Google Cloud has launched an exciting new initiative in a bid to democratise AI. In theory, the AI Hub should make it easier for more companies to take advantage of machine learning capabilities.
At present, only a handful of businesses have access to the talent and budgets required for ML and AI. Moreover, only a limited number of people can create advanced machine learning models.
Making AI simpler
According to a recent KPMG study, the majority of global leaders expect AI to drive business growth over the next three years. Despite this, Google said “the scarcity of ML knowledge in the workforce made it challenging to build a comprehensive resource.”
The AI Hub was created in order to address this. According to Google, it is “a one-stop destination for plug-and-play ML content, including pipelines, Jupyter notebooks, TensorFlow modules, and more.”
In addition to this, the hub provides ML resources developed by Google Cloud AI, Google Research and other teams across Google. It also provides a private, secure hub for enterprises to upload and share ML resources.
As a result, businesses can reuse pipelines and deploy them to production in GCP or on hybrid infrastructures using the Kubeflow Pipeline system. In alpha, the AI Hub will provide these Google-developed resources and private sharing controls.
In beta, these capabilities will expand. These will include more asset types and a wider range or public content, including partner solutions.
Microsoft AI Academy
Microsoft have also announced that it will be launching two new training programs to boost AI skills. The initiative aims to rectify the shortage of AI-related skills in businesses and universities across the UK.
The first of the two programs is Microsoft AI Academy. Microsoft’s program will conduct face-to-face and online training sessions aimed at enterprise and public-sector execs, IT professionals, developers, and startups.
According to Google, there are approximately 20 million developers worldwide but only 2 million data scientists. Google and Microsoft’s effort to provide the tools required to help data scientists scale their efforts will hopefully make AI faster, simpler, and more useful.