The post Enhancing Sparse-view 3D Reconstruction with LM-Gaussian: Leveraging Large Model Priors for High-Quality Scene Synthesis from Limited Images appeared first on AI Quantum Intelligence ..read more

[ad_1] An overview of the most prominent imitation learning methods with testing on a grid environment Photo by Possessed Photography on Unsplash Reinforcement learning is one branch of machine learning concerned with learning by guidance of scalar signals (rewards); in contrast to supervised learning, which needs full labels of the target variable. An intuitive example The post Hands-On Imitation Learning: From Behavior Cloning to Multi-Modal Imitation Learning | by Yasin Yousif | Sep, 2024 appeared first on AI Quantum Intelligence ..read more

[ad_1] Research Published 12 September 2024 Authors Robotics team Two new AI systems, ALOHA Unleashed and DemoStart, help robots learn to perform complex tasks that require dexterous movement People perform many tasks on a daily basis, like tying shoelaces or tightening a screw. But for robots, learning these highly-dexterous tasks is incredibly difficult to get The post Our latest advances in robot dexterity appeared first on AI Quantum Intelligence ..read more

[ad_1] Matching multiple vendor bills to a single purchase order is a common task in many AP processes, so it’s best to know how to handle this situation in NetSuite. The good news is that Oracle has a bunch of options to help you streamline this process – you can use the NetSuite UI, the The post Match Purchase Orders to multiple Vendor Bills in NetSuite appeared first on AI Quantum Intelligence ..read more

[ad_1] Whether you’re getting started with your custom NetSuite deployment, or just using NetSuite to run your AP process, one of the most common tasks you’ll do is creating vendor bills. Manually creating vendor bills can be a pain – the NetSuite UI is not very straightforward, and there are hidden complexities (and some really The post How To Create Vendor Bills on NetSuite using the API appeared first on AI Quantum Intelligence ..read more

[ad_1] Finding high-value patterns in transactions In this post, I will give an alternative to popular techniques in market basket analysis that can help practitioners find high-value patterns rather than just the most frequent ones. We will gain some intuition into different pattern mining problems and look at a real-world example. The full code can The post Market Basket Analysis Using High Utility Itemset Mining | by Laurin Brechter | Sep, 2024 appeared first on AI Quantum Intelligence ..read more

[ad_1] Large Language Models (LLMs) have revolutionized software engineering, demonstrating remarkable capabilities in various coding tasks. While recent efforts have produced autonomous software agents based on LLMs for end-to-end development tasks, these systems are typically designed for specific Software Engineering (SE) tasks. Researchers from FPT Software AI Center, Viet Nam, introduce HyperAgent, a novel generalist The post FPT Software AI Center Introduces HyperAgent: A Groundbreaking Generalist Agent System to Resolve Various Software Engineering Tasks at Scale, Achieving SOTA Perform ..read more

[ad_1] Understanding multi-page documents and news videos is a common task in human daily life. To tackle such scenarios, Multimodal Large Language Models (MLLMs) should be equipped with the ability to understand multiple images with rich visually-situated text information. However, comprehending document images is more challenging than natural images, as it requires a more fine-grained The post Optimizing Document Understanding with DocOwl2: A Novel High-Resolution Compression Architecture appeared first on AI Quantum Intelligence ..read more

[ad_1] Retrieval-augmented generation (RAG), a technique that enhances the efficiency of large language models (LLMs) in handling extensive amounts of text, is critical in natural language processing, particularly in applications such as question-answering, where maintaining the context of information is crucial for generating accurate responses. As language models evolve, researchers strive to push the boundaries The post NVIDIA Researchers Introduce Order-Preserving Retrieval-Augmented Generation (OP-RAG) for Enhanced Long-Context Question Answering with Large Language Models (LLMs) appeared ..read more

Recent advancements in diffusion models have significantly improved tasks like image, video, and 3D generation, with pre-trained models like Stable Diffusion being pivotal. However, adapting these models to new tasks efficiently remains a challenge. Existing fine-tuning approaches—Additive, Reparameterized, and Selective-based—have limitations, such as added latency, overfitting, or complex parameter selection. A proposed solution involves leveraging The post SaRA: A Memory-Efficient Fine-Tuning Method for Enhancing Pre-Trained Diffusion Models appeared first on AI Quantum Intelligence ..read more