What to do with AI-intruders.

Listen to what Matilde Sánchez Conde, an Infectious Disease physician tells me in an email:

It bothers me that I think I’ve been a little ahead of all this, wanting to do things like defining the fragility model for more than 10 years now…it’s now the bandwagon everyone’s jumping on, and despite having a clear understanding of it from the beginning, I’ve never been able to get funding for anything in this line. At first, nobody understood it, and now everyone’s an expert.


That’s right, dear internet friend.

Matilde is suffering… (drumroll…) the innovator’s dilemma.

There’s a very famous book on the subject.


But this book can be summarized quickly.


The idea is that when you come with something very new, nobody will pay attention.

And, as technology is exponential, when it explodes, it will do so suddenly.

And then everyone is into it, talking about it, and acting like an expert.


And that poor innovator, ignored for a decade, feels frustrated and powerless because their ahead-of-their-time initiative is diluted in the excited mass.


If you’re reading these emails, it’s probably happened to you.

And it may have happened to you with AI.


Well, I’ll tell you something. And you know I’m not one to sugarcoat things.

It’s not a big deal.

Nothing at all. Just relax.


Because those who are jumping on the AI trend, but were in the Metaverse yesterday and will be in genomics-at-home tomorrow (which is probably the next big thing), are harmless.

Because their manifest lack of depth won’t take them anywhere.

To do an AI project that’s worthwhile, it’s not enough to copy and paste ideas.

You have to understand what’s going on behind the scenes.

Why it’s happening.


Why one algorithm is more relevant than another.

Or how often it needs to be retrained.

Or if the question is clustering or stratifying the risk.


You don’t acquire that knowledge by reading news.

You learn it over the years, by proposing studies and making mistakes.

That will protect you from any intruder.


Just ask three questions, three, and you’ll know if the person behind it really knows why machine learning is completely changing medical research.

And that, precisely that, is what we’re going to take away when we do a project together here.


What are the 3 questions? Here.

Complete the info, and a KAM will contact you ASAP:

Want to use it?:

Start with your proposed AI + RWE use case:

This is the first step for AI + RWE: