Software maintenance is an integral part of the software development life cycle, where developers often visit existing code bases to resolve errors, implement new features and optimize the performance. A critical task in this phase is code localization that clarifies specific locations in a code base that needs to be changed. This process has been … Read more
LLMs quickly go across multiple domains, but their effectiveness in tackling complex financial problems is still an area of ​​active study. The iterative development of LLMs has significantly driven the development of artificial intelligence to artificial general intelligence (AGI). Openai’s O1 series and similar models such as QWQ and Marco-O1 have improved complex reasoning features … Read more
Artificial intelligence has made significant progress in recent years, yet it is a complex challenge to integrate real -time speech interaction with visual content. Traditional systems are often dependent on separate components of voice activity detection, speech recognition, text dialogue and text-to-speech synthesis. This segmented approach can introduce delays and may not be able to … Read more
In the field of artificial intelligence, multilingual speech recognition and translation have become important tools to facilitate global communication. Development of models, which, however, can precisely transcribe and translate multiple languages ​​in real time, constitute significant challenges. These challenges include managing different linguistic shades, maintaining high accuracy, ensuring low latency and implementation of models effectively … Read more
In today’s information -rich world, it is crucial to find relevant documents quickly. Traditional keyword -based search systems often fall short when dealing with semantic significance. This tutorial demonstrates how to build a powerful document search engine using: Hugging Face’s embedded models to convert text to rich vector representations Chroma DB as our Vektordatabase for … Read more
Fetch-Augmented Generation (RAG) has emerged as a strong paradigm to improve the capabilities of large language models (LLMS). By combining LLMS ‘creative generational skills with the actual accuracy of the retrieval systems, RAG offers a solution to one of LLMS’ most sustained challenges: hallucination. In this tutorial we build a complete clothing system using: FAISS … Read more
Machine learning has been expanded beyond traditional Euclidean spaces in recent years and examined representations in more complex geometric structures. Non-Euklidic representation learning is a growing field that seeks to capture the underlying geometric properties of data by embedding it in hyperbolic, spherical or mixed curvature product spaces. These approaches have been particularly useful for … Read more
LLMs are widely used for conversation AI, content generation and company automation. However, balancing performance with calculation efficiency is an important challenge in this field. Many advanced models require extensive hardware resources, making them impractical for smaller businesses. The demand for cost-effective AI solutions has led to researchers developing models that provide high performance with … Read more
Multimodal Large Language Models (MLLMS) have shown remarkable capabilities across different domains, which propel their development into multimodal means of human help. GUI automation agents for PCs are facing particularly scary challenges compared to smartphone counterparts. PC environments present significantly more complex interactive elements with dense, different icons and widgets that often lack text marks, … Read more
The rapid development of artificial intelligence (AI) has launched a new era with large language models (LLMs) capable of understanding and generating human -like text. However, the proprietary nature of many of these models constitutes challenges for accessibility, collaboration and transparency within the research community. In addition, the significant calculation resources required to educate such … Read more