Thriving in an exponential world requires more than a better strategy. It demands quantum thinking, the shift from linear ...

Penny Liang's book, "Understanding Large Models for Humanities Students (1.0)," explains the core technologies of large ...

"Corporate philanthropy has acted as a force multiplier to build ecosystems. They have invested in strengthening ...

In today's machine learning field, deep neural network models are becoming increasingly large and complex, posing significant challenges to traditional electronic computing hardware. To address this ...

Peter Routledge (pictured), superintendent of financial institutions at OSFI, emphasized that while climate change is ...

ORNL and partners are using HPC to study quantum materials outside equilibrium, aiming to inform future quantum computing ...

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...

Instead of bending a training-centric design, we must start with a clean sheet and apply a new set of rules tailored to ...

In 1999, one of us (Morin) introduced the term "polycrisis" to describe the web of interconnected catastrophes threatening ...

Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the ...

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.