The Strange Attractor

A Deep Dive into Synthetic Biological Intelligence with Hon Weng Chong from Cortical Labs

January 19, 2024 Co-Labs Australia Season 1 Episode 6
The Strange Attractor
A Deep Dive into Synthetic Biological Intelligence with Hon Weng Chong from Cortical Labs
Show Notes Transcript Chapter Markers

Have you ever wondered what happens when the frontiers of biology and technology collide? Hon Weng Chong, the  CEO of Cortical Labs, sits down with us and takes us on a recap of his journey thus far. Starting with his transition from being a medical doctor, through to being a tech innovator, Hon takes us through the crests and troughs of startup life, explores some of the philosophic implications of his organisation and outlines the fascinating ways in which biological systems predict, interact and make sense of the world.

Join us as we uncover a symphony of stories that weave together medicine, technology, and the human spirit, like the tale of a medical student's crusade against childhood pneumonia using a digital stethoscope and smartphone wizardry.  We navigate the complex terrain of bio-ethics, the nuances of transdisciplinary collaboration, and the thrill of pushing the boundaries of innovation. 

Before we sign off, we turn our gaze towards the horizon, where the synthesis of deep tech and automation heralds a new era. 

Listen in to the unfolding tale where biology and technology converge, and be part of the conversation that's charting the course of tomorrow! 

Keen to know more about Cortical Labs? 

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This experimental and emergent podcast will continue adapting and evolving in response to our ever-changing environment and the community we support. If there are any topics you'd like us to cover, folks you'd like us to bring onto the show, or live events you feel would benefit the ecosystem, drop us a line at hello@colabs.com.au.

We're working on and supporting a range of community-led, impact-oriented initiatives spanning conservation, bioremediation, synthetic biology, biomaterials, and systems innovation.

If you have an idea that has the potential to support the thriving of people and the planet, get in contact! We'd love to help you bring your bio-led idea to life.

Otherwise, join our online community of innovators and change-makers via this link.




Samuel Wines:

Hello and welcome to the Strange Attractor, an experimental podcast from CoLabs, a transdisciplinary innovation hub and biotechnology co-working lab based in Melbourne, Australia. I'm your co-host, Sam Wines, and alongside my co-founder, Andrew Gray, we'll delve deep into the intersection of biology, technology and society through the lens of complexity and systems thinking. Join us on a journey of discovery as we explore how transdisciplinary innovation, informed by life's regenerative patterns and processes, could help us catalyze the transition towards a thriving future for people and the planet.

Samuel Wines:

This week, we sat down with the CEO of Cortical Labs, hon Wang Chong, and just had a chat about everything they're doing. It's a crazy cool company doing synthetic biological intelligence, which is just as crazy as it sounds, and a really, really interesting story about how he transitioned from being a medical doctor through to CEO of this company. So I will not say too much more and just jump right into it. Alright, let's go, let's get things started so you all might loop back to some of the things we've had a chat about. So yeah, hon, welcome to our podcast. Thanks for having me on the show. Yeah, no stress. Thanks for being able to help us co-create all of this sort of together. It's been a really exciting journey in the past year.

Hon Weng Chong:

I know it's been actually how many years has it been? Like five years?

Andrew Gray:

Well, since you first stopped by the little shipping container lab.

Hon Weng Chong:

Yes.

Andrew Gray:

Yeah, I'd say that was about five years 2018, 2019.

Hon Weng Chong:

I think it was 2018, yeah, 2019.

Andrew Gray:

Try to figure out how to fit you what was your initial thoughts.

Samuel Wines:

Oh shit, this is way smaller than I anticipated. No, I loved it.

Hon Weng Chong:

I'm still thinking about container lab idea, except it's just not really practical.

Samuel Wines:

Maybe it would be a fun way to do modular server racks in shipping containers that are called, that can be transported around the place.

Andrew Gray:

Exactly, it's possible. You could definitely modulate like. It just would be a big upfront infrastructure cost. But once you've figured that out, then you've got your labs and you can just plug and play them like Legos.

Hon Weng Chong:

I did see this at one of the longevity startups headquarters in San Francisco, in River City they actually had built out an entire like laboratory space. I think it was. What is it? I think they had 10 or 12 different containers just stacked with HVAC and so forth. But then again I realized that BSL2 is actually less stringent than the PC2 here.

Andrew Gray:

Well, yeah, the US BSL2 is self-regulated. So you just say yeah. I'm meeting the requirements.

Hon Weng Chong:

I know.

Andrew Gray:

Which is why, like you can like Garage, biotech is a legit thing in the US.

Hon Weng Chong:

Yeah, I walked in and I saw a sign that said BSL2. I was like okay, it's BSL2. But wait a minute, all they have is a wall with those ceiling in a warehouse. I'm like that's not really contained.

Andrew Gray:

And then even some of the things you can do in the US are pretty wacky compared to here, like you can have, I think, every Halloween. I see this like image of someone doing a jack-o'-lantern, but instead of having a candle in there, they have like bioluminescent bacteria that they've modified like outside, which would like freak out any of our regulators here in Australia.

Samuel Wines:

They saw that. Is that literally in your garden, in your pumpkin patch? No, no, it's on the porch, it's in the lab it's contained. It's within my property.

Hon Weng Chong:

It's in a pumpkin. Yeah, oh gosh.

Samuel Wines:

Yeah, so okay, you loved it. I'm glad that you thought it was pretty cool.

Andrew Gray:

Oh, and for reference, which there was bioquisitive that you visited back in the day it was bioquisitive.

Hon Weng Chong:

yeah, and for reference, it was Meow Meow who got us onto bioquisitive. Ah yeah, I don't know how I came across Meow, meow or something like that, but somebody, I think everyone just comes across it.

Andrew Gray:

Yeah, it's a Disco Gamma Ludo Meow Meow.

Hon Weng Chong:

And so I think he was like doing some biohacking stuff and people were like, oh, you should talk to him.

Samuel Wines:

Was it the? I think he went in the news. I remember like back then he was in the news for doing a sub-dermal injection of the Opal card. Yeah, he did that. Yeah, he did that he did his court case.

Andrew Gray:

He went to court over that. I think he I want to say he won Like he. He still had to pay the fines, but there was like it was still a victory for him and for cyborgs.

Samuel Wines:

What a fascinating human.

Andrew Gray:

Wow, so yeah. And then from there you I remember because you had an advisor somewhere else that you were sort of talking to around I think some early research that was sort of underpinning what you guys were doing, and he was sort of calling in.

Hon Weng Chong:

Oh yeah, yeah, it was a guy by the name of oh gosh, Steve Potter Steve.

Andrew Gray:

Potter yeah.

Hon Weng Chong:

Steve Potter. He was actually a really big deal in the early 2000s when what we were doing was kind of hot, and he retired, I think, in the early 2000s. So in the late 2000s, moved to Ireland and had an interesting life as a maker, in the makerspace kind of thing. And interestingly enough, I think in 2018, I went on a bit of a break and caught up with friends that I had done my research year in between my preclinical years at Melbourne Uni where I had spent time at Johns Hopkins doing medical informatics. And it's so interesting how the threads kind of are interwoven, because my friends there, henry and Sonia, both did their undergrads at Georgia Tech at Steve Potter's lab. Oh, wow.

Hon Weng Chong:

And I told them what I was doing. They're like hey, we did that 60 years back or something like that. You can connect with Steve Potter. So that's how I ended up connecting with him and his advice to us was if you're going to do this, you can't be purely just on the tech side and just rely on somebody doing the wetwear. You got to own the entire stack, you got to do everything clean the wetwear and so once I heard about that, I was like, oh, okay, I guess I'll just have to go set up a wet lab. I'll find some space. And I was like how can it be?

Hon Weng Chong:

Like Melbourne, the Biotech Hub of Australia, I start calling around and spoke to Melbourne Uni. Floria was like actually, we're out of space. And I called up Biotech 21 out of space. And I was like, oh, my god, who has space? And I spoke to Weehai and they said well, there is actually a space, but you'll need to take up like 2,000 square meters or something like that up in La Trobe, la Trobe Uni, or something like that. Anyway, at that point in time I almost gave up. I was like, oh, this is too hard, until I came across you guys and I started speaking to you, but then the container was too small and there was not enough space, and I still remember your auto club was actually in the rice cooker or something like that.

Samuel Wines:

I still have that thing, and sitting in storage.

Hon Weng Chong:

And we're not for the fact that we need a rodent culture Because we started out doing primary rodent cultures. We might actually have done actually, no, we might not have done it as well, because if we didn't, if we had to do stem cells, we would need a PC2 anyway and that was only PC1. So that led me down to contacting the Alfred, right, and somehow along the line, somebody you know is just referral by referral, referral they said hey, you know, there's a new lab being built by Monash of the Alfred. You should talk to Terry O'Brien. So I did and there was a space and we negotiated something and that was where we kind of got started. So, yeah, that was like what? 2019 or so, yeah.

