Interview w/ Former Neuralink Engineer: Han Zhang

whoever climbs up to the second story to get the banana there everybody gets shocked so not just the one that climbs up to the second floor but everybody gets shocked so very quickly the monkeys will start punishing newcomers that try to climb up to the second story because they don't want to get shocked hey everyone in this episode i interview han zhang to hear about his experiences working for knurling a couple things to note about the structure of the episode are one the edits are made with the intent of improving the listener experience and two i think the questions become more and more interesting as the episode goes on and i'm hoping that this will incentivize watching the entire way through but if you're wanting to cheat the system feel free to use the timestamps in the description hope you enjoy the episode hey everyone welcome back to neuropod uh for this week's episode i'm really excited to have on han zhang he's currently working at seldom but he's a former neurolink full-time employee and was a microfabrication engineer so i'm extremely excited to be having this conversation and interviewing him i hope you guys are as well so han do you mind introducing yourself a little bit and just giving some background for the folks who are listening yeah so i guess brief background uh after graduation i moved to the bay area and uh started working for a company called neuralink which i'm sure your audience knows about um there i worked as a microfabrication engineer uh or on the microfabrication team but sort of as a mixed background engineer i did some mechanical engineering some electrical engineering ran some experiments and also some microfabrication as well uh and then after that i moved on to a smaller startup company uh one that came out of the illumina accelerator that company's name is eldum and that's where i currently work and there i do similar skills but for different applications i build instruments and robotic systems for them so very much still a mix of mechanical and electrical and software engineering and then i can delve into uh my background before then as well yeah uh like a little bit of your um involvement and your education at ubc yeah sounds good so back when i was in school i went to the university of british columbia and there i studied engineering physics so this is sort of like a mixed program in the sense that it covers many different disciplines physics math mechanical engineering and electrical engineering sort of are the four major components of it um and i did the mechatronics specialization and then also minored in mathematics so that's sort of what i studied in university and then extracurricular activities back then i helped run the ubc mars colony engineering team also did some international research opportunities in germany singapore and then helped also uh mentor incoming international students to the ubc campus that context is really nice and important to share because a lot of these steps although they may seem like beginner steps um i think they're instrumental in number one even just getting the job and then number two like performing well in that job yeah so do you mind sharing like how you think those two are related and what you think are some of the most important things that you learn from those experiences are that translated to doing a full-time job at neural link i think certainly the education is almost directly relevant because in engineering physics you learn a lot about the fundamental physics concepts that directly apply to microfabrication the mechanical engineering classes and electrical engineering classes sort of allow you to build tools that serve those purposes or goals that the microfabrication team is trying to achieve uh so those are the directly applicable sort of uh classroom concepts and theory and knowledge that led me to neuralink but then on top of that the engineering physics program is sort of particular and special in that it has a lot of hands-on components so it has three project major project courses one is the sort of second year robotics course that goes through all summer and then they also have two capstone projects so it really um the program stresses not only a good sort of foundational theoretical understanding of scientific concepts but also a lot of practiced experience with hands-on skills and applying that knowledge so that helped me gain a lot of relevant project experience and engineering experience which neuralink directly found useful like there were many times during the interview process where they asked me to elaborate on past project work and uh they were curious about um the past project work that i did neurolink is special in that it's it's a lot closer to a research organization than an industry sort of your typical industry startup company uh it has sort of very long-term goals and that kind of makes it more like a research institute and so a lot of the um the skills and and experience that i gained working in these uh research institutes building equipment for them setting up experiments running experiments collecting data and then and then inferring some sort of conclusion from that that was also directly translatable to neuralink so that's sort of a yeah long-winded uh explanation of how all that tied together to bring me to neuralink one thing that i really want to do with podcast is just try to inspire young folks and bring awareness to the possibilities that are out there with biotechnology and basically showcase and demonstrate how much curiosity is needed in the space in order to make progress it just feels like we know so little about the brain but all these young folks that are potentially watching this or just going through school in some way like i want them to realize okay there's all this stuff that the brain does but there's still a lot that we don't know