A fast and flexible approach to help doctors annotate medical scans | MIT News
To the untrained eye, a medical image like an MRI or X-ray appears to be a murky collection of black-and-white…
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Mixed-input matrix multiplication performance optimizations
AI-driven technologies are weaving themselves into the fabric of our daily routines, with the potential to enhance our access to…
Kyrgyzstan to King’s Cross: the star baker cooking up code
Company Published 26 May 2022 Today we caught up with Aliya Rysbek, a software engineer on the Platform team. She…
From Computation to Comprehension: Metacognitive Insights in LLM-based Mathematical Problem Solving
Large language models (LLMs) have demonstrated remarkable reasoning capabilities across various domains. But do they also possess metacognitive knowledge –…
First AI + Education Summit is an international push for “AI fluency” | MIT News
This summer, 350 participants came to MIT to dive into a question that is, so far, outpacing answers: How can…
MobileDiffusion: Rapid text-to-image generation on-device
Text-to-image diffusion models have shown exceptional capabilities in generating high-quality images from text prompts. However, leading models feature billions of…
BYOL-Explore: Exploration with Bootstrapped Prediction
Research Published 20 June 2022 Authors Zhaohan Daniel Guo, Shantanu Thakoor, Miruna Pîslar, Bernardo Avila Pires, Florent Altché, Corentin Tallec,…
MuMA-ToM: A Multimodal Benchmark for Advancing Multi-Agent Theory of Mind Reasoning in AI
Understanding social interactions in complex real-world settings requires deep mental reasoning to infer the underlying mental states driving these interactions,…
Study: Transparency is often lacking in datasets used to train large language models | MIT News
In order to train more powerful large language models, researchers use vast dataset collections that blend diverse data from thousands…
Intervening on early readouts for mitigating spurious features and simplicity bi
Machine learning models in the real world are often trained on limited data that may contain unintended statistical biases. For…