Samuel Wines:

So what I mean just to double loop back on that, like can you tell us a bit about the journey, like how did you go from you know studying like medicine and obviously going over to Johns Hopkins, to then flipping the switch and jumping in a sea of cortical labs? Like what was the, what was the moment where you're like I'm going to pursue this instead of?

Hon Weng Chong:

oh, this goes back even further. So I graduated medicine in 2012 and in 2011, I went back to to Johns Hopkins for my clinical elective. So I did my research year. That was in 2008. And boy was that a real weird time. Because you know, it was post GFC in Baltimore, which is like the roughest, one of the roughest cities in America. And I still remember, you know, taking the bus down from New York and I'm like whoa, all these houses have no doors, they're all boarded up, kind of thing.

Hon Weng Chong:

And then I came back in 2011 to do my clinical elective and it was about that time that I caught up with a mate of mine, si Hormé. So Si was working as a developer evangelist for Microsoft and he was like, hey, you know Microsoft runs this competition called the Imagine Cup. You know it's pretty sweet because you know they have the competition all around the world in different locations and if you win they fly you there and all that stuff. And he's like, given that you're doing medicine, you're pretty good and pretty smart with tech. If you combine these two, you know you likely have a winner in your hands. And I was like, yeah, maybe I'll think about it. So that seated the thought in my head and came back to, to Melbourne. I think this was in. What was it 2012?

Hon Weng Chong:

Yeah 2012 and I had just done like a unit in global health in pediatrics, and what was interesting was that I had learned that pneumonia childhood pneumonia, and I think it still is the single largest killer of children under the age of five in the developing world.

Hon Weng Chong:

And now in childhood pneumonia, it's actually very easy to treat if you can differentiate between two types, right, the two types of pneumonia there's viral pneumonia and there's bacterial pneumonia. Viral pneumonia you don't do anything, you just, you know supportive care, oxygen and so forth. It's the bacterial one that you really need to give antibiotics, because if you don't A, you know they're 68 and secondarily, they also get sepsis and they die. Identifying, you know, the early symptoms of pneumonia and getting care was quite critical, but that was really poorly done, because one of the ways we do it and I still think this is the case is the most sensitive measure is respiratory rate, and we, what we do is we watch the rise and fall of a child's chest within 15 seconds and count that and multiply by four, which is prone to a lot of error, as you can imagine, because kids are like twitching everywhere and doing all sorts of stuff.

Hon Weng Chong:

So the other way that we do is also using you are using a stethoscope, so you plug your stethoscope in, you listen, you count inhalation, exhalation time, it and so forth. But that's a hassle because, a you've got to recognize what a breath sound is. B you've got to take out the stethoscope and all that stuff. And then it occurred to me what if we could remove what's this interobserver reliability issue where somebody might hear a sound and classify it as a breath in and a different person will hear it as a breath out or so forth? And then that causes the discrepancy in picking up child pneumonia by building a digital stethoscope that you could plug into your smartphone like a really low cost one. And I was like you know what that could work.

Hon Weng Chong:

So I spoke to Professor Jim Black, who was a lecturer at the I don't know if they still exist the Nostal Institute of Global Health at Melbourne Uni pitched him the idea. He's like this is really good, why don't you go ahead and try and do this? So I went back home. I got an old stethoscope not my fancy Lippman 3M one and I snipped off the head, pulled the snipped off the tube, pulled out the head, saw how it was all done and then got, went to J-Car, picked up an electric microphone, soldered the wires into a stereo jack, threaded it through to through the tubing and shoved it at the head of the base of the head of the stethoscope, put it into the phone and record it while I was on my chest and I was like oh my.

Hon Weng Chong:

God, I can't actually hear my heart sounds and record it.

Andrew Gray:

You are a maker at heart.

Hon Weng Chong:

Yeah. So and then I did the lung sounds. I was like, oh wow, I can actually also hear lung sounds. So that was the genesis of the whole thing. I came back to Jim. I was like, hey, I got this. Would you like to be a mentor at this ImagineCup stuff? And he's like sure. So I cobbled together a team. Andrew Lin, who's my co-founder at Clinic Cloud, joined in the initial team. Kim Ramchin, who's a made from high school, was like a Matts and Limpy genius. He was supposed to be doing the algorithms. And then Master Solay, he was also a computer science like, algorithm algorithms person. So we banded together. We named ourselves Team Stethoscope Cloud because we were like what's hot in tech right now? Oh.

Hon Weng Chong:

Microsoft has this Azure thing. Let's just have a cloud component where you beam the recording up into the cloud and all that stuff. So, anyway, we did that, pitched in the Australian competition and we won the Australian competition. So we got to represent Australia. Unfortunately, however, for that year we were the final competition. The global competition was hosted in Sydney. So instead of a trip somewhere exotic.

Hon Weng Chong:

We just went up to Sydney and unfortunately we didn't actually win that. We came third in the global competition. But what was interesting in 2012 was that Microsoft decided to put an extra thing in for the ImagineCup, which was the grants. So and I think this was actually more important than actually winning the thing where they invited participants who made it to top three to submit grant ideas. And we submitted a grant idea where we were going to take the Stethoscope and collect a whole bunch of data to see if we could train a machine learning algorithm to classify lung sounds for the respiratory rate stuff.

Hon Weng Chong:

And we actually won $75,000 from Microsoft, so took that money, put it into a research program at the Royal Children's Hospital and I think it was a what was it? I hired two research nurses. I had a, a maid of mine who was a pediatric registrar help out as well and did the experiment. So we we ran the trial, we collected close to what like 200 participants recording lung sounds, and then the idea also evolved a little bit where we were like not just doing respiratory rate, but we wanted to figure out how, if we could build an algorithm that could classify wheeze or determine like severity of wheeze so that the emergency department would not be clogged up with people, kids with asthma Right, because if you go to the RCH you go to any pediatric hospital like. I guarantee 80% of the time it's somebody with asthma.

Hon Weng Chong:

Just undiagnosed asthma or Undiagnosed asthma or diagnosed asthma that you know, parents can't tell whether it's getting better or worse because, they've done the protocol and they don't see any change or they can't hear the change right Because they don't.

Hon Weng Chong:

They can't, they're not trained to listen with a stethoscope. So that was the idea behind it. So, anyway, ended up doing that, I did my internship year at Frankston. At the same time I was hacking and building back end mobile app services and all that stuff to support that research program. And then midway through 2014, or was it? No, it's not 2014 or something like that my, actually no.

Hon Weng Chong:

Midway through my internship, my research nurse came up to me and said hey, do you know that I'm getting a lot of questions from parents about how much this dinky little stethoscope device costs and where can they buy it? And I said why would they be asking something like this? And she said I'll let me ask the parents. So she asked one of the parents, and one was like a parent of a child with a congenital heart defect and they lived all the way up in Mildura. So they were like well, I have to fly all the way down to Melbourne for a 30 minute console. That's like a three hour trip. If only there was a way for me to do this in Mildura and not have to come down. This was way before telemedicine became a thing.

Hon Weng Chong:

So you know, with that in 2014, after I finished my internship and did a couple of months of residency, I told Andrew about this and I said I think there's something in this, let's go check it out. So we both left our jobs. I mean put it on hold. He was at Bain, I was doing my second year residency. We put it on hold, get the whatever savings we had, packed our bags and went over to San Francisco with a very simple prototype. You know met a whole bunch of people. You know pitched the idea. They gave a couple of pointers and one person I can't remember who he was was like saying you really should go to South by Southwest. Mm.

Hon Weng Chong:

So we looked at it as like how much does it cost? Oh, it's within budget. So we just bought a ticket from San Francisco to Austin. Wow.

Hon Weng Chong:

And we just, like you know, just walked around randomly and we were told the advice was don't go for any of the day sessions because all the deals happen at night. So we didn't do any of the day sessions, we slept, and then it was good for us because it was like Australian, like nighttime or whatever, and then we just went to all the parties, came across a whole bunch of people, that's where everything happens.

Hon Weng Chong:

It's where it all happens and people were like, oh, this is really cool here, have a check as an angel investor. And we collected a small sort of angel round, came back to Australia, worked on a prototype and then we launched a Kickstarter or a self-starter, whatever they call it now a Kickstarter thing and that caught the attention of Ping Un Ventures and Tencent Ventures and they flew. They were like they told Andrew, can you come up, because Andrew was CEO and I was CTO at that time Came up, he pitched the thing. They're like we really like this, we want to fund it, so sort of the bad. He's like yeah, we got five million US to make this a thing, so that was a lot of money actually back in 2014, 2015. Yeah.

Hon Weng Chong:

So, anyway, that was like the start of my first journey with Clinic Cloud took the money, build a product. What was it? We took the prototype, made it into an FDA C certified device and started selling to Best Buy, Amazon and so forth. But the problem with one of the things when you do take venture capital money is that you're somewhat, you know, on the hook because you have to grow.

