​[[{“value”:” Time series forecasting has long been integral to finance, healthcare, meteorology, and supply chain management. Its main objective is to predict future data points based on historical observations, which can be challenging due to the complex and varying nature of time series data. Recent… Read More »Salesforce AI Research Introduces Moirai-MoE: A MoE Time Series Foundation Model that Achieves Token-Level Model Specialization Autonomously Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The deployment of AI chatbots has long been a significant challenge for organizations, particularly for those without the necessary technical expertise or infrastructure to support advanced AI models. Developing AI chatbots requires training complex models, managing cloud resources, optimizing inference, and maintaining compatibility across… Read More »SambaNova and Hugging Face Simplify AI Chatbot Integration with One-Click Deployment Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Artificial Intelligence (AI) continues to evolve rapidly, but with that evolution comes a host of technical challenges that need to be overcome for the technology to truly flourish. One of the most pressing challenges today lies in inference performance. Large language models (LLMs), such… Read More »Cerebras Systems Revolutionizes AI Inference: 3x Faster with Llama 3.1-70B at 2,100 Tokens per Second Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Precise control over language models is crucial for developers and data scientists. Large language models like Claude from Anthropic offer remarkable opportunities, but managing tokens effectively is a key challenge. Anthropic’s Token Counting API addresses this by providing detailed insights into token usage, enhancing… Read More »Anthropic AI Introduces a New Token Counting API Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Retrieval-Augmented Generation (RAG) has significantly enhanced the capabilities of large language models (LLMs) by incorporating external knowledge to provide more contextually relevant and accurate responses. However, this technique comes with a major downside: it often leads to high computational and memory costs. These challenges… Read More »RAGCache: Optimizing Retrieval-Augmented Generation with Dynamic Caching Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models find it challenging to understand Mathematical reasoning. Mathematical reasoning involves various cognitive tasks like understanding and manipulating mathematical concepts, solving problems, and making logical deductions. Existing methods in this domain have been established to enhance the mathematical ability of LLMs. However,… Read More »Kwai-STaR: An AI Framework that Transforms LLMs into State-Transition Reasoners to Improve Their Intuitive Reasoning Capabilities Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have become foundational in natural language processing, especially in applications where understanding complex text data is critical. These models require vast amounts of computational resources due to their size, posing latency, memory usage, and power consumption challenges. To make LLMs… Read More »This AI Paper Introduces BitNet a4.8: A Highly Efficient and Accurate 4-bit LLM Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Retrieval-augmented generation (RAG) has been shown to improve knowledge capabilities and reduce the hallucination problem of LLMs. The Web is a major source of external knowledge used in RAG and many commercial systems such as ChatGPT. However, current RAG implementations face a fundamental challenge… Read More »HtmlRAG: Enhancing RAG Systems with Richer Semantic and Structural Information through HTML Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In today’s world, Graph similarity computation (GSC) plays an important role in various applications such as code detection, molecular graph similarity, image matching, etc., by evaluating the similarity between two graphs, and it is based on Graph similarity learning. Graph Edit Distance (GED) and… Read More »From Edges to Nodes: SEGMN’s Comprehensive Approach to Graph Similarity Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Document Visual Question Answering (DocVQA) represents a rapidly advancing field aimed at improving AI’s ability to interpret, analyze, and respond to questions based on complex documents that integrate text, images, tables, and other visual elements. This capability is increasingly valuable in finance, healthcare, and… Read More »Researchers from Bloomberg and UNC Chapel Hill Introduce M3DocRAG: A Novel Multi-Modal RAG Framework that Flexibly Accommodates Various Document Context Asif Razzaq Artificial Intelligence Category – MarkTechPost