SPEAKER_00: hey coming up on twist today we're talking about 23andme going straight down into bankruptcy then what will michael saylor do with a half million bitcoins after we get to the news lon and i are talking to three founders we're talking to etch to figure out why they're building transformer specific asics and what that means skyflow and how they've turned from a company all about keeping your data secure to actually now enabling enterprise ai and then medserv which wants to keep medicines safe secure and properly marked to avoid annoying the government it's a

SPEAKER_03: great show let's have some fun this weekend startups is brought to you by northwest registered agent starting your business should be simple with northwest registered agent you can form your entire business identity in just 10 clicks in 10 minutes from llcs to trademarks domains to custom websites they've got you covered get more privacy more options and more done visit northwestregistered agent.com twist today squarespace turn your idea into a new website go to squarespace.com slash twist for a free trial when you're ready to launch use offer code twist to save 10 off your first purchase of a website or domain and fidelity private shares if you want the all-in-one equity management platform fidelity private shares has you covered visit fidelity private shares.com and mention this podcast for 20 off your first year subscription hey everybody welcome back to this week

SPEAKER_06: in startups my name is alex that is lon harris we are here on monday march 24th to break down the

SPEAKER_00: biggest startup news in the world today but long we actually have a kind of a special show today we're going to do some news and then we have three banging interviews with awesome founders talking to the folks out there i'm stoked but let's start with a couple big news items the first one that you and i both agreed had to go to the top of the docket is simply that 23andme the famous at-home dna testing company has filed for a quote voluntary chapter 11 bankruptcy proceedings going back through the financials lawn not blown away by this but certainly an odd end to what seemed earlier to be almost a

SPEAKER_08: generational company yeah i mean this was one of those companies that in in that earlier internet or really captured the public's imagination because it was something so new they created a service or

SPEAKER_10: they were one of the companies that felt like they created this service that was not only like

SPEAKER_11: nothing that ever existed before but felt like futuristic in a way like you can send away for this kit and now like learn all of this stuff about your background and people were like finding cousins and relatives like there's whole documentaries about long lost twins and siblings that found each other via 23andme so yeah i think it was technology that at one time seemed like the bleeding edge like this really exciting new thing but you know it's one of those things that like i guess everybody who was really fascinated by it has now done it and like yes where do you go from there well the answer is your

SPEAKER_00: revenue goes down yeah just to give everyone a bit of context the last time we actually got financial numbers from 23andme was back in november of 2024 they were discussing at the time the second quarter of their fiscal 25 a lot of companies have a fiscal calendar that is offset from our calendar they do that strictly to annoy the financial press and to make sure that we are always on our toes uh but just keep in mind when i say fiscal q2 i'm talking about kind of the end of last year so right lon what happened well the company reported revenue of 44 million not bad until you realize that that was off 12 from the year ago period yeah they did get their uh operating costs down about 17 to just 84 million but they posted a gap loss of about 59 and ah man the company's cash balance was just going down and i went back and it turns out they did tell the sec there was going concern concerns so the writing was kind of on the wall a special committee was put together earlier this year to try to sell it and wojitski the preceding ceo who just stepped down offered a couple different times to buy it for different amounts didn't work out i he just you know what's that quote from books like every happy family is the same every unhappy family is unhappy in their own way yeah that's how this feels here like every company that kind of falls apart tends to dissemble at the end in a embarrassing and sad way i just oh story it's from anna karenina that quote the last thing that i want to throw in lon is just

SPEAKER_13: that this i think was another spac led debut and yeah so you know i was told growing up learning about

SPEAKER_00: finance that spax were just how you take out the trash and no offense to all the fine folks who worked

SPEAKER_23: at 23andme but this is not a shocking outcome for a spec led debut yeah it sort of reminded me in a

SPEAKER_08: weird way of instant pot you remember hearing about which i have an instant pot and it's great it's a

SPEAKER_11: great invention they work really well but the problem was you sell people one instant pot they keep it at last it doesn't it doesn't stop working it's not like an apple where after two years you got to get a new instant pot because this one goes too slow and so the company ended up being in trouble because even though they made this great product like well what do you do after you sell somebody an instant pot you're done transaction over and it feels like a little bit of that like 23andme didn't come up with a way to turn customers into repeat customers they just sold you your dna kit and then you did it once and then you never need to know your dna again and that was it and it does feel like you know like well you need to come up with some kind of second act and you need to follow up in some way or people get tired of it and then your yesterday's news the startup angle here is twofold therefore uh

SPEAKER_00: one don't go public via spac and two sas is popular because it involves inherently recurring revenue and so that's exactly that's my takeaway here thinking about absolutely kind of bedrock business fundamentals lawn uh we do also have a news item here from microstrategy the most boring average everyday company out there today and they have like many companies have before them boosted their bitcoin holdings to not pass the half million bitcoin mark and if you didn't catch it that was all

SPEAKER_29: sarcastic good job i did i caught it i will you and i talk all the time lon yeah i i did what's

SPEAKER_12: fascinating here is like i'm not saying and i'm i'm not saying this if you're out there and you're you're

SPEAKER_11: holding or whatever and you're you're a crypto fan and you're about to get mad at me i'm not saying bitcoin itself and all crypto coin is purely a ponzi scheme but it is hard for me to like distinguish exactly what these guys are doing versus what you'd be doing if you were running a pyramid scheme like they're just they're making the asset more valuable by buying a lot more of it themselves and so it's just like eventually some people are on the bottom of this pyramid right like it it only gets so valuable

SPEAKER_23: it doesn't you can't use it for anything well why is hodling such a popular rallying cry for bitcoin uh believers maxis and fans well it's a couple of things one is frankly that

SPEAKER_00: historically bitcoin has appreciated so if you hold or hodl you'll gain more appreciation over time the other side of this that doesn't get discussed i think quite as much is that it reduces the number of coins bitcoins that can be sold right there's scary scarcity so drive scarcity so when we see you know microstrategy now just strategy because they changed the name between march 17th and 23rd the company sold about 2 million shares about 600 million in revenue bought bitcoin and then they also sold an amazingly small number of their new um strk shares long story there but that was another million and so they bought another 7 000 bitcoin pushing them over the 500 000 mark 500 000 bitcoin mark that is enough buying lawn that i think actually you have a point normally i would say how can one company influence the market for an asset that's this large is this traded and dare i say amongst crypto coins is this liquid uh but yeah at some point you're just borrowing money or selling stock to purchase more of the thing you already own because that's what you do it just seems a little bit circular to me

SPEAKER_10: that's what i'm saying i'm not saying like of this of the entire crypto industry i have to say different projects and different coins and it's all like i i get that i get that yeah but in this particular case it's just it's starting to feel like he's borrowing money to pump up the value of the asset that he owns to make it more value it's just it's just going in a mission more stock

SPEAKER_00: because the stock went up and then you can buy more the thing that jason and i and we talked about this enough times on the show that we actually kind of decided to stop talking about it for a while so we'll keep this brief uh but our thought was just this why wouldn't you just go by bitcoin like if you were an investor and i i we never really got to the bottom of that other than the market was assigning a premium to microstrategy now strategies shares and if someone's going to give you a buck 50 for holding a buck okay i kind of get it but it did feel like a short-term apparition versus a long-term nav premium that was going to persist over the long run uh but we'll close with this michael saylor has now purchased 33.7 billion dollars worth of bitcoin at an average price of 66.6 k per coin and currently last time i checked today it was at 88 so there you go let's move on please the thing that i was most excited about this morning that i read about was a story from katie roof my friend over at bloomberg uh we used to do a show together katie roof is a reporter's reporter she's just always out there scooping deals i love her work can't say enough nice things about her and her and uh kate clark have been just crushing over at bloomberg shout out to them if you

SPEAKER_29: read a lot of tech news it's one of those bylines that comes up all the time you just learn that

SPEAKER_37: name because she's always uh reporting on something going on that day she reported some

SPEAKER_00: data from cb insights uh which is similar to crunchbase similar to pitchbook a repository of private market information lawn and she writes i'll just quote for the fun of it uh there have been 11 startup sales worth more than a billion dollars so far this year worth about 54.5 billion that's according to cb insights by contrast quote in the first quarter of last year there were only

SPEAKER_23: two startup acquisitions worth more than a billion dollars which together brought in just 3.2 billion the caveat here is that whiz was 32 billion dollars of the 54.5 so i think the more important number for us thinking about an unlocking of broader liquidity is the fact that there were 11 unicorn ish

SPEAKER_56: exits in q1 so far uh and we have core weave going out theoretically on friday all right founders okay

SPEAKER_57: digital nomads and my remote entrepreneurs i need you to listen to me right now i know you want to build

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SPEAKER_07: slash twist to start your business today all right look i don't want to be all positive and and happy and hunky-dory but it does feel long that there's a change in the wind when it comes to

SPEAKER_10: emanate activity absolutely it's undeniable i mean i think the interesting conversation is not is it happening which is yes it's more like why and and i mean i think that it's really it's one of those

SPEAKER_11: interesting like things sort of get gather their own momentum in some ways like i think it's undeniable

SPEAKER_10: that there is political like the administration changed the expectations about what sorts of transactions would be allowed there was a change in in regulation and there are expectations you know people guessing about what's going to be allowed and what's that but it also just feels like uh you

SPEAKER_11: know who knows why like people see other people doing it and then that gets them to jump in and

SPEAKER_40: it's just one of those systems that has its own kind of momentum we jokingly call this vibes but

SPEAKER_00: the thing is that's just called what's the temperature in the market today or this is a heat check or play the game that's on the field all of what you're just discussing reacting and acting in

