Currently state estimation is very important for the robotics, and the uncertainty representation based Lie group is natural for the state estimation problem. It is necessary to exploit the geometry and kinematic of matrix Lie group sufficiently. Therefore, this note gives a detailed derivation of the recently proposed matrix Lie group $SE_K(3)$ for the first time, our results extend the results in Barfoot \cite{barfoot2017state}. Then we describe the situations where this group is suitable for state representation. We also have developed code based on Matlab framework for quickly implementing and testing.

While'data' might be the new oil, the'dataset' is the refined gasoline that powers every Machine Learning (ML) and AI operation. These datasets are used to boost signal, accuracy, precision, profit/loss, Sortino or Sharpe ratios in the financial markets and biosciences industries. The following is a transcript of a recent AMA hosted by ABT Crypto Academy on Telegram with the founder of Vectorspace AI, Kasian Franks. We're extremely privileged to be joined by Kasian Franks the CEO of Vectorspace, it's only right we start off with a brief introduction -- can you tell us what exactly Vectorspace is and how the idea came about? We got our start in Life Sciences, now most refer to it as Biosciences at Genentech and Lawrence Berkeley National Lab https://www.lbl.gov There we were tasked with creating a system to identify hidden relationships between genes, drugs and diseases connected to breast cancer, chromosomal radiation damage and extending human lifespan for the purpose of deep space travel. We wrote a paper with Micheal I. Jordan, teacher of Andrew Ng, who developed the first AI for Google and China's Baidu. "The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made f…" Human genes are like stocks or cryptos. Our technology is based on datasets.

We work in the area of specialized algorithms in ML/AI for Life Sciences and the financial markets.