There are a lot of clues about Alzheimer's.
I think there's enough clues for us to understand.
What is actually causing the cognitive impairment.
Often these clues come from very disperate fields.
The shingles vaccine, there's a group in Wales where if you were born after this cutoff date, you were eligible for the.
Vaccine. And if you were born just before, you were not.
They basically stratified those patients and followed them over time.
And they found that people that had the shingles vaccine were 20% less likely to develop Alzheimer's or all caused dementia within.
7 years. Why? We have no idea.
And that's because again these are very distinct fields of science that don't interface with each other directly.
So with these LEMs kind of taking off, can we basically like get very smart scientists to train these models to approximate.
Some heruristic that they use and then just deploy these on like the knowledge graph of science to try and connect off.
That seems really tractable and like we have more than enough clues to figure out like the perfect target for something like.
Alzheimer's or other diseases.
Today I have the pleasure of sitting down with Sasha Skirmahorn and he is the founder and CEO of Babylon Bio.
They are currently trying to find a cure for Alzheimer's.
I think over the last like many decades uh tens of thousands of people have been basically working on a cure for.
Alzheimer's. Billions and millions of dollars have been spent and almost no progress has been made.
What about that got you excited?
>> So I I I would actually disagree with the premise that uh the no progress has been made.
I think a lot of progress has been made but by showing us things that don't work more than things that do.
Um so there's no existence proof that this is like uh attainable.
Which to me is extremely exciting.
Um and I think yeah the past several decades of failure have.
Um given the perception of intractability.
>> and if you were to take the second order implication of that intractability I think it's super interesting because it actually.
Makes it a more tractable problem to go after.
>> if everyone else thinks it's a graveyard.
Um that to me at a meta level is like obviously fertile grounds for for actual innovation.
Um.
Yeah I mean I think like you know we we we've kind of.
Still looking at this disease through the prism of like Dr.
Alzheimer from 1906 which is definitely a good thread we should talk about because he had a crazy story.
But yeah like this is um we are kind of focused on two pathologies.
Is we have no idea kind of how they're related.
But I think we've had enough clues in the clinic and uh on the diagnostic side and prognostic side to understand that.
Um you know a little more parts of the picture that you know maybe the the field hasn't updated their OS on.
>> Do you want to just go through some of the approaches that have been tried and why they didn't work?
>> Yeah. All right. Let me let me actually start with the the Dr.
Alzheimer thing cuz it's just it's crazy and it's a very good like backdrop.
Um so uh Dr. Alzheimer was this this dude from like way back when.
Um he was born in the late late 19th century.
Um and got super super interested um well first of all his degree uh his medical degree and his research during that.
Was um on ear wax.
Um so like you know started in the world of ear wax um and was was kind of lost kind of like.
You know just a roaming intellectual not really you know didn't have hadn't set his sights on anything yet um but he.
Got um uh when he was doing I think I I think it was his residency.
He was got introduced to August deer who was a patient who um was in her late 50s I believe and um.
Had this like disorientation,.
Discombobulation,.
General cognitive impairment.
Um people thought she was crazy.
People didn't know what was going on.
Maybe she had a mind virus and um and uh anyway spent a long time with her, characterized her very well clinically.
When she eventually passed, he he ended up doing uh hystopathology on her brain.
And he found these two used a um basically some variant of a silver stain which was um a way to visualize.
These proteins in her in her brain.
And he he was punched in the face by these two extremely large structures.
Um that shouldn't have been there.
Um and and it was what he called um uh plaques at the time and neuropibrillary.
Tangles inside of certain neurons.
And obviously the right conclusion from that was if this is not in a healthy brain and is present in the pre.
Uh in the brain of a patient with what was then to be called Alzheimer's.
Uh uh you know these are clearly causing the symptoms that she had.
Anyway he he ended up giving a a talk I think it was in Frankfurt um and it was a big seminar.
In front of all these people and uh and he presented the first case of Alzheimer's what was then to become Alzheimer's.
He was expecting a standing ovation.
Absolute crickets. People walked out in the middle of it.
They just took their bathroom break.
They didn't care at all. They came back to the next uh presentation to a completely packed house which was on chronic.
Masturbation.
So that was that was about like about summarizes you know the level of respect that he had.
He kind of died you know a bit of a you know um I don't want to call it a scientific pariah.
But he didn't get the credit he deserved >> like any good scientistically.
Did did some really good research and then no one cared in his time.
>> Yes. basically.
Um it's just such an insane like the following they kicked him off stage basically no follow- on questions to hear this.
Fabled talk uh on chronic masturbation.
Um so uh so anyway and then fast forward you know I think um the field really rightfully was saying well these.
Things are not present in a healthy brain let's get rid of them and that was many decades of research.
Um and.
Uh yeah the craziest thing is like we eventually had uh data to suggest that um uh we finally had these these.
Drugs that were able to produce amaloid in the brain.
The amaloid plaques is the plaques are made up of a thing called beta amaloid and that's you know was supposed to.
Be this this incredibly toxic thing and.
The reduction of these you can basically deplete this in the brain of an Alzheimer's patient and have relatively dimminimous efficacy.
Um and aducatamab.
Famously reduced amaloid pet I can't remember top I think it was 76%.
Um and had no impact on cognition whatsoever >> isn't the amaloid cascade basically what people have spent I don't know roughly.
Half of Alzheimer's research and dollars heaven's bat on >> that seems like a fair approximation 100%.
I mean this is a huge like it has been the dogma over many decades and.
You know my kind of like hot take within the Alzheimer's space is like amaloid you know because people have basically seen.
That hey we reduce amaloid has relatively trivial efficacy in patients.
Therefore it seems reasonable to conclude that that's actually like we've debunked the hypothesis but I actually think that's wrong and I.
Think you know a lot of the biomarker development over the past like 15 years even has revealed that amaloid starts deposing.
In the brain 20 to possibly even 30 years before you develop symptoms.
And so that pre-clinical phase is like clearly amaloid is causitive and it's necessary.
Um uh but it may not be sufficient.
Um and and eventually after 20 to 30 years you develop this like you you transition into the clinical phase and um.
Uh and so like if you were to go into a burning house.
Um it doesn't matter what started the fire right it doesn't matter if it was a match or a toaster or whatever.
It is on fire >> it's on fire so like you should put it out right and you should figure out clever.
Ways of doing so and I think that's where the field you know maybe maybe his you know, lagged a little bit.
Behind is like not um not updating their priors that like the cause is actually not the thing that you need to.
Target. Um like if you're developing a drug, you should probably not go after the cause unless you want to run a.
30-year trial. Um which like it already costs quite a quite a pretty penny anyway.
So um you want to keep them as small as possible.
But >> so if you're not going after the cause, what are you going after?
>> Um so so I think there's like many ways to tackle that problem.
I think um you know the thing that we spent a very long time thinking about and like I personally have thought.
About quite a bit was um this like transition period like how do you basically have this dormant stage for 30 years.
And all of a sudden you wake up and you start forgetting your you know where your keys are and you know.
That leads to this cascade.
And um it's just become abundantly clear that um fossil related tow is definitely a lynch pin in that process.
Um and so the thing that um Dr.
After Alzheimer kind of conceived of us these neuropibrillary ch tangles.
Um actually turn out to be uh uh like the number one predictor of the onset of cognitive impairment.
So they're not the predictor of whether you'll develop Alzheimer's period.
Um uh amaloid is like a very good marker to suggest early kind of development.
Um but if you look at the ARC.
Of like all the biomarkers you could imagine.
Uh there's a thing called ptow 217 which is a fragment of these towangles.
Um uh that uh yeah proves to be the most predictive of when you'll develop Alzheimer's.
Uh I should say the cognitive impairment phase.
Yeah. >> For you yourself like why did you kind of make this the thing that you wanted to work on for.
The next like 25 plus years?
>> I think like it was a parallel track of these two things.
I basically.
Um uh I was very.
Excited on the scientific side. I was you know very big reader when I was growing up um and I was kind.
Of like a music and art kid and not really into science.
And then when I was about 13, um I was also a big troublemaker.
Uh stole a book from my library, uh my my middle school library on neuroplasticity.
It was called The Brain That Changed Itself by Norman Deutsch.
And uh and I.
Horrible kid. Yeah. Um and uh I was just like absolutely engrossed by this thing.
I mean, I devoured the entire book.
And the the top guy that they talked about um uh was this guy Michael Mznik, who was like the godfather of.
Cortical plasticity. He was the first one to really show that um your brain can rewire itself in these fundamental ways.
Um, and so, uh, I emailed him just being like, you know, I found out he was in San Francisco.
Where I grew up. I emailed him,.
No response, and like, you know, just bombarded him basically until he finally met with me.
Uh, we stayed in close touch and then when I was about 15, I started interning with him, working,.
Happened to be on Alzheimer's.
Um, and around the same time, my grandmother had gotten diagnosed with Alzheimer's.
And I think just like you know as I progressed on the research side and like went to college was doing a.
Lot of research um there.
Uh and seeing these like what I conceived of as these breakthroughs in the lab and seeing the inongruity with like that.
And my grandmother having not a single drug.
This was pre-licanab preanimab.
All these other drugs that came out and um yeah that that just like crystallized my desire to eventually do something.
I was I felt angry to say the least let down.
What kind of gave you the uh conviction that this was a solvable problem if people have been working on it for.
Decades and it hasn't been solved that's you know a very big hurdle.
As I spent a lot of time asking pretty fundamental questions to these very very very top people who I respect tremendously.
By the way they like set the stage for a lot of really important research.
Um I mean even in the first like seven months of Babylon I probably met with 500 people I was flying all.
Over the world emailing cold emailing every single person uh I'd papers.
You know, I was reading maybe 10, 15 papers a day, emailing all the authors of the papers I thought were good.
And just going down that rabbit hole.
