Large Language Models (LLMs) have steered in a period of extraordinary growth for Artificial Intelligence (AI) technology. To address issues like conversation hallucination, these models are being used increasingly in various settings where unstructured multimedia data is converted into embedding vectors. Vector Data Management Systems (VDMSs) are specifically designed to manage these vectors effectively. Platforms, such as Qdrant and Milvus, have developed sizable user bases and vibrant communities, serving as the backbone of the LLM age. LLMs and other machine learning and information retri ..read more

On-device intelligence (ODI) is an emerging technology that combines mobile computing and AI, enabling real-time, customized services without network reliance. ODI holds promise in the Internet of Everything era for applications like medical diagnosis and AI-enhanced motion tracking. Despite ODI’s potential, challenges arise from decentralized user data and privacy concerns.  Some researchers have proposed methods balancing AI training needs with device limitations to optimize ODI’s potential. Cloud-based paradigms entail uploading data for centralized training but raise privacy concerns ..read more

Integrating artificial intelligence (AI) in healthcare transforms medical practices by improving diagnostics and treatment planning accuracy and efficiency. By leveraging advanced algorithms, AI supports a range of applications, from anomaly detection in medical imaging to predicting disease progression, enhancing the overall efficacy of medical interventions. One of the primary hurdles in deploying AI within the medical sector is ensuring the accuracy and reliability of AI-driven predictions, particularly when data is scarce. Small datasets are common in healthcare due to privacy concerns an ..read more

Generative models have emerged as transformative tools across various domains, including computer vision and natural language processing, by learning data distributions and generating samples from them. Among these models, Diffusion Models (DMs) have garnered attention for their ability to produce high-quality images. Latent Diffusion Models (LDMs) stand out for their rapid generation capabilities and reduced computational cost. However, deploying LDMs on resource-limited devices remains challenging due to significant compute requirements, particularly from the Unet component. Researchers hav ..read more

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