and we're kind of like at a point where a lot of it is being discovered so any words of inspiration or encouragement that you could provide for those young folks would be great firstly i mean you're absolutely right there's a lot that we are uncovering but uh still much more space to go i think there's like comparisons where like if all of the knowledge uh uh surrounding the human brain is like a mile long strip we would only have covered the first few inches of it so there's a lot more work to be done but uh just from what we know right about the brain there's already so many uh different potential applications and neurolink is just one company that that's working on uh these sort of applications right the ability to restore uh certain functionalities to people that are disabled or have have experienced strokes or other sorts of uh damage to parts of their brain restoring functionality and even enhancing functionality these are sort of the two main areas that applications fall under if you look at those sci-fi movies if you know about movies like the matrix these sort of um futures actually aren't that impossible like a lot of the things that are presented in these sci-fi movies or shows like black mirror are in theory possible and i think that that's something that's quite inspiring to me is imagine if you could take the information from the brain and move it outside of the brain into some digital format and use it to control things or use it to keep a record of your thoughts um or even compare to other people's thoughts in in a much more high fidelity manner so meaning that your thoughts are translated there's some loss of information when you transfer thoughts through words there's not a perfect translation between my thoughts to words some people are better at explaining their thoughts and others and then there's also not a perfect fidelity when my words are heard by the opposing party the the other person because whatever information i'm trying to present they may understand the words definitions slightly differently than i do or they may picture something different we may picture something different when we say the same word so there's some loss of information there and then you have to encode the verbal things that you hear into information in your brain so that sort of chain process and the losses along the along that chain make it so that verbal communication is actually inferior to many of the other potential forms of communication if you start to you know really dive into biotechnology especially like neurotechnology and neuroengineering there's a lot of exciting things that can be done today by pairing our capacities in digital technologies and computation with uh the human brain yeah so like super exciting uh how much is up there and just one want more people to be exposed to it right um okay so i guess i'm curious about uh just talking more about neuralink in your experience there so you started in november 2018 yeah yeah and then worked there for about a year right um can you explain what you did as a microfabrication engineer when i was on the microfabrication team i was one of the more i think generalist backgrounds so my tasks varied quite widely there was some micro fabrication processes that i actually ran myself and then i also did like chemical uh experiments so building fluidics baths and playing around with different uh ways of metallization forming sort of metal connector interconnects between the thin film electrodes and our actual silicon chips that do processing mechanical engineering of jigs and then a lot of pcb designs as well and also flexible pcbs and then some associated software to you know automate these sort of experiments do you mind talking about the overall like pace of work at neurolink and the exposure to leadership that you had while you were there pace of work very fast so uh yeah neurolink neurolink moves quite fast i think that's similar to um tesla as well like a lot of elon's companies are known for being fast paced so one of the uh traits that they look for in individuals is is mission oriented or mission first so these are people that are very dedicated to the overall mission of the company go-getter type of attitudes right like if a problem comes up you will find a way to overcome it or get around it i think it also is a testament to the talent that the company has managed to collect they have a lot of people that are able to whenever they come up against the technical challenge have the creativity and the flexibility and the resourcefulness and the tenacity to um assemble resources to overcome that challenge it's not like destructively fast-paced we're just like recklessly you know breaking things move fast and break things yeah that that slogan doesn't really apply i would say at neurolink that slogan is very much a software company slogan a software company a mistake in your own code can be usually fixed you know you can run it you can compile it run it test it and in the test suite it fails okay you've made a mistake somewhere you can just go back and fix it it's not really a high cost unless it actually rolls out okay then it's a high cost but there's many steps before that in mechanical engineering if you send out a part for manufacturing and has an error in it you you can't really fix that very easily you have to probably redesign it and then send it out for manufacturing again and that costs you know a lot of money and then a lot of time as well in in the manufacturer remanufacturing and then shipping it again so the costliness of a single mistake is i think much higher as you move from software to hardware and as a result because neuralink works on you know not just hardware but really uh fine fragile hardware we're talking about like nanofabrication or microfabrication like very thin film electrodes the costliness of a single mistake can be very high and therefore despite nearly moving at a fast pace it's also very especially in the microfabrication team very meticulous and and systematic in how it does its work did you see that progress or change throughout your time at neuralink like i guess like the day you left did you feel like the work environment was substantially different from the day that you joined in terms of the style of operation the way we operated that i think was fairly constant um at least within the microfabrication team there was some team reorganizations which is expected in a startup but the microfabrication team i think was very consistent it was very meticulous and systematic from the start when i was there mainly due to the fact that like if you make an error in micro fabrication uh you know you send out for example a design and you get like a mask for lithography uh and and you made some errors in there if you didn't even realize there was an error and you made like a bunch of wafers on it and then it showed up at the very end that whole process could take like a month and then you would have to redo everything it's very important that you don't make a mistake because that's a lot of time two months or one month even it's a lot of time i'm unfamiliar with what lithography is this is where you use uh light to write patterns onto usually some sort of material photoresist that is uh on a silicon wafer and the whole point is that you start off with like a blank slab of silicon usually in the form of a disk which is usually referred to as a wafer and then you're trying to write little features that are on the order of depends on your application but nanometers or microns in the case of neuralink trying to pattern these sort of features on onto the silicon and then you're going to after writing the features you're going to take away some of the silicon there's really three things that you do in microfabrication right there's patterning where you write some sort of pattern and then there's uh removal of uh material etching and then there's adding material which is depositions you just do those sort of three steps in different orders and then you use different materials and that's essentially how in a nutshell all of the microfabrication devices are are made it's just some combination of those three steps over and over again and with different materials and so the lithography part is one way that you can pattern you can write patterns onto silicon litho i think means stone graphene meaning right so writing into stone and you do this with white lasers so that you can get very fine features because you can you know focus light down to nanometers today i'm curious if the robot that would perform an implant surgery would also do some of this type of etching or or any of these profit processes so neuralink surgery robot is um highly specialized for surgery and and that's basically that's the only thing it does and when it comes to microfabrication it's probably very similar to what other people would would use if they did microfabrication so there's sort of an industry standard for what tools are used a whole bunch of companies that make these sort of microfabrication machinery uh they're in a lot of university clean rooms they're in uh a lot of actual silicon foundries and it's pretty standard across industries so so neuralink would likely use those these wafers are being used uh for the writing of information to the brain or reading of information to the brain or both both there's sort of two different areas that microfabrication comes in one is making those electrodes that go into the brain so that would be used for reading and writing that's uh sort of what neurolink does in house because those those are very particular to neurolink but then there's also sort of silicon chips specialized silicon chips that neuralink makes for data processing from the electrodes there's sort of two microfabrication components one is the silicon threads the other is the actual chip that reads and processes and cleans up information and both of them are used in reading and writing so can you remind me some of the other things that you said you worked on microfabrication processes building like just random rigs and and such for some mechanical engineering there and then pcbs designing pcbs for experiments test situations and then fluidics uh baths can you elaborate on the the printed circuit boards and the fluid because we make a lot of like electrical designs right uh and we want to you know test uh what what's the signal quality from these electrodes what kind of you know formulas work best how long do they last all of these are questions that we have to be able to answer about the electrodes that are that are made the pcbs that i designed were to run through a whole bunch of electrical tests on these electrodes you know testing their signal quality resistance variation stuff like that and then the fluidics paths that's that was sort of uh when we were exploring how to make interconnects between silicon chips and thin film electrodes uh there's many paths and metallizing a certain material and that that had to be done in the flutex path and so yeah that was where i designed the uh built flutex bath and carried some experiments and quantified like how much metallization was happening uh and how um essentially the quality of the metallization on this material if this would be a suitable interconnect between the silicon chip and the electrodes my instinct is that neuralink generally has the the biggest challenge that engineers and neural link has is is centered around material science do you think that's like the number one issue or number one like science or engineering related problems that they have there are sort of like a whole bunch of problems where like any one of them would make this technology not work so in that sense they are all uh in the same tier of like if this doesn't get solved this whole thing doesn't work for the robotics team how to get robots to very precisely uh move to a target on the brain and insert an electrode because the brain is not a still object the brain actually pulsates a little bit as you breathe being able to in real time detect the movement of the surface of the brain and compensate for that and being able to insert electrode that's something that's certainly a challenge adjacent challenge to that would be being able to spot blood vessels in the brain and avoid those obviously you don't want to puncture one of those if you're inserting a electrode on the electrical engineering side you're moving a lot of information right so you're reading from thousands of electrodes depending on the design it could be tens of thousands of electrodes uh or or more if you're reading from that many electrodes um and you want this device to sort of be compact and sit on someone's head you're going to have to come up with a very clever silicon chip to be able to process that information digitize it because it comes as analog signals from the electrodes digitize it and not be very power hungry because if you are very power hungry it's going to heat up that local region of the brain and at at fast it'll be uncomfortable and at worst it could actually cook tissue so that's you know a problem and i'm not saying that that's you know an actual problem we've run into i'm just saying this is in general something that you have to be cognizant of pretty much on any domain uh any any team or uh domain that neuralink touches on there's big challenges in in those domains and so yeah going back to microfabrication material science yeah like you say you know different materials have conductivity issues stress and strain issues you want these things to be flexible so you're bending it so you have to make sure that you choose materials that won't for example um over time if you bend it too many times or if it moves back and forth it hardens more or it just breaks so you don't want something super brittle uh you have to worry about things like corrosion because there's a lot of different chemicals floating around in in the brain you know you have ions you have proteins you have like a whole bunch of different things and you have to be your material that your electrodes are made out of has to be able to survive in that environment for years and not only survive but also carry the same signal quality through all that time you don't want it to drift so it can't not only does it have to survive it has to remain relatively constant in form factor and electrical properties and then at the same time it has to be feasible to manufacture so that also cuts down on the number of options uh and then also um not only feasible to manufacture but it has to work well play nicely with the surgery robot uh right so you're sort of constrained there with like the types of designs that you can do that a robot can interface with because it's not a surgeon that will be peeling these electrodes and sticking them in the brain they're too small and obviously you want to automate this eventually so you have to design it in a way that a robot can you know actually manipulate it physically so yeah those big challenges there and then on the software side right you get all this data stream from the brain it just looks like a bunch of uh i don't know if you've ever looked at these like neural recordings but just looks like a whole many many channels of like almost a flat line but there's like clearly something happening there like little spikes here and there so how do you then make sense of that information first off you have to be able to take this raw data stream and be able to be able to pick out when a neuron is firing and that's already harder than one might expect because you know if you see what looks like a spike how do you know that that's a spike versus um your electrode just being degraded during surgery for example during implantation maybe it was stretched too much or damaged in some way how do you know that that's not a signal issue or a noise issue rather than an actual genuine spike so you have to have some software to be able to decide on that and then after you you decide it's a spike how do you know that this is one spike from a nearby neuron versus like many spikes happening in the general background vicinity of the brain uh so again none of the things i'm saying are you know necessarily challenges that neurolink is facing i'm just saying that these are general things that are challenges when you're attempting something like a bmi after you pick out what are spikes then is the real hard problem which is like what do these spikes mean how do you make uh meaningful information out of just random spikes on 3000 channels like what does a single neuron firing really even mean it doesn't necessarily mean anything in and of itself it's really uh the combinations of neurons firing that really gives you a lot more information so using machine learning algorithms and stuff like that to be able to decode meaning from trains of neural data that's that's also a huge challenge and then that's only the engineering side right then there's the biology side the brain has like immune response system it has a scarring effects um it's an organ it's not really meant to have things implanted into it all of these uh things produce a lot of challenges with like for example if scar tissue forms then the live neurons get pushed away from the site of implantation um potentially that could cause signal issues immune responses or you may have weird things kicking on to your electrode you know i'm just throwing things out there that could be potential challenges you know obviously surgery is not not a trivial thing to do so you have to make sure that you you do that part right and not cause substantial risk to any patient that might