TuringPost

16 new types of RAG: ▪️ HtmlRAG ▪️ FastRAG ▪️ Auto-RAG ▪️ CORAG ▪️ MemoRAG ▪️ RAG-Thief ▪️ AssistRAG ▪️ LaB-RAG ▪️ Video-RAG ▪️ RAF ▪️ RuAG ▪️ MMed-RAG ▪️ Path-RAG ▪️ Multi-Reranker ▪️ G-RAG ▪️ RAGDiffusion Save the list and check this out for more info: https://lnkd.in/edYZg5QP

What is profiling in agentic workflows and why is it important? It's the mechanism that lets intelligent agents create detailed "portraits" of the environments, users, and tasks they engage with. It connects humans and machines and connects what an agent knows and what it remembers, leading to better decision-making, interactions, and task execution. In our new article, we discuss the concept of an “agent profile” and dive into special research papers about it: https://lnkd.in/eDqud335 #AIagents #agents #assistants #AI #ML #AIassiatants

Another treasure trove from NVIDIA. Their NVILA Vision-Language model demonstrates the efficiency of its training, fine-tuning and inference techniques together with special "scale-then-compress" strategy.👇

Great news from Alibaba Qwen! They released Qwen2-VL on Hugging Face, which provides: - Top understanding of images and 20min+ videos - Automatic operation of devices like mobiles and robots through integration - Multilingual understanding Check this out to easily access, use and experiment with Qwen2-VL-> 2B: https://lnkd.in/eMcM59yG 7B: https://lnkd.in/etGfZMrp 72B: https://lnkd.in/eCu7AMkc First QwQ, then this release. What will be next? 👀

A reminder of what Unsupervised Learning is 👇 It's time to refresh your knowledge of basic machine learning techniques—or maybe learn something new, right? Our flashcards are always here to help you digest key ML concepts. Find more flashcards on methodologies behind training ML models here: https://lnkd.in/eb92qSXm

Mixture-of-Experts is ubiquitous, right? Korean researchers from Korea University, Korea Advanced Institute of Science and Technology and AIGEN Sciences Inc. created a new MoE approach, called MONET (Mixture of Monosemantic Experts for Transformers) to address the difficulty of polysemanticity. What is it and how it work? Read here:

Google DeepMind, Google Cloud AI Research and University of North Carolina at Chapel Hill's innovational RevThink framework upgrades LLMs reasoning up to 13.53%! Genius idea of adding reverse thinking in models leads to great results. Explore:

Hybrid search. What is it and how does it work? It combines strength of semantic and full-text search: - Semantic search understands context and intent - Full-text search provides precise results through keyword matching In our guest post, Jiang Chen discusses hybrid search challenges in detail and explains how Zilliz's Milvus vector database enables hybrid search by integrating full-text search into the vector database on single platform. Explore more -> https://lnkd.in/eQ6GeMSZ

Speechmatics, MATS, UCL, Stanford University, University of Oxford, Tangentic, Anthropic offer one of the easiest Best-of-N Jailbreaking method ever. Another great news: this approach works with every modality 👇