The new open-source IBM Cloud-Native Toolkit is the focus of this week's automation tales. This solution is for individuals who want to integrate and execute AI and machine learning technologies in cloud environments. Codex, a deep learning model that generates software source code, has been revealed by OpenAI. One of the most compelling reasons to adopt a public workspace is to improve developer onboarding by shortening the time to first call (TTFC), the most essential measure for a public API. While Elon Musk's brain-chip company messes around with gaming monkeys, another group of researchers has achieved a major milestone in neuroprosthetics: allowing a man who can't talk to form sentences with his mind.

The tool is designed for those looking to integrate and run AI and ML technologies across cloud environments. IBM is announcing a new addition to its open-source Cloud-Native Toolkit that will allow developers to integrate their AI and ML applications "to cloud-native environments and optimize scalable, reliable deployments." Saishruthi Swaminathan, Carlos Santana and Sepideh Seifzadeh -- members of the IBM Center for Open-Source Data & AI Technologies team -- explained the effort in a blog post, noting that it was becoming necessary to integrate and run AI and ML technologies across cloud environments. Last year, the team released the Elyra AI toolkit and said the latest launch is a machine-learning, end-to-end pipeline starter kit within the Cloud-Native Toolkit. "Using critical hybrid cloud capabilities including open source and Red Hat OpenShift, developers can use the new toolkit as a starting point to transition their ML and AI-powered applications from Jupyter notebooks to production environments," the IBM team wrote.