be undergoing the surgery so i guess in summary like there were huge challenges ahead and and some that they're currently like working through a lot of the ones i mentioned they've actually already addressed and are no longer serious challenges but um i bring it up because it's it's you know something to to think about uh just to illustrate how monumental of a challenge neurolink is even attempting neurolink is one of those companies that is working on something that has challenges on so many different fronts any one of those challenges not working can scrap torpedo the whole idea this is really quite a feat like if they pull this off it would be quite an accomplishment because of of just the not not only the quantity but also the magnitude of the challenges that they're facing can you explain the specific difference between the electrodes the threads and the channels a thread looks like it's like a single polymer thing that you can't really separate and within a thread there are many electrodes so there are many sort of independent electrical paths within a single polymer thread so one thread will carry many electrodes there's many electrical pathways along that thread and they terminate at different lengths along the thread which means when that thread is implanted into the brain those electrodes will sit at different depths in the brain and so they will be hopefully reading from different neurons so that's the difference between thread and electrode and then typically what we call a channel is like basically correlates to one electrode so we read from all of the electrode sites and so each uh channel is with just one reading one signal train from one electrode okay and each of those channels is read and write capable there are ones that are read and write capable and there are ones that are read capable the eventual goal is to have both working if you had to describe what neural links end product or service is how would you describe what it is i think that there's like the super long-term goal being able to digitize human consciousness being able to control anything digital with your thoughts i think in the sort of shorter term you know next five ten sort of 20 years that that sort of uh time frame uh in our lifetimes i guess uh for sure in our lifetimes i think we will see products that enable people who might have lost some functionality in the brain to be able to recover those lost functionalities and to be able to control computers other sort of digital devices with their thoughts directly through the brain and do that relatively well like comparatively to a fully functioning adult or even better do you think it's possible that in the future neural link or some other company comes up with a way to use the information that they've been receiving to basically basically like train a neural net to eventually create like an artificial brain just talking about bmi brain machine interfaces in general i definitely think personally it's my personal opinion that that is the way that things will go where we start making artificial brains if you can digitize thoughts and if you can record information let's just say we get to the point where we're able to record information from all parts of the brain with very high fidelity we can basically map meaning and thoughts uh from the brain with very high accuracy right it's very natural for me to imagine the next step being just building artificial brains and and general intelligences that are based off of human brains you might be making it from scratch or you may even just be copying over someone's consciousness into a digital format i think both of those are are possibilities in the future and i think that that's probably where bmi in general like the whole industry not nearly in particular necessarily but the industry in particular will definitely be headed in that way and which which companies end up doing this it may be a company that doesn't even exist today uh but it also might also be neurolink or some other company in that space it's fascinating to me like how much the brain is able to do with such little energy versus like the world's biggest supercomputer or whatever yeah requires tons of energy yeah the brain is definitely a very fascinating uh object who is it that said is like the most informationally dense uh thing in the known universe um something along those lines but uh but yeah it is very impressive uh that's why we study it and the the question really that i have in my mind that i'm not sure what the answer to this is is like can you ever get to something that is um informationally more [Music] dense or compact electronically digitally compared to the brain and would that ever be more energy efficient than the brain like not necessarily the human brain but basically the question is like uh suppose you had a set of organic chemicals to play with and then another set of like silicon and metal atoms to play with and you tried making brains out of these two lego sets which lego set at the end of the day would produce the most energy efficient computational device which one can produce the most informationally dense and then which one can produce the best brain off of a combination of those two metrics information dense and also energy efficient and i'm not really sure uh personally which one of the two it would be if it would be a biological system or um a silicon metal sort of system with neuralink like they're the information that's being uh moved around in the brain is through electric signals and chemical signals too right right so how do you foresee like future interactions with medical like drugs with the physical like electrical signals being read and written from the brain with neuralink i think that neurolink is probably not going to be doing anything on the drug side of things maybe they will i'm not sure um the future is very much you know dependent