AI

Meetings play a crucial role in decision-making, project coordination, and collaboration, and remote meetings are common across many organizations. However, capturing and structuring key takeaways from these conversations is often inefficient and inconsistent. Manually summarizing meetings or extracting action items requires significant effort and is prone to omissions or misinterpretations. Large language models (LLMs) offer […]

Developing robust text-to-SQL capabilities is a critical challenge in the field of natural language processing (NLP) and database management. The complexity of NLP and database management increases in this field, particularly while dealing with complex queries and database structures. In this post, we introduce a straightforward but powerful solution with accompanying code to text-to-SQL using

In this post, we explore how generative AI can revolutionize threat modeling practices by automating vulnerability identification, generating comprehensive attack scenarios, and providing contextual mitigation strategies. Unlike previous automation attempts that struggled with the creative and contextual aspects of threat analysis, generative AI overcomes these limitations through its ability to understand complex system relationships, reason

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

Traditional and indie authors are flooding #WritersTok with videos of them editing their manuscripts to refute accusations of generative AI use—and bring readers into their very human process.

MIT Morningside Academy for Design (MAD) Fellow Caitlin Morris is an architect, artist, researcher, and educator who has studied psychology and used online learning tools to teach herself coding and other skills. She’s a soft-spoken observer, with a keen interest in how people use space and respond to their environments. Combining her observational skills with active community engagement,

During his first year at MIT in 2021, Matthew Caren ’25 received an intriguing email inviting students to apply to become members of the MIT Schwarzman College of Computing’s (SCC) Undergraduate Advisory Group (UAG). He immediately shot off an application. Caren is a jazz musician who majored in computer science and engineering, and minored in music

Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document or conversation, while neglecting the middle. This “position bias” means that, if a lawyer is using an LLM-powered virtual assistant to retrieve a certain phrase in a 30-page affidavit, the LLM is more likely to

This post is co-written with Vicky Andonova and Jonathan Karon from Anomalo. Generative AI has rapidly evolved from a novelty to a powerful driver of innovation. From summarizing complex legal documents to powering advanced chat-based assistants, AI capabilities are expanding at an increasing pace. While large language models (LLMs) continue to push new boundaries, quality