Researchers from MIT, Brigham and Women’s Hospital, and Duke University have pioneered a multifaceted approach to determine the transporters used by various drugs to exit the digestive tract. Leveraging tissue models and machine-learning algorithms, the team has discovered that doxycycline (an antibiotic) and warfarin (a blood thinner) can interfere with each other’s absorption.
All orally consumed…
MIT researchers have developed a technique to train robots on multiple tasks by combining and optimising data from a variety of sources. At the core of their work is a type of generative AI known as a 'diffusion model', which learns from a specific dataset to complete a task. However, the particular innovation here lies…
The complexities and inefficiencies often associated with handling and extracting information from various file types like PDFs and spreadsheets are well-known challenges. Typical tools for the job usually fall short in several areas such as versatility, processing capacity, and maintenance. These setbacks emphasize the demand for an efficient and user-friendly solution for parsing and representing…
IBM is paving the way for AI advancements through their development of groundbreaking technologies, as well as a broad offer of extensive courses. Their AI-focused initiatives provide learners with the tools to utilize AI throughout a myriad of fields. IBM's courses furnish practical skills and knowledge that allow learners to effectively implement AI solutions and…
Text, audio, and code sequences depend on position information to decipher meaning. Large language models (LLMs) such as the Transformer architecture do not inherently contain order information and regard sequences as sets. The concept of Position Encoding (PE) is used here, assigning a unique vector to each position. This approach is crucial for LLMs to…
The improvement of logical reasoning capabilities in Large Language Models (LLMs) is a critical challenge for the progression of Artificial General Intelligence (AGI). Despite the impressive performance of current LLMs in various natural language tasks, their limited logical reasoning ability hinders their use in situations requiring deep understanding and structured problem-solving.
The need to overcome…
The existing language learning models (LLMs) are advancing yet have been struggling with incorporating new knowledge without forgetting the previous information, a situation termed as "catastrophic forgetting." The present methods, such as retrieval-augmented generation (RAG), are not very effective in tasks demanding integration of new knowledge from various passages due to encoding each passage in…
A team of MIT researchers have developed a novel cryptographic ID tag to tackle product counterfeiting. This tag, which is remarkably smaller and cost-efficient than traditional radio frequency tags (RFIDs), uses terahertz waves to perform authentication. The small size of terahertz waves and their greater frequency compared to radio waves make them ideal for this…