Stanford University researchers have introduced MLAgentBench, the first benchmark of its kind, to evaluate AI research agents with free-form decision-making capabilities. The framework allows agents to execute research tasks similar to human researchers, collecting data on proficiency, reasoning and research process, and efficiency. The team is working to expand the task collection to include various…

GPT-4 was tested in various experiments to solve math problems in 16 different languages.

Neural Radiance Fields (NeRF) is a neural network-based technique for capturing 3D scenes and objects from 2D images or sparse 3D data. It consists of two main components, “NeRF in” and “NeRF out” network. NeRF-based human representations have applications in gaming, virtual reality, animation, film production, and medical imaging. ActorsNeRF is a category-level human actor…

Learn how to master SVM, a versatile model that every data scientist should have in their toolbox. Get a hands-on introduction to SVM in this informative article on Towards Data Science.

The text discusses the introduction of a new interpretable model by Meta AI, with further information available in the article on Towards Data Science.

Researchers have developed an open-source library in JAX for deep learning on spherical surfaces. This new approach, utilizing spherical convolution and cross-correlation operations, shows promise in addressing challenges related to predicting chemical properties and understanding climate states. The models outperform traditional CNNs in weather forecasting benchmarks and exhibit exceptional performance across various scenarios. The study…

Mistral-7B-v0.1 is a cutting-edge large language model (LLM) developed by Mistral AI. With 7 billion parameters, it is one of the most powerful LLMs available. This transformer model excels in natural language processing tasks such as generating text, translating languages, and answering questions. It performs well on benchmarks like GLUE, SQuAD, and SuperGLUE. Mistral-7B-v0.1 has…

AI language models have been used by scientists to create new tools for analyzing speech patterns in patients with schizophrenia, allowing them to identify subtle signatures.

Researchers from the University of Manchester have introduced MentalLLaMA, the first open-source series of large language models (LLMs) for interpretable mental health analysis. These models, including MentalLLaMA-chat-13B, outperform state-of-the-art techniques in terms of predictive accuracy and the quality of generated explanations. The researchers also created the Interpretable Mental Health Instruction (IMHI) dataset, which serves as…

Undersampling techniques are used to address class imbalance in data. There are two main categories of undersampling: controlled and uncontrolled. Controlled techniques involve selecting a specific number of samples, while uncontrolled techniques remove points that meet certain conditions. Some examples of controlled and uncontrolled undersampling methods include random undersampling, k-means undersampling, Tomek Links undersampling, and…