And I would just ask these very basic questions, you know, why do you think fibrals are toxic?
No answer, you know, no answer.
And again, I don't blame them.
There was not enough information for us to be able to have these answers, but it just felt like there were enough.
Of these like, you know, axioms of this disease that we just like had not yet characterized.
>> And that gave me a lot of confidence.
That was why the part of the reason I got into neuroscience to begin with was like the fundamental pillars of this.
Entire field aren't even there. >>.
Yeah. >> It's fertile grounds for innovation or discovery.
That's super exciting. >> And on that like when you were kind of coming up to speed on how everything worked like.
What was your process for doing that?
>> Yeah. I mean, look, I think like um.
I I think a part of it is just like constantly challenging your priors and like you know, one of the benefits.
I suppose like it was a luxury that I was afforded that I had not been in the field for 20 30.
40 whatever years like I was this.
Young uh uh kind of you know very very very hungry to learn kind of guy and like I was always always.
Asking questions always willing to update my priors.
I I I would say like there were certain points where I was almost myopically focused on very specific biology.
That I thought was relevant and then you know I'd go deep enough down the rabbit hole realize it's not zoom back.
Out and there was no ego in that process.
It was kind of like obviously I'm going to be wrong like definitionally like you know even like the the term Alzheimer's.
Expert for me is like almost oxymoronic.
You know I I if if if there were real experts in the Alzheimer's space I think we we would have a.
Uh we'd have a lot more answers.
Um so uh yeah I think just realizing that like no one was an expert and then that um I was in.
A unique position to just like you know rewrite how I think about this disease from the ground up was like a.
Pretty compelling.
Prospect. You basically have talked a number of times about updating your priors.
What kind of paths have you gone down in the past just over the past couple years where you thought that there.
Might be something, you know, some gold nugget of gold at the end of the tunnel and then realized that's just the.
Wrong direction and turned around? >> Um, okay.
So, so like I got really obsessed with Axon's degeneration.
For a while and thinking that that was, you know, the cause of of Alzheimer's, uh, specifically the cognitive impairment due to.
Alzheimer's and, um, uh, that was.
A very deep rabbit hole. I met all the, you know, people who published the seminal papers there and I I still.
Think it's incredibly compelling. I think, you know, sometimes you'll kind of hit a dead end in so far as it relates.
To the drugability of that pathway.
And so, um, uh, for that work, it was very compelling.
A lot of evidence showing that the rate of cognitive decline, meaning the slope of your decline once you actually become symptomatic,.
That varies significantly as a function of specifically what are called white minor hyperintensities.
In these long range tracks in the brain.
And um uh and I went very deep, very deep, very deep.
And I just realized, you know, drug ability of that pathway was was really hard.
There were no drugs that people had developed to actually intervene in that pathway.
And doing it denovo would have been like, you know, that's like a 10-year academic project, let alone then transition into something.
That you could could approximate a drug.
Um so yeah, I think there were a lot of these.
I mean, you know, honestly, our first program for Alzheimer's we worked on.
I think the biology I still think the biology is really compelling.
It was a completely novel target that no one had ever you know uh tried drugging.
And we got really excited about some of the uh uh some of the biology there.
And you know in the end we basically found that the you know we knew the the biological risk was like the.
Highest percentile you could imagine. Um but the the kind of like drugability ended up being in the first percentile and that.
Was just a really bad quadrant for us to be in and so we pulled the plug.
But I still think that's like a super exciting protein just a bad target for Alzheimer's.
There's been a huge amount of capital deployed into trying to solve Alzheimer's and it hasn't happened.
How did you kind of structure the way that Babylon operates so that you can actually get to a point where you're.
Able to solve it?
I think the first program gave me scar tissue that if you.
Like.
Alzheimer's is such a hard thing that any individual program it cannot be existential for the company.
If you're a single asset company trying to go after Alzheimer just like you know definitionally a moon a moonshot is something.
Where you're almost certainly >> you're starting to fail right and I think like you know it had me thinking a lot.
About like ways to kind of hedge against that um because you don't want to scale down the ambitions of what your.
Goal is obviously um in favor of like you know increasing the POS but um but at the same time uh you.
Need to be realistic about like no one's going to you know just bland you know I mean I'm not Elon Musk.
I can't go raise tens of billions of dollars tomorrow.
So I think like you know to really um you have to get creative around that problem and you know it had.
Me going very deep down the rabbit hole of like portfolio theory and like ways to kind of like hedge against this.
At the portfolio level and um uh yeah like more updates to come in the future there.
But like I think just financializing the process of self financing Alzheimer's moonshots.
That's something we've tried to be super thoughtful about and um uh yeah you know the goal is just to amortize the.
Risk of those moonshots basically and uh come up with clever ways to do so.
Are you able to go into any of those?
>> Um, all right. Like I mean I think at the highest level.
Um there are a lot of opportunities out there that are um not per se like venture exit size.
Um, and when I say opportunities, like in the context of the farmland, like I'm talking about drugs.
Um, and so there's a lot of drugs sitting on the shelves, um, that like, you know, Roy Vent obviously, you know,.
Famously kind of spearheaded this where they were like there are these multi-billion dollar blockbusters, but you have to derisk them significantly.
Through several successive stages to get them to the inflection point that warrants that acquisition size.
Um, but I think like there's actually an even larger number of these like assets where it's not going to be a.
Multi-billion dollar exit, but like low n figures.
For sure. um is that something that you know I think people should dedicate their lives to doing like absolutely not.
Um uh or maybe if that's your objective function.
But um but for us uh you know if that went back onto the balance sheet like the thought experiment was basically.
Like a lot of those drugs if that could go straight back onto the balance sheet instead of getting circulated up back.
To the investors.
Um uh sorry to the Babylon investors then you know that's an amazing way for us to kind of like again financialize.
This process and sell funds so that by the time we have a drug on the market uh for Alzheimer's.
That um you know we were able to take it away take it all the way through end to end without needing.
To kind of partner up at the very last stage right like how shitty would it be to run marathon and you.
Know you're you're 3 feet away from the finish line and then you have to you know hold hand in hand with.
A second place who was you know 10 minutes behind you like that would just feel super defeating and so we don't.
Want to give 50% of our drug or whatever at the very finish line um uh just because we ran out of.
Money or we weren't able to take it through or what have you.
>> The way I think about it is it's almost like a complex way of creating a new Google search where you.
Just have this like huge cash cow and you're able to siphon all the cash from it into the the research angle.
>> Sure. Yeah. commercial intermediates are like things that I think people who are thinking on a like founders specifically who are.
Thinking on a long time horizon should be very thoughtful about.
>> I remember Viagra at one point was like a heart medication and then someone realized that there was another application for.
It. Um and so they repurposed it and now it's worth you know billions of dollars I think a year.
How many drugs >> are like that out there that you have already the research has already been done and you can.
Just repurpose them for another use >> for another use.
Um you know it's not as simple as the mechanism of action is you know I think um.
Oftent times like conceivably targeting the same target so like you know most molecules have a single target um and that target.
Is um hopefully the thing that like elicits the cubrious effect if you target it um and so the the idea that.
Like that same target.
Um like you know for instance like seldanophil.
Which is Viagra.
Um uh targets um I think it's a phosphorase poor inhibitor.
Um, but that target alone actually is relevant for Alzheimer's.
Um, which is super interesting. Like totally makes sense.
Um, uh, cuz it's it's like proliferative in nature.
It actually leads to like, you know, cell outgrowth and neurite outgrowth and like these are very good things in the context.
Of Alzheimer's where you're getting this degeneration and you're actually stimulating regrowth.
Um uh and so there was actually a study that.
Um well okay to close that point real quick um it does not mean that the PK itself like the pharmacology of.
The drug may be totally different.
Maybe it doesn't even get into the brain.
So whereas it could conceivably be efficacious by targeting the same thing it's not going to actually get into the brain.
So I guess that's my like non-answer you know avoidance of your question.
Like I don't know what the exact number really is and what the like firmy estimate of that would be, but like.
I have to imagine there's probably.
Hundreds high hundreds of those opportunities out there where it would actually be a very good drug for the other thing.
Um but uh but but probably the super majority of those are just like off patent and like there's no market there.
For you to actually advance it.
But I will uh say so so um in the context of selenophil which is Viagra I think there's a very interesting.
Story which is there was a study that basically.
Um did uh look through your electronic health records and you know there the goal was like look through the prism of.
Epidemiology.
See if you can see these trends and then like use that as a repurposing angle.
Um and so they found that people who took seden.
Were 69%.
Less likely to develop Alzheimer's um it was all caused dementia But um than than people who did not and this is.
Like I mean it's just you know the number alone is hilarious that Viagra you know reduces your risk by that number.
But the um the overall was uh uh the conclusion was that okay well Viagra should be repurposed for Alzheimer's.
Followon studies were not able to reproduce it there's probably some like bias in terms of people who take Viagra need to.
Have you know healthy hearts healthy hearts probably better you know overall like anti-hypertensives.
Are also good for Alzheimer's so like longterm that's probably what happened there but um but Still, I just think there's a.
Lot of these like provocative stories out there and.
There's an AI element to that as well we can get into if you're interested.
>> Yeah, I'm I'm down. >> Okay.
Yeah. So, I mean, I think like there was a information scientist called uh Don R.
Swanson.
Um who did this thing called Swanson linking which was like his whole thing was basically that.
Um there are a lot of medicines.
Uh out there that um can basically be discovered.
Uh just based on information we already have, not new information that we need.
And I'm I'm like totally in on that concept.
I think it's like, you know, in the graph theory formulism of it, it's like you don't need to add a new.
Node to the network to feel like, you know, that that will unlock new biology that you uh can drug.
It's like there's probably a lot of medicines out there that can uh come from just drawing edges between pre-existing nodes.
And so he took that to the max.