SPEAKER_23: a way that is in concert with how other people are acting and reacting because that's how markets tend

SPEAKER_10: to move right well that's what like ceos and investors like that's how a lot of the job goes it's in the it when when the early conversations were happening about you know all the different

SPEAKER_11: kinds of jobs ai could replace and people were jokingly like what could ai ever replace like ceos or board of directors like i feel like it almost could because this is something you could kind of give an ai like here's the market here's all the mna activity here's everything go put in every variable you can about interest rates and financial markets and what the s p 500 is doing and

SPEAKER_12: everything and then you could like ask an ai like when would be the perfect time to ipo and it was

SPEAKER_23: like why not it could it could guess i mean our ipos are half alchemy half science so i think why

SPEAKER_00: not roll the dice with your favorite llm right let's just hit on one more thing long before we move into these interviews you and i are right now expanding the twist 500 from 275 up to 300 and we have actually completed our next 25 companies that we are in the process of building out to upload and so twist 500.com but one of them that i had on our list was browser use and this is a company that i ran into twice once uh through the latest by combinator batch they were part of and two because do you recall manis that uh ai agent yeah well they were using browser uses technology oh guess what other people have noticed too and that's why i was unsurprised to see that browser use raised a 17 million dollar and seed wrap so they raised a 2004 series c uh which is a 2025 seed round and i think this makes a lot of sense um felices led astasia myers previously of help me out here lawn red point

SPEAKER_71: where she used to work with uh jam and ball is not altimeter they're my favorite folks over there i

SPEAKER_73: don't think i know anyone in red points anymore anyways she's brilliant i can't help you out there i'm

SPEAKER_29: sorry get with the program lon i don't know those people you're not on the the vc group text

SPEAKER_00: neither am i no anyways uh paul graham a capital and nexus venture partners also put money into it and just so folks know if you don't browser use essentially takes the visual web and renders it into a text format and it's easier for ai agents to read and interact with so if you think agentic ai lawn is going to be a big deal well a lot of people might want to have their website be a bit more

SPEAKER_14: dare i say agent friendly so many of the companies were being hit so many of the companies were being

SPEAKER_11: saying this is the sort of thing they do is like the future is going to be ai talking to everything and so we're like smoothing that that middle ground and make those conversations easier there was another i don't remember the name of the startup which is probably good because i don't want to randomly throw them out here but they're all they're doing is figuring out different hardware devices that exist in the world like even things like fans or you know every kind of external appliance you could have and like how would we get an ai to talk to that one day and so i feel like there's a huge opportunity right now for just like making those like weird handshake introductions like how do i introduce the ai to this device or this technology or this platform do you know what

SPEAKER_62: you're making me want to do is go read samsara's latest earnings because samsara is essentially i think

SPEAKER_00: the the biggest breakout success from the iot era they went public sometime in the last two years if memory serves and they were incredibly impressive very fast revenue growth just a great company i

SPEAKER_23: think i talked to the ceo when they were going public and love them they're actually valued very highly for a while there uh but to your point about having other devices other things that create data interact with ai well you're going to need an internet of things and so i i wonder if i wonder if

SPEAKER_11: they've caught a wave you know it's it's fascinating i i was at ces it's got to be over 10 years ago now and we used to i i worked for a streaming company and we made content for samsung like they were our big sponsor so we would go run the samsung lounge at ces and we would cover all the samsung keynotes and they had a whole keynote they brought michael bay out during this keynote even about it when it was all internet it was the infamous michael bay uh yeah when he lost his teleprompter on stage and

SPEAKER_29: then said i'm sorry i can't do this and walked off i feel for him that whole keynote was just

SPEAKER_11: internet of things and how your toaster is going to talk to your garage door opener and they're all going to be connected to your mp3 player whatever every everything and so yeah i do feel like they were just like we thought that was going to be the future right then you'd get home and like your you know lights would all turn on before you got inside but this may be where that was actually going it's like

SPEAKER_12: it doesn't need you it needs your ai agent that's who it should be talking to i wanted to share a

SPEAKER_00: tweet that i saw that i've been holding on to that i think how to put this i think fits into this story so um liz wessel who's an investor over i think it's first round she tweeted out a couple days ago this has to be the frothiest vc market for seed and pre-seed i've seen in my tech lifetime 2000 to present it's becoming truly absurd and uh then she went on to talk to jason lemkin who says he'd be fine with it if public multiples were higher she agrees there's a huge gap true tracking that for a while and then kurt schrader uh jumps in and says going to be a lot of people hitting the series a wall hard in a couple of years and so the the concern here that i want to raise is it's awesome to see companies that

SPEAKER_23: are doing cool things like browser use raise these let's be honest insanely huge seed grounds yeah i you just you just really hope that we don't end up in a post 2021 similar moment when companies are stuck with cash and growth that doesn't quite add up to proximate venture rounds because that would just be

SPEAKER_10: a mess yeah it becomes almost like for an individual like a a getting into debt situation like well now

SPEAKER_11: you've got all of this like responsibility so even if you start earning more and and having more personal success you're not really reflecting that because you're you're carrying around this anchor with you and like that's what this becomes these massive early rounds for these companies is like well then they're just saddled with all of this responsibility to all these old investors kind of holding them

SPEAKER_00: back a little so what you're saying is is that raising a large pre-seed or seed round for your startup is akin to taking on lots of private debt to fund your time at harvard i mean i think that if there's comp

SPEAKER_10: it's comparable in some ways and in the same way that there's good debt and there's bad debt you know like student loan debt that you can pay off at a low interest rate over 20 30 years might be good debt you bring that on then you can earn more you're increasing your earning power pay it down

SPEAKER_11: like that's positive but then there's also you know going on a spree at zara's that you're then paying off for it's a clothing you're then paying off for the next you know several years that you didn't have to be and you could be using that money on more productive things moving forward so just to be

SPEAKER_29: clear the good news is that you can finance things the bad news is you can now i believe clarna your

SPEAKER_11: door dash right you can order your limousine for your burrito on layaway which is i don't think you should do unless listen i don't know everybody's situation but yeah let's not be too quick to judge

SPEAKER_12: just don't pay in four if you're going to eat in one i mean i think even if the pay for just like hit those payments man don't miss your burrito payment that's how they're gonna screw you that's their counting on to go back and beat you with the cilantro they're obviously making this offer because they think people are going to miss their burrito payments and then they're going to be able to if the burrito payment is interest-free they're hoping that you miss it so they can charge you in

SPEAKER_29: sometimes i realize how much more conservative i am financially by accident yeah right people get into

SPEAKER_66: real problems with these payday loans and you know the loan rates aren't always so bad unless

SPEAKER_12: you miss a payment and then that's where they really get that's where the teaser rate becomes

SPEAKER_109: not a teaser right exactly all right founders let's talk about your website yes i know it's

SPEAKER_58: embarrassing yes i know you're too busy to upgrade it well if you're going to launch something new or you need to give your brand a refresh which i know you do you need squarespace it's the all-in-one platform that makes building a stunning professional website ridiculously easy whether you're selling products offering services or showcasing your portfolio like i'm going to do with one of my kids they want to go and do artistic things in the world so i'm going to make them a nice beautiful squarespace site when they apply to college squarespace gives you everything you need to grow and you know what obviously you've heard me talk about how beautiful squarespace's templates are but now you can get a fully customized website in minutes with their ai tool called blueprint here's how it works you just answer a few questions and then you get a beautiful bespoke website in minutes personalized layouts visuals that are going to stun your customers and voila you're done want more control choose from award-winning templates and use intuitive drag and drop tools so you can make it your own easy peasy lemon squeezy you get to do it the way you want to do it so here's your call to action just fall in love with squarespace like i did squarespace.com twist for a free trial and when you're ready to launch go to squarespace.com twist to get 10 off your first website or domain purchase that squarespace.com twist the longest running partner for this week in startups because they were a startup and they still build their product with the enthusiasm and the cutting edge technology of a startup founder we love you square space lon let's go hear from some founders uh the

SPEAKER_06: first interview that we're going to do today is with etched now we all know that nvidia is the reigning

SPEAKER_00: chip god of the world but there's a star called edge that's betting that it's better to do one thing really well than to be a more generally available and usable programmable chip company and so what etched is doing as we'll hear about in just a second is building chips that are specifically designed to only run transformers which is essentially the thing that the famous attention is all you need paper introduced to launch what we now call the llm or ai revolution so let's hear from etched about why they think transformers are here to stay and why their chip in their view is going to take the

SPEAKER_48: market by storm hey everybody welcome back to twist we have yet another twist 500 interview for you

SPEAKER_00: today and this is one i've been hunting for some time because i think this company's bet on the future is both incredibly interesting incredibly bold and can have big market impact so please welcome to the show it's gavin uberti from etched gavin hey how you doing i'm doing well it's great to be on the show yeah no i'm so glad that you're here because when i was doing research onto all the startups out there that are building chips for the ai realm trying to figure out who might be the next nvidia the next i don't know rebellions whatever you guys had a very specific approach and i'm going to try to phrase it for folks out there but essentially the idea behind etch is to make transformer specific chips so i want you to tell me why you picked that thesis and also how the progress has been to this date right

SPEAKER_119: now it is clear that ai inference is going to be a massive massive market and there are already a number of chips on the market like nvidia's gpus and google's tpus that do a pretty good job of this and what they have in common is that they're all programmable you can go run code on nvidia gpu or google tpu to run many different kinds of models convolutional networks like resnet transformers of course lstms rnns whatever whack you think comes out of you know neural network factories but this is a trade-off because they're so flexible because so much space in these chips is spent on caches and control for the logic only a very small fraction of the die is actually spent on the math blocks

