MIT

Nothing great is easy

Research shows AI systems offer better measurability than human decisions, while GBS algorithm studies reveal specific cases where human expertise remains vital.

The method uses machine learning to compute mathematical variances revealing gene influences, analyzing relationships layer by layer to identify regulatory groups.

"MIT tests show LLMs fail at NYC navigation when 1% of streets close. Internal maps reveal imagined streets and impossible layouts despite high performance."

"MIT's ICSR Data Hub stores police data from 40 major US cities, using AWS to study systemic racism's patterns through machine learning analysis."

New MIT postdoc programme pairs AI experts with mentors in biology, physics, music & more, funded by $20M Tayebati gift to advance cross-disciplinary AI applications.

"HPT unifies 200,000+ robot trajectories across 52 datasets, processing vision and proprioception inputs equally, improving performance by 20% in real tests"

Universities collaborate on DARPA-funded AI tools for turbomachinery design. The project aims to optimise shape and material composition for aerospace components.

MIT team uses AI to improve simulation accuracy. New MPMC method with graph neural networks enhances data distribution in complex spaces.

MIT's 'Future You' AI system enables users to converse with simulated 60-year-old selves, aiming to reduce anxiety and improve long-term decision-making.

MIT create a dataset of 5,000 'illusory' faces, revealing differences between human and AI face detection and potential links to animal face recognition.

MIT's Clio enables robots to map scenes and identify task-relevant objects using natural language prompts, combining computer vision, language models, and mapping tools.

MIT researchers use AI to estimate particle size 60x faster in pharma manufacturing, reducing analysis time from 15 to 0.25 seconds.

Researchers propose labelling AI systems in healthcare with usage info, including training time, data origin, intended use, biases, and warnings.

MIT study: AI models in home surveillance inconsistently detect crime, recommend police calls, and show demographic biases in decision-making