By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
Category: Human-computer interaction
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AI simulation gives people a glimpse of their potential future self
By enabling users to chat with an older version of themselves, Future You is aimed at reducing anxiety and guiding young people to make better choices.
Study: Transparency is often lacking in datasets used to train large language models
Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
First AI + Education Summit is an international push for “AI fluency”
The three-day, hands-on conference hosted by the MIT RAISE Initiative welcomed youths and adults from nearly 30 countries.
Study: When allocating scarce resources with AI, randomization can improve fairness
Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.
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.