Hon Weng Chong:

And in order to raise the next trench, you have to grow two acts or three acts, whatever. We had massive difficulties scaling the business side of the equation because what we found and this was really the case in 2014 before COVID and so forth was that MedTech was not a thing and in many cases, a lot of people don't think about buying medical devices if they're healthy. It's like being in Vegas saying you should buy an umbrella, like why it doesn't rain here. I was like, yeah, on the opportunity, it does. So we couldn't really scale the business, tried many different ways of doing it.

Hon Weng Chong:

Eventually, you know, what really sank us was in 2016, when Trump got elected and we had secured a really big deal with the VA to supply them with the thermometers and the set of scopes, and that was our first big break. But then, along with the VA and everyone else, trump comes in and says I'm gonna rip up Obamacare and I'm gonna bring in Trumpcare. And so everyone who had a discretionary expenditure budget, which was where the money was coming to pay for our stuff, suddenly looked around and said we shouldn't spend the money that we've allocated for this discretionary expenditure because we have no idea where the money is gonna come from next year. So that was put in hold and I said that's okay, maybe Trump will come in and he'll figure out how to get Trumpcare through. Long debates ensues in months and months of negotiation. He proposes Trumpcare like, I think, mid 2017 or so, gets rejected and then we're back to square one. So we literally was just burning cash for the most of 2017.

Hon Weng Chong:

And then in 2018, I had enough of it. I was like you know what, we can't keep doing this, we'll close down. So, like what happened was Andrew stepped away from the thing. I inherited their business. I had no idea where to go with it and it was literally well, we got some money left. Let's just throw everything at the wall and see what sticks.

Hon Weng Chong:

And in 2017, Demis Hussab is the writer of paper in Neuron that I read in 2018, where he was calling for machine learning and AI people to re-engage with neuroscience. And I did exactly that. I was like this is really cool and we're trying to do something in the AI machine learning space. I went over to the Flory and I started speaking to people there and I said, hey, I'm a machine learning AI guy. Well, also from the doctor, tell me what's exciting in your world. And he's like, oh well, we have this device where we can grow in neurons and we can see the activity on them and we can give them a little bit of a jolt. I was thinking about it Like these neurons would have turned into a brain and we know that the brain computes. You now have a read and write access into these neurons. Why hasn't anyone gotten them to compute yet? Did the background research came across Steve Potter's paper once or twice, but nothing ever since then and I said, well, this sounds pretty cool, maybe we should look into this.

Hon Weng Chong:

So started working on this in 2018. That's how I got in contact. There was a lot of groundwork, a lot of infrastructure that needed to be done and the groundwork infrastructure I think that a lot of people forget about, and it was a big portion of what I was doing in 2018 was trying to figure out how do I do this, what do I need, who do I need, kind of thing, and came across Biquizidive and was trying to figure out this lab space thing. Came across the lab at Monash, at the Alfred run by Monash, and things were going OK until I realized we were running out of money and we would actually die in. I think it was like mid-2019. But that was OK because in the early part of 2019, it was March or so I was introduced to Nicky Skavak, who was the partner at BlackBid, and he made on my med Benjamin, who's an advisor now of the company. I was like you should really pitch your idea to Nicky. So I was like, ok, fine, this is so crazy, nobody would fund this anyway.

Hon Weng Chong:

Because what happened is interesting, because in 2018, while I was taking a break and I was just traveling around with mates from Hopkins, I was in Hong Kong and a friend of mine was like, do you want to introduce to John Tam from Horizons? And I was like sure, I'll talk to him about what we're doing. So I pitched him the idea and he's like this is really cool stuff, but it's a bit too crazy for us. And, to his credit and to his point as well, it was too crazy, like all I had was I had a hunch. I think this could work if I just had enough funding to get us across the line.

Hon Weng Chong:

The rest is history, because Horizons came back in and now they're actually our biggest backer. So they never say no to any meetings. You never know what happens down the line. So anyway, so where am I? So in 2019, we actually ran out of money and we had signed the term sheet and actually had negotiated everything with Blackbird, but we needed to get sign off from all these people to agree to taking this new trench of funding and to, I guess, recap and reincorporate the company as cortical labs, and we actually went into negative and I had to put in my own cash and it was so hairy. At the point I was like I'm 40k in debt with this stuff Maxing out credit cards.

Hon Weng Chong:

Maxing out credit cards and my bank account was getting close to the bottom part of.

Samuel Wines:

Wouldn't be a startup if that wasn't a part of the journey. Oh, yeah.

Hon Weng Chong:

And then I still remember taking walks around, laps around Falkner Park because that was where I was living and close by to the Alfred with my mate at Hooper and I was like mate, I don't know if I can keep doing this, I think I might just have to throw in the towel. He's like no, you're so close, you know, keep pushing, try to talk to Nicky, and stuff like that. And I still remember he was. I think they came down, they wanted to see the lab and so we did the meeting and I think this was like in September or so August or September, I can't remember exactly now In 2019, they came to see the lab.

Hon Weng Chong:

They were really impressed with what they saw and I was like I really need your help now because I'm trying to keep this afloat. I have one signature left and that was 10 cent. And I said can you just help us out and just wire us the cash, because I can't keep supporting this? And to their credit, they said look, we'll see what we can do. They worked it out. They said look, it seems like you have a verbal agreement anyway with those guys that it's only a matter of time before they sign it off. We'll wire you the cash tomorrow. What a relief, what a massive relief.

Andrew Gray:

I don't know.

Hon Weng Chong:

It always comes too close to the wire with Quarticle Labs. It also happened to us last year where in December and the reason why we were delaying it, we couldn't get started with CoLab was Wasn't it a signature you were waiting on right? It was also the same damn signature that was holding us back and we actually also went to negative territory.

Hon Weng Chong:

And this time I was supporting it again with my own cash, much higher this time because there was higher load, and one of our investors, Atlanta Daniels from Radar Ventures, was so great because I said, look, I got everything. I just need this one signature to come through. Everyone else can't wire it before because of different requirements and so forth. Can you just swap around the ordering so that you can buy the shares first, wire us the cash while the money is in the bank, I can work through to get the rest of it done? And she was so cool by saying, yep, no problems, I'll help you out with that.

Samuel Wines:

It's kind of one of those. It makes me feel like there's a few themes there like leaning in with curiosity and then also you don't know if you don't ask, and having the courage to be like, look, yeah, this is probably going to happen. It's with relative confidence, but can you help us out? And sometimes those unconventional things and being real and honest can kind of I don't know. It seems like it definitely helps and goes a long way. We've seen that happen with us as well 100%.

Hon Weng Chong:

I think the most important, one of the most not the most, but quite possibly close to the most attributes a founder needs to have is to have no shame, like absolutely grow the thickest, hardest, most callous skin that you can get. And just ask I mean, I get a lot of practice from Tinder, so it's all right. You get rejected a lot of times, but you don't know if you don't do it right. So don't be afraid to go up to somebody and say, hey, I need your help about this. Or trolling through LinkedIn going. I need an expert in this space. Can.

Hon Weng Chong:

I just find somebody on LinkedIn Kind of thing.

Samuel Wines:

And a lot of the time people at. First of all, I must say I thought you were going to say no shame and it's the Javierna's that you're wearing. That's no shame, Everyone's wearing Birkenstocks, it's 2024, but no, I've got time for the Javies. But yeah, I think the no shame and just asking, I think people are more than willing to help, like people want to help. If you give, if there's enough meaning and intent and it's a genuine call out and asking someone. It's not just like a copy paste, some narrative, like everything that we've sort of built along the way has been through that as well, being like hey, just like you know you're someone whose opinion we value, could you provide us some feedback, some thoughts? And more often than not, people go over and above.

Hon Weng Chong:

Yeah, 100%. I think the key difference is asking for help in an advisory way.

Samuel Wines:

Like.

Hon Weng Chong:

I don't know enough of this. Can you tell me about this so that I can go off and go do it?

Samuel Wines:

It's not like I don't want to build a codependency, it's just like there's this period, there's this bit that I feel like I know that you have a wealth of knowledge and you could save us six months of time and that also gets them involved and they feel like they're important and meaningful contribution to what you're sort of doing.

Hon Weng Chong:

Correct right and it reinforces identity for a person. Right. Let's say a person spent their entire lifetime working on a particular thing, and here's somebody coming up to them and saying I need your advice about this. That's actually really like a positive identity thing for the person giving the advice. What people don't like, however, is I need you to do this for me. Yeah right. Which is almost like 90% of when somebody's like hey, I need a favor. You know it depends on the favor right.

Samuel Wines:

Yeah, yeah, yeah.

Hon Weng Chong:

Right, and I think a lot of people walk away from that going, oh, this guy's an asshole, he didn't help me out and you're like, yeah, but that's not because he, you know, that's not because you're asking for his advice for you to go. Then take that advice and go do something with it. You're asking him to do this stuff and people don't have time for that right.