on uh progress the company makes and it has a very large exploratory arm there's a lot of things that are very research-like in in neuralink so very exploratory we know there are things that's that's what it means to take drugs right like colloquially there are drugs and chemicals that will affect the way the brain works and some of them are therapeutic and so i think more and more you're going to see an industry pop up around drug therapies to address mental health issues mental disorders uh other sorts of irregularities uh with brain function that should be getting more and more sophisticated because um right now okay for example painkillers right you just take a bunch of painkillers and you just flood your brain with opiates and that that's how you kill the pain sensors but perhaps there's a better way of doing that without triggering the addiction pathway in the brain so i would i would expect drugs in the future to be much more sophisticated and be able to do certain things without triggering a whole bunch of negative side effects so at the end of the 2020 update event uh they did like a round table in the room um they asked the same question of everybody like what's the thing you're most excited about for neurolink working on in the future um what would be your thing i think for me it would probably be the ability to digitize a brain so just upload my consciousness or some sort of digital equivalent to my brain onto the cloud and then be able to in a in a sense free myself from this biological body not that i have any problems with my particular body but uh the ability to like download my consciousness into any particular body anywhere is is something that is really amazing like inspiring as an idea right the ability to say if i wanted to download myself into a drone and fly around or a submarine and swim around or if i wanted to visit mount everest and climb to the peak rather than doing that in human body just literally port myself over to some stationary fixed robot planted on the peak of mount everest and just like look around or live stream um people's thoughts and and and experiences directly to my consciousness from wherever they are in the world freedom from the biological form is uh i think probably what i'm most looking forward to but this is like way in the future i mean there's equivalent um yeah and then there's other cool things like human hive minds for example that can come about that's a whole another thing as well um that would be very interesting these are super organisms that can form once you allow like an internet or a network of human brains yeah yeah yeah it'll be cool to like have all of them basically connected in some way or another yeah basically and and i you know it's it gets dystopian very fast because it's like well there's sort of emergent phenomena when you when you connect things right there's like um i don't know if you've ever heard of this experiment where like um they have like four chimps and then or four monkeys and then like yeah uh if if a monkey goes up into a second there's like a two-story environment and if they climb up to the second story to get a banana there they get shocked if they get a banana on the first floor everything's fine they slowly replace these monkeys one by one whoever climbs up to the second story to get the banana there everybody gets shocked so not just the one that climbs up to the second floor but everybody gets shocked so very quickly the monkeys will start punishing newcomers that try to climb up to the second story because they don't want to get shocked and eventually when you replace all four monkeys one at a time so that there's some ability for the other three to teach the newcomer not to do that when you've replaced all four original monkeys and you take away the shock mechanism they still punish every monkey from going to the second floor even though there's no cost to it anymore so these sort of like network effects that that happen from different independent agents enforcing inflicting punishment or reward on each other in a environment of imperfect information and assumptions there can be a lot of emergent phenomena that are very dystopian very unexpected and very persistent that have nothing to do with truth or anyone's individual beliefs there's there's a lot of very interesting both potentially very dangerous and potentially very uh rewarding things uh i think in the future for bmi yeah that that story like perfectly illustrates that point okay yeah well thanks for having this conversation uh i'm sure like everybody's looking forward to it yeah yeah sounds good yeah yeah okay well thanks for doing this and hopefully we can talk again sometime soon yeah looking forward to it all right thanks for listening please subscribe hit the bell notification icon and follow us on twitter instagram tick tock and medium for updates and highlight clips hope to see you at the next episode

Channel: Neura Pod - Neuralink

Views: 95,749

Rating: 4.908989 out of 5

Keywords: Neuralink, Elon Musk, Max Hodak, Update Event, What is Neuralink?, 2020, Neura link, Neura Pod, What is Neuralink, Tesla, SpaceX, starlink, Learn background summary, Nueralink, Nuralink, Brain computer interface, What does Neuralink do?, public, music, announcement, memory, brain machine interface, Alzheimers, How does it work, Can I sign up, stock, Surgery, Implant, Artificial Intelligence, Machine Learning, Medical Robot, When, Investing, gaming, Palantir, Peter Thiel, Man vs Machine, Website

Id: FZMIpUBycgQ

Length: 37min 6sec (2226 seconds)

Published: Sat Mar 27 2021

Reddit Comments

[u/evolutionxtinct]

Wonder why he left :(

[u/NewCenturyNarratives]

This was by far the most useful Neuralink interview I've come across

[u/digitAl3x]

Really great interview!

[u/boytjie]

Interesting interview. He seemed like a nice guy as well (not always the case). I wonder why he left?