We need to stop treating our data like something to be stored and more like a mission critical supply lines.
Andrew Schoka spent his military career in offensive cyber, including stints in the Joint Operations Command and Cyber Command. Now he's building Hardshell to solve a problem most organizations don't even realize they have yet.
Here's the thing: AI is phenomenal at solving problems in places where data is incredibly sensitive. Healthcare, financial services, defense—these are exactly where AI could make the biggest impact. But there's a problem.
Your ML models have a funny habit of remembering training data exactly how it went in. Then regurgitating it. Which is great until it's someone's medical records or financial information or classified intelligence.
Andrew makes a crucial point: organizations still think of data as a byproduct of operations—something that goes into folders and filing cabinets. But with machine learning, data isn't a byproduct anymore. It's a critical supply line operating at speed and scale.
The question isn't whether your models will be targeted. It's whether you're protecting the data they train and interpret like the supply lines they actually are.
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