Vectorspace AI (VXV) announces datasets that power data engineering, machine learning (ML) and artificial intelligence (AI) systems. Vectorspace AI alternative datasets are designed for predicting unique hidden relationships between objects including current and future price correlations between equities.
Vectorspace AI enables data, ML and Natural Language Processing/Understanding (NLP/NLU) engineers and scientists to save time by testing a hypothesis or running experiments faster to achieve an improvement in bottom-line revenue and information discovery. Vectorspace AI datasets underpin most of ML and AI by improving returns from R&D divisions of any company in discovering hidden relationships in drug development.
“We are happy to be working with Vectorspace AI based on their most recent collaboration with us based on the article we published titled ‘Generating and visualizing alpha with Vectorspace AI datasets and Canvas’. They represent the tip of the spear when it comes to advances in machine learning and artificial intelligence. Our customers and partners will certainly benefit from our continued joint development efforts in ML and AI,” Shaun McGough, Product Engineering, Elastic.
Increasing the speed of discovery in every industry remains the aim of Vectorspace AI, along with a particular goal that relates to engineering machines to trade information with one another, connected to exchanging and transacting data in a way that minimizes a selected loss function. Data vendors such as Neudata.co, asset management companies and hedge funds including WorldQuant, use Vectorspace AI datasets to improve and protect ‘alpha’.