Massachusetts Institute of Technology - MIT News An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data
MIT researchers develop an efficient way to train more reliable AI . . . MIT researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability This could enable the leverage of reinforcement learning across a wide range of applications
“Periodic table of machine learning” could fuel AI discovery After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, MIT researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones
How we really judge AI - MIT News A new study finds people are more likely to approve of the use of AI in situations where its abilities are perceived as superior to humans’ and where personalization isn’t necessary
Helping nonexperts build advanced generative AI models Helping nonexperts build advanced generative AI models MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient
MIT researchers advance automated interpretability in AI models MAIA is a multimodal agent for neural network interpretability tasks developed at MIT CSAIL It uses a vision-language model as a backbone and equips it with tools for experimenting on other AI systems