5 Advanced RAG Architectures Beyond Traditional Methods
Retrieval-augmented generation (RAG) has shaken up the world of language models by combining the best of two worlds:
The Super Weight in Large Language Models
Recent works have shown a surprising result: a small fraction of Large Language Model (LLM) parameter outliers are disproportionately important to the quality of the model. LLMs contain billions of parameters, so these small fractions, such as 0.01%, translate to hundreds of thousands of parameters. In this work, we present an even more surprising finding: …
Driving Content Delivery Efficiency Through Classifying Cache Misses
By Vipul Marlecha, Lara Deek, Thiara Ortiz The mission of Open Connect, our dedicated content delivery network (CDN), is to deliver the best quality of experience (QoE) to our members. By localizing our Open Connect Appliances (OCAs), we bring Netflix content closer to the end user. This is achieved through close partnerships with internet service providers …
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Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service
Generative AI has revolutionized customer interactions across industries by offering personalized, intuitive experiences powered by unprecedented access to information. This transformation is further enhanced by Retrieval Augmented Generation (RAG), a technique that allows large language models (LLMs) to reference external knowledge sources beyond their training data. RAG has gained popularity for its ability to improve …
A guide to converting ADK agents with MCP to the A2A framework
The evolution of AI agents has led to powerful, specialized models capable of complex tasks. The Google Agent Development Kit (ADK) – a toolkit designed to simplify the construction and management of language model-based applications – makes it easy for developers to build agents, usually equipped with tools via the Model Context Protocol (MCP) for …
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Confidence in agentic AI: Why eval infrastructure must come first
At VentureBeat’s Transform 2025, tech leaders gathered to talk about how they’re transforming their business with agents.Read More
Despite Protests, Elon Musk Secures Air Permit for xAI
xAI’s gas turbines get official approval from Memphis, Tennessee, even as civil rights groups prepare to sue over alleged Clean Air Act violations.
Centaur: AI that thinks like us—and could help explain how we think
Researchers at Helmholtz Munich have developed an artificial intelligence model that can simulate human behavior with remarkable accuracy. The language model, called Centaur, was trained on more than ten million decisions from psychological experiments—and makes decisions in ways that closely resemble those of real people. This opens new avenues for understanding human cognition and improving …
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Radial Attention: O(nlogn) Sparse Attention with Energy Decay for Long Video Generation
We just released RadialAttention, a sparse attention mechanism with O(nlogn) computational complexity for long video generation. 🔍 Key Features: ✅ Plug-and-play: works with pretrained models like #Wan, #HunyuanVideo, #Mochi ✅ Speeds up both training&inference by 2–4×, without quality loss All you need is a pre-defined static attention mask! ComfyUI integration is in progress and will …
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Mixture of Experts Architecture in Transformer Models
This post covers three main areas: • Why Mixture of Experts is Needed in Transformers • How Mixture of Experts Works • Implementation of MoE in Transformer Models The Mixture of Experts (MoE) concept was first introduced in 1991 by