​[[{“value”:” 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… Read More »Self-Play Preference Optimization (SPPO): An Innovative Machine Learning Approach to Finetuning Large Language Models (LLMs) from Human/AI Feedback Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:”This paper has been accepted at the Data Problems for Foundation Models workshop at ICLR 2024. Large language models are trained on massive scrapes of the web, which are often unstructured, noisy, and poorly phrased. Current scaling laws show that learning from such data requires… Read More »Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling Apple Machine Learning Research

​[[{“value”:” 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… Read More »Nvidia Publishes A Competitive Llama3-70B Quality Assurance (QA) / Retrieval-Augmented Generation (RAG) Fine-Tune Model Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” 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… Read More »Capsule Networks: Addressing Limitations of Convolutional Neural Networks CNNs Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” 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… Read More »This AI Paper by the University of Wisconsin-Madison Introduces an Innovative Retrieval-Augmented Adaptation for Vision-Language Models Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Home Table of Contents Introduction to Machine Learning: Why There Are No Programmed Answers Machine Learning Explained: Moving Beyond Hard-Coded Logic How Machine Learning Transforms Data into Insights: The Learning Mechanics The Crucial Role of Data in Machine Learning Insights The Impact of Data… Read More »Introduction to Machine Learning: Why There Are No Programmed Answers Hector Martinez PyImageSearch

​[[{“value”:” 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… Read More »NASGraph: A Novel Graph-based Machine Learning Method for NAS Featuring Lightweight (CPU-only) Computation and is Data-Agnostic and Training-Free Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” 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… Read More »Text to 3D Avatar Animation: A New Era in Virtual Character Creation Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” 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… Read More »NVIDIA AI Open-Sources ‘NeMo-Aligner’: Transforming Large Language Model Alignment with Efficient Reinforcement Learning Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” 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… Read More »PLAN-SEQ-LEARN: A Machine Learning Method that Integrates the Long-Horizon Reasoning Capabilities of Language Models with the Dexterity of Learned Reinforcement Learning RL Policies Sana Hassan Artificial Intelligence Category – MarkTechPost