Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
Why AI Systems Forget
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One of the most frustrating things about working with AI is when you get to the point where it seems like Claude or ChatGPT or your AI tool of choice really understands you and the way you work - and then all of a sudden it doesn’t. It’s like training a new graduate to be useful at their job, only to be told they’ve moved to another role and you have to start again, training someone else. This is annoying enough when dealing with AI chatbots. But, when building AI systems, it can be catastrophic. The reason it happens comes down to memory. Specifically, how AI agents store, retrieve and forget information. And it turns out there are three distinct types of memory every AI agent needs, each serving a different purpose. In the latest Value Boost episode of Value Driven Data Science, Dr Imran Ahmad, author of 30 Agents Every AI Engineer Must Build, joins me to explain what memory actually means in AI agents and what data scientists need to understand to build systems that actually remember what matters. In just 12 minutes, you’ll discover:
Getting memory wrong in an AI chatbot is frustrating. Getting it wrong in an AI system can be catastrophic. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 128: The Three Types of Memory Every AI Agent Needs Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
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