And this was like at a time where uh information gathering, scraping, all these things were like super analog.
So like kudos to him. But there was a few examples of like magnesium and migraine.
Um but but the big one that he did was um for a thing called reenode syndrome where um he basically saw.
That uh uh reode syndrome was linked to blood viscosity.
And that uh blood viscosity was also linked to fish oil.
Um and so you know he therefore posited that fish oil would be a good intervention to intercept or remediate the the.
Uh the renode syndrome blood viscosity issue.
And uh you know that was like a big paper that I believe did ultimately uh prove to be efficacious.
So I think there's a lot of these.
I think there's a lot of these and I think LLMs have unlocked a new ability to actually be able to do.
That in high throughput.
Um it's definitely something we've been exploring.
I I we'll see if it bear fruit it bears any fruits.
But um I'm very bullish on that general concept of just like A is connected to B, B is connected to C,.
Therefore A is probably connected to C.
Uh yeah. Is there any other like neurodedevelopmental.
Or like neurogenerative.
Diseases that are able to kind of be cured in the process of trying to solve Alzheimer's?
>> Oh, interesting. Um, if you believe that, um, false related to TOW and towerization.
Is like positive for the cognitive impairment in Alzheimer's, which I certainly do.
Um, then,.
Uh, absolutely. there's there's like other taopathies where that's the predominant pathology because part of the problem with Alzheimer's is yes it's.
Tow pathology but it's also amaloid pathology it's also ner inflammation like there's a litany of different things going wrong in the.
Brain um as you could imagine.
Um and so uh it's much harder to kind of isolate the thing that is very much causitive.
On the other hand you have like front temporal dementia you have pix disease PSP these other things where they are what.
Are called towathies.
And that's like the predominant pathology in all of those is tow fibrillization.
Um so.
Uh yes it's definitely conceivable that like depending on how you target towel that could be efficacious in other diseases that are.
Also rare and can also get accelerated approval and things like this and there's definitely companies out there doing that but um.
Uh but yeah often times like for something like Alzheimer's.
You know if you have a rare disease where you have a 100% chance of developing the pathology and you know going.
Into this neuro degeneration.
I think you'd be fine with like you have a much higher tolerance for for for toxicity you have probably you know.
A lot of these drugs are intratheal so they have to inject into your spine basically.
>> um which I imagine is like a high bar or barrier to doing it for sure and so um but people.
Are trying this directly in Alzheimer's there's a drug called bib 80 um from biogen Ionis and it's a tawaso.
And that's intratheally delivered and so I mean >> I don't know imagine giving your grandmother you know a spinal injection.
It just >> you have to do this like multiple times >> multiple times yeah dosing will vary there's Eli Liy has.
A tow sir as well um that's like similar thing just intratheal and I think these things will be really important proof.
Of concepts and like an existence proof that you can actually really stop progression of Alzheimer's.
Um uh because I do think we'll see the best efficacy um so far like that's my prediction for this year is.
Bib uh 080.
Is going to be um the most efficacious drug for Alzheimer's yet the readout is slated to be in May of this.
Year but um I have a strong suspicion it'll be like probably Q4.
Um just just cuz recruitment is really hard for things like that.
People drop out because again they don't want to keep coming back and getting a spinal injection but um but I think.
It'll be a maybe not an amazing drug but it'll definitely be an amazing proof of concept >> and for the drugs.
That have shown to be somewhat efficacious uh for Alzheimer's.
Um what's been the process for actually developing those?
Okay. So, rightfully so, people.
As kind of mentioned previously were going after this like beta amaloid because that's the thing that's the most present or kind.
Of salient pathology in the brain of an Alzheimer's patient.
Um,.
And so monoconal antibodies are a good modality because they're highly specific.
Uh, if if they're like humanized, then like you know it's.
There's no foreign agent that you're introducing into your body.
So, there's no, you know, minimal likelihood of getting an immune reaction, things like this.
Um and so.
Uh the benefit of these antibodies is they get to where they need to go uh very efficiently.
Well,.
More on that in a second, but um they they are highly specific and um highly efficacious once they target uh uh.
The the protein. The problem is uh 0.1% of the antibbody that you put into your uh body will actually get into.
Your brain because there are these massive entities that are trying to be shuttled across the brain.
And so the first generation of these were like you know the first drug.
Um so like Alzheimer's field had um mantene in 2003 which was like basically a symptomatic treatment.
19 years later you had aducanamab.
And so it was like nothing for 19 years and then aducanab which was considered a breakthrough.
Biogen famously.
Um and later infamously put this on the market despite not showing any cognitive improvement in these patients and um reverse you.
Know FDA adcom had I think it was 14 people on the panel zero of them approved it.
Um all of them rejected um but it was submitted anyway.
There's a whole another conspiracy around that.
We'll we'll save that for, you know, people can Google that if they're interested.
Um but yeah, it had an amazing job at at removing these plaques.
Absolutely no efficacy.
And um uh and the later generations got better and better.
So Danamab, Lacanab, which now is marketed as Lemi, and then Daanab, which is now marketed as Cassunla.
And um and the latest one that I'm most excited about is a thing called trontinamab.
Which actually hijacks a shuttle the transfer receptor in your brain.
So you have the bloodb brain barrier um which is protecting things from coming in which makes sense.
You don't really want anything that's going into your body to go straight into your brain um especially pathogens.
Um but this is basically hijacking that shuttle that allows for this active transport into the brain and it increases significantly the.
Amount of antibbody that can get in there.
And so trinamab has like the best efficacy in terms of amaloid clearance ever.
And.
Uh I I'm like super excited about that one especially a subcutaneous formulation because again going in every every other week or.
Every month to get a IV.
>> I I hate needles generally but like an IV going into an infusion clinic like when you're seven years old I.
Don't know it just >> it's tough.
>> Yeah. I remember I remember my uh my sister getting shots as a kid and she it was like the worst.
Experience. She was just like horrible crying and stuff and she really really hated it.
She had like PTSD from getting any shots.
Yeah. For the first like 18 years of her life.
Um and and that was uh >> that was a very big barrier.
>> I just had to get my blood drawn yesterday.
I almost passed out. Really? It's my biggest fear in life.
>> I had uh I had a blood draw where they took like 28 vials of blood in in one go.
>> Was this a like one of these health wellness things?
>> This was it was like a full blood panel and um.
That was that was pretty rough.
I definitely almost passed out and threw up.
Um I believe you from that.
So when you when you started this company, you've been at it for about three years.
What was kind of the first few months or or year like?
What what did you decide to do after?
>> Excruciating for sure. Um.
I.
I mean, you know, to be fair on the investors, I was going out pitching, you know, I I basically was telling.
People, we're going to go cure this undruggable disease.
Um uh I don't have a PhD.
Um and uh uh and I know there's all these failures, but like trust me, bro.
Um, and uh, and by the way, it's just me in my bedroom in New York.
Um, line up. And, and it was so hard, so hard to raise money.
I mean, like, literally, no one took me seriously.
People were laughing at me. People, you know, fell asleep during calls.
I had three people fall asleep during calls, like in the middle of calls.
Um, people would hang up after 5 minutes.
People go, I mean, it was like really, really brutal.
I'm glad I can laugh about it now because it was like, I mean, it was just hilar like I just kept.
Like chewing glass and I was like, it just became a game at a certain point, you know?
It's kind of like um uh and I had so much conviction in what I was doing.
I put I was self financing all the experiment.
I mean it wasn't like I was going to stop any of the experiments.
So paying for everything personally.
Um you know I think similar to you just like credit score like in the toilet.
Um but um but yeah I just like it just made a lot of sense and like I wouldn't do it any.
Other way. Um and I'm super grateful for that because it it just like you know probably just crystallized the like general.
You know I'm incredibly.
Strict on the finances. were were relatively,.
You know, very lean by most comparisons.
Um, I would say and uh.
Yeah, a lot of that just came was birthed from like the pain of paying for, you know, everything with my personal.
Credit card or like,.
You know, we we do a high throughput screen and they'd be like, you know, hey, please send your, you know, have.
Your CFO send a PO and like, you know, for the $59,000.
Wire and I was like, you know, do you take credit card?
Yeah. So, it's like, >> did you put a $59,000 wire in a credit card?
>> I ended up wiring it directly for my savings, but yeah, it was uh Did you have a lot of money.
To start this or not really?
>> Not not really. I would say like you know there was a brief period of like you know software ventures that.
I did and um one of them became lucrative enough that it gave me the liquidity to do it but I mean.
I I.
For the most part have been paycheck to paycheck like literally since starting the company because I put all of that into.
The that was like the pre-recede money of the company.
>> What was different about the story that you were telling back then cuz I know you kind of threw a whole.
Bunch of nose and people falling asleep.
I imagine that you realize that something about this like if you want to get that money, it's probably you probably have.
To tell a slightly different story than you're telling in order to to do that.
What what changed? What shifted? >> Um it's funny.
I think like you know as someone who I'd like to pride myself on like updating my progress constantly.
Uh.
Weirdly at the time I was relatively like stringent about this.
Like I I think there was like, you know, maybe local fluctuations in terms of like I'd meet with the Boston investors.
And they'd be like, "Hey, your science is really cool, but like who the hell are you and like why should we.
Give you a penny?" Um uh and.
You know, and so maybe I kind of like spoke a little more formally or tried to be a little more, you.
Know, present in the way that I thought was like necessary.
I'm very glad that that like, you know, I equilibrated and like yeah, I just went back to just being me.
Um but um.
But yeah, I think like I was I was pretty strict about not like succumbing to that pressure because I really wanted.
People who were going to join the mission for the right reasons and if they were joining because they thought it was.
A like a very high probability thing or whatever like that was not the right partner I wanted to have for for.
The rest of my life. And so um uh thankfully like long journey came in they were the first ones to observe.
