A.I.’s First Big Math Breakthrough Is Not What It Seems

Last month, OpenAI announced that its latest version of ChatGPT had solved a major math problem, one that had stumped experts ...
MIT Technology Review

A startup claims it broke through a bottleneck that’s holding back LLMs

The Miami-based AI startup Subquadratic came out of stealth mode last month with a huge claim. It announced that it had ...
GitHub

CPA - Compositional Perturbation Autoencoder

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: ...
GitHub

ESCHR: A hyperparameter-randomized ensemble approach for robust clustering across diverse datasets

This example jupyter notebook on Google Colab provides a walkthrough of ESCHR analysis using an example scRNA-seq dataset. If you launch the notebook in Google Colab ...
Microsoft

AutoGen: Enabling next-generation large language model applications

“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 ...
Nature

Learning hyperparameter predictors for similarity-based multidisciplinary topology optimization

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, ...
Nature

Taming hyperparameter tuning in continuous normalizing flows using the JKO scheme

$$\begin{aligned} \log \rho _0(x) = \log \rho _1\left( f(x)\right) + \log |\det J_f(x)|, \end{aligned}$$ $$\begin{aligned} \min _{\theta }~ \mathbb {E}_{x \sim \rho ...