SPEAKER_121: the matmoles that do the work to run the ai model just do that down for folks out there

SPEAKER_00: right now people are using a lot of chips gpus tpus from google for example they just dropped the sixth generation of trillium i believe these are flexible but that comes at a cost so if you want

SPEAKER_07: to boost the math capabilities you need to be less programmable but that does also make you more

SPEAKER_121: efficient in the process right we're taking a bet at etch our chip is not programmable it does one

SPEAKER_119: thing and one thing only and that is run transformer inference but in exchange it gets much higher throughput and much better time to first token latency and for folks out there who don't know

SPEAKER_23: what that means essentially if you're doing inference it allows you to have the results come back

SPEAKER_128: more quickly as i understand it you got it it means that both you can serve way more users with the

SPEAKER_119: same amount of servers or you can go and give your results back to each user way faster an order of magnitude more new nvidia blackwell gpus those blackwell gpus have been really not basically in

SPEAKER_23: the last quarter or so so you're saying that what etched is building could be an order of magnitude better than not old nvidia tech but what's state of the art right now that people are paying i mean i mean honestly hundreds of thousands of dollars per unit for oh yeah again it's a trade-off nvidia is

SPEAKER_119: a great company and their chip does so many things better than ours do we can never run resnet we can

SPEAKER_132: never run physics simulations what we are good at is running transformer inference and there we will

SPEAKER_23: outperform by 10x and this is why i'm calling the company a bet because if transformers remain the bedrock of most ai models out there you guys are building a technology that i could see having almost infinite demand but if the world of ai moves away from transformers you guys could be sitting ducks so

SPEAKER_00: i'm curious about the the level of confidence you have in transformers retaining their primacy in the ai game today compared to when you started the company because people are working and there's always

SPEAKER_23: new things coming up so i'm just curious how much you guys are like yeah transformers the correct place

SPEAKER_119: to bet the company well we first started the company it was a much riskier proposition we began this company midway through 2022 back there were some transformers like gpt3 but when there was no big

SPEAKER_139: demand yet gpt3 hadn't found a use case there was no chat gpt so as a result you had all the risk

SPEAKER_140: but none of the benefit so you guys were jumping off hoping to find a parachute on the way down and

SPEAKER_23: then chat gpt comes out and voila you guys must have felt like absolute geniuses when a transformer-based consumer ai product went from zero to literally the talk of the entire world overnight well it was

SPEAKER_128: certainly good for us don't get me wrong and helped us raise around a seat funding but there was still

SPEAKER_119: a lot of risk transformers were one key technology other things ran differently stable diffusion for example was a unit maybe that was the future okay diffusion 1 1.5 and 2 were all units dolly was a unit so we weren't clear what would happen but over the course of 2024 i think we really saw the bet crystallize stable diffusion 1 1.5 and 2 were all units but on stable diffusion 3 it turned out the transformers worked better and they've been transformers ever since or video generation i'm sure that you saw sora of course the breakthrough that sora had was using a transformer for video generation that was the secret sauce they talk about it in the sora blog post i missed that or i'm

SPEAKER_00: sure that you saw oasis transformer as well yes okay so it sounds like you guys made a bet the

SPEAKER_23: transformers were going to be the future and we'll build chips for it the market then drops chat gpt accelerates things but still not entirely clear where things are going to go but by 2024 last year you're pretty confident and i presume that that confidence was shared by investors because you guys raised a enormous 120 million dollar round uh i think it was june of last year it was a good round i preferred i could talk more about customers okay can you just break down for people how hard it was to take what i consider to be software and and kind of burn that into actual chips themselves because that translation is the part that i know the least about and would love to learn the most about

SPEAKER_119: this was hard and it's hard for a couple reasons the biggest one by far is utilization on a chip like an h100 there are you know about a petaflop of fps 16 flops on each one of those dies the h100 is the

SPEAKER_23: preceding state-of-the-art generation of nvidia gpus and can you explain to me that second half of your point because folks out there are not as deep in this as you are ah thank you for uh chiming in there

SPEAKER_119: when we run an ai model it's made of math operations and one math operation is way more common than all others called the multiply accumulate it's very simple you have three numbers a b and c and you do a times b plus c okay and one mechanism you can use to model how good or bad an ai chip is is to ask how many of those math operations a times b or plus c can we do per second and there are a lot on a modern ai chips nvidia's hopper classic chips the h100 can do almost one quadrillion multiply or add operations per second for fp16 one quadrillion which is a thousand

SPEAKER_118: trillion it is a thousand trillion okay that's the preceding generation how much faster is blackwell

SPEAKER_147: well the thing about blackwell is actually not much faster the highest spec blackwell chips the

SPEAKER_119: b 200s that are water cooled on each die they have 25 more flops so instead of being 1 000 trillion

SPEAKER_153: it is 1.25 000 trillion and you guys have written about how we're seeing moore's law this is where

SPEAKER_23: moore's law is crunching that you're not able to fit doubling amounts of transformers on these dies so the dies are getting larger now for these these chips right in fact moore's law doesn't even apply

SPEAKER_128: for the move from the previous generation of nvidia product to the current generation usually as time goes on

SPEAKER_119: you make your chips on more and more advanced process nodes a process node is a sort of assembly line for making semiconductors you hear about 22 nanometer 14 nanometer seven nanometer five nanometer

SPEAKER_156: and so on two nanometers the current state of the art as far as i understand it this is a bit of a

SPEAKER_119: misconception that when they went and made the h100 dies the previous generation of nvidia chips they built them on the essentially five to four nanometer process node okay but when they built

SPEAKER_121: blackwell for the first time in many years they did not change the process node the next gen three

SPEAKER_84: nanometers was not ready oh my but that does imply though that there's a next generation coming that will

SPEAKER_161: be again programmably quite powerful this advertisement is paid by fidelity private shares

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SPEAKER_128: about it here on this week in startups don't get me wrong nvidia is a great company and they will keep

SPEAKER_119: innovating but the pace of improvements on the semiconductor side is slowing down no longer can you keep

SPEAKER_172: getting the performance better for free every uh two years it will keep getting better but at a slower rate

SPEAKER_62: so essentially if nvidia is not able to squeeze more of this math per chip as time goes along and demand

SPEAKER_00: for llms which are transformer based remains high and growing that does perhaps open up a spot in the

SPEAKER_23: market for a transformer specific basic you got it okay so essentially my my big intention that this company is a is a bet or a wager that transformers will remain you know important is almost been answered by the market with a yes and with the information from nvidia there is space in the market for it so i guess actually maybe this is the right time to say okay your system is called sohu and you burn transistors into it so please get back to the translation from software to hardware

SPEAKER_119: part of this well on nvidia h100 or b200i you have some headline number of the amount of math operations per second it can do say a thousand trillion multiplies or ads per second so you might expect you could actually get that but this is not the case usually the number of operations you'll actually get is only about a third of what they claim in the headline number for example when meta trained llama 3 they got between 38 and 42 percent of the headline number of flops and they hailed at that it was one of the key points in their paper as a really great accomplishment they worked hard and they got less than half usage of the flops that are claimed on the side if 38

SPEAKER_147: percent is good gavin what's um an industry normal bad result you can easily see 20 percent

SPEAKER_119: whoa that's one-fifth it's a massive massive thing even with this nvidia is able to get that 20 that 20 30 38 because they spend a massive amount of software resources making their uh stack quite

SPEAKER_180: good which other competitors kuda kuda and pytorch from the whole ecosystem around it but for other

SPEAKER_53: products you'll see even less but i presume that we're working our way towards that etched has a much

SPEAKER_147: higher yield on flops well that's the key thing with an nvidia product they have to build it to run

SPEAKER_119: any kind of program and as a result it's much harder to model hey how do you pack data in for a transformer how do you get that really high utilization number but on an asic for example on a bitcoin mining asic you will get 99 100 utilization of the bitcoin mining hashes per second that they claim on the side because that's all that it does we should define asic here i'm so sorry gavin

SPEAKER_99: but it's application specific integrated circuit it's essentially a chip designed to do one thing

SPEAKER_119: okay back to you yes on the bitcoin mining chip what you see is what you get it only does one thing and also it'll be the same way of the number of headline flops that we claim uh you will find you will get more than 90 utilization of those flops because the whole thing is built around getting to

SPEAKER_00: that really high utilization number why does that matter because if i can get 38 and nvidia's making bigger or more powerful chips do i really care about the yield is it an economic point is it a

SPEAKER_23: simply a space and storage point why does that number matter it's a massively economic point because

SPEAKER_119: to go run a model to go get a token out of an llm you need a fixed number of math operations you can actually calculate it very easily to a first approximation if you just take the number of parameters and multiply it by two that's the number of math operations you need so to get one token as input or output of say llama 7db a 70 billion parameter transformer from facebook you need 70 billion times two or 140 billion math operations so if you're only able to get a third of the theoretical maximum the amount of math your chip can do you can only serve a third of that number of customers

SPEAKER_62: but if you get 90 you can serve three times more customers now this comparison works well if a etched sohu

SPEAKER_23: asic specifically built for transformers has a similar power draw to a competing chip because we're talking economics and it's three times as math efficient but 800 times less electricity efficient you're losing ground a little bit so what can you tell me about the power and cooling requirements of the eventual sohu chip which i don't think is in the market yet uh we have some

SPEAKER_139: very exciting stuff coming out later this year okay but how is it looking from an efficiency uh

