Automated software engineering (ASE) has emerged as a transformative field, integrating artificial intelligence with software development processes to tackle debugging,…
Machine Learning
Large language models (LLMs) are AI systems trained on vast amounts of text data, enabling them to understand, generate, and…
Artificial intelligence (AI) models have made substantial progress over the last few years, but they continue to face critical challenges,…
This post is co-written with Lawrence Zorio III from Mark43. Public safety organizations face the challenge of accessing and analyzing vast…
Retrieval Augmented Generation (RAG) has become a crucial technique for improving the accuracy and relevance of AI-generated responses. The effectiveness…
Email remains a vital communication channel for business customers, especially in HR, where responding to inquiries can use up staff…
In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their…
This paper considers the learning of logical (Boolean) functions with a focus on the generalization on the unseen (GOTU) setting,…
This paper was accepted at the Self-Supervised Learning – Theory and Practice (SSLTP) Workshop at NeurIPS 2024. Image-based Joint-Embedding Predictive…
This paper was accepted at the Efficient Natural Language and Speech Processing (ENLSP) Workshop at NeurIPS 2024. Tensor parallelism provides…
Drug discovery is a costly, lengthy process with high failure rates, as only one viable drug typically emerges from a…
Large Language Models (LLMs) have advanced exponentially since the last decade. However, LLMs still need to improve regarding deployment and…
Foundation models (FMs) and large language models (LLMs) are revolutionizing AI applications by enabling tasks such as text summarization, real-time…
The rapid expansion of data in today’s era has brought with it both possibilities and difficulties. Businesses handle and use…
Effective lesson structuring remains a critical challenge in educational settings, particularly when conversations and tutoring sessions need to address predefined…
Log-based anomaly detection has become essential for improving software system reliability by identifying issues from log data. However, traditional deep…
Using large language models (LLMs) has revolutionized artificial intelligence applications, enabling breakthroughs in natural language processing tasks like conversational AI,…
Planning and decision-making in complex, partially observed environments is a significant challenge in embodied AI. Traditionally, embodied agents rely on…
Posted by Jason Jabbour, Kai Kleinbard and Vijay Janapa Reddi (Harvard University) Everyone wants to do the modeling work, but…
As companies of all sizes continue to build generative AI applications, the need for robust governance and control mechanisms becomes…