This video will teach you how you can launch a Ubuntu instance on Google Vertex AI, which embodies the AI/ML tools you need for training LLM.

AI is at the heart of a revolution in the technology space. Organisations from all industries are looking for ways to put AI to work. Once they have finalised use case assessment, their next question is typically related to the environment they will use to develop and deploy their AI initiatives. They often prefer the public clouds as an initial environment, because of the computing power and ability to scale as projects mature. In addition to the infrastructure, enterprises need software where they can develop and deploy the machine learning models.

Weka report from 2024 showed that 47% of respondents will use the public cloud as the primary place to develop their machine learning projects. This is a result of a correlation of factors which include the need for compute power, easy scalability, and the ability to utilise existing infrastructure already in place on both hybrid clouds and public clouds. Join us to talk more about AI on the public cloud: what are the main benefits and what are the best practices an organisation could implement in order to easier adopt AI and leverage the most the public clouds.