The latest advancements in econometric modeling and hypothesis testing have signified a vital shift towards the incorporation of machine learning technologies. Even though progress has been made in estimating econometric models of human behaviour, there is still much research to be undertaken to enhance the efficiency in generating these models and their rigorous examination.
Academics from…
PyTorch recently launched the alpha version of its state-of-the-art solution, ExecuTorch, enabling the deployment of intricate machine learning models on resource-limited edge devices such as smartphones and wearables. Poor computational power and limited resources have traditionally hindered deploying such models on edge devices. PyTorch's ExecuTorch Alpha aims to bridge this gap, optimizing model execution on…
Advanced language models (LLMs) have significantly improved natural language understanding and are broadly applied in multiple areas. However, they can be sensitive to specific input prompts, prompting research into understanding this characteristic. Through exploring this behavior, prompts for learning tasks like zero-shot and in-context training are created. One such application, AutoPrompt, recognizes task-specific tokens to…
Gene editing, a vital aspect of modern biotechnology, allows scientists to precisely manipulate genetic material, which has potential applications in fields such as medicine and agriculture. The complexity of gene editing creates challenges in its design and execution process, necessitating deep scientific knowledge and careful planning to avoid adverse consequences. Existing gene editing research has…
Large Language Models (LLMs) are used in various applications, but high computational and memory demands lead to steep energy and financial costs when deployed to GPU servers. Research teams from FAIR, GenAI, and Reality Labs at Meta, the Universities of Toronto and Wisconsin-Madison, Carnegie Mellon University, and Dana-Farber Cancer Institute have been investigating the possibility…
Fine-tuning large language models (LLMs) is a crucial but often daunting task due to the resource and time-intensity of the operation. Existing tools may lack the functionality needed to handle these substantial tasks efficiently, particularly in relation to scalability and the ability to apply advanced optimization techniques across different hardware configurations.
In response, a new toolkit…
As parents, we try to select the perfect toys and learning tools by carefully matching child safety with enjoyment; in doing so, we often end up using search engines to find the right pick. However, search engines often provide non-specific results which aren't satisfactory.
Recognizing this, a team of researchers have devised an AI model named…
Advancements in large language models (LLMs) have greatly elevated natural language processing applications by delivering exceptional results in tasks like translation, question answering, and text summarization. However, LLMs grapple with a significant challenge, which is their slow inference speed that restricts their utility in real-time applications. This problem mainly arises due to memory bandwidth bottlenecks…
In this digital age, data has become a critical asset for businesses, driving strategic decision-making processes. However, the need to collaborate on data with external partners has increased the risk factors associated with security breaches and privacy concerns. Traditional data sharing methods entail the risk of sensitive data exposure, raising challenges to effectively manage and…
As the AI technology landscape advances, free online platforms to test large language models (LLMs) are proliferating. These 'playgrounds' offer developers, researchers, and enthusiasts a valuable resource to experiment with various models without needing extensive setup or investment.
LLMs, the cornerstone of contemporary AI applications, can be complex and resource-intensive, making them often inaccessible for individual…