The same set of facts and be attracted to them versus like repulsed by like you know maybe I won't name names.
But like one of the people at long journey when I told him about the life savings thing um he was like.
That is awesome and it was the first person who was not like you're an absolute idiot what are you doing you.
Know that's going to go to zero um it was someone who like actually saw the dedication and actually appreciated the fact.
That I was so committed and um uh so yeah thankfully they came in and you know since then uh thanks to.
To the efforts of the team like it's been our fundraising has gone much more smoothly since then.
That was the hardest round to ever raise.
Um but uh but yeah, I'm I'm super grateful for it obviously in retrospect.
>> So if you have most people that you meet just immediately are basically turned off by.
I mean at least in the early days the idea that there's this like super low probability bet that will require a.
Ridiculous amount of capital to actually even have a like reasonable shot in like a huge amount of time maybe like 10.
Plus years. How did that kind of enable you to find and attract the right types of individuals to be supportive of.
The mission? >> That's a very good question because I think um I think again a lot of the advice I was.
Getting from the more like you know uh Boston biotech like archetypes was like you need to um you need to work.
Backwards from compensation. You need to go as high percentile as your burn allows you to.
You need to you know and they gave me all this advice about winning the great talent over with the amount of.
Equity and whatever else. And it just did not sit well with me.
I just was like, you know, my goal is again to assemble a team of best-in-class people that are missionaries, not mercenaries.
And that was.
Also something where I felt like I was getting constant external pressure to hire the right people.
Thankfully, I was uncompromising in that.
I was just really like so insistent on only hiring people who were going to work for the right reasons.
Um, you know, I probably.
Um uh will not reveal my kind of like proxies for what ends up being very predictive of that.
Um, but I I I certainly am like I've got a very long list of things that I'm looking for when I.
Meet someone. And I don't do conventional like hiring processes or whatever.
It's very like get to know the person over many many months and see how they kind of fare.
Um, and um, and be very sober with them about like you're going to work your ass off.
Um, you know, you're going to age much faster probably than you would otherwise.
Um, I'm not going to be able to pay you, you know, more than anyone else.
Uh uh and um >> I think that's actually a really good um test because a lot of like especially here in.
Silicon Valley, a lot of the people that are getting hired that are really really smart today are basically just getting ridiculously.
Massive compensation packages. And I think it kind of sets the wrong tone for why are you even working here?
Like why are you working on this problem?
Is it for you know $20 million or is it because you care about the thing?
I think the fact that you have seen a.
Um massive kind of exodus of a lot of really exceptional talent or like the constant you know velocity of like people.
Moving back and forth like that's indicative enough of that that model is actually like not the right way to go about.
This problem. Um, and so I think to whatever extent you can kind of filter a priority for those kinds of people,.
You're you're in a much better position.
At least if you're working on something, you know, if we were a pure hedge fun or were some whatever, like maybe.
It's a different story. But for me, um, you know, thank god I was very insistent on this and very like.
Um, yeah, like it kind of like weirdly turns out that the best people on the planet just want to work on.
The hardest problems. Um,.
And so, you know, there was an early process of me trying to recruit these drug hunters.
And when I'd go meet with like very talented people and I'd be like, "Hey, you know, I'm going after Alzheimer's."
They're like, "Sorry, Alzheimer's is just like, that's impossible.
Like, good good luck to you."
Or they'd be like, "Hey, I need if you want my advice on anything, you need to start paying me 15 minutes.
Into the meeting." And I was like,.
"No worries. Let's hang up here."
Um, so, you know, I had to like filter through a lot of people.
Took me a very long time.
Um, and then like one thing kind of flipped for me in terms of like the hiring process where.
I I basically started looking for people that were just like the secret geniuses behind a lot of the success stories that.
I respected the most. And so one of them was, you know, the example of that was um uh a thing um.
So Biohaven was a company based in New Haven that um licensed a drug from BMS called Remedipant and it was a.
CGP antagonist for uh migraine.
And um anyway they sold it for I probably shouldn't disclose the number but a very low amount of money and then.
Um after you know having a successful phase 3 and going on the market they were bought by Fizer for 11.6 billion.
It's considered like one of the great successes in recent history.
Um in the neuros.
>> and so everyone was like celebrating the executives that kind of like took that forward and to be fair like Vlad.
Cororic who's the CEO of and founder of Biohaven is like exceptional world class um but I was more interested in the.
Geniuses who like the medicinal chemists who actually invented those that molecule and um and so I ended up reaching out to.
Everyone on that patent the composition of matter patent for regiment um I was most impressed with the lead inventor John Mor.
And um and again I think like when I met John for the first time.
I basically told him like, "We're taking the biggest swing you can possibly take.
This is like very, you know, any individual program has a very low likelihood of success, but like my goal is to.
Literally get like the Avengers of drug hunting, throw them in a room, and just throw them at this incredibly meaty problem."
And John was like, you know, sign me up.
I mean, there was not a again, I think these other one of the proxies I look for is like the extent.
To which they'll negotiate,.
Right? John could get paid way more than what he's getting elsewhere.
And um you know, we've been lucky enough to to have him kind of come come out of retirement to be with.
Us full-time. And like that was just a a direct byproduct not of the money, not of the equity, not of anything,.
But like because of the passion and the nucleation of talent that we we've been lucky enough to do have.
Money is definitely one factor for determining or figuring out rapidly whether or not someone is more missionary, more mercenary.
But what have been the other biggest like indicators or signal for you over the past like three years that you've developed.
For figuring out whether or not someone's a missionary?
>> Okay. Um I will I will give one um version of this which is um.
It's been very predictive.
Um if if someone is willing to just like jam with me on science.
Um and uh and uh have no you know it's not a formal hiring process.
It's literally just like hey two people who are super passionate about this space let's just talk for hours unscripted just like.
Are they willing to do that and not only are they willing to do that once but are they willing to do.
That like many many many times over many months.
And for me, the people who are like the right people, at least for Babylon, are the ones who basically are so.
Passionate about what they do, they do this for free.
And like the thought of getting paid is just like sure.
I mean, like it's a secondary kind of thing, >> like a byproduct of the thing, but it's not.
All at all front of mind.
>> Absolutely. I mean, I think like, you know, um.
Yeah, like and it's so funny because it is almost like the midwip meme, but like I've just found that like the.
The best people in the world really are just so down to just chat science.
They don't the money is not what drives them.
Um and and you know there there's probably like a skew towards like you know something in there in terms of like.
They have to have some financial stability etc.
But like.
>> yeah the best people in the world really just love what they do so much that they fail retirement multiple times.
They're like in their 70s they still just want to chat science.
29 retirement. >> Yeah. Totally. I mean like you know John I'm pretty sure has failed retirement like two two times.
Maybe this is the first time.
No, I think he I think but Bill at least has failed retirement a few times and yeah, these guys are indehaticable.
I mean, like it's I've been super impressed with the stamina.
Like it inspires me to work harder seeing how how much, you know, how they when they do the 12-hour days when.
They're, you know, sending me emails at 4 a.m.
On a Saturday. Like these are the kinds of things that.
For me I just, you know, the command of ultimate respect like.
Late 60s, early 70s still working that hard.
Like they must really love what they do.
And those are the kinds of signals I look for.
At least did this sort of process where you're really trying to optimize for these people that are working on the problem.
Purely because they care about the problem.
Did you basically have any other approaches at the very beginning where you went in another direction because you initially thought that.
That was the right mode of operation and then kind of worked backwards and said no this was a mistake I'm going.
To go in a different direction.
Um I think there is like a really tough balancing act between um you know you you you may have acute needs.
That like you need to immediately reconcile and like part of that is a uh you know.
Ends up skewing you towards just like compromising your standards in favor of like moving very quickly um and plugging the wound.
So to speak. Um and like you know I'd be I'd be lying to say there haven't been like you know examples.
Of that. Um but uh you know overall I think our hit rate is is really high and like part of it.
Honestly started with LA who's our first hireer.
She's the founding scientist of the team.
She's um just an incredible workhorse and was like so so so.
Just like.
Dedicated from day zero. Like I met her and you know to be fair I think I'm audacious enough that like I.
Just I'll have people do the work and you know see what happens.
Um and so like first time I met her and I was still in New York at the time and I was.
Super impressed. Um, and I just said, you know, the next day I was like, "Hey, um, I'm stuck in New York.
I need you to start going to all these different labs that I'm looking at in San Francisco.
And by the way, some of them are like two hours outside of San Francisco.
And like, by the way, I don't really have money to pay you uh or I definitely didn't have money to pay.
Her generally, but I definitely couldn't pay her to um uh uh even get the Ubers cuz all of my money was.
Just like going straight to these uh these experiments I was running.
And so, um, she uh yeah, just was like, "Okay, I guess I guess you know, sure."
And uh you know she helped out as a friend for a long time and then uh you know things kind of.
Worked out and when she was finished with her postto UCSF pulled her in full-time but um yeah like that kind of.
Dedication I think set the stage for everyone else and definitely like held my bar very high in so far related to.
Future hires >> keeping the DNA right >> yeah keeping the DNA right and like it's like such a it almost feels.
Platitudinous.
At this point when people say like well the first 10 hires will define like the rest of your company but it's.
Like we're still super early days of Babylon like this isn't even chapter one in my opinion but it is um like.
I couldn't be more true. Um and I think just being like you know um.
Culture can only be defined by um what you're willing to fire for in my opinion.
And I just think >>.
Um >> yeah pe people are like very scared to do that.
But but in doing so they actually it's like an adverse selection for future hires because if people feel like oh well.
The bar is kind of like all over the place like that's not going to hire the best people.
And so I think just being super super strict about that and uncompromising even if you really like the person is like.
Really has been important for us at least.
So Alzheimer's is something where there's very long feedback loops and I think this is going into it you recognize this is.
