Generative Artificial Intelligence (AI) is commanding conversations these days, a never-before-seen system that’s captured many millions of users since its debut in November 2022. A machine learning innovation that creates content of all kinds (and that’s just the beginning), generative AI also comes up with new product designs and optimizes business processes. We have only begun to exploit and understand this disruption.

Selecting a build system is an essential decision when creating a project. Changing is always painful, especially in a mature repository. Therefore the choice should be made carefully. With this article, I will try to describe a few advantages of what Bazel can provide in the context of an embedded repository and show how to set up a build environment with a cross compiler from scratch.

Generative AI projects like ChatGPT have motivated enterprises to rethink their AI strategy and make it a priority. In a report published by PwC, 72% of respondents said they were confident in the ROI of artificial intelligence. More than half of respondents also state that their AI projects are compliant with applicable regulations (57%) and protect systems from cyber attacks, threats or manipulations (55%). Production-grade AI initiatives are not an easy task.

Earlier this month, we released the first version of our new natural language querying interface, Query Assistant. People are using it in all kinds of interesting ways! We’ll have a post that really dives into that soon. However, I want to talk about something else first. There’s a lot of hype around AI, and in particular, Large Language Models (LLMs).