Latest / Age Defiantly with Mark Young / [Ep 39] Why "Normal" Labs Are Killing You (And How To Fix It) | Steve Giddens

Transcript

[Ep 39] Why "Normal" Labs Are Killing You (And How To Fix It) | Steve Giddens · Age Defiantly with Mark Young

• 0:00
  Welcome to Performance Driven Living, the podcast where we question everything.
• 0:05
  We don't tip to around tough topics, we walk right into them, not to provoke, but to
• 0:11
  get closer to what's real.
• 0:13
  You might not agree with everything you hear, and that's okay.
• 0:17
  The show isn't about being right, it's about being real.
• 0:20
  These conversations are meant to stretch your thinking, challenge assumptions, and spark
• 0:25
  something deeper.
• 0:26
  The views shared are those of our guests and may not reflect those of the host or team.
• 0:32
  And while we dive deep into health, performance, and transformation, this is not medical advice.
• 0:38
  Talk to your doctor before making changes to your health or lifestyle.
• 0:42
  Take what lands, leave what doesn't, but whatever you do, don't stop questioning.
• 0:49
  Alright, we are back at the Performance Driven Living podcast.
• 0:58
  We're coming live from the Metabolic Health Day here in Tucson, Arizona, and I have
• 1:04
  the privilege today of actually having a conversation with Mr. Steve Giddens.
• 1:09
  And Steve, I always say this, I always read the bio, which sounds very non-personal,
• 1:13
  but they frame it in such a way that I would never give you that kind of quality of an
• 1:17
  introduction.
• 1:19
  But Steve is actually works with MTomics, which is an arm of the business that actually
• 1:27
  brings Metabolic Health Day here to Tucson.
• 1:30
  This is the first in-person gathering for Metabolic Health Day.
• 1:33
  So this is like a big monumental moment, thrilled to be here and participating in today.
• 1:38
  But Steve, I really want to talk about what you're doing, because I find this remarkably
• 1:42
  fascinating.
• 1:43
  So I want you to kind of unpack a little bit.
• 1:45
  We actually interviewed Nation earlier and talked a little bit about it, but Nation is so
• 1:50
  all over the place with so many different things.
• 1:52
  Like, I really want to focus on what you're doing here with the relaunch of MTomics, MTomics
• 1:58
  soon to be branded terrain health.
• 1:59
  Sure.
• 2:01
  So your introduction, I've got to give you this flattering intro here.
• 2:04
  So today's guest is Steve Giddens.
• 2:06
  He's the president of MTomics, a health intelligence platform built to bring Metabolic
• 2:12
  Medicine into everyday care.
• 2:14
  He leads teams turning terrain-based science into practical tools for clinicians and patients
• 2:20
  by unifying clinical lifestyle, genomic, and real-world data in one place.
• 2:26
  Before focusing on Metabolic Health, Steve led major technology organizations experiencing
• 2:31
  now channels into making precision care usable, humane, and scalable.
• 2:35
  His work is also aligned in a broader terrain ecosystem, including partnerships with organizations
• 2:42
  like the Metabolic Terrain Institute of Health, as well as the rebranded launch of Terrain
• 2:47
  Health, a division of terrain holding company, on mission-driven ventures so that innovation
• 2:54
  actually reaches the bedside.
• 2:58
  So nicely written.
• 2:59
  I love that.
• 3:00
  I made a couple of edits in there because I'm seeing some like, yeah, I'm telling them.
• 3:03
  So I add them a little bit there, guys.
• 3:05
  I didn't exactly read that one, but Steve, welcome to Performance Driven Living.
• 3:09
  Thank you for having me.
• 3:10
  I appreciate you being here because I know a little bit, probably a little more than
• 3:14
  most, about what you're doing, and as the relatively new head of terrain holdings, which
• 3:21
  is now launching a terrain health, you guys are putting together a data platform, and there's
• 3:28
  one unique quality about it that you can explain what it is, but it's very similar to other
• 3:35
  things that have launched out in the marketplace recently that uses AI to actually, I'm going
• 3:41
  to avoid the word, diagnose, but to establish individualized protocols based on epigenetic
• 3:49
  expression, based on blood work, based on any number of data points, but isn't using
• 3:56
  broad data to make those decisions.
• 3:59
  It's using individualized data, which is a huge point of differentiation.
• 4:04
  Can you explain what terrain health is, like, give me the nutshell here?
• 4:09
  Yeah, I think it's difficult to encapsulate it in a nutshell, but one way to explain part
• 4:16
  of what we're doing is that we are leveraging machine learning, artificial intelligence,
• 4:21
  et cetera, in the way that a child would in essence use a kaleidoscope.
• 4:26
  So each gemstone in a kaleidoscope generates facets of a hypothetical shape.
• 4:33
  Which one of those facets is an aspect, in our case, of an individual's health profile.
• 4:39
  So the more data that we have, for example, from wearables and other data sources, the
• 4:44
  higher quality analytic we can do using that AI that is 100% bespoke to the individual.
