With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
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National Science Foundation (NSF)
A new generative AI approach to predicting chemical reactions
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Read MoreMIT tool visualizes and edits “physically impossible” objects
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
Read MoreThis new approach could lead to enhanced AI models for drug and materials discovery.
Read MoreThe unique, mathematical shortcuts language models use to predict dynamic scenarios
Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.
Read MoreA team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.
Read MoreResearchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Read MoreDeveloped to analyze new semiconductors, the system could streamline the development of more powerful solar panels.
Read MoreUnpacking the bias of large language models
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
Read MorePhotonic processor could streamline 6G wireless signal processing
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
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