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TensorRT-LLM: A Comprehensive Guide to Optimizing Large Language Model Inference for Maximum Performance

Unite.AI

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. NVIDIA's TensorRT-LLM steps in to address this challenge by providing a set of powerful tools and optimizations specifically designed for LLM inference.

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Striking Performance: Large Language Models up to 4x Faster on RTX With TensorRT-LLM for Windows

NVIDIA

Today, generative AI on PC is getting up to 4x faster via TensorRT-LLM for Windows, an open-source library that accelerates inference performance for the latest AI large language models, like Llama 2 and Code Llama. This follows the announcement of TensorRT-LLM for data centers last month.

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LLM Hallucinations 101: Why Do They Appear? Can We Avoid Them?

The MLOps Blog

TL;DR Hallucinations are an inherent feature of LLMs that becomes a bug in LLM-based applications. This “making up” event is what we call a hallucination, a term popularized by Andrej Karpathy in 2015 in the context of RNNs and extensively used nowadays for large language models (LLMs). What are LLM hallucinations?

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This AI Research Introduces Flash-Decoding: A New Artificial Intelligence Approach Based on FlashAttention to Make Long-Context LLM Inference Up to 8x Faster

Marktechpost

Large language models (LLMs) such as ChatGPT and Llama have garnered substantial attention due to their exceptional natural language processing capabilities, enabling various applications ranging from text generation to code completion. We are also on WhatsApp. Join our AI Channel on Whatsapp.

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MIT Researchers Introduce LILO: A Neuro-Symbolic Framework for Learning Interpretable Libraries for Program Synthesis

Marktechpost

It will be necessary to expand the capabilities of current code completion tools—which are presently utilized by millions of programmers—to address the issue of library learning to solve this multi-objective optimization. Al) Using a dual-system search methodology, LILO creates programs from task descriptions written in plain language.

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Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation

Flipboard

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. When a user asks a question, it searches the vector database and retrieves documents that are most similar to the user’s query.

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8 Ways Automatic Speech Recognition Can Increase Efficiency For Your Business

AssemblyAI

Using Automatic Speech Recognition (also known as speech to text AI , speech AI, or ASR), companies can efficiently transcribe speech to text at scale, completing what used to be a laborious process in a fraction of the time. It would take weeks to filter and categorize all of the information to identify common issues or patterns.