Google AI has introduced a new spoken language model called “Spectron” that processes spectrograms as both input and output. Spectrograms are visual representations of the spectrum of frequencies of a signal. The model uses pre-trained encoders and decoders to transcribe and generate text and speech continuations, improving the quality of synthesized speech. However, the model…

Apple researchers have introduced Matryoshka Diffusion Models (MDM), a family of diffusion models designed for high-resolution image and video synthesis. MDM utilizes a Nested UNet architecture in a multi-resolution diffusion process to process and produce images with varying levels of detail. The training plan progresses gradually to higher resolutions, demonstrating robust zero-shot generalization and high-quality…

This text discusses the installation and use of Rook Ceph as a replicated storage class for Kubernetes clusters. It provides step-by-step instructions on how to deploy Rook Ceph, create storage classes, deploy a file-sharing app, and test the resiliency of the storage solution. The article concludes by highlighting the scalability and reliability of Rook Ceph…

This article discusses the evolution of Large Language Models (LLMs) for code, from RNNs to Transformers. It covers the development of models like Code2Vec, CodeBERT, Codex, CodeT5, PLBART, and the latest model, Code Llama. These models have advanced code understanding and generation tasks, improving programming efficiency.

Researchers from Tsinghua University and Zhipu.AI have released an open-source bilingual language model called GLM-130B with 130B parameters. GLM-130B outperforms GPT-3 and PaLM on various benchmarks, achieving a zero-shot accuracy of 80.2% on LAMBADA. The researchers also shared their training process and experiences, highlighting their commitment to transparency in language model development.

According to an academic, Artificial Intelligence (AI) and algorithms have the potential to fuel racism, political instability, polarization, and radicalization. These technologies, which are not limited to national security agencies, can contribute to political violence and pose a threat to national security.

The HUB framework, developed by researchers from UC Berkeley and Stanford, addresses the challenge of integrating human feedback into reinforcement learning systems. It introduces a structured approach to teacher selection, actively querying teachers to enhance the accuracy of utility function estimation. The framework has shown promise in real-world domains such as paper recommendations and COVID-19…

A physical neural network has achieved a milestone in machine intelligence by learning and retaining information in a manner similar to human brain neurons. This breakthrough paves the way for the development of efficient and low-energy machine intelligence for complex real-world learning and memory tasks.

Large language models (LLMs) have gained popularity in the AI community as they are seen as a step towards artificial general intelligence (AGI). However, LLMs have limitations, such as dependence on unstructured text and difficulty integrating new knowledge. Researchers are exploring the use of graph-structured data to address these issues. Google Research has conducted investigations…

MATHVISTA is a benchmark to assess the mathematical reasoning abilities of Large Language Models and Large Multimodal Models within visual contexts. It combines various mathematical and graphical tasks and includes existing and new datasets. The benchmark reveals a performance gap compared to humans and emphasizes the need for further advancement in AI agents with mathematical…