Samuel Wines:

Can I ask you a favor? Depends. Okay, For those who don't know who cortical labs are like. What is cortical labs and like what's your mission? What are you aiming towards?

Hon Weng Chong:

So it's a good question because it keeps it evolves over time. And initially I started out cortical labs as a bit of a curiosity I don't have stories of personal family or whatever mission. It was more of a how come no one's doing this kind of thing? So, very naively, I just wanted to build the biological computer Because I was like, well, if intelligence is a form of computation and if the brain is the organ that does intelligence, then it must be able to do some sort of computation. They're all interlinked. No one was doing it so I wanted to do it and I was kind of naive in thinking how easy it was going to be. It turns out it's much more complicated.

Hon Weng Chong:

But that's evolved over time and actually it's through the advice of important people who tend to advise us that the mission and the vision has evolved over time. So it's no longer purely just to build a biological computer. It's more about what do we have here and how do we use it. Is it even still a biological computer? The more we learn about what these neurons are doing, the less we are actually now convinced that they are a computer per se. And really I guess what we've settled on here now, as in 2024, is that we want to be building tooling to help scientists in this field explore the electrophysiology of these neurons and what it means to actually have closed loop systems. And what I mean by closed loop is that currently a lot of electrophysiology is done in an open loop, where stimulus is given to the neurons and that's it. That's very unnatural.

Samuel Wines:

That's not how a complex adaptive system works Exactly. It's feedback loops upon feedback loops.

Hon Weng Chong:

Exactly, and what we've shown with our work is that you need that closed loop for more interesting behaviors to emerge, like playing pong or the jumpy dinosaur game. And so that's now been our mission, and the reason why we're developing this CL1 product here is to make it more accessible for people to start experimenting with neurons, be it either they have a laboratory and they can grow the neurons for the system, or we grow the neurons for them in a remote sort of cloud setting, but allow them to experiment with code, with systems, to probe and to get the results back and analyze it. So that's really our goal now, which is, I guess, in a sense, to still try to build a biological computer, but now with a lot more meat around the bone to say what exactly is this biological computer? How are we going to program this, all the nitty-gritty, specifics and details of what's going into it.

Samuel Wines:

Right, and just to riff off that, I've heard you before say that you're kind of looking at trying to build the next navidia. So that's the hardware side of things. But what you just sort of expressed there is that you're also looking at how do we co-create or collaborate with others to make the software side of things or the wetware side of things, let's say so the way we've started to define what a biological computer is is that take your traditional computer.

Hon Weng Chong:

It's got two components hardware fixed at the factory and what gives it its specialness? Special sources of software where you can make it do a lot of dynamic things. Now a biological computer now has a third vertex. The wetware the wetware and you now have more combinatorials between your software and your wetware alongside your fixed hardware.

Samuel Wines:

Because it's evolutionary, that's the.

Hon Weng Chong:

Thing.

Samuel Wines:

It's like when you're dealing with neurons or something that's alive. It's a dynamic process. It's not fixed, it's not static.

Hon Weng Chong:

Correct, and it's in real time, it's analog. That's the key bit, which is that analog is the real world and that digital is really an abstraction of that. And so, as you said, it's evolutionary, it's happening in real time, kind of thing. And not only that the neurons, all these cells, all these living organisms around us right now, we're a product of billions of years of evolution. Each organism has well, each organism exists today because it's been able to survive in depth to that particular ecological niche and with that also it inherits what I call, personally, genetic priors, for instance, a genetic prio is another way of talking about instinct. How does a spider know how to weave a web if it's never seen one? It's because of the genetic prio, it's encoded in its genes.

Samuel Wines:

It's the wetware.

Hon Weng Chong:

Correct, it's the wetware that has learned that.

Samuel Wines:

And what's so fascinating, when I hear you say that it's also then like what happens if we do an octopus brain Correct, or what happens if it's a whale brain. How does this impact the way in which the neurons respond to their environment? Because, in a weird way as well, you're abstracting them from the original context that they're from and putting them into a new one, but you're still having these priors which you know are going to play an impact on it within this new space, and it's just fascinating, it's so interesting seeing what can happen, right Like I remember we don't 100% have to go there, but there was neurons that seemed to almost be reacting Of the cardiac ones, yes.

Samuel Wines:

That was fascinating.

Hon Weng Chong:

Yeah Well, I mean, we know for a fact that mouse neurons don't play a pong as well as human neurons. That's something we've observed, so it'd be very interesting to see what Kephalopod, like an octopus one, does. Having said that, octopus neurons really different right. Apparently, even temperature will change this epigenetic like gene expression. Wow.

Samuel Wines:

Didn't someone want to bankroll you to do something?

Hon Weng Chong:

Yeah, somebody did, but then I think this person was a crypto bro with ADHD, and so he kind of got distracted by something else. Yeah, so it's actually quite sad that we don't have more discoveries in this space.

Samuel Wines:

Well, thinking of just like, how can we simulate other minds and will that help us better understand or potentially interact with them? Yeah, it's just a fascinating yeah.

Andrew Gray:

And I imagine as well with as technologies improve across, like within this space, not just with what you're doing in the lab, like when you start messing around or experimenting with organoids or three dimensional structures, probably, I imagine just keep learning new and new things about how these neurons work and behave in a group. What do you call cluster?

Hon Weng Chong:

Yeah, yeah, I think that's definitely going to be the case. But for me personally and you know, something I've set the team to look into we think that actually the bottleneck isn't in the size of the neurons, right? Because if you think about it, if fly only has 100,000 neurons, we're going to like 500,000 to 800,000, like 500,000 to a million neurons. It's kind of hard to pinpoint exactly, but we certainly have more neurons on the dish than what a fly has. You know, a fly can navigate the world, it can avoid being killed, find prey sorry, find poo and reproduce right or a thing that makes a fly happy.

Hon Weng Chong:

Yeah, I mean, flies are actually amazingly like powerful for the amount of energy that they use. Imagine a drone with a fly brain. Right, it could probably just keep flying forever.

Samuel Wines:

Yeah, it wouldn't get shot down either, it wouldn't get shot down. You know all of these things, but then what that makes me curious about is the genetic priors that you're speaking about, so correct me if I'm wrong. I don't want to be anticipating something that you might be looking at exploring, but it's almost like at what context would a certain type of brain be applicable for a certain type of technological device? Is that kind of a direction or an area that are looking at, leaning into the future? Yeah, definitely.

Hon Weng Chong:

I think that's something to look into. I mean, the most frequent question is, like you know, if you've got a pro gamer's cells and play this against some random person, would the pro gamer cells actually outperform them in particular games, right? We don't know.

Samuel Wines:

Got to get that tetris, the kid who finished Tetris' brain, onto a DSC. What happens?

Hon Weng Chong:

Exactly Get some, you know, e-spots champions, you know, get them in the game of Doom or something like that. I don't know, but you do raise a good question right About that. However, there is also a school of thought in machine learning and AI about the embodiment theory, that you cannot get AGI without embodiment and intelligence is actually shaped by the particular embodiment these systems are in. Which is to say that if you had human brains in the mouse body, you wouldn't get the same intelligence, and you might actually get better intelligence with the past brain and like human embodiment. That's it.

Samuel Wines:

Because I have heard, like is it the four E? Cognitive science? Like the embodied enacted, like there's all of these things. I can't remember them off the top of my head and I haven't been able to get chat GBT up quick enough to get it. It feels like, from what I can tell by reading the literature on cognitive science, that is a really big element that when you're, and because you're obviously taking them out of that context, like what does and as you're saying as well, like there's might be up to a million neurons, right, so there is something that it is like to potentially be one of these dishes.

Hon Weng Chong:

Yeah, and this is the really cool thing about like the, the, the, the bio-ledge computing system, right, If you want to change it, the embodiment, you can do it in software. The software gives these neurons embodiment because now they have the ability to to take in sensory information from a virtual world, process it and then action on that simulation world based on how you've encoded the embodiment. So, in the case of Pong, essentially a bat.

Samuel Wines:

Right, so you, yeah, this and this is your body part. And then because, because please go on how, how you manage to make it, I guess, how you taught it to play Pong through the reinforced feedback loops. Yeah, That'd be really cool to hear.

Hon Weng Chong:

Yeah, so essentially the where we got it to play Pong was we use the theory developed by Professor Carl Friston at UCL called the phantry principle, or that was one of our guiding principles.

Hon Weng Chong:

There might be other things. I mean, we also put some thought into heavy emplasticity and learning and so forth, and what we said was look, you know, we didn't have the ability to use dopamine because we had a purely electrophysiological system, no chemical reward and so forth. And we said, well, based on this phantry principle, which is very complicated I'm going to try and boil it down to the brain Instead of the traditional way of thinking where photons hit receptors, gets processed and an action then happens, it's actually the inverse, where we're actually predicting ahead of time, using a generative model of what the world is and the senses are actually providing us input, where we then determine how closely our generative model is reflecting the real world. And the whole point of biological systems is to get really good at predicting the world. And, if you think about it, that's a prerequisite for survival, right? If you predict the world accurately, a you can avoid being prey and find prey better.

