Skip to content Skip to sidebar Skip to footer

This AI Paper Proposes a NeRF-based Mapping Method that Enables Higher-Quality Reconstruction and Real-Time Capability Even on Edge Computers

In this paper, researchers have introduced a NeRF-based mapping method called H2-Mapping, aimed at addressing the need for high-quality, dense maps in real-time applications, such as robotics, AR/VR, and digital twins. The key problem they tackle is the efficient generation of detailed maps in real-time, particularly on edge computers with limited computational power. They highlight…

Read More

Using AI to fight climate change

How we’re applying the latest AI developments to help fight climate change and build a more sustainable, low-carbon world AI is a powerful technology that will transform our future, so how can we best apply it to help combat climate change and find sustainable solutions? Our climate & sustainability lead, Sims Witherspoon, who recently spoke…

Read More

Please Use Streaming Workload to Benchmark Vector Databases | by Eric Zhù | Dec, 2023

Why static workload is insufficient and what I learned by comparing HNSWLIB and DiskANN using streaming workload Image by DALLE-3Vector databases are built for high-dimensional vector retrieval. Today, many vectors are embeddings generated by deep neural nets like GPTs and CLIP to represent data points such as pieces of text, images, or audio tracks. Embeddings…

Read More

Meet GROOT: A Robust Imitation Learning Framework for Vision-Based Manipulation with Object-Centric 3D Priors and Adaptive Policy Generalization

With the increase in the popularity and use cases of Artificial Intelligence, Imitation learning (IL) has shown to be a successful technique for teaching neural network-based visuomotor strategies to perform intricate manipulation tasks. The problem of building robots that can do a wide variety of manipulation tasks has long plagued the robotics community. Robots face…

Read More