SPEAKER_119: perspective we're going to be 10x better in terms of tokens per watt now watts don't matter for the reason i think most people expect and i'll show you some back of the envelope math as to why okay for an nvidia 8x h100 box you can expect to pay around 300 000 for that system which is eight of those chips inside of one cage inside of one server you got it that will draw around 10 kilowatts and the rule of thumb is that a walk costs around a dollar a year okay so that would be ten thousand dollars per year to run that eight h100 cluster you got it what this means is that if say the lifetime is five years you're spending three hundred thousand dollars in capex and you're spending ten thousand times five or fifty thousand dollars in power costs that the economics of big ai chips are just dominated by the cost of how

SPEAKER_00: expensive the chips are ah it's so interesting okay so if you're talking about a 10x reduction though in compute per watt a equivalent system from edge would cost 5k over that same time frame

SPEAKER_119: versus 50. well the key thing is in terms of power we draw the same amount as the new blackwell chips but in terms of throughput you're going to get more than 10x more as a result the watts per token

SPEAKER_182: goes down by an order of magnitude so you guys actually had a riff on your site that just says what would happen if ai models get 20x faster and cheaper overnight it's sounding more and more like that's not actually polite height it sounds like you guys have a pretty good shot at executing that so

SPEAKER_23: how close are you guys today to getting this sohu chip out is it going to launch this year or are you going to show off more of like a demo run of manufacturing later this year how close are you and

SPEAKER_119: we've got getting a ton of customer interest uh from a huge variety of customers you have publicly traded ai companies clouds to labs to enterprise to high frequency trading firms that for those folks time to market is everything now the fact is demand is just not the bottleneck for us to get the product

SPEAKER_07: to market it's all manufacturing have you guys discussed who your manufacturing partner is oh

SPEAKER_119: uh yes we have picked this out it's not just one person that sure you need to have one partner who does the assembly of these servers but there are so many other parts of that supply chain who's going to go ahead and make the actual dyes how much allocation do you have very early on we were able to work directly with tsmc's emerging businesses group and 4p which allowed us to get pretty close access to

SPEAKER_182: their fab team how much capacity can you get through that tsmc program because i know that everyone right

SPEAKER_23: now is trying to get higher yields on their chips and to get more manufacturing capacity so from my end

SPEAKER_182: it would seem like nvidia is going to buy up all the available manufacturing capacity to leave you guys out in the dust but it sounds like you do have a good amount of available manufacturing capacity

SPEAKER_128: we're in a very good place there we have our hbm locked down we're in a good spot with tsmc as well

SPEAKER_23: hbm is high bandwidth memory which is an incredibly important part of the ai data center infra stack if you will if you have a lot of gpus but not a lot of hbm it's still slow you need both and also you need to have a quick fiber and blah blah basically it's very hard to do this because everyone

SPEAKER_156: wants to do it to the nth degree but the good news for you is that that means market demand is going

SPEAKER_119: to be uh bonkers i think it's such an exciting time right now in the ai inference space especially given some of these new reasoning models and some of the advances in video generation technology too

SPEAKER_209: so this brings me to something that i wanted to dig into because when i was going back to the etched

SPEAKER_23: stuff and we were joking before we hit record that you guys have been pretty quiet so most of the

SPEAKER_00: material is a little bit dated but you were talking about how quote scale is all you need for super intelligence and also you guys were talking about trillion parameter models which is the

SPEAKER_23: pre-training side of scaling and then we have post training scaling and then we also have test time computer reasoning which is what you're referring to now does the sohu chip from etched work in each

SPEAKER_119: of those three areas of ai scaling absolutely and i am extremely excited about a reasoning time scaling tell me why i'll give you an analogy back in 2006 if you were a telecom company you were limited by the size of your mark there were only so many americans if you're billing per minute there are only so many minutes that americans will hold talk on the phone and what changed this model sell data yeah the moment the iphone came out they were able to go sell way more bits in the same amount of time and grow revenue pretty considerably and i think we're seeing a very similar moment right now for llms in the past limit was the human eyeball that if every token that comes out of the model has to be read by a person the bottleneck's probably the person's time yeah there's only one token in a token but now that is changing thanks to reasoning models if every token the user sees the model has one ten a hundred thinking tokens and you get to bill for those then suddenly the size of the market has gone up by 100x a thousand x overnight which is very very exciting for us what is this sohu chip gonna cost me i can't say too much on pricing here we price 10x cheaper than nvidia in

SPEAKER_00: terms of dollars per token so it sounds like i won't be able to see these out in the market for

SPEAKER_23: a couple of quarters what's the next milestone from etch that i can have my eyes and ears out for as you guys work towards commercial viability and availability and so forth yeah i can't say too much

SPEAKER_139: now but i am a big believer in showing and not in telling and if you like seeing much of their like

SPEAKER_119: showing i guess let's have to look forward to in the next two quarters okay so before the end of 25

SPEAKER_00: okay good okay that makes me very excited if you guys fundraise let us know although given how much

SPEAKER_23: money you raised last year i didn't think you'd be doing that for some time but i'm blisteringly excited because i love everything i'm using ai i have this fancy open ai account i'm paying google

SPEAKER_00: i'm in a complete stop for this stuff so i can't wait to see the future when it's cheaper faster and better so gavin thank you so much and for folks who want to find you online what's the url

SPEAKER_180: and what is a role you're hiring for yes url etch.com you're hiring for many roles if you are a fantastic firmware fantastic kernel engineer we'd love to go bring you on staff alternatively if you're good at manufacturing we'd love to go talk as well so if you're doing uh real world stuff or digital

SPEAKER_182: stuff call gavin because he is hiring please please do this has been yet another fun twist 500 interview

SPEAKER_222: and i'm excited about etched can't wait to see how they do it's great to be on the show take care alex

SPEAKER_84: i had so much fun with that one i love talking to people who are so deep on something that i don't you know i don't talk a lot about asics in my day-to-day life because my spouse doesn't work in technology so it was so much fun to nerd out with them my big takeaway from this was how much you need

SPEAKER_11: to know how deep your knowledge has to go about what your company is going to do and what your competitors are doing and like where because he does have like a market fit like here's where i have an opportunity here's what nvidia is not focused on that i can focus on and like here's this narrow segment of the market that's open that i can sort of exploit but if you didn't have this kind of a nuanced understanding of ai architecture and chips and how eggs and not just how the

SPEAKER_10: technology works but what nvidia is doing and how you can sort of counter and complement their strategy yeah you couldn't do this like you could only build this company with this level of institutional

SPEAKER_07: knowledge my favorite kind of founder takeaway from this is don't be afraid of hardware i mean they're working with you know tsmc and all this but i mean just if this chip hits the market the way they think it's going to this company is going to print money and i think that we talk a lot about software which is great but there's just fewer companies out there trying their hardware game on and i think we're going to see some real generational companies built in the next couple of years and i'm

SPEAKER_23: i mean if i had five if i was an investor i'd put five bucks on etched you know versus a lot of other

SPEAKER_10: companies well i think with with software and and and these are you know our prejudices or our preconceived notions about it but it feels like oh there's so much wiggle room like if they're doing this you could build this other thing that's not exactly the same and with hardware it's just and and you know

SPEAKER_11: like i i don't think we're right but there's this sense of like well if they could build it any better why wouldn't they already be building it better you know like there's a best way to engineer something and once you've done it that's it and you know like you guys were even talking about in the interview like moore's law and like we have all these like hard like numerical like this is how much better chips can get over this much time and you know because it's physical it's like how how how small can you fit something you know and so i think yeah that's it's an interesting approach to like well there aren't these hard limits in hardware that we necessarily think are like

SPEAKER_229: built into the physical world yeah imagine how cool it would be if overnight the cost of a inference dropped by 10x i mean that would be explosive right it would be it would change

SPEAKER_11: everything and i mean that's what we keep we keep seeing this sort of promise like even the the deep seek sort of news and it's like is somebody going to figure out a way to like do the things we want to do but with dramatically fewer resources and power and and and everything else for a lot less money a lot faster and it does feel like we're we're tantalizingly close to that level of revolution

SPEAKER_234: we are we're very close but let's drop the hardware game let's pivot over to software our next interview

SPEAKER_00: is with a company called sky flow or sky flow if you want the ceo is anshu sharma i've known ashu for a long time long sky flow is a company that i've been tracking for a while we'll talk about what it does in a second but it's a company that started kind of cyber security and ended up in the ai game so for founders out there who think that they cannot expand their vision with time well here's an example of a company that did that and is doing quite well hey everybody welcome back to twist so today i'm gonna bring up a founder that i've known for a very long time i met him back when he was a venture capitalist previously he worked at salesforce and oracle and he started a company called skyflow when it came out it was a company that was built to help companies keep pii or personally identified information private and safe but since the company was born ai has seen a massive boom and the company has also begun to help other companies keep their data secure in an ai context i put them on the twist 500 because of their fundraising history their growth history and because i just happen to know the founder and think that he's quite smart so please help me welcome to the show

SPEAKER_237: anshu sharma from skyflow anshu hey how is that for a polite introduction well that's very nice of

SPEAKER_238: you alex and it's always a pleasure talking to you and arguing with you about the future of everything

SPEAKER_00: yes happily though we are not doing this on the phone this time we're doing this live so everyone can hang out with us but listen anju i've known you for a while i've known the company for a while not everyone who's with us today does so can you go back in time to when skyflow was incorporated put together and you guys launched your first product and just explain to me the market you were

