One of the challenges in creating GUI agents that perform tasks akin to humans on graphical user interfaces is the collection of high-quality training trajectory data. Existing methods rely on expensive and time-consuming human supervision or generation of synthetic data that may not replicate real-life diversity and dynamics. These restrictions, therefore, severely limit the scalability … Read more
LIGER is Most generally recommendation systems are important in matching a user to an appropriate content, product, or service. Dense retrieval techniques are a mainstay of this area, using sequence modeling to compute item and user representations. The main downside of techniques is that they require large amounts of computational resources and substantial storage to … Read more
Platforms Like, X and Reddit, are not merely instruments of communication; they have now transformed into significant environments to comprehend current social behavior beyond mere exchanging of information and forming communities. Living simulation is crucial in the analysis of misinformation, group polarization, and herd behavior. Today, computational models give researchers a relatively cheaper and scalable … Read more
YuLan Mini Severe amounts of pre-training huge data have to be done to develop world-level large language models (LLMs) using transformer architectures that predict sequential tokens. Such preparation is costlier and resource-hungry and the computational infrastructural requirements are not easy to come by with specific well-constructed data pipelines. Balancing performance with resource consumption has attracted … Read more
Artificial Intelligence (AI) has taken place in the cloud environment and on-premises infrastructure, providing organizations with efficiency, scalability, and performance. As businesses adopt different models of cloud for operational management, issues relating to resource optimization and cost management arise. This calls for a solution that can sufficiently meet an organization’s specific Artificial Intelligence-enabled process capability … Read more
The advent of big data analytics in drug development is radically revolutionizing the biopharmaceutical company. Historically, the development of novel drugs, particularly for complex diseases such as cancer, has been a long, expensive, and high-risk journey. It is estimated that the cost of taking a drug to market averages in the billions of dollars, along … Read more
Localized receptive fields form the basis of sensory processing in biological neural systems they make a neuron responsive to a specific stimulus in a different region of the input domain. It is because of the efficiency and preciseness of biological systems that such attempts have been made to replicate this aspect in artificial neural networks. … Read more
What is an AI Agent? An AI agent is a software entity powered by artificial intelligence and can independently execute tasks typically associated with human beings. These tasks can range across various sectors like customer service, human resource, IT support, and others. Instead of automating simple processes such AI agents can handle complex, multi-step processes … Read more
Understanding AI World Models World models, also known as world simulators, are gaining considerable attention as one of the most essential advances in artificial intelligence. They aim to study those subconscious reasoning processes from humans that help understand and anticipate the world around them. Thus, they aspire to reach humanlike intelligence. What is World Model? … Read more
Understanding Large Language Models’ Knowledge Storage Giant, Large Language Models (LLMs) have transformed the nature of human-machine interaction due to natural language processing over time. This makes machines not only understand but also generate human-like texts. At the heart of their efficacy lies a vast representation of a knowledge storehouse encoded in the parameters. The … Read more