​ The human brain is an extraordinarily complex organ, often considered one of the most intricate and sophisticated systems in the known universe. The brain is hierarchically organized, with lower-level sensory processing areas sending information to higher-level cognitive and decision-making regions. This hierarchy allows for… Read More »Researchers from ITU Denmark Introduce Neural Developmental Programs: Bridging the Gap Between Biological Growth and Artificial Neural Networks Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ Large Language Models (LLMs) have gained a lot of attention for their human-imitating properties. These models are capable of answering questions, generating content, summarizing long textual paragraphs, and whatnot. Prompts are essential for improving the performance of LLMs like GPT-3.5 and GPT-4. The way… Read More »Google DeepMind Researchers Introduce Promptbreeder: A Self-Referential and Self-Improving AI System that can Automatically Evolve Effective Domain-Specific Prompts in a Given Domain Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ By providing object instance-level classification and semantic labeling, 3D semantic instance segmentation tries to identify items in a given 3D scene represented by a point cloud or mesh. Numerous vision applications, including robots, augmented reality, and autonomous driving, depend on the capacity to segment… Read More »Breaking Boundaries in 3D Instance Segmentation: An Open-World Approach with Improved Pseudo-Labeling and Realistic Scenarios Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ The field of Machine Learning and Artificial Intelligence has become very important. We have new advancements that have been there with each day. The area is impacting all spheres. By utilizing finely developed neural network architectures, we have models that are distinguished by extraordinary… Read More »This AI Paper Reveals a New Approach to Understand Deep Learning Models: Unpacking the ‘Where’ and ‘What’ with Concept Relevance Propagation (CRP) Rachit Ranjan Artificial Intelligence Category – MarkTechPost

​ In addressing the limitations of large language models (LLMs) when capturing less common knowledge and the high computational costs of extensive pre-training, Researchers from Meta introduce Retrieval-Augmented Dual Instruction Tuning (RA-DIT). RA-DIT is a lightweight fine-tuning methodology designed to equip any LLM with efficient… Read More »Meta AI Researchers Introduce RA-DIT: A New Artificial Intelligence Approach to Retrofitting Language Models with Enhanced Retrieval Capabilities for Knowledge-Intensive Tasks Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ The emergence of Large Language Models (LLMs) in natural language processing represents a groundbreaking development. These models, trained on vast amounts of data and leveraging immense computational resources, promise to transform human interactions with the digital world. As they evolve through scaling and rapid… Read More »Meta AI Researchers Propose Advanced Long-Context LLMs: A Deep Dive into Upsampling, Training Techniques, and Surpassing GPT-3.5-Turbo-16k’s Performance Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ By additional pre-training using image-text pairings or fine-tuning them with specialized visual instruction tuning datasets, Large Language Models may dive into the multimodal domain, giving rise to potent Large Multimodal Models. However, there are obstacles to building LMMs, chief among them the disparity between… Read More »Overcoming Hallucinations in AI: How Factually Augmented RLHF Optimizes Vision-Language Alignment in Large Multimodal Models Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ Large language models (LLMs) have significantly reshaped the landscape of Artificial Intelligence (AI) since their emergence. These models provide a strong framework for challenging reasoning and problem-solving problems, revolutionizing numerous AI disciplines. LLMs are adaptable agents capable of various tasks thanks to their capacity… Read More »All You Need To Know About The Qwen Large Language Models (LLMs) Series Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ Action recognition is the process of automatically identifying and categorizing human actions or movements in videos. It has applications in various domains, including surveillance, robotics, sports analysis, and more. The goal is to enable machines to understand and interpret human actions for improved decision-making… Read More »How Can We Optimize Video Action Recognition? Unveiling the Power of Spatial and Temporal Attention Modules in Deep Learning Approaches Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

​ The demand for more advanced and versatile language assistants has steadily increased in the ever-evolving landscape of artificial intelligence. The challenge lies in creating a genuinely multimodal AI that can seamlessly comprehend text and interact with visual and auditory inputs. This problem has long… Read More »Reka AI Introduces Yasa-1: A Multimodal Language Assistant with Visual and Auditory Sensors that can Take Actions via Code Execution Niharika Singh Artificial Intelligence Category – MarkTechPost