SPEAKER_243: going after at that time i like to talk about it from the perspective of an end user so this morning you probably went and bought coffee and either at starbucks or duncan since you're on the east coast you know coffee companies used to sell coffee which meant that you walk in you walk out they know nothing about you i'm 99 sure you ordered ahead which means you have a mobile phone with an app that app means that they have your phone number they also now know that you visited this location in rhode island so they know where you live approximately in fact if you think about your coffee company knows more than maybe your wife does because you know who you're having coffee with i can coordinate that and that's just your coffee company now think about the streaming company you interact with the airline company when you used to buy flights 15 20 years ago you bought a flight you know the end of it now everybody has a frequent flyer number and that's not enough they also have a credit card number well why do they have credit card numbers for the frequent file numbers because they want to collect data so that's the world i was living in when the big breaches at companies like capital one facebook kept happening yeah and i got sick and tired of it and i was like what's happening behind the scenes inside of these companies and the answer is they are drowning in data and the data is about you and the sad truth is we want them to have our data you really do want to order your coffee ahead you really do want that 13 off coupon from company that sells you know online dog food at the same time we don't want our social security number credit card number date of birth email address in plain text in all of these places and your coffee company was not built like a bank even though they have no data about you than the bank and so the question i asked like what does bank great security infrastructure for data look like and the answer was what do banks have they have a wall so we decided we're going to build a vault for your personal information that we sell to enterprises and that was the founding story of the company fairly simple what if there was a company that could securely manage this information for the pharma companies that you buy drugs from the coffee company down to the last small bit of information exchange you're going to have so we live in a world where we want to have personalized service we want agents now we want ai and none of that can happen unless we trade personal information the coffee analogy works for me because the problem

SPEAKER_00: that i've had with cyber security and its progress is that it seems that the tools have gotten better over time to keep things more secure but the rate at which more companies have taken on more of our personal data has grown faster and so even though i think the state of cyber security has improved i felt less secure and that's why originally when you were telling me about polymorphic encryption and you know privacy vaults and so forth i was into it but that's all back in i think it's the company was founded in 2019 yeah that is right before covid that is heading into the 2021 boom so talk to me about the uh the time from founding up until chat gpt launches and how growth went at skyflow for the

SPEAKER_243: cyber security business yeah any company starting out the first question is will anybody ever trust you with information and security because you're not follow-up to networks and you're not ibm although

SPEAKER_245: people do get fired for buying ibm now sometimes uh so i think for us what we discovered very fast was

SPEAKER_243: if we went and talked to companies that were building fast-growing companies they were the fastest to take us up because they intuitively knew that security was important so think about companies like nomi health it's a health insurance company companies like equal identity which is building the clear of india all of these startups they were like hey this makes sense i don't have the same 40 engineers that amazon's pharmacy team has or netflix team has building their equivalent version of a pi wall so let me just buy it and i can just turn it on and then over the next few years we climbed up from these startups to bigger and bigger logos so you know we got bigger quicker customers all the way up to good rx which has you know publicly known information over 20 million subscribers 100 million people's information they interact with if you want to buy insulin or you

SPEAKER_250: want to buy a glp1 drug you can get it for 80 off if you use our customers coupons at good rx but that

SPEAKER_256: was the journey before sam markman changed the world yes but before we get into the launch of

SPEAKER_99: chat gpt and everyone wanting to use their enterprise data inside of ai safely talk to me about

SPEAKER_00: how much your acv went up a lot of founders watch this show aren't you and i bet they're curious

SPEAKER_239: as you went from startups up to even now public companies as customers how quickly did your average kind of contract value change and uh looking back would you change anything about the choices you

SPEAKER_243: made along that journey yeah so i always tell founders you have a choice you can build a company in a known market but everybody knows they need storage they need computing they need crm and if you go in that market you can call up any customers and all the question is going to be like why you as opposed to why should i buy this in the first place the challenge is once you get your first 100 customers eventually you have to become differentiated and then the long pain journey starts on the other hand there are companies like mongodb you know if you started mongodb in 2006 or whenever they started for the next five years nobody knows what a no sql database is even today if i ask you what's a document database and what's no sql well you know it's not sql but what is it and the answer is when you're creating a category because it's trying to solve a problem in a new way you have to educate them show them a new way and that's how you get started so we got lucky frankly because security is such a high priority for these cto's that we were able to get to our first million year are pretty much within the first nine months of our company starting off but we didn't then go out and hire 100 sales people overnight we knew that we had to prove with these first set of customers that product is reliable product is secure and the product just works so we took a measured approach we tried to be trying to double or more every year for the last five years and we've hit our goals so we're excited about the rate of growth we are at but the goal is not growth for the sake of growth the goal is to prove to the customers now today we have you know you might have seen press releases with service now visa and all these logos it takes many years of getting good rx and nomi health to be passionately happy with you to convince a visa or service now or walmart to engage with you but just

SPEAKER_00: putting this kind of concrete terms uh how big were your earliest acvs with startups and then i know you can't tell me exactly how much individual customers are but uh how big have your contacts become now our

SPEAKER_243: early customers paid us anywhere between a few thousand dollars a year all the way to a hundred thousand dollars a year okay and now that would be considered a very small deal that may be one of our insights is rep handles and the size of deals with some of the largest companies of the world is truly orders of magnitude higher got it i can't share those numbers but think about the largest fintech company in indonesia right the largest e-commerce company in all of asia they have 380 million users data when they sign up with skyflow you can multiply that number with hey it's still

SPEAKER_252: of extremely large number thank you for that but let's keep uh on this uh chronology so chad gpt comes

SPEAKER_00: out the world goes oh my god llms are the best everyone races to begin to experiment with them then as time passes people get a bit more sophisticated and i think people really got the idea that if you want to apply ai to your business to your software you're going to want to use your own data and there was some news items out there about companies accidentally leaking information into llms so i presume pretty quickly honestly that the market was like okay if we're going to go this route we're going to need to have a solution that will keep our information both secure and i think segregated in such a way that it had a different i'm going to butcher this permissions structure so that way llms didn't reach it and grab the wrong thing at the wrong time

SPEAKER_156: so talk to me about market reaction from your perspective to the post chat gpt world up through

SPEAKER_243: today yeah so when chat gpt came out you know i started trying it out and i was like this is fun i have no idea why like people are worried about privacy and security because all i'm asking it is what i call wikipedia questions right they're in english language and so i can say tell me more about why you know india got independence in 1947 versus 20 years ago but the data i'm talking about is just data that's available to everybody right it was my chance conversation with actually the co-founder of salesforce parker harris where he started telling me about what they were beginning to build for their customers and how they had to worry about security and privacy and that led me to start thinking about wow when you take this technology apply it to customer data you now have a whole set of challenges there's challenges for software vendors whether you're starting a company that's automating call centers or legal documents you now have to earn the trust or the enterprise that's going to consume that technology how are they going to hook up their most valuable data to these startups or even large enterprises and still trust them and so this trust problem became very apparent and it actually took me a few months of these conversations repeatedly with very very large companies to realize oh polymorphic engine that we built for securing data in your databases in your crm in your snowflake and databricks can perhaps be purposed for unstructured data and the light bulb moment for us was a healthcare company that was building ai models they just want to be able to build models of with real data because you can't buy fake synthetic data if you bought synthetic data you would find out that 20 year olds have the covet at the same rate as 80 year olds right which is just not true so synthetic data in one sentence is amazing to do what i call scenario testing you know what if the car started driving on the road in the opposite direction you can it's hard to how to create real data for that on a 101 synthetic data is easier so when you're testing by creating outlandish scenarios that you may not have thought about or just testing the basic functionality of your software should i punch

SPEAKER_270: any bazillion dollars into this field and see if it implodes synthetic data is great for that okay

SPEAKER_243: that makes sense but the keyword in ai is machine learning you don't want the machine to be learning off of bad fake data you want the machine to be learning off of real world data but without knowing my date of birth and social duty number right so besides entering the market there can you de-identify and certify the data that's going into models can you do it not just for structure data but also for pdfs actually one of our customers passes all the voice files through us so how can you build models off of real data and then you can test it with synthetic data by the way later on without risking any of the sensitive information sensitive information is not just personal information if you have a rare disease that's sensitive information right if you are a drug manufacturer and running a clinical trial on some new drug molecule name of the molecule is sensitive information so it turns out all of those pieces of information need to be protected in the same way that we will protect yours and my social security number so we took that technology applied it to all of the sensitive information and start shipping our model training and drag infrastructure product line which was uh the skyflow

SPEAKER_236: gpt privacy vault that you guys put out in uh 2023 i believe exactly right six months after

SPEAKER_243: we started playing around with and honestly at that time it was more of an experiment right you know i learned both at oracle and salesforce ship early versions and see the test the market and the response was interesting startups were immediately on top of it because what was happening to them was they were building these amazing demos getting those ar that's not really repeatable because innovation team has green lighted the product right and then getting blocked by the cso getting blocked by the chief privacy officer because who wants to save three dollars in a call if the personal information about a customer's life insurance policy is going to get leaked yeah so as startups running into that wall and bigger companies started running into this wall we started getting interest from them and then it took another six to nine months before enterprises started realizing that because it went from being a vendor problem to being an enterprise problem so when we

SPEAKER_23: spoke back in i think it was kind of early 2024 you had said that you know you were now seeing about

SPEAKER_00: 30 percent of your revenue i think net new revenue was coming at that point from large language model related usage uh how much of your business is now predicated on ai versus kind of the cyber security picture and how is the revenue mix changing as 2025 gets underway an amazing thing happened we took our data security

SPEAKER_243: product applied it to ai security and privacy meanwhile ali goazi and the new ceo snowflake either had this vision that actually ai and data are the same platform right things are going to build on your data is the ai applications and so weirdly enough our product is no longer two distinct complete solutions because our customers have their data in bigquery in snowflake and database they're trying to build models they're built in chatbots so they actually now view this as the modern ai data stack

