Helping data storage keep up with the AI revolution
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
This new approach could lead to enhanced AI models for drug and materials discovery.
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.
The CodeSteer system could boost large language models’ accuracy when solving complex problems, such as scheduling shipments in a supply chain.
A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Developed to analyze new semiconductors, the system could streamline the development of more powerful solar panels.
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.