Recently, pioneering company in the field of clinical AI, Aidoc, announced that it is collaborating with NVIDIA to develop a new guide called 'BRIDGE' (Blueprint for Resilient Integration and Deployment of Guided Excellence). The goal of this guide is to accelerate the adoption of artificial intelligence in the healthcare industry, with an expected release in early 2025.

Recently, teams from Cambridge University and others published a groundbreaking paper that reveals the true nature of large models (LLMs), providing an in-depth analysis of the actual performance of current large language models (LLMs). The results are shocking — these AI models, once highly anticipated, perform far below expectations on many basic tasks. The study conducted a comprehensive evaluation of several cutting-edge models, including o1-preview. The findings indicate significant discrepancies in understanding capabilities between AI models and humans. Surprisingly, the models struggle with tasks that humans excel at.

Recently, Abridge announced the successful raise of $150 million, with plans to better integrate generative AI technology into the healthcare industry. This startup focuses on transcribing conversations between doctors and patients, automatically organizing these records into electronic health records. Source Note: Image generated by AI, image courtesy of service provider Midjourney. As the healthcare industry faces staffing shortages, Abridge aims to help clinicians reduce administrative burdens by enhancing its technology. The company partners with electronic health record giant Epic.

Researchers from Stanford University and the University of California, Berkeley conducted an experiment to explore the consequences of retraining AI image generation models using images generated by the AI itself. The experiment utilized the Stable Diffusion (SD) model and selected high-quality facial images from the FFHQ dataset for automatic generation. The results showed that after retraining, the AI model produced highly distorted images. This distortion originated not only from the text prompts used for retraining but also persisted even when retraining was done solely with real images.

Recently, scholars from multiple institutions have discovered a new technology known as Physical Neural Networks (PNNs). This is not the kind of digital algorithms we are familiar with that run on computers, but a completely new, intelligent computing method based on physical systems. As the name suggests, PNNs utilize the characteristics of physical systems to perform computations in neural networks. Although they are still a niche area of research, PNNs could be one of the significantly underv

Abridge announced the completion of $150 million in Series C funding, garnering widespread attention after the launch of ChatGPT, which heightened interest in the clinical documentation field. The funding will impact Abridge's development and challenge competitors, bringing more intelligent solutions to the healthcare industry.

Cambridge Dictionary has announced 'Hallucination' as the Word of the Year for 2023, as AI technology redefines the concept. AI tools like ChatGPT have sparked significant interest but have also raised questions about the reliability of AI-generated text. AI 'hallucinations' are having real-world impacts, involving fabricated legal cases and other practical situations. An AI ethicist from Cambridge University points out that AI 'hallucination' anthropomorphizes artificial intelligence.

Artificial intelligence will be a major disruptor in life. It will help people make progress in productivity, education, healthcare, and other areas. Employment disturbances may already be underway.