Mixture-of-Experts (MoE) efficiently trains large models by using sparse activation to lower costs, selecting a few experts based on data characteristics. However, it faces challenges such as ...

CpGPT: a Foundation Model for DNA Methylation. Contribute to lcamillo/CpGPT development by creating an account on GitHub.

Epistemic uncertainty measures what your model doesn't know due to lack of training data. It can be explained away with infinite training data. Think of epistemic uncertainty as model uncertainty. An ...

Photovoltaic (PV) power forecasting is important for promoting the integration of renewable energy sources. However, neural network-based methods, particularly deep learning for PV power forecasting, ...

VERSES AI says its robotics model outperformed current methods on Meta's Habitat Benchmark without needing a lot of data.

Training large-scale artificial intelligence models used to power many modern applications are driving a surge in electricity demand, a new report said. The report from ESPR and Epoch AI said training ...

Ultimately, CNRS@CREATE is not just a research hub – it’s a blueprint for how international partnerships can deliver meaningful change.

Electricity needed to train large AI models is more than doubling each year and could require as much power as some cities within a few years, researchers said.