• 4:51
  So we have blood work, we have other labs, we have all manner of health data that we accumulate,
• 4:57
  which is pre-processed and, again, delivered to a person or to a clinician in certain cases
• 5:03
  in a way that's optimally useful for that patient and the health conditions that they're
• 5:07
  dealing with.
• 5:08
  Now, correct me if I'm wrong, I'm making a little bit of an assumption here, so bear
• 5:12
  with me.
• 5:13
  But when a lot of systems, okay, as a functional practitioner myself, I don't practice,
• 5:19
  but clearly have that knowledge, one of the things that we see a lot of, we get blood
• 5:24
  work back, but the blood work says, you know, your cholesterol is 150, right?
• 5:30
  We're like, oh, 150, good, that's great range.
• 5:34
  Great range for what?
• 5:35
  Right.
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  Great range meaning what?
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  And in most of those cases, that those ranges, that highs and lows mark, that says you
• 5:42
  as long as your little needle indicator is somewhere in the green, everything is fine.
• 5:47
  The only thing that's in the green is the metric based off of the rest of the population.
• 5:52
  Right, the norming.
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  Right.
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  And the norming of the population, I would arguably say, is based off a pretty unhealthy
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  population.
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  And what I love about what you guys are doing, because I've got a little bit of inside
• 6:03
  information here, is you guys aren't norming the data.
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  In fact, I mean, legally, we give the norming, but then there's also a level that's indicated
• 6:15
  in your data that talks about optimal range or functional range, that is, what should
• 6:23
  that number be?
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  And I want to ask you a question here, in my conversation with Nayshell, I'll just
• 6:29
  give you a scenario and you can speak to it.
• 6:32
  We were doing, and I was talking with my dad, and we actually, we team teach a monthly
• 6:37
  class with Kroger executives of all crazy things.
• 6:41
  And then that it's all talking about, you know, health and more of a functional health
• 6:45
  type training course.
• 6:47
  And we were talking about AI and the use of AI, and how are you using this?
• 6:51
  And I use AI for my own health all the time.
• 6:54
  But here's my supplement stack.
• 6:56
  Here's my recent blood work.
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  What am I missing on here?
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  What could I overlap?
• 7:00
  That the human side of me has to say, I don't agree with you, AI.
• 7:05
  I know better than what you just said here.
• 7:07
  Now granted, AI knows better than 90, something percent of the population.
• 7:12
  But periodically, I'm like, for instance, like I was actually shocked because I take two
• 7:16
  different supplements that both actually contain heavy amounts of K2.
• 7:21
  And I was like, well, I know K2 is very good for you, right?
• 7:24
  Like I agree with K2.
• 7:25
  I also agree that K2 is absolutely fantastic for liver function.
• 7:30
  Too much of it actually puts too much stress on your liver, and I was like, oh, wow, I'm
• 7:34
  glad I did that test.
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  Like I didn't even pay attention to that, right?
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  Or people don't realize that vitamin A sounds like a good thing.
• 7:40
  Too much of it stops your heart, like we got to be careful.
• 7:45
  In this class, using AI, my dad gave an example, and he says, you know, he actually had a prostate
• 7:50
  cancer diagnosis treated it using metabolic means is undetectable at this point.
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  But he uploaded all of his recent lab work and said, I'm a 68 year old white male.
• 8:02
  I live in the Midwest in Detroit, Michigan, blah, blah, blah, and framed all this out
• 8:06
  for AI.
• 8:08
  And said, here's my blood work.
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  Tell me what I need to know from it just to use it as a data point.
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  Normal, normal, normal, normal, normal, normal.
• 8:18
  And everything came back normal, but what was interesting, where I love where he dug deeper.
• 8:23
  And I'm curious how this relates to terrain health because he did a follow up question
• 8:30
  with it and said, you gave me all of the normal ranges for a 68 year old man.
• 8:36
  Do that again, but treat me as a 30 year old man.
• 8:42
  Outer range, outer range, outer range, outer range, like every single thing that came back
• 8:46
  was like, this is bad if you were 30, bad if you were 30, bad if you were 30.
• 8:50
  And he and I had a conversation about it in live during training.
• 8:54
  And the conversation was, why is it normal at 68, but it's not normal at 30?
• 9:00
  And the answer is, norming data.
• 9:02
  It's the norming of the data for sure.
• 9:04
  So biomarkers, life stage, many, many other factors that create the context for the analysis
• 9:11
  that we do on the back end that allows for, I think, the most useful, relevant data to
• 9:18
  be provided to the patient with the express goal of empowering that patient's decisioning
• 9:24
  throughout life.
• 9:25
  You spoke about supplements that's a key area.
• 9:29
  There are others where we want people to be informed.
• 9:33
  And that truly informed service delivery, if you will, is predicated on every bit of
• 9:41
  data that we can get.
• 9:43
  So it is life stage.
