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Understanding Global Health Challenges Supporting the health of diverse populations requires a deep understanding of how human behavior interacts with local environments. We need to identify vulnerable groups and allocate resources effectively. Traditional methods are often…

MotionLM is a new approach for predicting the behavior of road agents in autonomous vehicles. It treats the prediction task as a language modeling task, similar to how language models capture complex language distributions. MotionLM outperforms…

Researchers from UC Berkeley and UCSF have introduced a new approach called LLM-grounded Video Diffusion (LVD) to address the challenges in generating videos from text prompts. LVD utilizes Large Language Models (LLMs) to create dynamic scene…

Large Language Models (LLMs) are used for natural language processing applications, but they struggle with extended sequence creation beyond their pretraining. Researchers propose StreamingLLM, an architecture that allows LLMs to work on indefinite text without fine-tuning.…

Discover the advantages and key factors to consider when selecting a vector database for your application.

Lyzr Automata: A Low-Code Multi-Agent Framework for Advanced Process Automation Introducing Lyzr Automata, an innovative framework designed to streamline complex workflows and enhance automation processes. It incorporates a Human-in-Loop mechanism and adaptive learning through a rule-based…

Introduction to Multi-modal Large Language Models (MLLMs) Multi-modal Large Language Models (MLLMs) have advanced significantly, evolving into multi-modal agents that assist humans in various tasks. However, when it comes to PC environments, these agents face unique…

The text provides a tutorial on transforming a llama into a giraffe. For further information, please refer to the article on Towards Data Science.

Unifying Language Models and Databases with Table-Augmented Generation (TAG) Enhancing User Interaction with Large Datasets Artificial intelligence (AI) and database management systems are converging to improve user interactions with large datasets. Recent advancements aim to enable…

The CHiME-8 MMCSG task addresses the challenge of transcribing smart glasses-recorded natural conversations in real-time, focusing on activities like speaker diarization and speech recognition. By leveraging multi-modal data and advanced signal processing techniques, the MMCSG dataset…

‘Large language models’ (LLMs) have gained prominence in the field of artificial intelligence and generative AI. This article discusses the collection methods and use cases of LLM data, projecting its significance in 2023. AIMultiple provides tools…

Researchers have encountered significant challenges in developing drugs for Idiopathic Pulmonary Fibrosis and renal fibrosis due to their complex pathogenesis and lack of effective treatments. However, utilizing AI, they identified TNIK as a promising anti-fibrotic target…

Amazon researchers have developed KD-Boost, a knowledge distillation technique, to address the challenges of real-time semantic matching in web search and e-commerce product search. KD-Boost uses ground truth and soft labels from a teacher model to…

The Value of Large Language Models (LLMs) in Education A Large Language Model (LLM) is an advanced type of AI designed to understand and generate human-like text, revolutionizing education through personalized tutoring, instant answers, and democratizing…

PB-LLM is an innovative approach for extreme low-bit quantization in Large Language Models (LLMs) while preserving language reasoning capabilities. It strategically filters salient weights during binarization, introduces post-training quantization (PTQ) and quantization-aware training (QAT) methods, and…

Cardiac Magnetic Resonance Imaging (CMRI) segmentation is critical for diagnosing cardiovascular diseases, with recent advancements focusing on long-axis (LAX) views to visualize atrial structures and diagnose diseases affecting the heart’s apical region. The ENet architecture combined…

Transforming Search and Information Retrieval with AI Searching for information has gone beyond just finding data; it now plays a vital role in improving business efficiency and productivity. Companies depend on effective search systems for customer…

This blog post serves as the conclusion to a series on training BERT from scratch. It discusses the significance of BERT in Natural Language Processing, reviews the previous parts of the series, and outlines the process…