Andrew Gray:

What goes to those instincts that you were talking about before?

Hon Weng Chong:

Exactly right. So somewhere in these biological systems there is a genetic prior, the very important genetic prior for intelligence, which is trying to create a generative model of the world and to accurately predict that world, based on the senses and also our motor functions in changing them. So if those are the properties that we are looking for, we figured that if the desirable outcome was to move the paddle to hit the ball, the neurons would need a positive signal for that, and the positive signal was in the form of a sine wave, and if they missed the ball, we would give them a random, noisy signal. Now, there is a reason for that. If you took two signals, a sine wave and a white noise signal of equal length, you can actually summarize the signal, at least with a sine wave, into one function. Right, Because from one period you can predict n number of periods going forward. So that has what we call very low information entropy. And a random signal is unpredictable because from one segment you can't predict n number of segments. Right, so that has a very high information entropy.

Hon Weng Chong:

So entropy is a really important measure, right, so it's used in everything in computing, particularly in things like file compression. Right, Like your zip file. How does it know how to compress something that is like a meg down to like sometimes like 10 kilobytes? Well, it realizes that there are sequences that repeat over and over again. So, rather than encoding all of these things like, the simplest way I can explain to you is like saying, if I had the sequence of ABC, ABC, ABC, rather than writing out you know the characters, nine characters all the way through, I can summarize it by saying take ABC multiplied by three in a sequence right? So that is a compressible piece of information and therefore a low information entropy. So, yeah, it turns out that these neurons are seeking low information, sorry, seeking low information entropy targets. So by being low entropy, they are predicting the world more effectively.

Samuel Wines:

So if I was going to interpret that, what you're essentially saying is that they like an ordered signal and that kind of and that allows them to like coherently communicate as a collective. So you might get a whole bunch of random signals, but if you start picking up on a concert of sine waves, then it knows okay, great, that's when I you know I'm firing or something.

Hon Weng Chong:

Yeah, exactly, and we haven't done any formal thing around it, but it's kind of intuitive. You think about that and have impassivity, which says that if two neurons fire together, they wire together. Right, your chances of a coincidental event happening increases if you actually have a predictable signal as opposed to a random signal.

Andrew Gray:

So what does a happy neuron look like?

Hon Weng Chong:

Well, I don't know what ha like. I mean happy is a, is a is a very used it very yeah. Anthropomorphic term but we do know what the healthy looking one is Right and healthy cells are ones that have good electrical activity, that has to adhere to the surface of the, of the chip and and have very good synaptic connections. So morphologically we can, we can tell what they, what a healthy cell is happy? Not quite sure.

Andrew Gray:

So when you, when you give them a sine wave, for example, is there like an observable behavior, is the behavior firing versus the random noise?

Hon Weng Chong:

They start to coordinate their firing patterns. Cool yeah.

Samuel Wines:

So they, they sync up, which to me it makes sense Like, given that I know as well like neurons also sync up through like multiple things, like they pick up on vibration, they pick up on like electromagnetism. There's so many different things and I'm wondering if, like, yeah, so fascinating thinking about how, how all of this sort of works, and imagine being able to ask them like, how are you feeling today?

Hon Weng Chong:

I mean, maybe one day we could do that At the end of the day. You know, if you think about it, it's kind of what we're working towards as well. Right, Can we build these things where you can actually start probing them? And they give you responses back and then you can teach them to do things Right, because the moment you can start teaching them to do things, you now have a programmable system.

Samuel Wines:

On that note, I remember chatting with you would have been maybe about six months ago. You actually had some pretty interesting progress on that front with programming of neurons, something that might have been a I don't know if it was a world first, or at least it was the first time that I heard about it. Yep. Do you remember that conversation about the encoding information into neurons?

Hon Weng Chong:

Oh right, yeah, so we've been looking at. We've been looking at how do you, how do you take digital information right, which is? Take, for instance, a JPEG image. Jpeg image is your width times, height times three, right, because you have RGB channels and your RGB channels are zero to 255. Let's just say you know that's how you encode information thing. So all digital information is presented in the form of a vector, matrix or a tensor. The JPEG is a tensor of width times, height times three, of numbers that go from zero to 255. People have said why don't you just connect these neurons to a neural net and see what happens? I'm like, yeah, I could. But then again, what the hell does a tensor mean to these neurons, and let alone a tensor that is just these numbers? Because that's not how the neurons work, that's certainly not how a vision works, right.

Samuel Wines:

It's like trying to play a vinyl, like on, like you don't just plug your headphones into a vinyl, or something right. It's like a different way of like different operating system 100%.

Hon Weng Chong:

I mean, it's just. It's just. It's just not how the physical world works, right? So if, like, take your example with vinyl, vinyl is essentially all the grooves and you have that little head and you know, every time though it hits a groove it vibrates a little bit. On the other hand, a CD is just bits, right, like you know say so, you hear these terms like 16 bit, 44, 100 hertz, right. What that actually means is that when a microphone or something that is picking up the recording that is put into the CD, it's getting a number that is 16 bits in integer, right. So it can go from zero to, like, I think, 16,384 number or something like that, or maybe more. That's probably eight bit. So double that number, so 32,000 or so, and each of those numbers represents some point in the sound the audio spectrum.

Hon Weng Chong:

In the spectrum, and the 44, 100 hertz is how fast this microphone is splitting up time. So and this is a very interesting thing, because time is a bit of a weird dimension in computing space it doesn't really have a concept of that. But let's just say you have 44, 100 hertz. It means you take one second and you're slicing the thing into windows and at the end of one second you're getting at 44,100 windows of a signal, and that's just how audio works right. And so when you take 16 bit audio, 44, 100 hertz, and you feed it back into what we call a DAC, a digital analog converter, it's like an audio interface.

Samuel Wines:

To keep the metaphor going.

Hon Weng Chong:

Correct, yeah, you take that and that will take each of those points right and play it back. And it takes that and it vibrates a membrane and that's how you get audio back from recording to that. Now, if you took those numbers and you put it on a vinyl gramophone kind of thing, it just has no idea what to do with it. Same thing with the neurons. Right, we can get these matrices in tensors. You put it in neurons, like I have no idea because neurons it's got no context for it. Exactly, neurons speak the same lingo like a vinyl record, that it does it as a time encoded thing. And so what we've been working on and we've had some breakthroughs here is trying to convert the digital representation of, say, mnist, the Henrydon digits, into spike trains that we can feed into neurons. Now we're building new hardware, so once the new hardware is online, we can then start training the neurons by feeding these spike trains in and see if they can recognize the Henrydon digits.

Samuel Wines:

So in a way, if I was going to interpret that, it's like you're trying to create a language of coherence that they will be able to understand, like that audio interface layer.

Hon Weng Chong:

Yep, it's the translational layer and this is the really exciting thing as well, because it has not just impact in our field, where the end, like one of the North Star goals, was to still try to get to the play doom, but real doom, like pixel-based doom, not like the top-down view of doom, the pixel-based one. This is also really important the brain-computer interface space. Right now, brain-computer interfaces are limited to read. Only. The only real right-capable brain-computer interface today that we have is the cochlear implant.

Samuel Wines:

And just for context, because as soon as I hear right I just think oh gosh, brainwashing. But I assume that your meaning more so like hypothetically someone could have epilepsy and you could send a right code to sort of essentially like a stop program for I mean, we already have that today, but more so, not really brainwashing, but think about it.

Hon Weng Chong:

How could it be if you could just think a thought.

Samuel Wines:

Learn French.

Hon Weng Chong:

Yeah, or you know. Essentially what we have is our smartphones today. Right? Someone like wants to show you what the view of the world is. They take a photo, they send it to another person's phone and that person sees it on Instagram as what the representation was. But imagine if you could encode information.

Samuel Wines:

It's just removing a layer, so it's almost like literal telepathy Telepathy.

Hon Weng Chong:

Wouldn't it be cool if I could see something from the same perspective?

Andrew Gray:

Yeah, I mean that actually might solve a lot of.

Samuel Wines:

I think most of our problems in humanity come from back communication and the inability to perceive another's perspective, or from a holistic perspective, rather than an individual, isolated atomic reductionist sort of randomly in the world.

Hon Weng Chong:

It is a little bit black-mirror-ish. We don't know where this technology could go. But what if you could actually tap into the amygdala right and read the activity of someone's emotions? Like you know, somebody could be struck with grief. You just don't know about this and it's encoded and you're feeling the same thing because it's transmitted of the wire. And now there's a decoder that we can then decode it back into what you would feel the same thing in your brain.