SPEAKER_00: the way that i've been thinking about things as in you guys protect pii and also help companies use their data inside ai models safely really those are not distinct use cases anymore it's all kind of the same

SPEAKER_236: product and sales cycle because what what are you building here on top of it's your data yeah okay where

SPEAKER_00: is the data exactly what but it implies that companies that were probably even prior skyflow customers are working their way towards building their own ai services solutions models whatever is my read correct that what you're saying is that every company wants to use their data inside of ai and this is not a subset of your prior customer base it's pretty much all of them yeah so all of our

SPEAKER_243: conversations now start merging with each other it still happens that some companies will say hey i want to build an internal it help desk ai need to protect the data going in let's start there and then we say hey so where is this data coming in from and where is this data going oh you know my application is service now and my data lake is data breaks okay now you have to protect the data going in and out of these places so a perfect example is you know we just announced a partnership with visa and service now service now has this amazing new product called credit card dispute management right you charge back you dispute a charge well in the old days that would be a manual process and service now with their not ai platform and their data platform they want to make it such that a bank or a merchant doesn't have to spend weeks figuring out what's going on but to process that what information are you processing what is that data warehouse app or model looking at well it's the details of your transaction it's your credit card number it's the thing that you bought maybe a medication that you bought but you didn't really buy because someone else bought it on your behalf well all of the data has to be carefully protected before you will let that information go between multiple systems and that's what we are doing with service now and visa so very very simple use cases but deep vertical use cases suddenly you realize oh ai is all about data and workflows and therefore it has to be protected in that context

SPEAKER_23: i mean that's bullish for future skyflow growth i'm curious though you mentioned earlier that you

SPEAKER_00: guys have been i think you said something along the lines of doubling every year or shooting for that one thing we have seen from a number of what i might call ai first companies is historically quick

SPEAKER_156: revenue growth and i know you and i both share a little skepticism about how durable some of the arr is

SPEAKER_00: innovation budgets people testing etc but no matter how you slice it growth for the leading startups today has never been i think faster so have you felt any pressure as a founder and ceo to try to grow skyflow even faster than old-fashioned startup growth norms i think i learned this from

SPEAKER_243: looking at the growth charts of salesforce and hubspot and every other company that's durable and large the key is growing you know 2x or more in the early years and then being able to sustain that growth of 50 plus for another 5 10 years and then 30 for another five years what we are selling is so core to the infrastructure of these startups these enterprises these ai solutions people are building that you can't just go in and say hey why don't you start out if it doesn't work come back to me later i would rather have 10 customers like service now visa and others who are referenceable and happy then have 18 customers who are trying it out so our revenue tends to be much stickier it's kind of

SPEAKER_246: like you know once you build it in uh you leave it on nobody turns soft data security unless they

SPEAKER_236: want to have a breach i guess exactly you're saying that your gross retention at skyflow is very close to 100 yeah so companies that die are the only companies that leave skyflow there's only one way

SPEAKER_242: out it's in a casket a little dark but no it's good news for you and last year a lot of fintechs did die

SPEAKER_243: so and now they're back in growth mode again so it does happen so we're not immune to the market forces sure but customers that rely on data security data residency building the ai models tend to stick with it for a very long period of time and i think you can always grow faster by hiring more sales people and their times and phases for that and we are planning to grow faster but i think it's been exciting so it

SPEAKER_00: seems that in and around the skyflow area of the market there is elevated compared to the last couple years m a interest and so i'm curious anshu um are big companies sniffing around now are they trying to kick the tires on skyflow and see if it's something that they want to pick up for themselves

SPEAKER_241: you know i've worked at most of these companies that are most of these ceos we are always talking

SPEAKER_243: to them working with them but in the context of partnering with them right so we have partnerships with snowflake we have partnership amazon we have partnerships with service now you know my goal is to build a generational company and the best way to build a generation company is to have these

SPEAKER_00: companies as partners people have been talking a lot about where value will accrue in the the ai stack if it's going to be at the data center layer what jensen's now calling ai factories the model layer the application layer or kind of where i put skyflows if you will which is like enabling the app layer on top of models if that makes sense i'm just curious from your perspective and you know the other founders and ceos you talk to where do you think most of the value will kind of pool because

SPEAKER_71: i'm sure that other founders want to know where they should be building a very simple way to think

SPEAKER_243: about it is where is actually value getting created for certain types of businesses the value is in legal know-how so how we can capture a lot more value than whatever else they're using under the hook so verticals aside okay for most of the other things it comes down to actually how replaceable you are in a world where there is only one leading cloud provider all the revenue growth was going to one large cloud provider today we have three or four cloud providers so the prices is this competition we only have one gpu player that was meaningful until a year ago and that's mostly still true and if that says to your pricing power so pricing power goes between layers not based on how important you are or how big of a keynote you do pricing power shifts on how many other companies similar to you can deliver almost the same functionality i call this are you one of n or n of one so one of n is there is any companies that can do this right compute virtualization storage and the moment any companies can do it you're basically doing feature function price analysis and of one is there is only one nvidia three years ago that's building a gpu on which you can tell you more you can complain as much as you want about blackwell being late by three and a half months what are you going to do unless you have google you can't build your own tpus right so i think that's the framework why we go as a result something has fundamentally changed 18 months ago i assumed there would be a few companies just like gpu was the only layer there was only one model company that was winning the whole thing there's only really one or two platform companies but today oracles in the game so is you know multiple model companies deep seek meta so as a result i believe the more other layers get commoditized the more unique companies and unique assets not just us you just saw weights and biases get acquired for like a billion dollars basically why because there's not any players that can do what weights and biases does if there was five companies that were very similar in success as rates and biases right they'd be acquired for 50 million dollars as a founder my job is to create value for customers which is revenue but my job is also to create the multiple and the multiple gets created when you are truly building something differentiated and you are enough one or enough two all right well anju thank you so much

SPEAKER_00: we'll have you back on in a couple quarters in the meantime thank you everybody and don't forget twist500.com the coolest companies in the world takeaways lon from the the skyflow chat what you got

SPEAKER_10: i think it was one interesting thing for this chat was you know you you normally think of sales as being this you know sort of aggressive like you gotta close the deal or whatever and he was really talking about it in terms of trust that when you work in uh security and cyber security and protecting people's data it's less about giving people the hard sell and more about establishing like we know how to do this we're gonna actually protect your data and then once you sort of do establish that and people agree to sign with you they don't they don't leave you don't then lose those customers because it's about building up that level of trust so it it feels different than a lot of other kinds

SPEAKER_11: of companies or b2b sort of businesses where you know the idea would be you shop around there's always somebody who's gonna maybe make a better deal and this is really like no it's it's something more

SPEAKER_23: it's a it's it's a different kind of market there's a luxury though and so i i don't think what anshu is saying applies to every single situation uh as we said their gross retention is near 100 and so if that's the case then you're not going to be dealing with kind of standard sas churn and so probably longer term relationships are even more important ergo trust etc so this is pretty far

SPEAKER_18: away from like plg ai consumer sass right like it's yeah the other end of the fence but it is

SPEAKER_00: interesting to see how a company that does sell to the largest companies approaches that so if you are thinking about going up market i hope anshu's comments were useful to you i think skyflow is a cool company i think they actually did a small memory service a small down round in their last funding round because after their 2021 valuation but i suspect they're going to be okay and keep on trucking so that's why i put them on the twist 500 lawn and we have one more company shall we hear from them uh please can't wait all right so we're going a little bit of field this time you know we started talking about chips and ai then we talked about cyber security and encryption now we're going out to outpatient clinics we're going to talk to a couple of guys from med serve med serve is a startup that is building essentially secure cabinets for medications now why do we care about that lawn well it turns out there's a lot of rules about that and uh sometimes people might want to take a medicine that's not for them at that time so hospitals have large secure cabinets with relatively intense security in them but those are big and costly and they don't fit in an outpatient thing like an

SPEAKER_71: urgent care clinic or a partial care program for example so med serve is tackling that particular niche

SPEAKER_00: and they want to build a similar level of security but for smaller clinics out there in the market replacing uh not pen and paper this time but instead uh small filing cabinets that are not

SPEAKER_318: sufficiently secure so let's hear from the med serve guys to take us home hey everybody welcome back to twist we have been banging on about ai for quarters and quarters and years now but sometimes lost in the startup game are the companies out there that are really impacting the real world slightly out of sight and in the united states healthcare is one of the biggest industries period and so when we look into the startups that are working in that space we often find interesting things that are just outside of our vision one of those companies is med serve they are building a very interesting cabinet we'll get to that it's going to help with both drug dispensing and preventing drug diversion i'm really excited about this company so please help me in welcoming we have alex and matt the ceo and president of med serve hey guys how's it going hey alex nice thing great to be with you uh so i'm just going to start

SPEAKER_320: at the top here teal is the company color by the looks of it that is yeah we're matching today yes

SPEAKER_234: i love when people show up in coordinated colors it reminds me of like old yc demo days when teams

SPEAKER_118: would all wear like bright purple t-shirts that you could find them in a little group

SPEAKER_326: ah old days that's that's how me and matt are all on the regular well i appreciate that now another

SPEAKER_06: thing that i like about med serve uh is that you guys are actually a midwest based company you guys

SPEAKER_318: were founded i think in milwaukee is that right alex yeah yep milwaukee based and i i gotta say i have uh i i kind of grew up in the chicago tech scene back when i was in university so i do have a big appreciation for the midwest but i don't know jack about milwaukee so tell me about the startup