• 9:44
  It is biomarkers.
• 9:45
  It is, you know, we talk oftentimes about the terrains of metabolic health.
• 9:51
  All of that data is combined in our platform and pre-processed in a way that is optimal
• 9:58
  on a per individual basis, irrespective of where they're coming from, meaning we're not
• 10:02
  using the norming data.
• 10:04
  It's specific to you, your results, your age, that sort of thing.
• 10:09
  And I think that makes it pretty unique on the market.
• 10:11
  I agree with you on that.
• 10:13
  So how does that differ?
• 10:15
  So I'm just going to say, like Mark Heimann has function health, right?
• 10:18
  Like this is a AI health platform, so on, so forth.
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  And I know Mark, I like Mark, nothing against Mark whatsoever, but there's a juxtaposition
• 10:26
  to be made, because you guys are similar to that type of platform.
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  So your launch is AI health-driven protocols where you can upload years worth of health
• 10:35
  histories and get AI insights into your own health.
• 10:39
  The intention behind that is, yes, I can personally use it, but as you mentioned earlier,
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  I can also use it to collaborate with my healthcare practitioners.
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  And I believe, and I know the way function functions, but I'm curious if you can make a distinction
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  for me.
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  Well, I think there are possibly two to be made.
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  I think that they're wanting to be as much as possible to the largest possible audience.
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  And that's not our goal.
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  So we understand that we're serving more of a kind of a niche role in that we're focused
• 11:19
  on all things metabolic and not necessarily Western medicine, for example.
• 11:24
  Okay.
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  Right.
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  I think that's one thing.
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  Another thing is that-
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  So you're more functional than function.
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  I would like-
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  Perhaps.
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  Perhaps.
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  Interesting distinction.
• 11:35
  Yeah.
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  I hadn't thought about that.
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  But I think that's one thing.
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  The other thing is that we're contemplating, and I don't know that they're not, but we're
• 11:46
  very much contemplating a horizontal growth model where we're able to address, you know,
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  where today we're very focused on cancer, but because the lowest level of the medicine
• 11:59
  that we're using is metabolic in nature that really applies to all disease.
• 12:07
  And we are contemplating that as we go forward in order to do that and maintain that kind
• 12:13
  of bespoke service delivery that we were speaking about earlier, we're not able to focus
• 12:19
  on Western medicine, standard of care, normative data, all of those things are a little bit
• 12:27
  antithetical to what we're about.
• 12:29
  Yeah.
• 12:30
  I agree with that.
• 12:31
  So it's funny to me because like function health, right?
• 12:33
  You think it's functional medicine, but it really does lean to norms for Western medicine,
• 12:37
  right?
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  Which is probably a wider audience as opposed to a person who really wants functional data
• 12:45
  in there.
• 12:46
  Right.
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  Which, again, I couldn't agree with you more on that.
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  So let me ask you, Steve.
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  So with this data, we're obviously looking at metabolic disease, and I would say that
• 12:57
  we as a nation are in a metabolic crisis, that what's the number that 90 something percent
• 13:02
  high 80s to 90% of the population is in metabolic dysregulation in some nature, right?
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  Like is part of the goal behind this to get people back into metabolic regulation?
• 13:15
  Is it just a disease prevent?
• 13:17
  Is it to optimize health?
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  Like what would you call that?
• 13:20
  I think the goal is to optimize health.
• 13:22
  You know, doing quick math, I think that that metric of high 80s to 90% translates to something
• 13:28
  like five billion people worldwide, who are not in an optimized state, certainly it may
• 13:36
  not be healthy, but there's an opportunity to improve the lives of all of those people.
• 13:41
  And that going back several years was the driver, the generation for the thought that became
• 13:49
  emptyomics, and all of the things that we're doing there was not so much to touch people
• 13:57
  directly in the initial ideation, but to improve quality of life generally.
• 14:04
  So the science, creating the science that would in turn, at some point, that point being
• 14:10
  now be scalable and portable in a way that allows us to deliver what's been built to people
• 14:19
  without any real limitations.
• 14:21
  Pivot.
• 14:24
  I love that.
• 14:25
  I love the functional side of what we're talking about that.
• 14:29
  We talked earlier about, could it be a consumer product where a person can use it to just
• 14:33
  optimize their own health, avoid disease, you know, find warning signs before they check
• 14:37
  engine light actually comes on.
• 14:41
  Healthcare's changing.
• 14:42
  There is such a fast change in healthcare right now, and I'm a big proponent on people
• 14:48
  getting on board with AI because it's not going anywhere.
• 14:51
  Right.
• 14:52
  I know people who are like, oh, no, I don't trust it, well, I don't trust the government
• 14:56
  either, but I still live here, right?
• 14:58
  Like, it's in the internet, it's not a fact.
• 15:00
  Absolutely, it's part of the system.
• 15:03
  It's now part of the system, and I think like the internet, as you say, the internet can
• 15:07
  be used for extraordinary evil, can also be used for extraordinary good.
