Digital pathology is transforming the analysis of traditional glass slides into digital images, accelerated by advancements in imaging technology and software. This transition has important implications for medical diagnostics, research, and education. The ongoing AI revolution and digital shift in biomedicine have the potential to expedite improvements in precision health tenfold. Digital pathology can be…
Google has developed a comprehensive large language model named Gemini, originally known as Bard. The motivation behind Google's ambitious multimodel was their vision of a future broader in scope than was realized with OpenAI's ChatGPT. Google Gemini, might be the most exhaustive large language model developed to date, and most users are still only discovering…
Machine translation (MT) has advanced significantly due to developments in deep learning and neural networks. However, translating literary texts remains a significant challenge due to their complexity, figurative language, and cultural variations. Often referred to as the "last frontier of machine translation," literary translation represents a considerable task for MT systems.
Large language models (LLMs) have…
Foundation models are critical to AI's impact on the economy and society, and their transparency is imperative for accountability, understanding, and competition. Governments worldwide are launching regulations such as the US AI Foundation Model Transparency Act and the EU AI Act to promote this transparency. The Foundation Model Transparency Index (FMTI), rolled out in 2023,…
Recent advancements in Artificial Intelligence (AI) have given rise to systems capable of making complex decisions, but this lack of clarity poses a potential risk to their application in daily life and economy. As it is crucial to understand AI models and avoid algorithmic bias, model renovation is aimed at enhancing AI interpretability.
Kolmogorov-Arnold Networks (KANs)…
Large Language Models (LLMs) like GPT-4 have demonstrated proficiency in text analysis, interpretation, and generation, with their scope of effectiveness stretching to various tasks within the financial sector. However, doubts persist about their applicability for complex financial decision-making, especially involving numerical analysis and judgement-based tasks.
A key question is whether LLMs can perform financial statement…
Large multimodal language models (MLLMs) have the potential to process diverse modalities such as text, speech, image, and video, significantly enhancing the performance and robustness of AI systems. However, traditional dense models lack scalability and flexibility, making them unfit for complex tasks that handle multiple modalities simultaneously. Similarly, single-expert approaches struggle with complex multimodal data…
Reinforcement Learning (RL) involves learning decision-making through interactions with an environment and has been used effectively in games, robotics, and autonomous systems. RL agents aim to maximize their results and increase their efficiency by improving performance through continually adapting to new data. However, the RL agent's sample inefficiency impedes its practical application by necessitating comprehensive…
Robotic learning typically involves training datasets tailored to specific robots and tasks, necessitating extensive data collection for each operation. The goal is to create a “general-purpose robot model”, which could control a range of robots using data from previous machines and tasks, ultimately enhancing performance and generalization capabilities. However, these universal models face challenges unique…
Foundation models are powerful tools that have revolutionized the field of AI by providing improved accuracy and complexity in analysis and interpretation of data. These models use large datasets and complex neural networks to execute intricate tasks such as natural language processing and image recognition. However, seamlessly integrating these models into everyday workflows remains a…
Researchers from various institutions have recently unveiled a unique linear property of transformer decoders in natural language processing models such as GPT, LLaMA, OPT, and BLOOM. This discovery could have significant implications for future advancements in the field. These researchers discovered that there is a nearly perfect linear relationship in the embedding transformations between sequential…
Since Bitcoin's launch in 2009, artificial intelligence (AI) has played an increasingly essential role in the evolution of cryptocurrency systems, proving instrumental in enhancing security and efficiency. With a wealth of expertise in data analysis, pattern recognition, and predictive modelling, AI is uniquely equipped to address the diverse challenges posed by advanced cryptocurrency systems.
One prominent…