https://meowuu7.github.io/GeneOH-Diffusion/

“We just crossed 100,000 organizations on HF! Some of my favorites: – The MLX community for on-device AI: https://t.co/l2c3WiZS6M – The @AiEleuther org with over 150+ datasets: https://t.co/BQSE3lG0JF – The @Bloomberg org to show big financial institutions can use the hub:…” / X – https://twitter.com/ClementDelangue/status/1763575302863605876

A Turing test of whether AI chatbots are behaviorally similar to humans | PNAS – https://www.pnas.org/doi/full/10.1073/pnas.2313925121

2402.17764.pdf – https://arxiv.org/pdf/2402.17764.pdf

DIBT/10k_prompts_ranked · Datasets at Hugging Face – https://huggingface.co/datasets/DIBT/10k_prompts_ranked

[2402.14660v1] ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models – https://arxiv.org/abs/2402.14660v1

Ten AI Insights from Databricks, Anyscale, and Microsoft – Foundation Capital – https://foundationcapital.com/ten-ai-insights-from-databricks-anyscale-and-microsoft/

[2402.15838v1] ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-shot Retrieval – https://arxiv.org/abs/2402.15838v1

[2402.15627] MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs – https://arxiv.org/abs/2402.15627

[2402.16153] ChatMusician: Understanding and Generating Music Intrinsically with LLM – https://arxiv.org/abs/2402.16153

Introduction to Gorilla LLM – https://gorilla.cs.berkeley.edu/blogs/8_berkeley_function_calling_leaderboard.html

The paradox of diffusion distillation – Sander Dieleman – https://sander.ai/2024/02/28/paradox.html

[2402.18158v1] Evaluating Quantized Large Language Models – https://arxiv.org/abs/2402.18158v1

[2402.18078v1] Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image Synthesis – https://arxiv.org/abs/2402.18078v1

[2402.18115] UniVS: Unified and Universal Video Segmentation with Prompts as Queries – https://arxiv.org/abs/2402.18115

Modular: Getting started with MAX Developer Edition – https://www.modular.com/blog/getting-started-with-max-developer-edition

The paradox of diffusion distillation – Sander Dieleman – https://sander.ai/2024/02/28/paradox.html

Foundation Model Development Cheatsheet – https://fmcheatsheet.org/

[2402.17188v1] PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning – https://arxiv.org/abs/2402.17188v1

HiGPT – https://higpt-hku.github.io/

[2311.06783v1] Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models – https://arxiv.org/abs/2311.06783v1
Paper page – EMO: Emote Portrait Alive – Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions – https://huggingface.co/papers/2402.17485

Be Sure To Read “This Week In AI”

This week’s executive overview and top links are here:

AI News #22: Week Ending 03/01/2024 with Executive Summary and Top 25 Stories

The post you just read 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.

Credits/Sources

Most of these weekly links come from just a few prolific oversharing sources. Please follow them, as they work hard to find the news each week and they make it a lot easier for me to compile.