• 15:12
  And I think AI kind of has that exact same that takeaway, right?
• 15:15
  Use that power in a way that's optimal.
• 15:18
  But what I'm seeing in the healthcare space specifically is Dave Asperin, in fact today,
• 15:25
  just posted about AI is better at diagnosis, it's better at coming up with treatment
• 15:30
  plans, and it's just better at being unbiased in the way that it approaches things.
• 15:37
  Doctors quit pretending you know more, and I was like, okay, which is actually, I say
• 15:43
  it's extra kind of funny because today also I was featured in a podcast that funny enough,
• 15:49
  you know, Dave Asperin, I'm sure I made the comment about Dave as controversial to which
• 15:54
  Dave commented on the social media post and said, well, if you mean that I actually check
• 15:57
  science, I might have, it was a good thing, Dave, it's not a bad thing, and then he posts
• 16:01
  on this.
• 16:02
  Oh my God.
• 16:03
  So it was just kind of funny, Dave's props to your love, you man.
• 16:07
  But he's not wrong.
• 16:08
  This idea that AI, there was a study that was done recently showing that they actually
• 16:12
  took patient files that had already been diagnosed and so on, but they took the intake
• 16:17
  forms, gave a stack of them to doctors, gave a stack of them to AI, and AI diagnosed
• 16:23
  correctly 80% of the time, and the doctors only did 20, and I'm like, why aren't professionals
• 16:29
  leaning into this more?
• 16:31
  Everybody's answer is, well, AI hallucinates, and like, well, AI does hallucinate, but that's
• 16:34
  why I know what I'm talking about to be able to identify when it goes off course, because
• 16:40
  AI will bias my answer towards anything that I tell it, I'm bias, if it knows me as being
• 16:47
  a naturopath, it's going to answer all of my questions in a naturopathic way, right?
• 16:51
  Like, I need to be very specific in what I'm asking.
• 16:57
  All of that said, I believe that healthcare is changing because we're losing the sage
• 17:03
  on the stage doctors.
• 17:06
  It's no longer, I tell you, you obey me, we're seeing a healthcare system that's turning
• 17:12
  into a collaboration, and good doctors are getting on board with it, and good doctors
• 17:18
  are recognizing this power, and not just the power of AI, but the power of the patient,
• 17:24
  because AI is not replacing the doctor, AI is just empowering the patient, and not to
• 17:31
  go crazy on terrain health specifically as a platform, but speak to me about how you
• 17:37
  see that, and then feel free to plug in, how does your system work in that new ecosystem
• 17:45
  of healthcare?
• 17:46
  Yeah.
• 17:47
  So, you know, I couldn't agree with you more about AI, generally.
• 17:50
  It's a tool in the toolkit, but it's not your ordinary tool.
• 17:54
  It's indispensable, and it's available literally to everyone.
• 17:58
  It's in everyone's toolkit.
• 18:00
  Some people are not using it yet, yet, and many people are, but it's a great equalizer,
• 18:06
  right?
• 18:07
  Because the same information is available to everyone, and sure it's fallible.
• 18:11
  It makes mistakes, and it's typically contextually driven, you set it yourself, it's the way
• 18:16
  you ask the question, you can lead it down a path, but if you don't, you very often get
• 18:21
  a good, right, useful answer, and for that reason, we think that MTOMICS is, or terrain
• 18:29
  health, as we've recently designated it, has enabled the patient to take control of their
• 18:38
  own healthcare journey, right?
• 18:40
  So, it gives you information, it gives you tools, it allows you the opportunity to make
• 18:45
  decisions that you previously were not able to make, and I'm speaking very specifically
• 18:51
  about going to the doctor, getting a diagnosis, going to the pharmacy, getting that pharmaceutical,
• 18:57
  that pill that you take that probably symptomatically addresses what you went to the doctor
• 19:02
  for while simultaneously creating something else that you may need to take, another medication
• 19:07
  for, et cetera, et cetera.
• 19:09
  In this case, you have the option to decide, is this a good idea?
• 19:12
  Is this a path that I want to go down?
• 19:15
  The platform accommodates you under all scenarios.
• 19:19
  So if you want to upload your records and your wearables data, et cetera, and then stop
• 19:26
  there and get analytics around that, around nutrition and supplements, you can do that.
• 19:31
  If you want to share that information with an advocate or a practitioner, you can do that.
• 19:37
  If you want to revoke access from a doctor or practitioner and provide it to someone else,
• 19:43
  you can do that.
• 19:44
  It's really empowering the patient in a way that I don't think, as patient, I don't think
• 19:49
  I've ever seen before.
• 19:51
  Yeah.
• 19:52
  It's such a new, it's a different world, and I want to go down that path, but you said
• 19:58
  something, and then you said it's the great equalizer, and I've said this multiple times.