Like a multi-deade journey where there's not really a very clear end date uh or like you know this is when we're.
Going to solve it. >> How do you both maintain.
That very long-term view while also keeping your you know foot on the gas as much as possible?
I think a huge part of why the team works so hard is because again like I've I've just filtered for that.
Upfront.
And like you know maybe this is ignorant but um I'm very much of the belief and have come to the realization.
That the super majority of management problems are actually just hiring.
Problems that are kind of masquerading as something else.
Um, and so, you know, I I don't have to like push the team to be working, you know, from, you know,.
Early in the morning to late at night.
Like, that is that's a byproduct of the people that I've happened to have filtered for.
Um, and and so I think like,.
You know, the the burnout thing is like um and again, like three years in, but like at least I personally have.
Been working this way for pretty much my whole life.
Like I think um when you're just incredibly passionate about something, there's just like a infinite resource um that you can tap.
Into. too. And I think the burnout does come as a byproduct of like not having impact.
So that that definitely matters and that's been said before.
But like yeah, again, like how are you able to get like a 67year-old.
Flying red eyes every other week from New Jersey and like working 12 hours a day?
Like I don't know. I think it's just like hiring for someone who is just built like that, right?
Like Dario on our team is built different.
Like he's he's a beast. >> Sam has talked about the idea of burnout in the past and I think he basically.
Said like work does not actually cause burnout.
What causes burnout is losing. >> Absolutely.
And if you're always winning and you feel like there's momentum, you never burn out.
>> Yeah. I' I'd probably like, you know, fork that idea and put like a correlary to it, which is like maybe,.
But um my revision actually of that would be that I think it's like a lack of agency that breeds burnout.
It's it's actually not like losing.
Um because if you feel like you had agency over the decision and it blows up in your face, I still think.
Like you you internalize that differently than if something blows up in your face and it wasn't even like you had no.
Control over the situation. >> >> Um, so, uh, I think just like continuing to make sure that the team like, you.
Know, feels that agency over these things and like they're working super hard, but like they also are able to, um, uh,.
Influence things like that that probably really matters.
Um, and I think like that's also just a byproduct of keeping the team super small is like, you know, the numerator.
Will always be one. You're always just one human being hopefully.
Um but uh but like keeping the denominator small just means that your contributions to the total like pool of activity is.
Basically much larger when um when you have a small denominator versus a larger one.
And uh I think that's why like a lot of really talented high agency people are leaving a lot of the like.
Hyperscalers is because they kind of like irrespective of how talented they are the denominator has gotten so large they're individual contributions.
No matter what how good they are is just like dimminimous in comparison to what it would be on a very small.
Delta Force team of like super talented people.
I've talked to a couple people from SpaceX and it's the same thing where, you know, if you have a single person.
At SpaceX, they may not have a huge impact on,.
You know, actually like moving the needle at that company, whereas they could take the same amount of action and have a.
Much bigger impact working on their own product or problem.
>> For sure. Yep. Yeah. I I definitely subscribe to that.
Yeah. I think Martin talked about this where he said there's just a whole bunch of going back to this idea of.
There's a bunch of drugs that are out there that have already been synthesized or made and they just haven't been properly.
Like productized for the right disease.
How have you kind of been able to.
Figure out >> how to go through that search space and figure out which ones are are worth going after versus not?
So, so my kind of like crazy vision for the future at this nexus is that um this is like a conversation.
I've had with Jacob Kimmel from New Limit and I he really like influenced the way I think about this specific problem.
But um you know John John Mor for instance like on our team like bonafide kind of like drug hunting genius like.
His track record speaks for itself but like you just you spend 20 minutes with that guy and you're just like okay.
He is like almost extraterrestrial.
Um, and I think like um, so.
John is is is let's say bandwidth constrained by his own biological compute.
Okay, he's he's one entity. He's one person.
He's like, you know, so so could you get a million John Makors in a server room trying to find new medicines?
Like >> I think that's a really exciting prospect.
Obviously, that's a great north star.
How do you get there? That's a separate story.
But, um,.
Yeah, that's like something that I've tried being thoughtful about.
Um and like you know I think part of constraining the search space is like just baking in really good priors baking.
In really good heristics and like.
Yeah so to whatever extent you know with our very small team like we've been able to kind of do that that's.
That's you know that's something I guess I'll just say that's something we we.
We think about a lot and like something we're building towards and like again this is one of these card flips that's.
Like not yet occurred but um but I I'm pretty sure it will be like a really good investment.
The first time that I talked with uh Lada, she mentioned that she didn't have a phone and it really confused me.
And then I realized that you also don't have a phone and I think that you're the person that she got that.
From and it's this idea of like eliminating distraction I believe and kind of eliminating the things that will make you be.
Able to leave the actual office.
How do you think about kind of eliminating distraction.
And just focusing on the thing you're actually doing?
>> Um I think it's just like.
My lens here is pretty simple.
Like I look at life through the prism of life minutes and >> life minutes.
>> Life minutes. Yeah. And if you're just like throwing away a third of your life like waking life minutes just like.
Into the abyss that's like probably like not net productive.
Yeah it's it's like something I think about a lot is just like you know you have this like it's the one.
Resource or currency that we're given in life and like you have to deploy those resources meaningfully.
So like where do I want to deploy my life minutes?
For me, the thing that I believe is the most important.
For uh uh just like my life trajectory is Babylon.
And I want to kind of like increase as much surface area to that as possible.
And so part of that is a distraction minimization.
Another part of that is just like, you know, not feeling good.
Existentially about this idea of just like throwing things into the abyss, like you know.
So, so yeah, I I'd say like it's probably Yeah, it's been like about three years now.
No cell phone. People are like, "Oh my god, how do you travel?
How do you like if you're stuck somewhere, how do you get directions?
And I'm like, speak to a human the same way we've been doing for millennia, right?
Like prior to this. So like it's a very recent phenomenon that's been like incredibly,.
You know, it's it's distributed itself so quickly that like now it feels impossible to imagine life without a phone.
But um but it's cool and like honestly at the least like when I tell people like at the airport and I.
Have them print out my ticket instead of like scanning a QR code like it's actually it's nice cuz it actually like.
You can just like see like something at least like some switch flipping somewhere in their brain of like oh this person.
Thinks a little bit differently. >> Yeah.
Well well yeah but like also like oh maybe it's like not the thing that I maybe is not as necessary as.
You know I may have thought and um yeah my my life has been like significantly enriched as a result of it.
How did you make the decision in the first place?
>> I had a very complicated relationship with my phone always.
Like in college, everyone always made fun of me because I I had the oldest version like I had an iPhone 4.
Until 2019, maybe 2020. Like that was that was my whole thing.
Um because I just I I think I just like saw the kind of like iteration rate like people basically conflating.
Change with progress as it related to the Apple products and being like, "Oh my god, you know, now I have this.
New a new icon for my YouTube channel."
And I was like,.
And there was actually a really sobering moment with the YouTube, like with the iPhone, where.
Um you used to be able to uh watch YouTube videos, which I'd like play music there, and I'd play a YouTube.
Uh like a song, close my iPhone, and it would still keep playing the music, and it was actually also a good.
Hack to get around the ads.
Um and then one day they pushed an update, and now I had a, you know, the red YouTube icon instead of.
The old like TV thing they had.
And then I no longer could do that.
And they got rid of that feature very intentionally.
And I was just like, we've passed the inflection point where like they need to kind of appease us as customers because.
The retention is just so amazing that like they can basically get away with whatever they want.
And I think like yeah, that just crystallized my like these phones are like not trending in the right direction.
So I started using like black and white everything.
This was like 2016.
Probably at this point. Um and then uh yeah, just like in college hated my phone and then eventually it just became.
A super easy decision when I started Babylon.
So, you just mentioned off camera when we were talking that you think the information to cure Alzheimer's is already out there.
>> Yeah. >> What do you mean by that?
>> Okay. So, I mean, look, it's it's like it's a crazy thing to say, but um but I think like you.
Know, the the the amount of information that's like, you know, let's call it the scientific literature that comes out every week.
That's like worth reading um relevant to whatever field is like has far outpaced our ability to read um just like period,.
Right? Like if you had a Nobel laureate trying to ingest papers every single week like.
Okay well it's just like it was intractable decades ago to even catch up on all the latest.
Um so for me the kind of like you know taking that to the extreme like if there's way more information than.
Any individual can like you know have uh to to be able to like determine what the cure is.
Yeah. synthesiz.
Allows us to.
Reliably let's just say ingest.
Information in text space or like language space.
Then um those two things together could probably be super powerful so like there are a lot of clues about Alzheimer's I.
Think there's enough clues for us like at the epidemiological level molecular level whatever to understand what is actually causing the cognitive.
Impairment and so like.
You know um and they come like often these clues come from very disperate fields.
So like in the world of like you know vaccine biology, it's like okay well well the shingles vaccine there's a group.
In Wales in like I think it was there were people born in the early '9s that's got to be before but.
Anyway people born at a certain time there was a mandate in Wales where if you were born after this cuto off.
Date you were eligible for the vaccine and if you were born just a just before you were not.
And so this was like you basically stratified the entire like whales population into two camps.
And so people that were born within a week of each other.
There's no.
There's nothing different about them except they one of them half of them got the vaccine, the other half did not.
And they found that uh people that um uh had the shingles vaccine were 20% less likely to develop uh Alzheimer's or.
All cause dementia. It was actually all cause dementia within 7 years.
Why? We have no idea. And that's because again these are very kind of distinct.
Uh fields of science that don't interface with each other directly.
So all we know is like you know the latent space of those observations like clearly there's there's like there's something there.
We don't have the common language to be able to interface with them.
And so I've gotten super excited about this idea of like this is something I've been toying with for years now.
But like, you know, with these LM kind of taking off, can we basically like a fine-tune these LLMs with our like.
