AI

  A groundbreaking initiative has emerged from esteemed research institutions aiming to unravel the enigmatic intricacies of lithium-based batteries. Employing an innovative approach, researchers harness machine learning to meticulously analyze X-ray videos at the pixel level, potentially revolutionizing battery research. The challenge at the heart of this endeavor is the quest for a comprehensive understanding…

  A captivating puzzle awaits resolution in scientific exploration—proteins’ intricate and multifaceted structures. These molecular workhorses govern essential biological processes, wielding their influence in fascinating and enigmatic ways. Yet, interpreting the complex three-dimensional (3D) architecture of proteins has long been a challenge due to limitations in current analysis methods. Within this intricate puzzle, a research…

  A recent study has highlighted the effectiveness of natural language feedback in improving the performance of language models. A team of researchers from KAIST has introduced a new SelFee model designed explicitly for self-feedback and self-revision generation. Unlike previous approaches, SelFee does not require external, significant language or task-specific models to generate high-quality responses….

  Language models have made significant strides in natural language processing tasks. However, deploying large language models (LLMs) in real-world applications requires addressing their deficit in moral reasoning capabilities. To tackle this challenge, a Google research team introduces a groundbreaking framework called “Thought Experiments,” which utilizes counterfactuals to improve a language model’s moral reasoning. This…

Compared to their supervised counterparts, which may be trained with millions of labeled examples, Large Language Models (LLMs) like GPT-3 and PaLM have shown impressive performance on various natural language tasks, even in the zero-shot setting. However, utilizing LLMs to solve the basic text ranking problem has had mixed results. Existing findings often perform noticeably…

A recent study conducted by researchers at IBM and Oxford University revealed a breakthrough in antiviral drug development. The researchers utilized generative artificial intelligence (AI) to design novel molecules that have the potential to block the SARS-CoV-2 virus, which causes Covid-19. This approach proved successful, as the team identified four potential Covid-19 antivirals in a…

Natural language processing and computer vision are only examples of the fields where generative pre-trained models have succeeded incredibly. In particular, a viable strategy for constructing foundation models is to combine varied large-scale datasets with pre-trained transformers. The study investigates the feasibility of foundation models to further research in cellular biology and genetics by drawing…

In computer vision and graphics, photo-realistic portrait image synthesis has been constantly emphasized, with a wide range of downstream applications in virtual avatars, telepresence, immersive gaming, and many other areas. Indistinguishable from genuine images, recent developments in Generative Adversarial Networks (GANs) have shown a remarkably high image synthesis quality. Contemporary generative methods, however, don’t model…