• 20:02
  My team is probably sick of me hearing me say it, and that is by next year, I believe,
• 20:07
  we are going to notice a, I'm going to say, civil war level divide that's going to start
• 20:13
  being created, and that is the haves and the have-nots are no longer going to be who controls
• 20:18
  the money.
• 20:19
  It's literally going to be the smart people versus the not smart people, because people
• 20:23
  who are able to adopt AI and then adapt to it are going to, everything is available to
• 20:32
  everyone now.
• 20:33
  Nobody starts with an advantage that another person didn't have other than perhaps parenting.
• 20:39
  I had a car in the garage very recently that my mechanic was struggling with, and I
• 20:44
  printed out instructions at home and went down and handed it to him, and he fixed it,
• 20:49
  and he said, did you get that from AI?
• 20:51
  I said, of course, I did.
• 20:53
  He said, so it's really that good, and so well, you're the proof.
• 20:57
  Yeah.
• 20:58
  The AI at this point can't touch the car, but it can certainly provide the intel, and
• 21:05
  that's the type of stuff that we're noticing, and it's, say, downright spooky when you think
• 21:11
  of it in that capacity, but I am noticing there's rift that's starting to take place.
• 21:15
  There are people who are, who are outputting 10 times the amount of work that they were
• 21:20
  once able to output, and there's other people who just get the mistakes faster.
• 21:23
  That's true.
• 21:24
  Yeah, I mean, it's just getting you to the mistake faster, but the question, and this may
• 21:30
  be related to ring health, I don't know.
• 21:34
  One of the things I do when I use AI, and that is I am, what I love most about these
• 21:39
  types of things, particularly in medical type cases, but in marketing and anything that
• 21:43
  is I use AI, and I don't call it a tool.
• 21:45
  In fact, I like slap hands in my office when people call AI a tool, and it gets a collaborator.
• 21:50
  This is not, this is not Google.
• 21:51
  You didn't ask a question, get an answer.
• 21:53
  That's not the way this works.
• 21:55
  This is a collaborator, much like a class project.
• 21:59
  Not only do you get, it doesn't mean you've got an expert on the team.
• 22:02
  It means you've got a really smart classmate, and you'd be a fool not to use that input,
• 22:07
  but you still need to participate in the project, not just take the answers and run with
• 22:11
  it.
• 22:13
  One of the things that I love about it, for instance, if I'm having a conversation,
• 22:18
  or I'm collaborating with AI, and I'm talking about cancer, let's just say, I'm like, incorporate
• 22:25
  the thought leadership of Dr. Nathia Winters into this conversation.
• 22:31
  I want you to lean on her as an expert.
• 22:34
  When I'm dealing with marketing type questions at my own agency, like when I'm collaborating
• 22:39
  to come up with ideas or to write or to optimize landing pages or anything like that, I've
• 22:45
  got a prompt that just says, invite the team, and it is a team of thought leaders who think
• 22:50
  the way I think, or whose works, public works, have made an impression on the way that
• 22:57
  I believe things work, and I say invite the team, and then all of a sudden I get thought
• 23:01
  leadership from Donald Miller, from Dan Martell, from Tony Robbins, from Wilgweed Outta,
• 23:05
  from all of these people, and I've got different teams for different things, but I don't need
• 23:10
  to know, you know, Donald Miller's take on cancer, but I can create a bot that actually
• 23:17
  has thought leaders that are all sitting in the next room, and I can pull all of their
• 23:22
  public information and get their thoughts on a topic.
• 23:27
  Is it fallible?
• 23:28
  Of course.
• 23:29
  Sure.
• 23:30
  But National Winters has spent 34 years talking on this topic.
• 23:33
  There's plenty of podcasts where her voice is heard.
• 23:36
  There's books that are written by her.
• 23:38
  There's YouTube channels, social media channels, and everything else.
• 23:43
  I can literally get other people's opinions with remarkable accuracy.
• 23:51
  When I'm using a tool or a platform like terrain health, can I optimize those ranges?
• 23:58
  Because sometimes I will actually go in and say, what would Dave Aspery say about this?
• 24:01
  What would Natalie Nittam say about this?
• 24:03
  What would Ben Greenfield say about this?
• 24:05
  And I get different answers, and it's up to me to decide which influencer, opinion I
• 24:11
  hold most dear, because in this world of functional space, there's a lot of disagreement.
• 24:17
  And I think where terrain has done a great job is, you know, this person says you must
• 24:23
  eat this way.
• 24:25
  This person says you must do this.
• 24:27
  It's like terrain and nature specifically in her conversations has very much been, I can
• 24:33
  give you generalities, but everybody's an individual.
• 24:38
  So individualized health care stuff, but can I also use the voices of other people?
• 24:44
  Do you find that beneficial?
• 24:46
  You can, beyond beneficial, I think it's essential.
• 24:49
  So there are multiple, you use the term thought leaders, practitioners of consequence in the
• 24:58
  space around the world.
• 25:00
  And their methods are not identical.
• 25:02
  And we've architected the platform to account for them so they can run their practice there,
• 25:07
  they can see patients there, they can use their method there.