SPEAKER_62: scene there is it is it active is it burgeoning should i go visit well actually let me turn this

David Friedberg: over to matt matt's got the background in uh milwaukee's tech ecosystem as in startup ecosystem as

SPEAKER_332: he was one of the builders ah matt please yeah so milwaukee has i think a lot of great potential um

SPEAKER_334: you know i think building a company milwaukee has allowed us to access talent um that we may not have necessarily been able to find elsewhere and and what's really cool is as you can see behind alex we manufacture uh medication cabinets pure narcotic cabinets and and we do that right down the street and we're seen wisconsin about 20 minutes away so it's a great place to have a startup that you have to bend metal uh as well as push lines of code to be successful you know i i heard that all

SPEAKER_318: american manufacturing was gone so i guess that wasn't true is there still a pretty solid industrial

SPEAKER_334: base in the milwaukee midwest area yeah we've had a great um you know time in terms of co-developing our technology was originally developed by a manufacturing company um that didn't necessarily see the uh you know technology application of you know cloud-based software and and doing the reporting and stuff that we do um so you know we were able to take that idea and kind of take it to the next level by acquiring kind of some of the intellectual property around medservs cabinets and um improving on it

SPEAKER_318: all right we're going to get into how our cabinet talks to the cloud in a second but first i want to talk a little bit about the problem space because uh my spouse works in healthcare so i have some visibility into what we're talking about but a lot of folks don't and so when we think about drug dispensing and drug diversion it might help alex if you just kind of run through the terms what they mean and then just uh anything you can tell about the scale of the diversion problem that we

David Friedberg: have here in the states so alex i think probably to level set my background is i'm a pharmacist been in the pharmacy world for nearly 20 years now that's hard to say uh but nearly 20 years i grew up professionally within a large health system you know health systems and fancy hospitals they have all the fancy technology outside of the hospital system however you're like traveling back in time so the problem that we're solving we're we're providing digital medication security

SPEAKER_325: and management at the point of care so the point of care what i mean by that you can think of it as a surgery center that's out in the community uh a dentist office uh a clinic every imaging center uh a veterinary's office there's so many different areas where medications are housed and admit

SPEAKER_344: administered to a patient that are outside the hospital that don't have the hospital technology or

SPEAKER_318: budget okay so is this a little bit like if i go to rob a bank like i know there's a vault there's security there's cameras but if i want to go to like an atm there's probably a little bit less security it's a little bit easier to well maybe not atms but you know what i mean essentially if

Chamath Palihapitiya: you're out in the field the fences are lower yes yes so i guess if you went to a bank that's inside of a grocery store and try to rob that maybe that's a good comparison do they have banks inside

SPEAKER_351: of grocery stores they do they do in that in the midwest okay that's a great spot in the little

SPEAKER_352: community you got everything in one place i think that's because it's so cold there you don't want

SPEAKER_353: to go outside and change venue and i recall that from my chicago time yeah okay so we're talking about

SPEAKER_318: surgical centers dentist office these are all around the country and because they do need to deal with uh controlled substances even addictive substances they need to keep them safe so if i did not have access to a medserve cabinet what is the standard legacy solution that you guys are going

SPEAKER_352: up you're not going to believe me so uh these facilities literally use like a kitchen cabinet

SPEAKER_325: that has a lock on it or two locks somebody has the keys on them so sometimes one of the stories we hear all the time is people go to lunch with the key people leave uh the office with the key and then they can't access narcotics because they love uh some people will use a metal like little more secure metal box with a key but the key problem remains the same uh many facilities will also invest in the little like realtor uh key holding box that's on the wall it's got the little pin code you can put in but the pin code shared when somebody quits nobody replaces it they should replace it and uh reset it but it doesn't happen so they're opening stuff up to so much risk by doing this really old school process now this is just the physical storage of the medication uh now there's also documentation component the documentation component i don't know if you've ever if you if anybody remembers the prescriptions handwritten by a doctor imagine those scribbles in a bigger hurry

SPEAKER_344: done by an anesthesiologist on the paper log where they're just jotting down how much they administered to who and trying to make sense of that and people forget how to do math people make

SPEAKER_361: mistakes forget to enter data and a poor nurse or a director of nursing or a manager at the end of the

SPEAKER_325: day has to sit there and try to figure out the numbers and why they don't add up matt so if the

SPEAKER_318: numbers don't add up does that automatically ring an alarm bell and if so how shrill is that that uh that

SPEAKER_332: signal well it's alarming because unfortunately a drug diversion or drug theft and yes alex you're

SPEAKER_334: welcome there it really is a growing problem in healthcare unfortunately healthcare providers about seven percent have self-reported that they struggle with substance abuse issues um we unfortunately see a horror stories of of healthcare providers diverting or stealing drugs intended for patients patients going through healthcare procedures without proper anesthesia um and when this happens that often you know it has to be reported to the dea the dea is the reason why you know we exist in a lot of ways is we're helping you know with the compliance automate that workflow um secure uh narcotics to their standards um so all these facilities you know when when drugs go missing it is

David Friedberg: a very alarming and that's and then just just to add a little bit to it so it's alarming in a number of ways one is uh you're short a controlled substance that you are responsible for so the center

SPEAKER_126: that is the way the dispensing holds the uh the bolus of responsibility yes okay uh so it's the

David Friedberg: center it's the person in charge of the center so let's say the administrator and it's the physician whose name is on the license the da license who's really got the most to bear okay if there are issues let's let's say this is negligence there's not great policies in place procedures aren't being

SPEAKER_325: enforced the facility can be shut down they can have their license suspended so they can basically be

David Friedberg: put out of business and that's without having horrible headlines like matt was mentioning uh and you know we can we can dive into that a little bit later if you'd like but uh so so you have that as

SPEAKER_325: an alarming issue a controlled substance that you're legally responsible for is going missing second is well where did it go is one of your employees under influence taking care of patients

David Friedberg: or is like matt uh pointed out is one of your patients going through a procedure paralyzed can't

SPEAKER_318: move can't yell but doesn't have pain medicine so the liability here is multifaceted the problems are diverse and it sounds like the that you're really protecting the drugs from the providers i was curious if this was keeping drugs out of the hands of patients but it sounds much more like the

SPEAKER_342: concerns on the provider side yeah it's an it's on the anybody who works in the facility and has access to the medication so it's nurses and providers does this also apply to like nursing

SPEAKER_325: homes and urgent care clinics and that sort of thing too yes and anywhere and anything and everywhere where there's medications there's a risk for things to be diverted so whether it's a control substance

SPEAKER_344: that people are using to get high whether it's a medication that's just being stolen because it's expensive or because they're just not tracked i you know i'm hungover today i took azofran which is an anti-nausea medication to make me feel better yeah it's only a dollar or whatever it may cost

SPEAKER_156: but i'm stealing from the organization i'm just thinking about what i've heard about compensation for staffers who work at like nursing home like facilities and it being incredibly low that plus the

SPEAKER_318: cabinet with a little lock just sounds like an absolute catastrophe not just waiting to happen but must be happening all the freaking time how have why did it take so long for you guys to build a better solution like why did why didn't the market solve this like 15 years ago and i say all this as a

SPEAKER_201: recovering attitude into rehab so like i am sympathetic here to the issues that i play yeah so

SPEAKER_325: uh alex i think uh this this problem has been being solved for has been being solved for the last 20 30 years it started with hospitals so technology for this didn't exist in hospitals 30 years ago but it started it started slowly with certain more progressive hospitals now every hospital has a automated dispensing cabinet that is on every wing of the uh hospital floor uh centrally located for medications for the patients uh but it hasn't spread outside of there because economics really weren't there at these smaller facilities can't afford the premium price tag for a product that's built for a

SPEAKER_318: hospital okay talk to me about about dollar six i know that in the healthcare world prices get a little bit inflated so if i was a hospital let's say a 500 bed facility and i was going to put the legacy enterprise solution if you will onto each floor how much would that cost me

SPEAKER_390: millions so they millions it's a filing cabinet with a cool lock so the system yeah the system the

SPEAKER_325: systems in the hospitals are uh they're very they're very company they're very complex and very comprehensive for good reason they follow different workflows they house a ton of different medications uh there's a lot of intricacies and complexities so each machine on every floor will may have two or three machines each machine is probably 150 grand wow okay times however many

SPEAKER_344: floors plus however many other areas around the hospitals they may have those machines okay so just to

SPEAKER_156: summarize we have a ton of healthcare facilities in the nation we have a ton of controlled substances we

SPEAKER_318: have a theft and abuse problem and we have existing technology that only applies essentially to the biggest players in the market you guys want to bring it at a lower price point to those other facilities to prevent theft so then the question becomes how much cheaper is the medserve cabinet that

SPEAKER_118: i can see behind you compared to those 150k uh examples you just mentioned sure so the cabinet

SPEAKER_396: that you see behind me is eight thousand dollars oh well that's like six percent as much yes it's

SPEAKER_325: very very affordable so they're priced right for the market the beauty of our system is our system is scalable and it's modular so a facility can go in with a smaller cabinet or scale up their locker to be much bigger based on their needs and thus their budget uh the bigger the facility the larger the budget of course that they will have uh and uh same thing so most of the products in this industry are

SPEAKER_344: hardware and software products same with ours so the hardware is eight thousand dollars and the software can range between 150 to maybe 600 a month and this is thousands if you talk about the other systems that we talked about earlier in hospitals all right so what i want to know alex is how this

SPEAKER_398: thing actually works if i was out in the field putting this to the test walk me through a standard

