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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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Beyond ChatGPT; AI Agent: A New World of Workers

Unite.AI

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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Enhanced Section-Based Annotation in NLP Lab 5.2

John Snow Labs

The NLP Lab, a No-Code prominent tool in this field, has been at the forefront of such evolution, constantly introducing cutting-edge features to simplify and improve document analysis tasks. Automatic Section Identification The NLP Lab has made section identification a breeze.

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AI code-generation software: What it is and how it works

IBM Journey to AI blog

Auto-generated code suggestions can increase developers’ productivity and optimize their workflow by providing straightforward answers, handling routine coding tasks, reducing the need to context switch and conserving mental energy. It can also modernize legacy code and translate code from one programming language to another.

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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Beyond Metrics: A Hybrid Approach to LLM Performance Evaluation

Topbots

Unlike traditional machine learning where outcomes are often binary, LLM outputs dwell in a spectrum of correctness. Therefore, a holistic approach to evaluating LLMs must utilize a variety of approaches, such as using LLMs to evaluate LLMs (i.e., auto-evaluation) and using human-LLM hybrid approaches.

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Say Goodbye to Costly Auto-GPT and LangChain Runs: Meet ReWOO – The Game-Changing Modular Paradigm that Cuts Token Consumption by Detaching Reasoning from External Observations

Marktechpost

Augmented LLMs are the ones that are added with external tools and skills in order to increase their performance so that they perform beyond their inherent capabilities. Applications like Auto-GPT for autonomous task execution have been made possible by Augmented Language Models (ALMs) only.