• 25:11
  And so inherently, we've captured the ability to toggle between those.
• 25:15
  We have not yet exposed that to patients, but we have it.
• 25:19
  So because we don't believe we can not have it, we're still having the conversation around
• 25:24
  the best way to use it, the best way to expose it, to not be confusing, for example, to patients.
• 25:30
  So they may be very well versed in Dr. Nation's method, and they may have heard of another
• 25:38
  physician in the UK, for example, they want access to that, but they don't necessarily
• 25:42
  know how to consume it.
• 25:43
  And we want to be sure that we've polished that delivery in a way that it continues to
• 25:48
  be beneficial, you know, as opposed to confusing a patient.
• 25:51
  But the answer to your question is yes, we provide that.
• 25:54
  That's super interesting to me.
• 25:56
  Does the patient get any insight as to whose opinion or when there's a different opinion,
• 26:02
  which one wins?
• 26:04
  Well, that's the rub, right, because there isn't a unified source of authority on that.
• 26:11
  So we're providing multiple approaches that, again, coming back to a patient choice,
• 26:20
  they will have the ability to choose between, but we need to ensure that we've provided
• 26:28
  a way for them to understand what the differences are between the methods.
• 26:33
  And where if there are differences in outcomes or efficacy, we need to be able to share
• 26:37
  that with them, which is the reason we haven't yet rolled that out, but it's all built
• 26:41
  into the framework of the platform and will be coming.
• 26:44
  I would have to imagine that if I were to into it into that, what I would imagine is
• 26:48
  that most of the differences between those practitioners are going to boil down to the
• 26:51
  patient's overall compliance with lifestyle choices.
• 26:55
  I think that's a big part of it.
• 26:56
  I think that many of the physicians have almost a branding or a following, right, right?
• 27:06
  And they're not identical.
• 27:07
  And so they would like, they've said to us, we want to use your platform, but I want
• 27:12
  to be able to deliver my method in your platform.
• 27:14
  I don't want to start using your method in your platform, right?
• 27:19
  And so we've accommodated that from a technology perspective that we can have a physician
• 27:24
  or a practice come in and say, here's the way that we're going to measure.
• 27:28
  Here's the way that we're going to coach.
• 27:29
  Here's what we believe, and we can handle that in the system.
• 27:34
  I mean, that has me, I've got so many questions about that that we can unpack offline.
• 27:39
  But if I'm a follower of Dave Aspery, I'm grass-fed, grass-finished beef, non-stop,
• 27:46
  right, like that is my go-to, and I avoid kale, right?
• 27:49
  If I'm a Stephen Gundery follower, I eat more of a plant-based diet.
• 27:53
  I mean, I'm not, I mean, I eat meat, but I'm going to eat more of a plant-based rotation.
• 28:01
  You know, there's such a different philosophy or theory.
• 28:09
  I don't know what I want to call that, but that methodology that either one of them
• 28:13
  would use to treat, and both may be effective, that's the interesting part to me.
• 28:17
  It's like following this plan or following this plan often gets me here.
• 28:22
  It's the following, no plan that kills me, but both of them are going to agree on core things,
• 28:27
  like don't intake sugar. Alcohol's not good for you.
• 28:31
  Like, we're going to agree to some of those things.
• 28:35
  But as an example, I have a friend who owns a company that actually is a wine bottler.
• 28:42
  There's no cancer treatment that's going to get him to stop drinking a bottle of wine,
• 28:46
  like not a bottle of Dave, but you get him saying, like, he's going to drink wine,
• 28:49
  which means there needs to be a care package built that says maybe this person's theory,
• 28:59
  or this person's protocol, is more effective to a person who refuses these types of lifestyle
• 29:04
  changes. Sure, similar to what a weight loss, for example. Correct, yep.
• 29:08
  Yeah, if the person lives in a cold climate and is not going to get an adequate amount of sunlight,
• 29:14
  perhaps this is a better treatment plan. If the person lives in a, you know, I live downtown
• 29:20
  Fort Lauderdale. So I laugh and say any mitigation I use towards EMF is a clown show, right?
• 29:25
  Like, I'm kidding myself that I'm doing any good by turning my Wi-Fi off because I live in a high-rise
• 29:30
  building. Like, if I don't get my Wi-Fi, I'm getting 17 people all around me, but it's a hot bed for
• 29:36
  it. And it's like, really makes you question my life choices, but the reality is that there's some
• 29:40
  things that aren't going to change about my life, and with the exception of sleeping in a
• 29:44
  Faraday peg, I'm not going to fix that, that problem, but other people have different lifestyle
• 29:51
  choices, right? Like, there are people who are vegan, and they refuse to go away from that.
• 29:55
  Well, putting them on an entire carnivore diet, telling them that fixes their metabolism
• 30:00
  isn't going to work because lifestyle-wise, they're not going to comply. Right. Yeah, it's not
• 30:05
  binary. Agreed. And I think maybe that's where that decision-tree, if you will, in the technology,
• 30:11
  helps play out is what are the lifestyle choices that the person is willing to make? Yes.
