Google DeepMind's new report maps four pathways from AGI to artificial superintelligence. Here's how scaling, paradigm shifts ...

You may have already seen "AutoResearch" released by Andrej Karpathy yesterday. It is another interesting experiment: research agents training on a single-GPU implementation of nanoGPT. In this ...

Energy prediction is significant for modern power grids, ensuring their efficient operation, mitigating instability, and optimizing resource allocation and renewable energy source integration 1. In ...

Code for the paper "Generating realistic neurophysiological time series with denoising diffusion probabilistic models", (2024). The repository contains all the scripts to run the experiments presented ...

Hyperparameter tuning is a critical step in optimizing machine learning models for optimal performance. It involves selecting the best combination of hyperparameters, such as regularization strength, ...

“Capabilities like AutoGen are poised to fundamentally transform and extend what large language models are capable of. This is one of the most exciting developments I have seen in AI recently.” Doug ...

Structural topology optimization (TO) methods are computational techniques which optimize the distribution of a given material within a specified design space based on boundary and initial conditions, ...

CPA is a framework to learn the effects of perturbations at the single-cell level. CPA encodes and learns phenotypic drug responses across different cell types, doses, and combinations. CPA allows: ...

For example, the embedding matrix in a language model is of size vocabsize x width. While the width tends to infinity, vocabsize stays constant and finite. During matrix multiplication, the difference ...