Generative models aim to replicate realistic outcomes across various contexts, from text generation to visual effects. While much progress has been made in creating real-world simulators, the ...

In a new paper NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models, an NVIDIA research team introduces NV-Embed. This generalist embedding model significantly boosts the ...

One of the major challenges in modern scientific research is finding effective ways to model, interpret, and utilize data collected from diverse sources to drive new discoveries. As scientific ...

Recent advancements in large language models (LLMs) have generated enthusiasm about their potential to accelerate scientific innovation. Many studies have proposed research agents that can ...

A research team presents SciAgents which aims to automate the process of scientific discovery by revealing hidden interdisciplinary relationships that traditional research methods often overlook.

In a new paper A Generalist Learner for Multifaceted Medical Image Interpretation, a research team proposes MedVersa, a generalist AI model designed to enable flexible learning and tasking for medical ...

In recent years, substantial progress has been made in generating photorealistic human representations in both 2D and 3D, thanks to advancements in the precise estimation of various visual assets.

Leading Graph Database company Neo4j organized GraphConnect 2018 on September 20 in New York City to introduce their latest products and developments — foremost among them the new Neo4j 3.5 Graph ...

The rapid progress of large language models (LLMs) has greatly influenced natural language processing (NLP), driving advancements across numerous applications. However, LLM training is typically ...

Large Language Model (LLM) providers often build entire families of models from scratch, each varying in size. However, training multiple multi-billion-parameter models from the ground up is highly ...