• 30:16
  And then find the protocol or treatment plan that aligns. Absolutely. And predictably,
• 30:21
  you know, as you move around globally, you also have cultural consideration. 100%.
• 30:25
  Right. So we wanted to be able to address all of that. And foundationally, we have architected
• 30:31
  the platform to be able to do that. So we think that is another rather unique feature today.
• 30:37
  Yeah. And I think that's enormous because patient compliance, not that these are patients,
• 30:43
  but users, but compliance is the biggest problem for any product, to be honest with you.
• 30:48
  I mean, I work with product companies and supplement companies and everything else, and it's like
• 30:52
  just getting people to do what they're supposed to do with it is the hardest problem. Like, use
• 30:57
  this once daily. You know, and I laugh because I get one of the companies that I work with as a
• 31:03
  skincare company. Absolutely brilliant people. Their skincare is absolutely amazing and so on.
• 31:09
  And I laugh because I mean, I'm 50 and a lot of people are just like, there's no way you're 50. I'm
• 31:13
  like, why use your skin? Do I use your skincare every day? No. I've got bottles of it that I've
• 31:17
  had for months that I've never used because I'll use it periodically once in a while. I'll remember,
• 31:22
  but like I'm a guy like I don't think in those lines. I've got, I just moved recently and I've
• 31:28
  got boxes of bottles of skincare products more than any man ever possibly needs and it's all
• 31:35
  clients and all samples and all this other kind of stuff. And it's like compliance is the problem.
• 31:41
  Like I'd probably look 25 if I'd actually use this stuff. But I don't, people don't stay on
• 31:48
  diets, right? They need lifestyles. Workout plans are great for a while. Right. But that sort of
• 31:56
  stuff supplements like, yeah, people take them great up until they get the second bottle in the
• 32:01
  mail and they realize they still have half of the first bottle on the shelf. Sure. And they've
• 32:04
  already paid for the third bottle. Correct. So yeah, we, you know, and we thought about this,
• 32:09
  especially in our consumer facing interface, this notion of should we incorporate journaling?
• 32:16
  Do we believe what's in the journal? Is that a good way to build a large language model and
• 32:22
  end-in-book AI? And we decided it's really not. As a feature set, sure, people can do that.
• 32:28
  But that's not data that we're going to use to analyze your health, right? We need empirical data.
• 32:34
  We need data from the wearables. We need data from the labs. We need stuff that you're not going
• 32:39
  to embellish. That you're not going to maybe outright lie about in order to change your
• 32:44
  diagnosis. We're processing the data that we're getting effectively from third parties at the end
• 32:52
  of the day about an individual. And yes, they can log things, et cetera. But that's excluded
• 32:57
  from the data set from the language model. Because otherwise, it becomes more subjective than
• 33:02
  as useful over time. And I'm curious. So I've got a sponsored FDA study that we're in the process
• 33:09
  of right now. And second one I've done. And, you know, we will actually, you know, we talk about,
• 33:15
  you know, adverse events, right? So SAEs or SAEs, significant adverse events. Like, during the
• 33:21
  course of using this product, you know, the person experienced hair loss. Like, we have to record
• 33:26
  that. And I'm curious if that would be, you know, even if it was a voice journal,
• 33:31
  crosses my mind, like the person's able to just hit the record button and voice journal,
• 33:35
  which can obviously be transcribed and then cataloged. So that if in that catalog, could it,
• 33:41
  if multiple people are saying the same thing, maybe where they're smoked, there's fire.
• 33:45
  But just in a voice journal, you know, they don't, because no people don't journal.
• 33:51
  They don't effectively know. Right. And when they do journal, it's all super subjective. I'm just
• 33:55
  wondering if there's the occasional footnote on a day trying to think if that would be something
• 34:00
  that I would use if it was as simple as hitting record and just saying it as opposed to having to
• 34:05
  type it in. I think that would make it easier, but I'm not sure that that would impact the
• 34:10
  veracity of the data were in the context of co-mingling it with. Fair enough. Not to co-mingle.
• 34:16
  Correct. I'm thinking of it more of like the adverse events that we get in the clinical trial
• 34:21
  or absolutely ridiculous, right? Like the person, like the clinical trial is over a blood pressure
• 34:25
  device that Zona.com that uses hand grip, you know, during the midst of this, the patients left
• 34:31
  toe got broken and you're like, probably not the same. But we have to record it because the patient
• 34:37
  set it. And then afterwards we end up having to go back and, you know, well, this is unrelated,
• 34:42
  this is unrelated. And we think more becomes a subjective, you know, would this be attributed to
• 34:47
  this in a professional's opinion? Sure. I think could be interesting. I'm stoked for terrain
• 34:54
  health to launch. Like hopefully by the time this podcast even goes, goes public terrain health
• 34:59
  is already in there and people can go. So we're going to actually make sure that everything that we've
• 35:03
  got here goes into the show notes leads to this so that people can actually get set up with it.
