Modern-day LLMs are "fiction machines," designed not to be truthful but to make sense. What can we expect from these machines, and what are their limitations?

There are three common problems people face when working with AI: not understanding how AI made a decision (opacity), the human in the loop becoming over-reliant on AI and falling asleep at the wheel ...

A new technical paper, “Towards Structured Training and Validation of AI-based Systems with Digital Twin Scenarios,” was ...

Generative AI works a lot like fossil fuels “work”—narrowly, intermittently, and with a lot of nasty side effects.

Numerical modeling of ore-forming dynamics and 3D mineral prospectivity modeling are pivotal for deep mineral exploration, though each has inherent constraints. Commercial software such as FIDAP and ...

Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Multiphysics simulation allows engineers to evaluate complex interactions in a single environment, reducing the need for physical prototypes. In healthcare, simulation helped design electromagnetic ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine learning has proven to be very powerful for predicting mutation effects in ...

Using data from ten healthy adults, we trained a Gradient Boosting (GB) surrogate model to predict normalized metabolic cost as a function of Peak Magnitude and End ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Free energy perturbation (FEP) methods are among the most accurate tools in ...