Samuel Wines:

That's fascinating to think that you could feel someone else's emotions.

Hon Weng Chong:

Right. I mean those are kind of the things that an encoding-decoding bit for the neuron to digital system, one they could unlock.

Samuel Wines:

And I imagine that you could also potentially, depending on the bandwidth of knowledge transfer, you could potentially like this is going to go crazy. You could potentially screen someone's visual field and you could potentially observe their visual field from another location. Yeah, theoretically. That's yeah.

Hon Weng Chong:

Theoretically, that could be a thing where, if we could, you know, tap into the visual cortex and we could stream information back out and into a digital system we could see on the screen, or if I could write back into your brain. I could write what you saw into your brain and go oh my God, I'm actually what's the word? Vicariously living through a person own eyes.

Andrew Gray:

It's like a whole other Twitch platform right there.

Samuel Wines:

So fascinating, but so many ethical questions 100% which is the thing, right.

Hon Weng Chong:

So there was a post that came up recently Tom Oxley posted on LinkedIn about bringing computer interfaces. And how do you think about it? And I say it's very simple. The simplest way to think about bringing computer interfaces is that every great leap in computing comes with a change in human-computer interaction. We had the terminal to begin with. The first big computing revolution was the GUI. That's how Windows became a thing. That's how Microsoft became the most valuable company on the planet. What happened for them to be disrupted? Touchscreens, the smartphone. Apple won that war and I guess Google as well.

Hon Weng Chong:

The question is what is the next thing? Some people think it's AR, some people think it's VR, whatever right. What we don't know is what's in between. But we know that the end of the line is a brain-computer interface Directed the brain. So if you just think about that and just go, you know what, I'm not gonna bother with anything and be in the middle and I'm just gonna go straight for the end of the line. If you own that technology, you have a technology that is indisruptible, very powerful, but also very scary kind of control.

Andrew Gray:

And so it's really heartwarming to see that you guys are already writing papers on ethics. That's gonna be my next thought. Did you have an ethicist in residence, don't you?

Hon Weng Chong:

We don't really have an ethicist in residence, but we do work very closely with people like Julie and Sevillescu and so forth, who you know. At the end of the day, ethics is and I keep saying this is a conversation. What I mean by that is that ethics, just like values, change with time and with societies right. So, for instance I give you a good example would be IVF very acceptable today, even I guess governments are now subsidizing it. But it was only just, I think what is it? The 70s I think it was only 40 years ago where it was looked on as an ethical technology?

Hon Weng Chong:

You know, we're meddling with something that God could only do or something like that right, and a very religious base. That's completely changed because of time, because of society becoming more used to it. We're seeing positive outcomes come from it happier families and couples and so forth. I mean we don't really talk so much about a negative thing like potentially screening for particular traits or so forth the Gallagher style. But, as I said, that was one of the things that people thought about and why it was not a good thing to allow Other things, societal things like gay marriage right, tell that to anybody in the 50s. They'd be like get out of here. That would never happen.

Hon Weng Chong:

Values change, so ethics also have to change, and I think this is the reason why we've engaged with the biathesis, because we do it as a way of saying what is the current temperature today, what are red lines that we should and shouldn't cross? But what are the things that are informing for these red lines, you know, and then, as time progresses, as people get used to things, it's like the Alverton window you keep moving it up. You then sample it again. You say what is the temperature now in the room? What are acceptable and unacceptable things? Right, because, for instance, what if and this is a very interesting hypothetical the pathway to creating a cure for things like dementia or Alzheimer's, dementia or Parkinson's requires the creation of potentially semi-conscious organoids. What is the risk? What's the trade-off? We really have conscious beings, or partially? It depends on what your consciousness, your definition of consciousness is, but I think a mouse is pretty conscious.

Andrew Gray:

Like right.

Hon Weng Chong:

And we sacrifice a lot of mice in laboratories to find cures for diseases. Right, we as society have deemed that an ethical use of animals.

Samuel Wines:

It is getting phased out, I will admit but I mean you're actively looking at finding ways in which you could use organoids to address that right Exactly.

Hon Weng Chong:

But then there are these red lines that people are saying what about a conscious organoid?

Samuel Wines:

What about all the other humans that we? Everything you're saying is like I agree, but it's almost like. To me, it feels like the layer that we need to be working on is the human-to-human interactions and how we relate to one another and then how we can be wise stewards of the technology that we're co-creating. And I think this is happening. Yeah, as you said, there's a conversation that happens adjacent to, but yeah, it's still a.

Hon Weng Chong:

Because it's a very interesting ethical question, right, like, let's just say you're very let's just say with animal studies, right?

Hon Weng Chong:

And you are very much against the use of animals for experimentation and testing. Yet, let's say, your best friend's grandfather is dying of dementia a slow, horrible want to watch death. Who's more unethical now? The person doing the experiments to find a cure but is killing these animals for that, or you, preventing that person from doing that work? That could find a cure? Right, but there's now, I guess, leaving that person to die the death of dementia, right. It's these very difficult questions that need to be thought out.

Samuel Wines:

And it's not a binary, yes, and, and I think that's a really important thing with this sort of stuff, but I don't even know what a yeah, it's such a fascinating.

Samuel Wines:

Like I feel like we could literally speak for hours just on this topic. Because if we are like, can I imagine, like if you are programming them and ask them hey, how are you today? Like if that's something that you bake into it, just as like a quick way to update. Oh yeah, you know, maybe give me some more media, but like I can instantly see that people might find that like that could be a very big red flag.

Hon Weng Chong:

Oh, yeah, right.

Samuel Wines:

But in a way, doing that could then lead to the cells not suffering and not dying, because they can actually communicate with you what they need or want.

Hon Weng Chong:

Yeah, so, yeah, it's such a. I mean, how do we know that what we're doing in the laboratory, like all around the world, many laboratories, is not even causing suffering for these neurons? We don't know, right, like, for instance, maybe we grow them and we just leave them there with no stimulus? That could be a bad thing, we don't know. So you know, it opens up, see, like a whole bunch of counter worms, and this is what science does, right? Science finds the discovery and then now the world has to look at it and go, well, what are we gonna do with this? Right? Yeah, and this was, like, I guess, the big whole thing about, like the Oppenheimer, you know, he was like yes, let's go do this.

Hon Weng Chong:

And then later he was like actually I didn't really think it was that well, picture this yeah.

Samuel Wines:

Whoops. Yeah, at least this isn't dropping a nuclear bomb, but in a way it's an internal nuclear bomb. Should Should it be used in that Gattagablack mirror sort of style thing? But I think no. It's exciting to see that that's not the direction I feel like I think it's important to think about it and it has to be, but realistically for you, like I see so much of this as having, like, given your background, like the implications for healthcare for this could be immense as well. Oh yeah, 100%.

Hon Weng Chong:

I mean, like, one of the things that we're very excited, and the directions that I personally wanna take as well, is can we use these systems, these dish brains or, you know, cr1 systems with neurons on them, as a analog for a person that we can then use it for drug development and testing? Right.

Hon Weng Chong:

Because if you say take blood and transform that into stem cells and stem cells through neurons or whatever organs, those organs or organoids should theoretically inherit the same genotypical diseases and conditions and states. And we've seen this where patients with epilepsy, where we take their blood and we turn them into neurons, also exhibit epilepsy in a dish. Wow, yeah, and the because they have the same genome, same genotype, they would have the same drug profile resistance side effects 渡 implications for personalized medicine 100%, and so I think this is the path to actually doing personalized medicine.

Hon Weng Chong:

Alongside, you know, there's a whole like big genomic screen with, like you know, big data and so forth. But why not just grow an analog of that and just test it?

Samuel Wines:

This is the fascinating thing about what you're doing, because you're essentially if I'm reading between the lines you're building a platform and along the way towards, like I know we've spoken about this before like you know, one of the like the constellation goals I guess you're aiming towards is like well, maybe AGI needs to be biobased, so maybe this can be a way of actually getting towards like a true AGI. But that aside, you know that might be a star that you are aiming towards, but on the way, you might be making some really cute constellations which could have an even bigger impact in the short to medium term, I guess.

Hon Weng Chong:

I think you know you're absolutely right and I think the way to think about this is that this is far too big and undertaking for just us or any one company. Right, different people will have different goals. Some may want to do more drug discovery that's fine, we're here to support you. Some may want to do more AGI that's fine, we're here to support you. Right, it's hard enough trying to do the hardware, let alone the software interface, with that, plus the wet wear. So I think what we should focus on is to say what are we good at? We're good at building the tools that will help other people take that and implement whatever they see fit. Right, hopefully within ethical reasons as well, you know, within the ethical realms.

Samuel Wines:

But then again, it's really hard if you sell these things right and that's why, if you do it as a service, I guess there is that Service level agreement that you can put in. Yeah.

