While existing speech datasets are heavily skewed towards English, many EU languages are underserved in terms of accessible and high-quality speech data. This lack of resources leads to AI models that better understand and process English than other languages in tasks like recognition, machine translation, and other natural language processing tasks. The scarcity of well-organized,… →
AI and the Internet of Medical Things IoMT are transforming healthcare, particularly in managing terminal diseases like cancer and heart failure. These technologies enhance diagnosis, personalize treatments, and improve patient monitoring, leading to better outcomes and quality of life. As terminal diseases progress, palliative care becomes crucial, focusing on symptom relief rather than cure. Integrating… →
Recruitment is a dynamic process that has undergone tremendous transformation in recent years, with the adoption of new technologies playing a crucial role. One of the latest tools revolutionizing the recruitment landscape is OpenAI’s ChatGPT. With its advanced natural language processing capabilities, ChatGPT offers recruiters numerous opportunities to streamline their processes, improve candidate experiences, and… →
Generative Intelligence has remained a hot topic for some time, with the current world witnessing an unprecedented boom in AI-related innovations and research, especially after the introduction of Large Language Models. A significant amount of funding is being allocated to LLM-related research in academia and industry, and it is intended to create the subsequent breakthrough… →
Large Language Models (LLMs) generate code aided by Natural Language Processing. There is a growing application of code generation in complex tasks such as software development and testing. Extensive alignment with input is crucial for an adept and bug-free output, but the developers identified it as computationally demanding and time-consuming. Hence, creating a framework for… →
Automatic Speech Recognition (ASR) and Diarization technologies have become essential tools for transforming how machines interpret human speech. These innovations enable accurate transcription, speech segmentation, and speaker identification across various applications like media transcriptions, legal documentation, and customer service automation. By breaking down audio data into comprehensible text and attributing speech to different speakers, these… →
The rapid advancement of generative AI has made image manipulation easier, complicating the detection of tampered content. While effective, current Image Forgery Detection and Localization (IFDL) methods need to work on two key challenges: the black-box nature of their detection principles and limited generalization across various tampering methods like Photoshop, DeepFake, and AIGC-Editing. The rise… →
Training Large Language Models (LLMs) that can handle long-context processing is still a difficult task because of data sparsity constraints, implementation complexity, and training efficiency. Working with documents of infinite duration, which are typical in contemporary media formats like automated news updates, live-stream e-commerce platforms, and viral short-form movies, makes these problems very clear. Online… →
A popular method when employing Large Language Models (LLMs) for complicated analytical tasks, such as code generation, is to attempt to solve the full problem within the model’s context window. The informational segment that the LLM is capable of processing concurrently is referred to as the context window. The amount of data the model can… →
Natural language processing (NLP) has experienced rapid advancements, with large language models (LLMs) being used to tackle various challenging problems. Among the diverse applications of LLMs, mathematical problem-solving has emerged as a benchmark to assess their reasoning abilities. These models have demonstrated remarkable performance on math-specific benchmarks such as GSM8K, which measures their capabilities to… →