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Over the last few years, large language models (LLMs) have evolved from mere research artifacts into useful products Open AI [1]. This advent of large language models (LLMs) has brought new possibilities to the agent development. Current LLMs have shown great power in understanding instructions reasoning and solving problems and interacting with human users as well as external environments. Built upon these powerful LLMs, emergent LLM-based agents can present strong task fulfillment abilities in diverse environments, ranging from virtual assistants to more sophisticated systems involving complex and creative problem solving, planning and reasoning. This study explores the architecture of LLM-based agents and provides research directions for the future of LLM-based agents...... ReadMore -
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Large Language Models (LLMs) are enabling more natural and sophisticated interactions between human-beings and machines, enhancing user experience in existing applications like coding [1], web search [2], chatbots [3,4], customer service and content creation. This transformation brought by LLMs is also paving the way for new innovative AI applications. While large-scale transformers such as Chat GPT [57] and GPT4 [58] demonstrate impressive successes on seemingly complex tasks they also display astonishing failures on seemingly trivial tasks which spark critical open questions about how to faithfully interpret their mixed capabilities...... ReadMore -
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Parallel computing gained a strong relevance with the introduction of the first dual-core CPU in the early 2000s. From there, parallel architectures as well as research in parallel computing achieved significant milestones, such as the possibility to pack dozens of CPU cores in a single chip, new parallel algorithms and the development of parallel programming languages and tools [1]. Today we have a large ecosystem of parallel processors sitting in many of the devices we use every day; from laptops and cellphones to TVs and Cars. In the last couple of years, with the surge of artificial intelligence and videogames, parallel computing has become even more relevant, as it is the technological bed for many states of the art applications that require high performance. During these last 5-6 years, the computing community has witnes..... ReadMore -
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In the rapidly evolving field of data management, numerous terminologies, such as data warehouse, data lake, data lake house, and data mesh, have emerged, each representing a unique analytical data architecture. However, the distinctions and similarities among these paradigms often remain unclear...... ReadMore -
Short CommunicationView abstract
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Operations research (OR) is a scientific research technique or mathematical technique used to aid decision-making in large organizations or organized systems management. Transportation is the movement of people, livestock, and goods from one location to another in the real world, and it is a massively coordinated process. The transportation problem...... ReadMore -
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Mathematics serves as the cornerstone for expressing the logic of macro-to-micro artificial intelligence. It provides a quantitative framework to describe cognition, emotion, and high-level intelligence. By delving into fundamental mathematics, we gain insight into the direct structure of correlation and causality in artificial intelligence...... ReadMore -
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In this paper, a plasmonic refractive index sensor based on metal insulated metal waveguide (MIM) with three rings and a resonant cavity is first proposed and numerically evaluated. Next, we add four teeth to the sensor structure. We study and simulate the resonant wavelengths and refractive index of resonators using the time difference finite difference method...... ReadMore -
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The article based on the traditional data mining with large data mining perspective, probes into the connotation of the large data mining, puts forward the cloud computing service integration of data mining and mining system frame work, and to merge the multi-function large Hadoop data mining platform as an example, the analysis of large data mining internal work processes and analyzes the advantages and challenges, So as to provide a reference for users’ cognition and application needs of big data mining...... ReadMore