Image created with OpenAI gpt-image-1. Image prompt: Single-panel cartoon with loose, hand‑inked lines, bean‑bodied figures, muted flat colors, minimal props, and deadpan humor: Lecture hall in Andes. Professor llama in tweed jacket explains context windows to attentive alpacas, occasionally spitting for emphasis. Large bold title text centered at top: “LLAMA” Muted colors, flat shading, black ink outlines. 16:9. Caption: “Enrollment spikes after Llama 3 announcement.”
“Wait, Nvidia dropped a 4 MILLION context length Llama 3.1 Nemotron 🤯 could literally drop entire codebases in it! https://x.com/reach_vb/status/1912743420851875986
“Llama 4 Maverick illustrates a key challenge in calculating AI training compute: How to account for when a smaller model is trained using a larger model’s outputs? We’re updating our methodology and removing Maverick from our list of models exceeding 1e25 FLOP. Here’s why… 🧵 https://x.com/EpochAIResearch/status/1913329195171688742
“ByteDance announces Vidi on Hugging Face Large Multimodal Models for Video Understanding and Editing https://x.com/_akhaliq/status/1914925322413264937
“Fully sharded systems use fixed strategies, ignoring dynamic memory changes during training. DeepCompile compiles models into graphs, using profiling-guided passes to flexibly time operations based on runtime memory. It boosts Llama 3 70B/Mixtral 8x7B training up to https://x.com/rohanpaul_ai/status/1914866314122015149
“LlamaIndex’s integration with @milvusio now supports full-text search with BM25! Full-text search allows hybrid search for RAG pipelines, combining the power of vector search and traditional keyword matching. Check out how to use the integration in this tutorial: https://x.com/llama_index/status/1914815391798534571
