Oct 27, 2026 · 33 min · 10 segments
Vitallog.AI is using AI Native that embeds the artificial intelligence directly in the firmware as compared to AI enabled which essentially bolts on the AI to existing firmware.
Jim HerlihyHostMark ThompsonGuestTy BaughGuest
Well, let's start with the genesis of Vitalog.ai. And first things first, please give us a definition and walk us through the difference between AI-native and AI-enabled.
So I'll give you a simple way to kind of think about this is that AI native is sort of like if you're a native English speaker versus a non-native speaker.
And so when it's designed from the get go with AI in mind, it's like an English speaker.
It's not that if you, you can add AI to anything and it's not that they won't be able to communicate just like you can meet someone from another country and probably understand them.
And the problem is that you just end up, the AI is far more likely to make mistakes, the same way you do when you're hearing them and maybe they say the wrong word and maybe you hear it a different way.
So that's really the kind of foundational difference is that we've designed this to be native speaking to AIs.
People can use it, everything else, but AIs, it's just, you know, chef's kiss.
Now, one of the questions that I have when you say making mistakes, obviously we all make mistakes and we've all been very impressed with the rollout of AI in the last couple of years.
But from time to time, we've all experienced hallucinations and where AI gets it wrong.
So are you telling me that with AI native, there's less of a likelihood of hallucinations than there would be with the AI bolt-on model?
It's just that all of these things add up to make it far less and less likely to occur.
And so each one of these barriers is just, as you take it out of the equation, now you just get better and better results.
Well, particularly when you're dealing with medtech, medical devices, healthcare, etc.
Well, let's start with the genesis of Vitalog.ai. And first things first, please give us a definition and walk us through the difference between AI-native and AI-enabled.
So I'll give you a simple way to kind of think about this is that AI native is sort of like if you're a native English speaker versus a non-native speaker.
And so when it's designed from the get go with AI in mind, it's like an English speaker.
It's not that if you, you can add AI to anything and it's not that they won't be able to communicate just like you can meet someone from another country and probably understand them.
And the problem is that you just end up, the AI is far more likely to make mistakes, the same way you do when you're hearing them and maybe they say the wrong word and maybe you hear it a different way.
So that's really the kind of foundational difference is that we've designed this to be native speaking to AIs.
People can use it, everything else, but AIs, it's just, you know, chef's kiss.
Now, one of the questions that I have when you say making mistakes, obviously we all make mistakes and we've all been very impressed with the rollout of AI in the last couple of years.
But from time to time, we've all experienced hallucinations and where AI gets it wrong.
So are you telling me that with AI native, there's less of a likelihood of hallucinations than there would be with the AI bolt-on model?
It's just that all of these things add up to make it far less and less likely to occur.
And so each one of these barriers is just, as you take it out of the equation, now you just get better and better results.
Well, particularly when you're dealing with medtech, medical devices, healthcare, etc.
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