David Friedberg: use case if you would all right perfect so uh let's say i'm a nurse and i'm at a facility and i need to take out some medication for patients so we'll uh sign in so i'll scan my badge to sign in and uh i'm going to go and take out some fentanyl that's not here as um probably many listeners and viewers know fentanyl is a highly abused uh controlled substance um so it's behind a digital

SPEAKER_327: double lock so i have it's a two-factor authentication i have to put in my pin code as well as scan my badge so i'll put on my pen code here oh helps if you put it in the right pen code well it just shows that the technology works exactly so then we'll go through and now i can take i can return medication but we'll take some for a patient so we will take let's say one vial of fentanyl for a patient uh and select our patient this comes through from our integration with the ehr or electronic health record uh so we'll select the patient here from the list uh and uh go ahead and uh it unlocks the compartment for us and

David Friedberg: now this is a safety step here where we're asking the nurse to count how many vials are in the cabinet prior to him or her taking them out so this is where if somebody takes an extra cabinet or extra vial or extra pill because as you can see here you have access to the entire content of the cabinet you're double checking the person before you and if the count is incorrect so let's put a 11 or 10 and hopefully it's going to be wrong it gives us a warning that the count isn't correct and i can try again or create a discrepancy when i create a discrepancy as a nurse i'm able to continue and take care of my patient however as my administrator or my manager just got an instant notification letting them know that there is a miscount on medication so they can come and address it right

SPEAKER_403: away and not have to wait until the end of the day uh for them to figure this out and there's no siren

SPEAKER_318: that goes off but essentially there's a digital bat signal sent to the right person to alert them

SPEAKER_406: right away that there's a potential discrepancy or loss of a drug correct and then also there is a little icon that now appears on the screen in the corner here to let us know that there's an alert and that something something needs to be addressed all right and then if you close it up let's see what happens so now it's just closed now i can go in and access a different compartment so here i have

SPEAKER_347: four medications but then i can go through and take out another medication for another patient for the

SPEAKER_386: same page all right a certain stuff here require two people so for example if i wanted to restock the

SPEAKER_347: cabinet uh we require a second person uh so that we always know accurately how much stock was actually

SPEAKER_410: put into the system oh so to prevent people from not putting in as much i see yeah and actually any of

SPEAKER_325: these uh steps here that you see any of these can require two people so different facilities sometimes will have a lot of staff turnover and they always want to have extra um security so that will require

SPEAKER_406: a second person and how tall is the overall cabinet that uh we're zoomed in on here on the video so this one's uh 36 inches tall but they come in different sizes so there's a smaller and a larger cabinet and just because i'm now curious how tall is your tallest cabinet this is actually the tallest cabinet oh i'm

SPEAKER_325: sorry but they are stackable and so you can have multiple cabinets together so typically for average person's height this is the great height from top to bottom where they can reach it and then

SPEAKER_318: they would just have multiple next to each other like a locker wall two more questions and they're both about security now normally i talk to folks who are just building software so we only talk about cyber security but you guys actually have a thing if i was to bring in a sledgehammer or a cutting torch today how robust is it versus me the unintelligent man with a hammer so uh this is this is a good

David Friedberg: point uh so big distinction between a safe and what we do we're not a safe we are we are a cabinet that

SPEAKER_325: keeps things separated and tracks all of the activity and yes we keep it more secure than a regular cabinet but we are not a safe so have you if you bring in a jack as a a sledgehammer or whatever it is that you bring in yes you can break into it now you have to rely on the facilities security systems they have a certain level of security that protects their fence and all that's sitting in the kitchen cabinet door locks employee badges uh cameras yeah exactly some facilities even go as far as put um shocks uh motion sensors or shock sensors on the cabinets if somebody shakes it it sets off the alarms

SPEAKER_344: similar to like your window uh shutter sensor you mentioned scales earlier those are kind of like the

SPEAKER_318: las vegas mini bar effect right that if you take uh yes so this is that that's uh something that we

Chamath Palihapitiya: have on our roadmap is just have to it has to be at the right price point oh no no i i'm not saying

SPEAKER_318: you guys are lacking that i'm just trying to understand the various levels of security here okay so that helps a lot now in a cyber security uh concept it has to be much more durable than a cabinet so i know i know there's a lot of regulation about medical data but how hard was it to get your cyber security set up to the point to which you guys were confident to take on that responsibility

SPEAKER_336: for your customers well it's been a journey um and we're continuing you know it's it cyber security

SPEAKER_332: is something that obviously continues to evolve and whatnot we take it extremely seriously we've built out a security team with you know various vendors and internal resources um here to industry standards and best practices around data privacy and security and um that's allowed us to gain the trust of some of the largest health systems in the country who are excited to

SPEAKER_209: count as customer so and uh no major breaches problems so far all right well i i don't know yeah

SPEAKER_318: i haven't seen your logs um but i'm really glad to hear it um and then finally just one last question about the the long-term future here um are you guys gunning to eventually go public are you hoping to sell to a major provider in the space what's the uh what's the end game you're working towards

SPEAKER_332: i definitely see a strategic and end game here um a lot of providers in this space um and uh you know definitely are looking to build something that they have not necessarily figured out how to do which is go to market these tens of thousands of endpoints in health care alex do you agree you're not

SPEAKER_428: going to take this public you're you're going to sell out before you reach wall street i'm kidding

SPEAKER_325: yes yes uh yes i think uh the market is just prime with a num a number of uh strategic buyers for

David Friedberg: whom would be a great add-on either providing them a market they don't have a solution they don't have

SPEAKER_318: well i mean if there's a plethora of possible providers who might buy you make sure to you know make them pay through the nose when it's time actually sorry one more question when will you guys feel like you've like gone far enough alone as a company that you would be willing to entertain an acquisition offer because it's kind of a matter of taste i think yeah and i think uh so today when

SPEAKER_344: we talk about it we talk about it being a three to five year timeline from where we are today okay um but i think things evolve so they've seen what the opportunity is ahead of us uh and uh we it may make sense to do this for longer it may make sense to uh exit sooner if the right

SPEAKER_437: opportunity comes up well i will be pulling for an ipo but in the meantime i'll be keeping my eyes

SPEAKER_318: peeled for mna but i'm really happy with what you guys are doing i love the idea of keeping drugs out of the wrong hands at the wrong times it's a issue that's very important to me personally so thank you very much and if folks want to find you online where should they go and what is a role you

SPEAKER_438: are hiring for that you are having a hard time landing a candidate for well i'll uh start with

SPEAKER_325: how to find us so uh we are medserv and uh medservrx.com uh is our url we're on linkedin uh and uh quite

SPEAKER_336: visible there um and i think we're always hiring for people that are going to help medserv to the next

SPEAKER_332: level um expand and grow so always looking for account executives that have experience and healthcare

SPEAKER_424: technology sales or capital equipment medical equipment sales all right well there it is

SPEAKER_318: ladies and gentlemen medserv it's not medserverx.com it's medservrx.com that threw me off and i was typing and prepping for the show guys thank you so much and uh come back when you reach the next revenue milestone all right thanks alex thanks alex i think all founders should be forced to wear

SPEAKER_234: color coordinated tops when they come on the show because that was too much fun the most intriguing

SPEAKER_10: part was when you asked is this like a safe like you're imagining like the tom cruise dropping down

SPEAKER_11: from the ceiling no because that was the question that i had like i think it's really interesting if you thought about this as a consumer facing product yeah that's what it would need to be it's like we're this is the next generation safe because your apartment's not that safe it's like if you're going to keep your valuables in here we're going to protect it from a guy with a crowbar and what these guys are saying they had that level of knowledge of being insightful about working at a doctor's office or a pharmacy or they've already got protocols like you're not in the back at the pharmacy anyway they're only looking out for the people who are already licensed to be there yeah not not the uh impossible mission force breaking in through the ceiling yeah it also just goes

SPEAKER_182: to show how specialized things are because i would have just presumed it was a lock with you know the

SPEAKER_12: spinny little you know like a safe style thing three metal bars that come through to make sure that uh gerard butler and uh o'shea jackson jr can't just uh crack in you know you see and that's

SPEAKER_00: why i love having lon on the show because he actually knows the names of people who appear in films whereas i just go it's that guy i've seen him there in the den of thieves alex they're in the

SPEAKER_29: den of thieves well i just want to say that i did frankly kind of come of age in the chicago

SPEAKER_00: technology scene so i will always have a deep and abiding affection for people that are building in the middle of america even though i have now lived on both coasts which is kind of where i culturally fit uh it's great to see people out there building great companies uh everywhere proof founders that are watching that you don't have to live in the same eight blocks of san francisco as uh everyone that you see over on x lon i i think we can wrap here we're back on wednesday we're back on friday live shows jason will be back with us tons of news coming i'm already kind of pulling in stuff for the wednesday docket belong where can people find you on the great wide internet

SPEAKER_11: go on twitter at l o n s that's the easier no it's it's x now we should be saying act to a twitter

SPEAKER_10: twitter long dead uh go on the place that used to be twitter i'm at l o n s that's the easiest place

SPEAKER_182: uh and i just want to say that because i know i knew lawn's twitter handle before he was on the team i keep trying to at lawns in slack and it keeps absolutely not working so can you can you fix that

SPEAKER_226: for me it's not my real name it's not actually my name well it's how i think of you anyways i'm alex

SPEAKER_00: uh alex over on x of course this week in startups comes out three times a week we're on every podcast platform we streamed live on youtube and linkedin and x and instagram and i think also tick tock now and we're trying to go everywhere so wherever you get your podcasts we are going to be there back soon see you then