Best-in-class team or whoever, but like just get very smart scientists to train these models to approximate some heruristic that they use.
And then just deploy these on like the knowledge graph of science to try and connect us like that seems really tractable.
And like we have more than enough clues to figure out like the you know perfect uh target for for something like.
Alzheimer's or other diseases. you started working I think with OpenAI.
To basically try to design models that are super good at this.
Um so how did that happen and what's the goal of that?
I mean so so it was like birthed from um a conversation I had with our leadership around this topic and it.
Sounded like you know the opening I had been thinking very similarly along those lines.
Um and so then from there um you know it it became a question of like.
If you want to fine-tune models to just be better at particular tasks.
Um the classic thing I always say is like you know for to to calculate an objective function you need to compute.
A delta to compute a delta you know in number space that's like a minus b it's a subtraction and very simple.
In string space that's levenstein distance.
In reasoning space that's like that's an unsolved problem no one's really like cracked that yet and so they were like well.
How do we kind of compare scientific hypothesis A with B if you know we want to train the model to get.
Better and better at generating good scientific hypothesis.
And so the calculus.
Was pretty simple it was like the closest thing we have to binaries in the world of biology is like clinical trial.
Readouts.
Um and it's not perfect but it's It's the closest you can get, I think.
And um and so we use that as a way to basically compute deltas to say like, okay, it either hit the.
Primary endpoint or did not. And then that becomes like a yes no kind of thing.
And from there you can compute a loss function finally in the world of biology and start trying to train a model.
To understand.
Um uh you know how you can map from the world of biology.
To the world of clinical trial like outcomes.
And my my dream for that project was like one day if we had a model that could reliably predict these outcomes.
Um and say like hey we're going from the world of biology now tell us what's going to work that one day.
We can do the opposite and say there was a successful phase 3 for Alzheimer's on this end point what was the.
Biology that we drugged.
>> and I think that was a bit you know idealistic let's just say like in reality that's that's not really that.
Wasn't a tractable path but um it's still something I think a lot about but u >> what else with the kind.
Of explosion of AI has unlocked or has has become made possible over the past couple years that would have been impossible.
For the past hundred.
>> I mean, you know, it just makes like I'm not going to say anything new here, but I just think generally.
Like you know, search space is like um you can constrain the search space much more readily and I think like not.
Being bandwidth constrained in terms of like as as humans we're it's very hard for us to hold like many many many.
Different things in context and so and models you know LLM are having that problem as well.
Um but like if you can kind of extract the like quantum of information that's relevant to you from you know hundreds.
Of papers.
It it it like reduces the compute complexity let's just say required to like actually get information very quickly.
So, like if I have clue A like in my mind and then I'm like, you know, deploying these bots to kind.
Of like retrieve relevant information,.
It's much easier for me to kind of like lay out on the table all the clues that I need to kind.
Of like synthesize together in one basket instead of the usual process which is like, okay, uh, I'm going to go read.
A paper. Oh, that's interesting. Let me now go read these like 10 other papers.
Now, let me go. You forget paper the first paper you read, but you know, by the time you're done with like,.
You know, a week of that investigation.
And so I just think it like your iteration loop is just much faster and that's probably a good thing.
>> You talked about controversial science.
Uh going to that. >> All right.
Um I just think it's it's super interesting when there is like a a collision.
Between like society and science and like you know what we as humans or society kind of like choose to do with.
That. Um, and so, you know, I think the proverbial example of this is like,.
Um, there was a researcher in the early '90s called Simon Lavey,.
And, um, I think it was 1991.
He came up with what he.
Dubbed to be the kind of neurological substrate of homosexuality.
And, um, and so this was a thing called the third interstitial nucleus of the anterior hypothalamus.
It was published in science, which is like the top journal.
And, um, uh, and, you know, it was featured on Oprah and like, you know, 60 minutes maybe um, all these things.
And you know he was expecting the Nobel Prize um and uh and by the way just specifically on the science like.
What he actually found was that um there's a small kind of nucleus of cells um that uh is 2.8 times larger.
In um in in heterosexual males than it is in homosexual males and women.
Um and so there was like no delta between the latter two groups but like a 2.8x multiple on um in the.
Size there on average. I think the N was like it was like 40 plus people.
Um and so there were a lot of critiques about the science like well some of these you know the the men.
That were the homosexual men that were enrolled in this were you know had um a lot of them died of HIV.
AIDS and like maybe that was a contributing factor or whatever but for the most part it was it was like just.
An observation he was not saying what to do with that um and.
He's expecting the Nobel Prize basically and instead he gets excommunicated from sulkq he joins some random you know institute he took.
A leave of absence.
Um and one year.
He gets completely like he becomes the scientific pariah of the century.
It's like, you know, the left hated him because it gave a therapeutic target for sexuality.
Um the right hated him because it validated homosexuality.
And so you kind of had this like convergence pinser attack that just like skewered him basically.
And um and so you know since then he's been a kind of like roaming intellectual and he's an amazing you know.
Researcher and all these things. But it was just so interesting that like when you have an inongruity between like well basic.
Science should be in theory agnostic to these kinds of things within the bounds of some ethics but like a discovery someone.
Should not be penalized for a discovery.
He didn't say what to do with it or anything >> and um >> he just literally showed like data.
>> He just showed data.
Anyway, he he's since been you know more or less like you know he's gone in the the winds of of scientific.
Discovery. But.
Um the irony that I think is like just like so.
Sobering is he's gay.
He just wanted to understand his own sexuality.
And so like and again I'm not like you know without commenting on like the science itself of of that biology like.
It is really just like and I don't even know what the right answer is there too because it's like I think.
You know it it kind of giving a therapeutic target or a filter for things like sexuality like that is like controversial.
Same with gene editing right like should we put a moratorium on all crisper research just because you can gened babies and.
Like some people think that's a bad thing.
I don't know. You know, these are these are these are maybe not questions for the basic researchers who make the discoveries.
To answer.
And and probably the period just like goes there.
Yeah. >> Is this idea that like science and discovery kind of progresses one death at a time?
How do you think about that >> in the sense of, you know, if we're living longer, how do we kind of.
Keep on pushing the envelope on science?
>> I think like.
Uh I think the the.
It definitely calls branches of scientific discovery.
I don't think you know.
Um I don't think the right if you imagine like a tree that like bifurcates constantly and like it's a knowledge tree.
And it's kind of like you have these different branches spirit I don't think the right way to increase the number of.
Scientific discoveries is to like prune branches and reallocate resources into like ones that are currently bearing fruits.
I think, you know, long history of of amazing discoveries coming from surprising places.
And so, um, you know, and this is part of the, by the way, the argument around like funding for the NIH.
And like, you know, academic institutions, like should we even still be investing in basic research or do we just need to.
Like concentrate capital in these other places?
But yeah, no, I I would definitely like reject the premise that like deaths are like, you know, deaths of scientific um,.
Inquiry or whatever are like the right way to go about things.
I think, you know, discovery obviously breeds further discovery and so we should be like whatever extent possible pouring gasoline on the.
Fire when we see that there's like a tiny tiny little something there.
>> I noticed on your website the first thing you see is not like we're going to cure Alzheimer's.
It's actually we want to give more time back with your like loved ones in effect.
>> I'm wondering what other things can you basically target in the process of trying to cure this specific disease like let's.
Talk about ner degeneration.
Um if you don't necessarily cure Alzheimer's, but you're curing other things that relate to it and like relate to neuro degeneration,.
Um you're able to give people more time with the people that they that they love.
Is this something that you're thinking about where you're trying to target this specific thing, but over the course of doing that,.
You're going to find other cures and and remedies for things?
>> I I think it'd almost be hubistic for me to answer yes.
Like I think you know is it um I think the process of like anyone kind of like pursuing a scientific path.
Is that um uh kind of going back to the bifurcation of different branches.
It's like there will be spin-off things that that hopefully bear fruits on their own.
And um you know the perfect instantiation of Babylon is one where the mission you know proves to be true um or.
Like we're able to achieve that.
Um maybe like the secondary one is that we're able to plant several flags that you know allow the field to kind.
Of advance further. And so, um, yeah, from that perspective, I think like, um, it's interesting the, um, I think like the.
Giving family families more time with their loved ones, like that's like a super important prism through which to look at this.
Problem because you want more quality time.
Like my grandmother had a really horrible.
Um, final few years. It was like.
It was not right for someone to go through that.
Um and so to whatever extent we can kind of like you know I think the longevity field generally is like you.
Have like people who are focused on health span and then people who just like want to increase the number of like.
Total life uh total life years lived and like I'm definitely not in the latter camp.
I think like >> just like suffering for the last 20 but you live forever.
>> Exactly like that that is just like obviously not good.
Um yeah, I think um there's a human element to to that kind of like you know um that statement as well.
Which is like.
You know I'm very we think in the world of like molecules and proteins and my team is like you know always.
Thinking through that through that lens.
Um, but I think an interesting kind of decision I made as well early on was like, you know, for us to.
Also get exposure to the other side of that, like go meet real human beings that are living with this disease.
Like, you know, we had a patient come in here the other week and or the other day rather.
And um, and that was like again, it's just such a like sobering thing to kind of see what's on the other.
Side. Um, and like volunteering at memory clinics, like these are the kinds of things where it's like look, you know, we're.
Kind of going through the lens of like a pharmaceutical that will help these people at the same time.
There there's like so much work you can do in the meantime, right?
Like I often wonder this that like you know for all these companies that are spending billions of dollars on this like.
And and you know ultimately they may fail to like have the drug the cure for whatever disease they're going after like.
Would they have just been better like with the kind of like AU of like overall kind of benefit to humanity just.
Been higher if they had just put like those hundreds of people to like you know volunteer in these like community centers.
Or whatever like.