• 35:10
  I love the idea of using, I use the phrase artificial intelligence and human intelligence
• 35:18
  combined that there isn't one or the other. It's together. We're better. And I love how you're linking
• 35:24
  that stuff in together that we're, we're taking artificial intelligence to empower the humans,
• 35:29
  not to enslave them. Yes. And that becomes the biggest thing. And into a listener who's listening
• 35:34
  to this and talking about, oh, it's scary to think of what AI is probably involved in most of the
• 35:39
  things that are going on in your life now and you just don't know about it. The reality is is that
• 35:44
  when we're talking about AI, my plea to people is it's not going anywhere. So I'm always saying
• 35:51
  please and thank you because I want to make sure that when the robots take over, they remember me
• 35:55
  fondly. But the reality is is that it's not going anywhere and to the extent that we can tap
• 36:01
  information and, and I say not just gathering information but synthesizing information in a way
• 36:08
  that we've never had the capacity to do before. It is incumbent on us as humans to use that to
• 36:16
  its capacity to, to create the greatest human experience we can for ourselves, our loved ones,
• 36:22
  our community around us. And, and that's how I see AI is really impacting our world right now is
• 36:28
  it is, it is a way that we can make everything better. And the only people I think that get hurt
• 36:34
  in this new economy that will be happening are the people who aren't adapting. I think for me
• 36:41
  personally, like does it make me wonder what goes on in my businesses, you know, it's just changing.
• 36:46
  Sure, it's a lot of work right now having to reimagine the way that a business that's been
• 36:51
  functioning for 12 years now all of a sudden has to be different but it's worth it. And it's a new
• 36:57
  it's a new world and it just welcome aboard. It is market. The one distinction I would make is that
• 37:03
  we view terrain health not as an AI platform, but as a patient platform that uses AI.
• 37:10
  Fair. Fair. And again, it's that partnering the human intelligence with the artificial
• 37:15
  intelligence for a greater intelligence overall. And I think that's where where I see AI is,
• 37:22
  you know, when I was in school, we were told that, you know, undergrad taught you the vocabulary,
• 37:27
  master's degree, graduate stuff taught you how to synthesize that information.
• 37:34
  Doctorate level work taught you how to create new knowledge. And to me, I'm like that undergrad
• 37:40
  vocabulary now kind of exists already. I can fast track. I can use AI for higher level processing
• 37:49
  to synthesize information. I can take a look at multifaceted lab results and ask if there's a
• 37:55
  connection between, you know, this is wrong, this is wrong, this is wrong. Are any of these
• 38:01
  things related or do I have three diagnoses? Like that's a fast track. That's such a fast track.
• 38:07
  And the truth is we can get to a better patient outcome faster, which is the goal anyways, right?
• 38:11
  Early detection. And in all of that, I just see it as then let the humans go start to work on the
• 38:17
  new knowledge, like let the tool deal with the vocabulary, let the tool to collaborate or deal
• 38:23
  with the synthesis. Let's go create greater things that it can't even do yet. Like let's elevate
• 38:29
  all of that. Steve, thank you for joining us. It's been a pleasure. Like I said, I'm super stoked
• 38:34
  about getting health terrain off the ground and being able to see where this goes. And it's next
• 38:38
  iteration. But what a great conversation about that. I love it. Listeners, take care of yourselves.
• 38:45
  You have all of this information available to you on your phone, right? We're all worried about
• 38:51
  government tracking. And we carry a device around that literally is tracking us. So use it.
• 38:56
  Use it. Find out what there is out there. AI chat GPT. It's not Google. It is not ask a question,
• 39:02
  get an answer. It is a collaboration tool. And the only thing that limits your ability to use it
• 39:07
  is your imagination. Think of the ways that you can be using this different and starting
• 39:12
  corporate it into your everyday life into your health plan. Ask the questions when your doctor
• 39:17
  tells you something. Have you challenged it when you get your own diagnosis? Ask what could
• 39:24
  this be related to? Ask questions like, what lifestyle changes should I be making today based
• 39:30
  on this diagnosis that I just received? And to the point that we made, ask nation winters opinion
• 39:36
  or ask Stephen Gunter's opinion like get thought leaderships into your conversation. And I strongly
• 39:43
  encourage you to do that because you will find knowledge that you've never imagined available to
• 39:47
  you. Use it. Own it. And I look forward to terrain health coming on. Steve, we'll put all of the
• 39:52
  stuff down in the show notes. Look for terrain health below. Look for all of the social handles related
• 39:57
  to that, including all of the related organizations that you guys are involved with. We'll keep all of
• 40:02
  that front and present. And guys, we thank you again for joining us. We're challenging conventions
• 40:07
  here and learning new things all the time. So thank you for being part of that as well, Steve,
• 40:10
  and we'll see you next time.