Computer manufacturers offer platforms for users to describe device faults using textual reports such as "My screen is flickering". Identifying the faulty component from the report is essential for automating tests and improving user experience. However, such reports are often ambiguous and lack detail, making this task challenging. Large Language Models (LLMs) have shown promise in addressing such issues. This study evaluates 27 open-source models (1B-72B parameters) and 2 proprietary LLMs using four prompting strategies: Zero-Shot, Few-Shot, Chain-of-Thought (CoT), and CoT+Few-Shot (CoT+FS). W e conducted 98,948 inferences, processing over 51 million input tokens and generating 13 million output tokens. W e achieve f1-score up to 0.76. Results show that three models offer the best balance between size and performance: mistral-small-24b-instruct and two smaller models, llama-3.2-1b-instruct

Computer manufacturers typically offer platforms for users to report faults. However, there remains a significant gap in these platforms' ability to effectively utilize textual reports, which impedes users from describing their issues in their own words. In this context, Natural Language Processing (NLP) offers a promising solution, by enabling the analysis of user-generated text. This paper presents an innovative approach that employs NLP models to classify user reports for detecting faulty computer components, such as CPU, memory, motherboard, video card, and more. In this work, we build a dataset of 341 user reports obtained from many sources. Additionally, through extensive experimental evaluation, our approach achieved an accuracy of 79% with our dataset.

Knowledge graphs (KGs) are essential in applications such as network alignment, question-answering, and recommender systems (RSs) since they offer structured relational data that facilitate the inference of indirect relationships. However, the development of KG-based RSs capable of processing user inputs in natural language faces significant challenges. Firstly, natural language processing units must effectively handle the ambiguity and variability in human language to interpret user intents accurately. Secondly, the system must precisely identify and link entities, like product names, to their corresponding nodes in KGs. To overcome these challenges, supported by Lenovo, we developed a novel chatbot called "Prometheus," which integrates a KG with a large language model (LLM), specifically designed for recommending computer components. This chatbot can accurately decode user requests and deliver personalized recommendations derived from KGs, ensuring precise comprehension and response to their computer setup needs.

A computer component that uses vibrations rather than electrons could approach the physical lower limit for energy use when processing and sending information. The minimum amount of energy needed for a computer to perform a computational step is called the "Landauer limit", named after the 1960s physicists Rolf Landauer. In his calculations, Landauer did not consider any specific computer design, but rather the basic energy cost required to manipulate information, like erasing or re-writing a bit.

You don't have to look far or wide to find guides on building the best gaming rigs. That is a tougher search, although there can be some overlap. There aren't many companies talking about the ins and outs of DIY AI computer build essentials. It is exactly for that reason that we have compiled a list of the most important components you will need for an artificial intelligence (AI) build and what we recommend. What else should you consider for an AI computer?

You don't have to look far or wide to find guides on building the best gaming rigs. That is a tougher search, although there can be some overlap. There aren't many companies talking about the ins and outs of DIY AI computer build essentials. It is exactly for that reason that we have compiled a list of the most important components you will need for an artificial intelligence (AI) build and what we recommend. What else should you consider for an AI computer?

Japanese researchers envision a future where swarms of cyborg cockroaches roam freely inside homes, carrying out a variety of small tasks. A team at the University of Tsukuba modified Madagascar cockroaches with cybernetic implants that navigate the insects up walls and across floors – places other robots have difficult accessing. Called'Calmbots,' the cockroaches were installed with electrodes, a chip antenna, battery and a pixel strapped to its back that can be used as a display. Researchers say the cyborgs can transport objects around the home, drawing things on paper and may one day act as an'input or haptic interfaces or an audio device. Calmbots are a project of Digital Nature Group, a department at the university, which aims to release their creations into people's homes.

In a world first, scientists have stored light-based data as sound waves on a computer chip - a feat they compare to'capturing lightning as thunder'. Storing light as sound has been pursued by large companies such as IBM and Intel for years, but until now has never been achieved. The researchers hope their breakthrough could lead to the creation of computers in which data can safely travel at the speed of light. The researchers' chip is made of chalcogenide glass, which provides optimal guidance of both optical and acoustic waves. The chip operates at room temperature and can be used with other computer components, which means it can be easily integrated into photonic circuits.