I don't know like that's like that's a provocative question but like.
Yeah it's like something something that um at least we're trying to do both.
>> Yeah. And on the like volunteering at memory clinic side, you have basically I think every single week you bring your.
Team and your like entire team to go work and like help at those clinics um and just try to like keep.
Yourself close to the problem. How did you come up with that?
>> Yeah, it's not the the right cadence per se, but like you know it's whenever they let us.
But yeah, um I think the again like the calculus was like pretty simple.
It's just like we're working super hard.
I'm always pushing my team. Like you know the the big joke in the company is like you know what's Sasha's favorite.
Timeline? like it's yesterday and so like I'm always pushing these timelines, always cranking, you know, hard um and really trying to.
Get the team to to move with urgency.
Um and I think you just like internalize that urgency so much more differently when you like see these people and you're.
Like man like they deserve to live like you like you want to work harder to like give them the right let.
Them benefit from the eventual work if everything works out.
And like you know, I think the the the kind of thought experiment that I definitely try to have the team do.
Is like if you had a parent that like were suffering from this or like you knew had a 100% chance of.
Getting this in 10 years, like would you be able to live with yourself if you didn't work as hard as you.
Possibly could to like, you know, prevent that eventuality.
So yeah, I I think it's just like it's incredibly important.
I think more companies should do this and um for us has been just like rewarding on all fronts.
On uh the distraction side, you are basically like trying to systematically eliminate all the distraction in your life that doesn't have.
To do with Babylon. How do you think about basically staying focused on the the long-term mission.
While also basically doing all these other things in the meantime in order to get there?
So, you have to go make a bunch of money.
Like, if you had a massive checkbook of $10 billion, maybe you can do, you know, a different set of steps, but.
Because you don't have that, you have to go find those drugs and like >>.
Yes. >> You know, do whatever you do with them.
>> Yeah. I I think this applies.
In so many things just like this metal level concept but like 100% I think the um the need for a commercial.
Intermediate is almost something I quietly resent.
Um like you know in a perfect world like.
You know again someone would hand us like you know just a cart blanch to just work on this problem and I.
Mean a true cart blanch I think like we see a lot of companies that are incepted with like billions of dollars.
And like you know we'll remain those unnamed but like there's a lot of these mega rounds that are happening now in.
The bio space and you're seeing a concentration of capital into certain companies, but.
You do not see that balance sheet be put to work.
Like I think.
The balance sheet is incredibly like the the kind of like impact per dollar goes up or like let's call it the.
Impact per dollar is inversely proportional to the number of like people on the team because with a super small dedicated team.
Of like extremely talented people, um I'm pretty sure it's like better to give them the same amount of money than like.
A team that'll have hundreds of people immediately because their balance sheet now allows them to hire all these people.
And so yeah, I think it's like time to bureaucracy is like much shorter if you are like incepted with a billion.
Dollars versus like you kind of have to, you know, fight your way up to the top.
And you even see that with like a lot of companies that are started in downturns, like macro level downturns,.
Those some of the most successful companies ever were started in economic, you know.
>> Do you think that model of getting a bunch of money right at the start?
So like opening, you know, creating a lab and then just having, you know, like $3 billion or something.
Does that model even work or does it basically create the wrong muscle memory for commercializing a drug and making that work?
>> I can't speak from experience.
Um, so I will say that I can definitely say that being very very very scrappy early on um has just like.
Been imbued into the DNA of the company and like we will I hope and pray that we will never not be.
As scrappy as we we have been.
I think it's like it's been really um yeah integral to to how we do things at Babylon and that was a.
Pure byproduct of the early days where I had zero money and I was feeling that pain of like again just wiring.
Those money for my life savings that like that didn't feel great.
>> What like net results do you think are going to come from having that like scrappy DNA versus having a massive.
Checkbook? >> Um I think it's a forcing function to be a lot more thoughtful about like the decisions you make.
And um and I think like by the way I've done this to the extreme where like we've said no to a.
Lot of things we should have said yes to because I was just so like no.
It's like it's too much money is too much money.
And then 6 months later I'm like I really regret not doing that.
Um so like you know um thankfully it's been nothing that's like been actually like you know overall massively influential.
But yeah I think it just like it forces you to be a lot more thoughtful and uh uh and then just.
Generally like again it kind of hires for the right people.
This is part of the reason we haven't even announced like how much money we raise or anything like that is like.
I just think it puts a big neon dollar sign above your head and like it could just be a.
A kind of bat signal for the wrong talent.
Um and again I I don't want to like say that's the case cuz I've never been on the other side of.
It. But like at least for us it's been very good to just like not signal those kinds of things because then.
It doesn't become an inclusion criterion for the people that we hire.
After having those situations where you basically say no and then you later realize that you made the wrong call, how do.
You kind of update your decision-m going forward?
>> Um, I definitely feel the pain on a very emotional level when I make a a bad decision.
Um, and I internalize that pain.
I think part of like,.
You know,.
There are a lot of things where like, you know, maybe our first default is to just be like, "Oh, well, I.
Feel pain. That's a bad thing.
Therefore, I should like not feel that."
And obviously then there's like the second order of thinking around that which is like hey the pain is a good forcing.
Function just to get better and you need that as part of your gradient descent right like you need to feel the.
Pain of making the wrong decision.
And so yeah I think I just like you know I really have those like I feel it on a visceral level.
When I made a bad decision and I like sit with that.
I don't try to reject it.
I'm like good I'm glad that I feel the pain because it helps me you know informs the next decision I'll make.
And yeah I think it's just a pro process of kind of iterating on that.
What's your process for experiencing that pain and dealing with it?
>>.
Um, probably not like, you know, not one that's like optimal.
I think I'm just generally like.
Um, you know, I sit with it.
I write a lot like I have like a um, a notion uh, file which is just like stream of consciousness like.
Every now and then if there's something where I'm like, "Oh, I got like a real gut punch," I will just like.
Dump it out on the on the kind of screen so I can like read it back to myself honestly in the.
Future. And um, and I found that to be incredibly fruitful.
Um, yeah, I've had a rolling document since day zero of the company and it's just like my stream of conscious thoughts.
At all these different points in our our company.
And um, >> do you feel like after you have one of those setbacks and then you write it out, you're able.
To kind of work through it in a better way?
>> Yeah, that's that's for sure.
And I would say like, you know, the other thing is um having almost like internal proxies to like it's really hard.
To know where you are at in terms of like your growth rate.
And so I think you need to like look for these external signals that can give you a sense that you're in.
Like a high first derivative kind of situation.
>> And so the um my proxy for this is like time to last embarrassment.
And like you know if if you like if it takes you if you need to look back 2 years like in.
Your records to be like oh I'm really embarrassed that I like thought this way or that I like wrote that thing.
Or like spoken that way. Like that's probably like way too long.
And if you're really embarrassed by like even the way you were like thinking about a problem or like speaking you know.
Generally.
Uh like two months ago I think that's like you're in a high first derivative kind of environment.
So like that to me is is definitely my proxy.
I'm constantly looking back and just being like, "Oh god, I can't believe I was like so juvenile in my way of.
Thinking about this." I'm sure I'll say the same thing about this interview in, you know, a few months.
And and I like I hope that's the case, right?
Like I kind of want to constantly be checking myself on these things and and updating accordingly.
>> I would almost say that the uh how often you're being embarrassed is or you're embarrassed by the way that you.
Were thinking before or the actions that you took is kind of a proxy for the amount of risk that you're willing.
That you're taking at any given moment.
Um, and so if you're taking no risk and you're not changing anything anywhere, then you're probably not embarrassed at all.
Um, how do you think about risk- takingaking and like deciding what risks are worth taking?
>> Uh, that's a good question.
I put it in context with the rest of the stuff that we're doing.
So like again at the pipeline level when we look at the assets that we're working on like it is um nothing.
Can be taken like these things are not pisson in their distribution like they are very much beholden to each other.
And so if if I'm like, you know, I know when we're stretched very far in the risk dimension because I'm internalizing.
It constantly and then we have to hedge against that by, you know, having another thing.
It's not like a very mathematical formulism of like portfolio theory, but it is like how I think about just even the.
Portfolio of different decisions I'm making on any given time is like I think if we've overextended ourselves like just financially in.
The past like week, let's call it, I'll be very conscious of like the future deployment if I don't see an ROI.
In the like you know within a month or whatever.
Um, so yeah, I think it's just like spending a lot of time just internalizing these things, feeling like at a visceral.
Level. Like I think that's like a underrated thing is like if you're deleting all inputs except your company, you just like.
Internalize things almost sematically like differently.
And so um yeah, your intuition will like hopefully like give you a gut check.
Haha. Uh like a gut check on like you know, hey, we've overextended ourselves.
>> How has your intuition kind of updated over time as you gathered this new information?
>> Um I don't know.
I don't know. I think um.
You know, I'd like to think that um.
Yeah, I try to like take stock of like times where I've been like really like strongly like this is going to.
Happen and I've been wrong. Like those large deltas in like confidence and outcome is like those are really rich with information.
Yeah. And it just comes back to logging it, right?
Like you just like have.
Yeah. Like just like literally dump that into notion like man, I was so sure this was going to work and it.
Didn't. Or like the other way around.
Um, >> how often does that happen?
>> Hopefully like, you know, less frequently over time.
Um, I'd say in the early days it was it was like.
Once every few months. Um, and like now I don't remember the last time.
I have to dig up my notes.
Yeah. >> Let's just talk about like what causes cognitive impairment over time.
>> Um, in Alzheimer's, I mean, I think like a the answer is we don't know.
Um, it's obviously not unknowable, but we just like we don't yet know.
Um I think like on like a biological or like molecular level like what I think is going on is that you.
Know my favorite question to ask Alzheimer's people is like why are to fibrals toxic?
