Merging design and computer science in creative ways
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
Artificial intelligence enhances air mobility planning
Lincoln Laboratory is transitioning tools to the 618th Air Operations Center to streamline global transport logistics.
Training LLMs to self-detoxify their language
A new method from the MIT-IBM Watson AI Lab helps large language models to steer their own responses toward safer, more ethical, value-aligned outputs.
Teaching a robot its limits, to complete open-ended tasks safely
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
Study: Browsing negative content online makes mental health struggles worse
Researchers have developed a web plug-in to help those looking to protect their mental health make more informed decisions.
Using ideas from game theory to improve the reliability of language models
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
Natural language boosts LLM performance in coding, planning, and robotics
Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.
Three from MIT awarded 2024 Guggenheim Fellowships
MIT professors Roger Levy, Tracy Slatyer, and Martin Wainwright appointed to the 2024 class of “trail-blazing fellows.”
3 Questions: What you need to know about audio deepfakes
MIT CSAIL postdoc Nauman Dawalatabad explores ethical considerations, challenges in spear-phishing defense, and the optimistic future of AI-created voices across various sectors.
Reasoning and reliability in AI
PhD students interning with the MIT-IBM Watson AI Lab look to improve natural language usage.
Leveraging language to understand machines
Master’s students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
Using language to give robots a better grasp of an open-ended world
By blending 2D images with foundation models to build 3D feature fields, a new MIT method helps robots understand and manipulate nearby objects with open-ended language prompts.
Re-imagining our theories of language
Department of Brain and Cognitive Sciences faculty members Ev Fedorenko, Ted Gibson, and Roger Levy believe they can answer a fundamental question: What is the purpose of language?
MIT researchers make language models scalable self-learners
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
3 Questions: Jacob Andreas on large language models
The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.