MIT welcomes David Siegel SM ’86, PhD ’91 as its next Innovation Fellow
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
More from the blog
MIT students gain a humanist lens on technical innovation in Tulsa, Oklahoma
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
The promise and peril of using visual AI to study cities
In their new book, “How AI Sees the City,” the leaders of MIT’s Senseable City Lab examine the technology’s implications for researching urban life.
Poitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders research
Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.
A new chapter for MIT Reads
A new focus on fiction and memoir aims to help the MIT community celebrate the power of storytelling and strengthen social connection.
Related papers
ECCOLA - a Method for Implementing Ethically Aligned AI Systems
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
AI-powered Code Review with LLMs: Early Results
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
LLM-based agents for automating the enhancement of user story quality: An early report
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
System for systematic literature review using multiple AI agents: Concept and an empirical evaluation
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.