I couldn’t agree more. The space of ML and MLOps is still at a very early stage, and unfortunately it feels as if organizations have to re-learn all the lessons from software development that were learnt the last 20 years. Tools have a great chance here to bridge the gap a bit more harmonious than what we’ve seen in classical software engineering.
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I couldn’t agree more. The space of ML and MLOps is still at a very early stage, and unfortunately it feels as if organizations have to re-learn all the lessons from software development that were learnt the last 20 years. Tools have a great chance here to bridge the gap a bit more harmonious than what we’ve seen in classical software engineering.