Large Language Models (LLMs) have demonstrated remarkable abilities in generating human-like text, answering questions, and coding. However, they face hurdles requiring high reliability, safety, and ethical adherence. Reinforcement Learning from Human Feedback (RLHF), or Preference-based Reinforcement Learning (PbRL), emerges as a promising solution. This framework has shown significant success in fine-tuning LLMs to align with…
In the quickly changing field of Natural Language Processing (NLP), the possibilities of human-computer interaction are being reshaped by the introduction of advanced conversational Question-Answering (QA) models. Recently, Nvidia has published a competitive Llama3-70b QA/RAG fine-tune. The Llama3-ChatQA-1.5 model is a noteworthy accomplishment that marks a major advancement in Retrieval-Augmented Generation (RAG) and conversational quality…
Convolutional Neural Networks (CNNs) have become the benchmark for computer vision tasks. However, they have several limitations, such as not effectively capturing spatial hierarchies and requiring large amounts of data. Capsule Networks (CapsNets), first introduced by Hinton et al. in 2017, provide a novel neural network architecture that aims to overcome these limitations by introducing…
Researchers in computer vision and robotics consistently strive to improve autonomous systems’ perception capabilities. These systems are expected to comprehend their environment accurately in real-time. Developing new methods and algorithms allows for innovations that benefit various industries, including transportation, manufacturing, and healthcare. A significant challenge in this field is enhancing the precision and efficiency of…
When imagination and technology come together, limitless opportunities arise for designers in the dynamic fashion industry. The most recent technological breakthrough is artificial intelligence (AI), which is changing how we design, manufacture, and personalize clothing. The possibilities are limitless when people are willing to go beyond the box and use AI. AI is more than…
Researchers from Purdue University have introduced GTX to address the challenge of handling large-scale graphs with high throughput read-write transactions while maintaining competitive graph analytics. Managing dynamic graphs efficiently is crucial for various applications like fraud detection, recommendation systems, and graph neural network training. Real-world graphs often exhibit temporal localities and hotspots, which existing transactional…
Designing state-of-the-art deep learning models is an incredibly complex challenge that researchers have been tackling using an approach called Neural Architecture Search (NAS). The goal of NAS is to automate the discovery of optimal neural network architectures for a given task by evaluating thousands of candidate architectures against a performance metric like accuracy on a…
Creating 3D avatar animations from text input represents a significant leap forward. Imagine simply typing a few sentences and watching a detailed, lifelike avatar spring to life on your screen, moving with realistic animations. This technology isn’t a sci-fi fantasy; it’s an exciting reality driven by cutting-edge artificial intelligence (AI). The transformation of textual descriptions…
The large language models (LLMs) research domain emphasizes aligning these models with human preferences to produce helpful, unbiased, and safe responses. Researchers have made significant strides in training LLMs to improve their ability to understand, comprehend, and interact with human-generated text, enhancing communication between humans and machines. A primary challenge in NLP is teaching LLMs…
The robotics research field has significantly transformed by integrating large language models (LLMs). These advancements have presented an opportunity to guide robotic systems in solving complex tasks that involve intricate planning and long-horizon manipulation. While robots have traditionally relied on predefined skills and specialized engineering, recent developments show potential in using LLMs to help guide…