While approaches and capabilities differ, all of these databases allow you to build machine learning models right where your data resides. In my October 2022 article, “How to choose a cloud machine ...

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integral to database management, driving new levels of automation and intelligence in how data systems are administered. Modern ...

Built by the team behind Amazon SageMaker. Having attracted investment by Wing Venture Capital, with Wing’s Founding Partner and early Snowflake investor, Peter Wagner, joining startup Pinecone’s ...

A group of researchers are launching an open-source database of chemical synthesis procedures that they think will benefit artificial intelligence algorithms for reaction prediction, synthesis ...

Promising the best of both worlds, startup Splice Machine last week announced the latest stab at putting SQL on Hadoop, but this time it's a fully SQL-compliant and ACID-compliant relational database ...

A machine learning application's value is dependent on the quality of data used to train and deploy it. Organizations are responsible for creating or acquiring enough data, that this data is useful ...

Snowpark for Python gives data scientists a nice way to do DataFrame-style programming against the Snowflake data warehouse, including the ability to set up full-blown machine learning pipelines to ...

Pinecone, a new startup from the folks who helped launch Amazon SageMaker, has built a vector database that generates data in a specialized format to help build machine learning applications faster, ...

Data science brings several skills together. Python helps learners work with data programmatically, statistics provides a way to test assumptions and interpret uncertainty, and machine learning adds ...

A machine learning application's value is dependent on the quality of data used to train and deploy it. Organizations are responsible for creating or acquiring enough data, that this data is useful ...