How To Organize Continuous Delivery of ML/AI Systems: a 10-Stage Maturity Model | Outerbounds
outerbounds.com
How To Organize Continuous Delivery of ML/AI Systems: a 10-Stage Maturity Model | Outerbounds
the single most important metric for executives to focus on is time-to-value, which can be instrumented most easily as committing to deploy latency for each team. Many companies can’t innovate because they can’t get out of their own way, and short time-to-value (target less than a day) releases pent-up innovation from your teams. Third, there is fa
... See morePini Reznik • Cloud Native Transformation: Practical Patterns for Innovation
Scaling Without Losing Trust
As your AI system grows, you’ll inevitably face pressure to reduce the human effort involved in evaluation. This is where many teams go wrong – they automate too much, too quickly, and lose the human connection that keeps their evaluations grounded.
The most successful teams take a more measured approach:
As your AI system grows, you’ll inevitably face pressure to reduce the human effort involved in evaluation. This is where many teams go wrong – they automate too much, too quickly, and lose the human connection that keeps their evaluations grounded.
The most successful teams take a more measured approach:
- Start with high
Hamel Husain • A Field Guide to Rapidly Improving AI Products – Hamel’s Blog
Technology Infrastructure + Artificial Intelligence Is there a way to structure, pipe and manage data better?Are there ways to improve productivity given the information overload and noise we have in our work communication?Can we make access to information affordable?Can we assist in critical machine to machine communication?Can we make it easy to ... See more