Anthony V.’s Post

Now in developer preview: Astra DB Vectorize 💥 Designed for developers, Vectorize with @NVIDIA NeMo simplifies the embedding process, allowing you to focus on what matters most—building powerful, efficient GenAI applications. Sign up to try: https://ow.ly/Q64q30sB0CL

Building Advanced RAG Systems: From Basic to Agentic! What's New in RAG? Traditional RAG is evolving into Agentic RAG, combining retrieval capabilities with intelligent decision-making frameworks Key Components of Modern RAG Core ArchitectureMulti-agent frameworks for enhanced decision-making Tool-calling capabilities with Llama 3.1 NVIDIA NeMo Retriever integration Business Benefits Improved accuracy with multi-step reasoning Scalable deployment options Enhanced data security Flexible integration capabilities Implementation Features Query decomposition for complex questions Intelligent routing systems Hallucination checking Post-generation verification #AI #RAG #MachineLearning #NVIDIA #DataScience #Innovation

Watch how RAG, built on NVIDIA GPU architecture and CodeLlama 34B, transforms access to #UnrealEngine5 documentation, saving developers time and reducing the need for costly model training and fine-tuning. #RAG #nvidia #ai #artificialintelligence

You hear about RAG and NVIDIA NIM Get a quick overview of RAG using NVIDIA NIM APIs & llama index in around 6 mins with working code demo In this video, I • Got the NVDIA NIM API key • Used nv-embedqa-e5-v5 model for embeddings • Used meta llama-3.1-8b-instruct model from NVIDIA • Built a simple Q&A system on custom text file RAG's power is real - enhancing LLMs with domain-specific knowledge. Even though it took some time to figure out the framework and how to access NVIDIA models, LlamaIndex integrates seamlessly with NVIDIA. Perfect for quick prototyping and scalable AI apps. Who else is exploring RAG or building projects? Let's talk. #AI #MachineLearning #RAG #LlamaIndex #NVIDIA

Now compatible with NVIDIA's #trajdata framework 🔄 We are committed to enabling seamless integration of our traffic data into our customers' simulation environments. With our latest update, we now also offer automatic conversion to trajdata, an open-source framework for trajectory data. The video below showcases our Stuttgart dataset in the trajdata format. Are you curious to explore our data in your simulation environment? Download thousands of kilometers of processed, high-quality traffic data directly from our web app via the link below 🚗 #DataFormat #TrajectoryData #Simulation

See how RAG, built on NVIDIA GPU architecture and CodeLlama 34B, transforms access to #UnrealEngine5 documentation, saving developers time and reducing the need for costly model training and fine-tuning.

See how RAG, built on NVIDIA GPU architecture and CodeLlama 34B, transforms access to #UnrealEngine5 documentation, saving developers time and reducing the need for costly model training and fine-tuning.

See how RAG, built on NVIDIA GPU architecture and CodeLlama 34B, transforms access to #UnrealEngine5 documentation, saving developers time and reducing the need for costly model training and fine-tuning.

See how RAG, built on NVIDIA GPU architecture and CodeLlama 34B, transforms access to #UnrealEngine5 documentation, saving developers time and reducing the need for costly model training and fine-tuning.