A gorgeous baroque library. A book lays on a sofa next to a roaring fireplace. The book is very thick and has the title “Long Context Window” written in ornate gold letters.
“Agentic RAG for Time Series Analysis Proposes an agentic RAG framework for time series analysis. Uses a multi-agent architecture where an agent orchestrates specialized sub-agents to complete time-series tasks. The sub-agents leverage tuned small language models and can
“Johnson Lambert, a leading audit firm, boosted audit efficiency by 50% using Cohere Command on Amazon Bedrock, supported by Provectus. By automating routine tasks, their team focuses more on high-value analysis. Another great example of how AI is becoming essential in industries
“Nice GraphRAG Survey paper – explores GraphRAG techniques, bridging graph-structured data and language models. Original Problem 🔍: Traditional Retrieval-Augmented Generation (RAG) systems struggle to capture complex relational knowledge and often provide redundant or
“Superposition prompting accelerates and enhances RAG without fine-tuning, addressing long-context LLM challenges. 93× reduction in compute time on NaturalQuestions-Open with MPT-7B 🤯 Key Insights from this Paper 💡: • Parallel processing of input documents can reduce compute
“Long Context vs. RAG Paper Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach This research paper, conducted by Google DeepMind, provides guidance on whether it’s better to use Long Context natively or leverage RAG, specifically
“Introducing the Together Rerank API: A new serverless endpoint for enterprise search and RAG systems. We’re excited to be the exclusive launch partner for @salesforce @SFResearch LlamaRank – a new reranker model that outperforms Cohere Rerank in document and code ranking tasks.
“Great news for @Cohere developers: Refreshed v of Command R and R+ are here, with performance boosts in reasoning, coding, tool use and multilingual RAG. Both models come with new safety modes and have lower latency. R has now 3x reduced price for input and 2x for output tokens,” / X
Updates to the Command R Series
“RAGLAB, great for standardizing RAG research, modular design and fair comparisons. Original Problem 🔍: RAG research faces challenges due to lack of fair comparisons between algorithms and limitations of existing open-source tools, hindering development of novel techniques. https://twitter.com/rohanpaul_ai/status/1827843916034404430
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