Andrew Gray:

And that's what we're looking for and yeah, I mean everything you've spoken about today and everything that we've seen at least suggests that you'd be able to offer it, you know, probably better service if it's maintained you know to some level here or with you guys 100%.

Hon Weng Chong:

I mean, at the end of the day, the AWS model right. Like you know, people want to write applications, they want to solve business problems. They don't want to solve running servers.

Andrew Gray:

Yeah.

Hon Weng Chong:

And then they want to do patches and all that stuff, changing media, yeah exactly. So why not let us do the same thing where we can do all this less exciting maintenance work while you go off and think about the applications? And you know we can always revisit it and improve the system to accommodate for newer capabilities and so forth. So it is a platform and it's continuously evolving.

Samuel Wines:

No, it's so fascinating even seeing, like the renders of what it's all going to look like. I can't wait to have them in the lab. Oh yeah, so there was another thing I wanted to potentially have a chat about. So like we speak a lot about the need for transdisciplinary innovation and how that's going to be, and especially like biology as a technology, I mean, you guys are like the epitome of transdisciplinary innovation with what you're doing. I'm just curious, like how has it been for you trying to find ways to weave those multiple different disciplines together to create?

Hon Weng Chong:

like a coherent language across?

Samuel Wines:

like your departments and teams, is there been issues with trying to, I guess, make sense of all of the different ways of looking at the world and the team members that you've got?

Hon Weng Chong:

Yeah, I think it's a really great question and one that even we have difficulty and we're still trying to work our way through. I think it really starts with the leadership right. Firstly, leadership has to be comfortable. We're not knowing everything, and to asking for help or asking for advice and listening, that's the first thing. Once you have that and those values are passed down the ranks, it makes it a bit easier, and so a lot of the times what we do we still try to work a more efficient way of doing things is a client, a client, a client client service model internally. So, for instance, our engineers are now trying to build hardware that our software people can write, the software for our biologists to use.

Samuel Wines:

Copy that. It's like a fracterly linked stack where everyone's kind of like the UX and UI is going to be designed in a way that makes sense for the user, rather than from the person doing the coding or the creation. Yes, exactly.

Hon Weng Chong:

Right, and then the biologists will do the experiments and then they will feedback, you know, advice back to engineering. This is how we do it. This is what we need Now. Having said that, the language used is different. What we say for one thing is different for another thing, and so having the need to translate that is critical. Like, even within the engineering we had this issue actually. It's quite interesting. So we came across this issue of the word crosstalk. So in engineering, electrical engineering, crosstalk happens when you have wires that are too close to each other and you have a poor signalized ratio. Turns out, our dishes also have crosstalk, because when we stem one electrode, because it's a salty media around it, the ions carry the charge across to the other side. So you end up with crosstalk in the solute in the biology.

Samuel Wines:

Right, that checks out.

Hon Weng Chong:

So when we were talking now, we have to clarify which crosstalk we're talking about the circuit crosstalk or the dish crosstalk?

Samuel Wines:

And this is the thing that I find about transdisciplinary is so fascinating is that you know you're gonna have to transcend and include both of them and find new ways of communicating as a whole and you're kind of creating your own language to be able to address that in a way.

Hon Weng Chong:

Yeah, 100%. And what's really interesting with transdisciplinary is you may actually end up finding out solutions that are completely like unorthodox, based on the other disciplines. You know view of things. So we've had other people like Finn, she's a chemist, right. So we're like, hey, you know what we observe. There's like, oh, it makes sense. And it's like, what do you mean? She goes on praddling about whole chemistry stuff. You're like, oh, I guess it makes sense now, right? Or when the engineers like look at it and they're like, oh, it makes sense, why you're getting this like biology problem and then they go fix it.

Samuel Wines:

Yeah, yeah, I love it. I just think true, and real innovation happens at the eco tones. So, like you know, that's like a ecology metaphor of like, eco tones are the two areas where multiple different ecosystems overlap. That tends to be where the most biodiversity is. Same with innovation, multiple disciplines coming together, that's when you're going to have all of these aha moments. Oh, of course, like, yeah, and we and we see this all the time, but it's been really fascinating, like, because normally that's happening from one company chatting with another company, but this is happening internally internally yeah cortical, so it's fascinating to see that.

Hon Weng Chong:

It's a double-edged sword because, well, it's really great for us doing all of this stuff. It's really hard when you have to talk to say funders or some of the next, yeah right, Because they love their buckets. And then when they look at you, they're like what the hell are you? You are biotech.

Samuel Wines:

Whatever you want me to be baby.

Hon Weng Chong:

What is it today? What is it?

Samuel Wines:

Quantum, I can be quantum if you want me to be quantum, yeah.

Hon Weng Chong:

I can be room room temperature quantum computer.

Samuel Wines:

Yeah, I don't know, but it's crypto backed.

Hon Weng Chong:

It's really hard because and I think this is it right why people complain about? Oh you know, why do we not have enough transdisciplinary? You know, companies cross-disciplinary, like startups and so forth. Well, the reason is because the funders make it difficult. Funders want to bucket you into something. If you're cross-disciplinary, you don't fit into one bucket, you fit into multiple buckets.

Hon Weng Chong:

And in that case, when the bureaucrats looking at which I give a grant for this, they're like which is funny, because the bureaucrats love to put cross-disciplinary as a thing as a criteria, but then they have to, like, decide where the bucket this thing goes into in order to grant the funds. So it's a catch 22. Like well, I can be more cross-disciplinary, but then that means my chances of getting funded goes down. You know what? I'll just be X.

Samuel Wines:

And it's such a pain, but you've definitely called out a massive like, like a root cause of a lot of the reasons and this is everywhere in everything in innovation is like why are we not having more of this? It's like if you just look at the root causes of it, so much of it comes back to the way in which the funding is allocated out. To tick a box, yeah.

Hon Weng Chong:

And VCs are guilty of this right as well because, they like to bucket things. Are you a FinTech thing? Are you a biotech thing?

Samuel Wines:

That's just humans in general right.

Hon Weng Chong:

It's a very left brain thing to do, correct To categorize things and every time you go to a conference or you go to something, there's always a drop down. You're like all these things, right? Other Other Right, exactly Every time.

Hon Weng Chong:

It'd be great if you have another. Sometimes they don't even have another and you just have to pick the closest thing, you know, I just have to update our ABN. It's the same problem as I would. What the hell are you right and you have this list of finite lists of what you can and can't be? So?

Samuel Wines:

Yeah, it's not a fun constraint and I think that, yeah, honestly, I don't know from a design perspective. It's like all you can do is talk about it and have these conversations and hopefully people hear and realize, but realistically, like the feedback loops for change in those places are so we just need better brain computer interfaces.

Hon Weng Chong:

No actually no, it's actually even simpler than that. We just have we need better design thinking in our forms. So, the simplest thing is remove the drop-down box. Remove, you know.

Samuel Wines:

Just let people fill in what they are.

Hon Weng Chong:

Yeah, make it a free text thing, what the hell are you? And that will allow for more cross-disciplinary startups.

Samuel Wines:

And then just get GPT to put it into a spreadsheet for you after the fact. Maybe you could yeah, just collate it.

Hon Weng Chong:

Exactly. But having like free text allows you to be more descriptive, a lot more free to say what you are, and I think that will hopefully allow for you know more cross-disciplinary companies and stuff to emerge right. Because you know it's really a pain enough for us when we have to put down something like Like people come up to me and they're like oh, you're a bi-tech. That's like not really, because I don't actually make a drug or a device. They're like what are you? Then I'm like well, we are a computing thing, but we also use biology for that stuff.

Samuel Wines:

You've kind of circled around deep tech. Since I've kind of known you, I feel like that's a safe space for you to.

Andrew Gray:

It's a bigger bucket. I guess it's the other bucket, maroon. Yeah. Really.

Hon Weng Chong:

Everyone who doesn't make it in just falls into it, right? I mean, I guess, like culture, meet right before it became a thing was a deep tech. Other thing, Because what is it? Are you an agricultural company or are you a bi-tech company?

Samuel Wines:

Yeah, and I know for a fact, both like Paul from Magic Valley and then also the VOW team, when we had James in. They were saying they're always having to deal with this. Yes, getting put in buckets. What's your hat? Yeah, where do you fit? Like, what house are you in at Hogwarts? It's like, no, I'm a muggle, I just Well, I think, probably how much. How are you feeling You've got enough? Like maybe 15, 20?

Hon Weng Chong:

Yeah, yeah, I can do another 15 minutes Sweet.

Samuel Wines:

Perfect, great Well, is there anything on your mind, andrew, apart from having a drink?

Andrew Gray:

Did I miss anything when I had to step out?

Hon Weng Chong:

No, you just missed the backstory, damn.

Andrew Gray:

So you were part of the backstory, though, so so what does this look like to you in the future, in the next? Like it's deep tech, so we'll say 10, 15 years, potentially, if things go smoothly do you have, or is it hard to tell because you don't know how this is going to develop? I know that you mentioned community, mm-hmm, so you want to talk to potentially like how community would grow like and how that might start and what people could look out for if they want to.

