​[[{“value”:” Machine learning models, which can contain billions of parameters, require sophisticated methods to fine-tune their performance efficiently. Researchers aim to enhance the accuracy of these models while minimizing the computational resources needed. This improvement is crucial for practical applications in various domains, such as… Read More »Researchers from Columbia University and Databricks Conducted a Comparative Study of LoRA and Full Finetuning in Large Language Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Accurate propagation modeling is paramount for effective radio deployments, coverage analysis, and interference mitigation in wireless communications. Path loss modeling, a widely adopted approach, enables generic predictions of signal power attenuation along wireless links, equipping network planners with essential insights into physical layer attributes.… Read More »Machine Learning Revolutionizes Path Loss Modeling with Simplified Features Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” State-space models (SSMs) are crucial in deep learning for sequence modeling. They represent systems where the output depends on both current and past inputs. SSMs are widely applied in signal processing, control systems, and natural language processing. The main challenge is the inefficiency of… Read More »This AI Paper Introduces Rational Transfer Function: Advancing Sequence Modeling with FFT Techniques Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. This process captures local and global graph structure, facilitating node classification and link prediction tasks. Effective graph pooling is essential for downsizing and learning representations, categorized… Read More »Enhancing Graph Classification with Edge-Node Attention-based Differentiable Pooling and Multi-Distance Graph Neural Networks GNNs Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The recent Yi-1.5-34B model introduced by 01.AI has brought about yet another advancement in the field of Artificial Intelligence. Positioned as a major improvement over its predecessors, this unique model bridges the gap between Llama 3 8B and 70B. It promises better performance in… Read More »01.AI Introduces Yi-1.5-34B Model: An Upgraded Version of Yi with a High-Quality Corpus of 500B Tokens and Fine-Tuned on 3M Diverse Fine-Tuning Samples Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The artificial intelligence and machine learning world has witnessed rapid advancements, with OpenAI at the forefront of these innovations. One of the latest developments is the release of GPT-4o, an optimized version of the highly acclaimed GPT-4. Let’s delve into the key updates in… Read More »GPT-4 vs. GPT-4o: Key Updates and Comparative Analysis Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Machine Learning (ML) is everywhere these days, playing a crucial role in countless fields worldwide. Its applications are endless, and we rely on it more than ever. As ML models become more complex, it becomes more challenging to understand and interpret them. Understanding complex… Read More »Model Explorer: A Powerful Graph Visualization Tool that Helps One Understand, Debug, and Optimize Machine Learning Models Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Data mapping is a critical process in data management, enabling the integration and transformation of data from various sources into a unified format. The concept of data mapping as a search problem provides a unique perspective on efficiently and effectively discovering mappings between data… Read More »Exploring Data Mapping as a Search Problem Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” As Artificial Intelligence (AI) systems advance, a fascinating trend has emerged: their representations of data across different architectures, training objectives, and even modalities seem to be converging. Researchers have put forth, as shown in Figure 1, a thought-provoking hypothesis to explain this phenomenon called… Read More »The Pursuit of the Platonic Representation: AI’s Quest for a Unified Model of Reality Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Although recent multimodal foundation models are extensively utilized, they tend to segregate various modalities, typically employing specific encoders or decoders for each. This approach constrains their capacity to fuse information across modalities effectively and produce multimodal documents comprising diverse sequences of images and text.… Read More »Meta AI Introduces Chameleon: A New Family of Early-Fusion Token-based Foundation Models that Set a New Bar for Multimodal Machine Learning Mohammad Asjad Artificial Intelligence Category – MarkTechPost