Um and tow fribles. So like we know that amaloid starts pausing 20 30 years before symptoms eventually that starts to lead.
To the hyperphosphorilation of tow um and that hyperphosphorilation.
Of tow ends up leading to the detachment of tow from microtubules.
And then like tao fibrillizes.
And it causes ner degeneration and like that final link is just like a huge question mark.
And so my like crazy theory that was really like the birth of Babylon.
Um was that basically these so so.
Um Tao is like a relatively like disordered protein that like forms a very specific structure when it fibrillizes.
Which just means it basically binds to itself and um and and uh you know maybe a note to the editor that.
Uh you should look up 6hre.
In uh the protein database and like that you know you can display that up on the screen but it's like basically.
It looks like um when talibrizes.
That's the the crystal or it's a crym of of the talibr.
It looks almost like a celery stock that's slightly elongated.
And then stacked up against each other.
Um, and it's like back to back two celery stocks and like if you're looking at a like you know bird's eye.
View cross-section.
And um and so they stack into these like long celery stocks and.
My strong belief is that they basically are sequestering essential proteins.
And these like really essential proteins that your body almost like nutrients for your neurons.
They're getting sequestered by this like uh this celery stock that's suddenly now in the middle of your neuron.
And um it's just like a sponge or like a black hole that's just like sequestering all these essential proteins.
And so it's the loss of the soluble protein that is like causing the cognitive impairment or nerve degeneration,.
Not the like actual just presence of these things.
So anyway, that that's like one kind of thing.
And then the other that I think is really interesting is um uh neuroinflammation.
And like you know um I don't know if you've ever had a concussion but like yeah they they they suck.
Uh I like phenopies.
Like when you have two things that are phenotypically like very similar like clin clinical presentation is like relatively similar.
I mean, this is like pseudoscientific,.
But it's like a way to gro these things is like a concussion.
Um, you know, you have like discombobulation,.
Like cognitive impairment, like short-term memory loss, inability to form new memories, like just kind of like, you know, sounds Alzheimer's.
Like um so I so I think it's wrong to like therefore conclude that the underlying path of physiology is the same,.
But I also don't think it's crazy to like start there.
>> So, it's a little bit A equals B equals C.
So, it's >> Yeah, kind of.
Right. Like I mean it's like it's just like observing like basically the same thing with like two completely different diseases and.
Then just being like well are there clues?
Yeah. Is there like a kind of like underlying thing between them?
And so.
>> you know a concussion like you know symptomatically like emerges like within seconds right like you get hit the concussive blow.
And then you like immediately feel whatever the discombobulation.
And >> >> um and so I think that that time horizon like the fact that the temporal resolution of that is.
Like on the order of seconds that's a clue.
And so like what's the only thing that can like mobilize that quickly?
It's probably and like immediately cause issues at the cognitive level.
It's probably inflammation.
And so you have this like immediate inflammatory response and like that's happening on the order of seconds.
And so like we know that more or less like I I'd contend that 100% of the like variance is explained by.
Neuroinflammation in the concussion case.
And it presents similarly.
Like does that port over to Alzheimer's?
Like that's a huge question mark.
And like again, I'm sure you know, >> is inflammation basically a massive indicator of future onset Alzheimer's?
>> Um, uh, well, so like inflammation seems to be long-term.
Um, which is where a lot of the like, you know, uh, vaccine biology is like probably linked.
Um, like systemic inflammation, but neuroinflammation.
Specifically like for sure and a lot of people have like tried drugging this.
This is like a thing. This is a known kind of mechanism.
But um, but what percent of like the cognitive impairment is like described by.
Specifically the neuroinflammation?
That's a huge question mark, but like my pseudocientific.
Kind of thing here is like maybe it's 100%.
>> Really >> and maybe the towel is just like a trigger for that.
>> So you mentioned that concussions and Alzheimer's are similar.
Are you able to take anything from like concussion.
Or research and port it over to Alzheimer's?
>> Yeah, that's like in a sense what I'm suggesting.
Like I think the the clinical presentation being similar is enough to just like at least warrant investigation beyond that.
And so yeah, there are things around like resilience and like recovery rates of co concussions that I think are interesting.
Um, and like definitely targets that I've seen in the Alzheimer's like OMIX data sets.
So like.
Yeah, again it's it's a bit of a like poor man's like you know estimate or like you know inquiry, but I.
Think it's a I think it's kind of fun to play with those like intellectually.
>> How many different little bits of information or indicators from all these different fields are you kind of thinking that you.
Want to take into basically solving this one mega problem?
I think the way that I think about going uh trying to cure Alzheimer's is just like you just you need a.
Fortress balance sheet to take as many orthogonal shots on goal as possible.
>> and you can have a very strong prior about the biology.
You're very likely to be wrong and so to whatever extent you can absorb the blows of being wrong in the clinic.
That's probably like yeah you just need to be wrong long enough to one day be right.
>> So your like success vector is effectively just creating a company that could take a bunch of hits.
>> Yeah, for sure. That's right.
That's right. and like.
Um and and then being like super super.
Um first principles about how you think about this disease and like again trying to be as orthogonal in biological space as.
Possible but like hopefully.
Synergistic and execution space where like the day-to-day looks very similar from like program A to program B but in biological space.
You're like hedging some of the risk >> other than actually writing down how you're feeling and and what decisions you've made.
What other things do you do to basically kind of prime yourself to be able to take hits as a person?
Um cuz you're basically the company yourself.
You're like the soul of the company.
So, how do you prime yourself to take hits?
>> I don't have an answer for that.
I I don't think I've done that well.
Um I think like I think I just like take them on the chin and just like sit with them and I'm.
Like ouch. Uh and >> you have like days where you just lock out and then you've you like unre recover and.
Then go back in. I mean, I think, you know, the process of like obviously being a founder is just like getting.
Punched in the face a thousand times a week and just being like smiling and asking for more.
Um, >> but most most companies are not designed like with the understanding that you're going to have a whole bunch of.
Failure on the road. >> That's true.
And like the failure like the scale of the failure is like so grand, right?
It's like, you know, if if we,.
You know, if we have a failure in phase two or even phase three, like that could be hundreds, maybe thousands of.
Patients and like years of work and like many years of work and like hundreds of millions of dollars and like right.
Like the scale of these failures is like pretty catastrophic.
So like yeah, I I can't you know um.
It's very likely that I will at some point know what that feeling looks like.
Um uh I I haven't had one on that scale.
I think generally like we just like calibrate to whatever distribution we're kind of like presented with.
So like for me I'm probably emotionally like in terms of the responses I've had so far to the things.
They may be small in absolute space like how bad the the blast radius of that thing was.
But like I'm sure the feeling will be the same when we start to like get comfortable with larger scales.
Um but uh but yeah, I think like you know there are definitely some days where I'm just like oh like you.
Just get like gut punch. It's like mainly when there's like successive gut punches and for me it's like it's never really.
Lasted more than 24 hours but like you know you just kind of go home that night and you're just like I'm.
Just going to instead of like doing emails I'm like I'm just going to like watch some stupid like Netflix thing or.
Like something like that. There's been a few times like that since starting a company of just like you just go home.
You just reset. You sleep and you wake up and it's another day.
I like will feel terrible for I can feel terrible for 12 hours like during a certain day you know something something.
Happens.
>> in the rare case like the biggest setbacks maybe it might be a couple days but then eventually.
>> what I would actually do is I have these moments where I would just like play video games for like three.
Days straight completely delete everything from my brain just play a video game and then by by the third day I get.
Bored and I'm like got to get back at it >> 100%.
Yeah, I yeah, deleting inputs is so critical.
I did it before Babylon. I I that was the first brush with like no cell phone whatsoever, cold turkey.
I went two weeks in a very remote part of Scotland, sleeping on a like shitty mattress like on the floor in.
A creaky old like cabin um chopping wood, you know, to make fire things like this.
Um, and.
It was like totally life-changing.
Because.
Yeah, I think like you know when you delete your inputs, you realize that like the majority of these things that we.
Misconstrue as thoughts are just reactions in thought space.
And that process.
Changed my worldview where I was like, "Wow, we're just being subliminally primed all the time in ways that we don't even.
Realize." And when you just like drown out all the noise, you just come back with a new perspective you've never had.
And that gave me actually the clarity to start Babylon.
So, um, >> yeah. What are the things that keep you up at night?
>> I think one thing that I've been thinking about lately that's, um,.
>> definitely been interesting to like sit with is like, you know, um, are these like it's the question I think everyone's.
Asking that's like, you know, some like level of AI adjacency is like.
Are the secular trends of like all these hyperscalers and the rate of improvement of these models is that just like always.
Going to exceed our ability to fine-tune on top of them?
Like if you're sitting at the application layer of any of these,.
Is there even room to like actually be ahead of the curve?
I'd like to think yes, but like it's been very interesting watching these trend lines of like constantly kind of like paddling.
To stay like just like ahead above what everyone else is doing.
And like it probably will become a thing of diminishing returns in the future where like you know the rate at which.
You have to paddle to like you know stay just like ahead above like everyone else is probably like going to have.
To increase so much so that it becomes intractable.
So like that's one thing I think about a lot that I'm.
Observing and trying to kind of like understand.
Um >> have you actually experienced like this acceleration in the past 3 years even?
>> Uh for sure absolutely. Um like I feel like everyone has felt that at some level like emotionally.
Um, and then also the um because I'm like totally convinced that fine-tuning will define the next decade of AI, but like.
I mean I think you're just going to see um a lot less people doing that.
Um uh because I think the infrastructure is also like non-obvious to support that with over on top of these LLMs.
And I think other people are kind of looking around being like, well, if if I'll spend all these months to like.
Fine-tune a model and then like three weeks later it'll be obiated by like whatever new model comes out from OpenAI or.
Whoever, then like what's the point?
And I think that's like probably a good existential question to be asking.