Hon Weng Chong:

Yeah, so I think community is really important. I think we unfortunately have been a little bit delayed with this, but we kind of jumped the gun on it too, which is we don't have the platform ready yet, but we already have a community of PD like dedicated followers, and they're not really that visible. I mean, there's a bunch of people on Twitter and stuff like that. The real core people are actually on our Discord and that's where we actually release a lot of early stuff. So we've had early videos about what we do in the lab and there's a VODCUS, so episode thing that Peter is working on, where we're going through the basics, we start with the paper, and he's interviewing people like Brad and Dad and asking them can you explain to us what you do and how does it matter? How do you? What is a stem cell? How do you?

Hon Weng Chong:

grow these things and so forth, and we're going to have Frank come in and take some video footage really to educate people about what is going on here.

Samuel Wines:

Is this content accessible after the fact, or is it live stream only, like you're thinking of?

Hon Weng Chong:

No, we're going to do it properly, like content library. Like there's going to be high production value and we're going to make it interesting and engaging kind of thing. Because people have always asked me, like why don't you have so much social media? Or what's your content strategy? I'm like, what do you mean? Content strategy? Which is, you know, if you're a content creator, you have to continuously pump up stuff to people interested.

Samuel Wines:

Tell me about it.

Hon Weng Chong:

And we're not that. We're a deep tech company and we put out stuff that is purely either A educational or impactful. So, like journal articles and so forth, I think having an educational series about how stem cells, neurons are made, how does the you know, the interfacing of the system works, and so forth, all these things help with our brand, which is credibility and seriousness. So that's one thing how I see this kind of pan out. Really, I kind of hope that this would be like the Silicon industry, but in a much compressed time scale. So the Silicon industry we have today is like 70 years Well, actually 1950, yeah, it's about 70 years old now, and what we have today is only like what? Two years old or sorts. But hopefully we can get to somewhat at this point in a much shorter time scale, which is a having people who understand how these things work and having companies build machines around the technology. So you know, we have, like, for example, intel and video, amd building the chips. On top of that you have software people building the operating system layer right.

Hon Weng Chong:

So you go Linux, you got Windows, and then on top of that you have your app developers who then build applications on top of, you know, the hardware, subtracted by the software, the operating system layer, and so then you know, you have, you know, your SaaS businesses, your open AI and so forth.

Hon Weng Chong:

What we're hoping is for the same thing to happen with our space, where there's a I mean, I guess there's an extra layer which is the wet wet, but it should just follow the same thing. There will be people doing the wet wet. They will have it with different types of cells. Some may be demented cell lines, some may be epileptic cell lines, some will be normal cells, some may be enhanced cells all these things that you can swap in and out and you can end up with, like you know, better or worse performing systems. Some people write different software that will take advantage of these different types of cells, and then, you know, some people build the hardware that will then put them all together, like what we do, and on top of that, other people will then start thinking about the applications that they can apply to in their daily lives. So that's what I really hope for. How it pans out, not quite sure yet, but we're trying to follow the same playbook.

Samuel Wines:

Right. So it sounds like you're kind of hoping for the emergence of like an interconnected, like collaborative community of people working on this sort of space. Is there any element of that that will be open? Or is it like so, for example, you mentioned the Linux, you mentioned the Windows like are you looking at going, you know we might do elements of this open and we might do elements of it closed? Like, where are you sitting with that? Like is that something that you're considering as well?

Hon Weng Chong:

Yeah, I think so. I mean we're going to have a mixture. So there are some things that are going to be closed because you know it's going to be too hard anyway for most people to like use any anyhow. So things like specific timings, how do you like stimulate them? You know the pattern generators, all that stuff. You know we're probably going to keep that a bit closed. On the other hand, the APIs are going to be open.

Samuel Wines:

Yeah.

Hon Weng Chong:

How do you interface with them at a higher level? How do you, you know, use them, which is going to be like, I would say, 90% of the users out there. They're not going to care too much about the specific details. For the other 10%, who really need to know, we're happy to, like you know, walk them through as well and maybe you open it up as well. You know, if they sign your spec, like deals with us or so forth, but it's more so also, we just don't want to give people, like you know, tools that they may potentially shoot themselves in their foot with right, because the hardware we're building has a lot of like capability, but if you don't know how it works, it can potentially even fry yourselves. So a lot of it is is sort of abstracting that away.

Samuel Wines:

Yeah, that checks out. Yeah, I mean, that's pretty much most of it from our end for the conversation. I'm just trying to think I'd love to know, like one last question in the context so obviously you know that's a great vision of where we're trying to aim and go towards, but how do you think it will like? What are your predictions for how the world will go over the next sort of that five to 10 year time frame? And then how does this fit within that context, if that makes sense, like what?

Hon Weng Chong:

So I think there is a growing trend for automation, right, regardless of what we're going to say or do. It is going to happen Because you know capitalism and the fact that we are trying to make margin and we've really started to see that with automation software, you know, starting with software as a service platforms, that's now being accelerated by things like Generative AI, but all of these are happening in the white color space. You know office desktops and so forth. The one big area that hasn't really been fully automated yet is in the blue color space. Right, the physical labors of, say I don't know tiling or construction or whatever. These kind of things are still very much in the realms of humans because we do not have systems that operate well in the real world. Potentially, a system like the Dish Brain or biological intelligence could start to do that.

Samuel Wines:

Integrated with something like a boss in dynamics, correct?

Hon Weng Chong:

And the next we think is going to be the next big leap in automation, where we no longer just automate in the digital realm for, like paperwork, you know, clerical tasks. It's now starting to automate the physical tasks and it wouldn't be kind of great. Like you know, nobody really wants to, like, I don't know, do garbage collection? Get a robot to do it. Nobody really wants to go mine in a deep, dirty coal shaft, get a robot to do it.

Samuel Wines:

Yeah, I mean, I think, yeah, that that's sort of crossing over of automation, and I guess what you would say yeah, the wetware, yeah, I think that will, because it'll have to happen for it to be able to like is like depth perception and like this, like the sensory awareness. I just feel like it doesn't feel like robots are fully there yet. No and I think that the wetware element of that will be a real game changer.

Hon Weng Chong:

Yep, we think so as well, potentially so fascinating.

Andrew Gray:

So the next podcast will be on the ethics of merging neurons with robots, so cyborgs cyborgs.

Samuel Wines:

Yeah, just go go full cyborg. Yeah, I got, I got time for that.

Hon Weng Chong:

The clarification of are you more human cyborg or more robot cyborg?

Samuel Wines:

It's a spectra, it's like Robocop.

Hon Weng Chong:

Yeah, the two, the two cyborgs.

Andrew Gray:

Yeah, that's true. Oh man, my brain's fried after that, yeah.

Samuel Wines:

Always, always, always speechless. But yeah, thanks, so much for coming.

Hon Weng Chong:

Thanks for having me on the show, always a pleasure.

Samuel Wines:

Yeah, now we really appreciate it and look forward to seeing how things continue to evolve on a merge over the coming few years for you.

Hon Weng Chong:

Perfect.

Samuel Wines:

Thank you, my gosh, what a conversation. Thanks so much for tuning in. We hope you enjoyed it just as much as we did. Yeah, the stuff that's happening at Cortical Labs is so, so fascinating and so cool. Like that intersection between biological and computational intelligence and ways in which we've biology into technology, that wet layer being able to help people with potentially personalized medicine, like the opportunities for this thing are potentially endless, and it's just so cool to see this sort of stuff happening here in Australia and we're really proud of all the work that they're doing.

Samuel Wines:

So, yeah, if there's any other cool innovations or folks you think we should have a chat with on the podcast, please let us know. Drop us a line, give us some feedback. We always love hearing from our listeners. And on top of that, I just thought to let you guys know that we are also going to be doing a bit of a special on biomaterials and the built environment this year.

Samuel Wines:

So we're going to be releasing a white paper or a report on, I guess, on the industry with collective fashion justice soon, and then we'll also be looking at collaborating with metabolic and a couple of other folks on what it would look like to be able to co-create a regenerative materials economy here in Australia. So, yeah, you're going to be hearing a lot more about this sort of stuff. We think it's a really important area that needs support and help. So if that interests you, please reach out, say hello. This is a living, breathing, ongoing dialogue between ourselves and everyone else in the ecosystem and, yeah, we'd love to hear from you. Thanks so much and see you here again next time.

Synthetic Biological Intelligence and Innovation
Digital Stethoscope for Pneumonia Diagnosis
The Journey of Cortical Labs
Electrophysiology and Building a Biological Computer
Neurons and Predicting the World
Digital Information and Neuronal Encoding
Ethics and the Future of Technology
Challenges and Opportunities in Transdisciplinary Innovation
Future of Deep Tech and Automation
Special Report