State-of-the-art recommendation systems in online marketplaces struggle with providing nuanced item relationships. Contextually relevant item pairs can have confusing or controversial relationships that may negatively impact user experiences and brand perception. For instance, *

The Biden administration is set to release a comprehensive AI executive order on October 30th. The order will focus on areas such as immigration, safety, and the consolidation of the tech industry. It aims to ensure thorough assessments of advanced AI models before deployment, lower barriers to entry for skilled workers, and enhance national cyber…

In this paper, the researchers study how to improve the accuracy of device-directed speech detection (DDSD) systems, which distinguish between voice assistant queries and side conversations or background speech. They explore fusion schemes to make the systems more robust when some of the verbal cues are unavailable in real-world settings.

Researchers have developed FANToM, a benchmark to evaluate large language models’ (LLMs) understanding of Theory of Mind (ToM). ToM is the ability to attribute beliefs and perspectives to oneself and others. FANToM tests LLMs’ knowledge of others’ beliefs in dynamic scenarios. Results show that current LLMs struggle with maintaining a consistent ToM, highlighting the limitations…

This article provides a step-by-step guide on how to create compelling line charts using Matplotlib. The author explores various techniques to enhance the visual appeal and readability of the charts. The article includes code snippets and examples to illustrate the concepts. The final result is a professional-looking line chart that effectively tells a story. The…

Numerical weather prediction (NWP) has played a crucial role in economic planning and saving lives through accurate weather forecasts. Improvements in computational power, parameterization, and data assimilation have enhanced weather forecasting. Data-driven deep learning models have gained popularity due to their low processing costs and ability to generate large ensembles. However, these models must improve…

Here is a summary of the text: Non-profit researchers have made several advancements in artificial intelligence (AI) in 2023. These include methods like ALiBi and Scaling Laws of RoPE-based Extrapolation, which improve the extrapolation capabilities of AI models. Other advancements include FlashAttention for training transformers faster, Branchformer for speech processing, Latent Diffusion Models for image…

A team of researchers from UC Berkeley, UCL, CMU, and Google Deepmind propose a solution for optimizing large language models using composite reward models. They address the issue of over-optimization by using constrained reinforcement learning and dynamic weighting. The study highlights the importance of considering correlation and proper weighting among reward models. Future research should…