In the midst of increasing patient demand and workforce shortages in health systems, standardized protocols and procedures have never been more vital, particularly for patients with brain injuries. However, some protocols are more effective than others, resulting in inconsistent care for certain conditions.
One such condition is intracranial hemorrhage (ICH), a brain injury associated with high…
Researchers in the UK have trialed an AI-based tool called Foresight that can create "digital twins" of patients and effectively predict future health conditions and treatment responses. By making use of patient information from electronic health records (EHRs), most of which is unstructured, the AI tool can develop a representative model of the patient. Foresight…
Scientists from Loughborough University, MIT, and Yale have introduced a concept titled 'Collective AI,’ proposing a framework called Shared Experience Lifelong Learning (ShELL). This approach supports the development of decentralized AI systems comprised of multiple independent agents that continually learn and share knowledge. The researchers compare this model to a 'hive mind,' stating it could…
Large Language Models (LLMs) have become pivotal in natural language processing (NLP), excelling in tasks such as text generation, translation, sentiment analysis, and question-answering. The ability to fine-tune these models for various applications is key, allowing practitioners to use the pre-trained knowledge of the LLM while needing fewer labeled data and computational resources than starting…
Large language models (LLMs) such as ChatGPT, Google’s Bert, Gemini, Claude Models, power our engagement with digital platforms, behaving like human responses and generating innovative content, participating in complex discussions, and solving intricate issues. The effective operations and training processes of these models bring about a synthesis between human and automated interaction, further advancing the…
Researchers from the Max Planck Institute for Intelligent Systems, Adobe, and the University of California have introduced a diffusion image-to-video (I2V) framework for what they call training-free bounded generation. The approach aims to create detailed video simulations based on start and end frames without assuming any specific motion direction, a process known as bounded generation,…
Business-to-business (B2B) payments can be a complex task for many businesses. Traditional payment methods often involve dealing with a myriad of processing options and managing numerous accounts, vendors, and payment recipients. Integrated payables address this issue by streamlining and simplifying the payment process into a single-source platform.
Integrated payables are a technological solution for payment processing…
The process of managing B2B payments has become increasingly complex with the need to handle cross-border transactions, myriad payment processing options, and the task of keeping all these straight and error-free. This issue affects a range of payment recipients and vendors. However, technological innovations are simplifying this process through the implementation of integrated payables. These…
Artificial intelligence (AI)'s potential to have unprecedented capabilities has raised concerns about the possible threats it could pose to cybersecurity, privacy, and human autonomy. Understanding these risks is essential for mitigating them. This is usually achieved by evaluating AI systems' performance in various domains but often requires a deeper understanding of their possible dangers. To…
The article outlines the process of creating synthetic user research using Autogen, an autonomous agent orchestration tool. The application of the Large Language Model (LLM) from OpenAI was explored with versions GPT-3.5 and GPT-4. The whole process starts with setting up the environment and creating the Autogen configuration, LLM, and API keys.
The LLM instance has…
Technological trends reveal a significant shift towards edge computing influenced by advancements in GenAI and conventional AI workloads. In the past, these AI workloads were exclusively reliant on cloud computing. However, realizing the constraints of cloud-based AI, such as data security concerns, network connectivity issues, and sovereignty issues, organizations are considering edge computing as a…