AGI In 26 Months?! The Future No One’s Ready For

Transcript

[Music] welcome bankless nation to the AI rollup where we cover the weekly news in the AI industry ai is accelerating us into a weirder and more chaotic future and we are here to help you keep up with the future that's hurtling towards us we're trying out a different format this week because the crypto AI industry is pretty dormant uh while the Silicon Valley AI industry is only getting hotter so me and Jaws are bringing in a third commentator Josh Kale who's done a couple episodes with me on Bank list before all about Frontier Technology and who we are tapping in to help us go through the AI news this week jaz Josh how are you guys doing i mean I'm Yeah I'm I'm feeling good it's It's awesome to have Josh um though I can't really

get rid of the uh yeah the $10 trillion wiped out of the stock market this week thanks to Trump's wonderful liberation day tariffs which has in my opinion obliterated any kind of economic recovery that we wanted to get but more so it looks like he's using chat GPT to create his tariff formula right I don't know if, you, guys, saw, this, but, um, if, you type into any AI LLM so that's like chat GBT claude whatever um you know can you create a basic tariff formula you get essentially what the US announced for their tariffs across every single country which is just insane it's pretty hard to get away from talking about tariffs this week just because everyone

is just looking at the market looking at tariffs tariffs tariffs tariffs tariffs but I'm I'm pretty glad that we are also going to focus on AI which I think we're all pretty pretty stoked about josh it's good to have you on the uh the AI roll up this week my man it's great to be here yeah thanks for having me i'm excited to talk about this stuff the the funny thing about what EJ just said is the way that we found out they used AI is actually by using AI ourselves and kind of reverse engineering it and then they openly admitted it after the fact so did they did they admit that they did use chatbt to come up with their tariff not that AI was used but that there was this weird formula that wasn't just tariffs and the way it was discovered was by actually using AI and kind of

reverse engineering it and then they were like oh yeah we actually did do that so it was implied it wasn't directly stated but like there was some artificial help in the decisions being made last week i mean I feel like that's just a harbinger of things to come of like global decisions being made using AI influence uh you know the the crypto technologist will would love to say it's like oh yeah eventually the future will just be governed by AI and you know we accidentally got there maybe a little bit too ahead of schedule a little bit too soon a little too early for comfort yeah it makes the AI alignment conversation a lot more scary when world powers are using it to make decisions or or even write law all right, let's, get, into, the, the, news, of

the week big news this week uh five big things that we're going to cover first the most controversial AI model release ever came out of Meta meta released a new llama 4 AI model uh which on paper is very impressive but people are worried that they are lying about his performance uh and which will also lead into an AA's conversation about why he thinks no one is using AI models correctly that's up first uh second some legends in the AI space author a document called AI 2027 a theoretical roadmap for the how the next three years of AI development will go featuring things like espionage geopolitical warfare and runaway AI intelligence uh third topic this week uh Toby Lutzki from Shopify ran a internal memo saying

that using AI is now a job requirement is an expectation for all employees he released that memo on Twitter so we're going to go and talk about that uh fourth Claude Education focuses on using AI models for just revamping the education industry and we've already seen a a school in Texas rocket their students learning scores to become like top 2% in the nation and then lastly AI6Z is planning a 20 billion AI super fund uh focusing on vibe creation platforms like Cursor for Vibe Coding so so those are the big news of the week before we go into each one of those specifically though um Jos maybe I'll just throw it to you uh set the tone for us this week uh how was this week as a

vibe in the AI space i I feel like over the last couple of weeks we've been kind of increasing tension between model producers right so what do I mean by that it's obviously a very highly competitive market and ever since we had Deepseek come out and compete with OpenAI you know open OpenAI was the darling child right it was you know way far ahead no one was competing with it and now we have these guys that are like you know competing every week now it's become a meme on this show that there's a new frontier model drop um I feel like we've reached the boiling point this week david controversy with a top AI model producer not just from any company from Meta themselves you know we've got

the Shopify CEO announced that if all his employees don't adopt AI tooling in their workflow processes you're probably going to get axed you know tension is getting to a point where like AI might start replacing jobs it might start having significant impact and I feel like people are really feeling it this week josh what do you think about just the acceleration of the AI arms race because like Jaws says every single week on this show we are like ah there is a new like a new leaprogging of AI models there's a new number one and it's been consistent it's been consistent for the past like 10 weeks um how do you think that when it's going gone on for so long how do you think that finally is manifesting in like in it in the current day it is unbelievable that we're still

getting 10x improvements week overw week and that happened this week with the meta um release it was controversial but the main headline that I was excited about is a 10 million token context window and previously Google's Gemini model had 1 million as the flagship so we've got 1 million last week so so week over week we've 10xed the context window which is a very big deal because that is the um like quick access memory for a large language model and it allows you to get a lot more data packed into your queries so to go from 1 million to 10 million week overw week we are still accelerating so so quickly yeah let's let's unpack context window just pretty thoroughly here for people who are like learning about a context window for the

first time josh how would you define a context window okay it is um it's fun to look at it like if you had a book if you have a really big book of pages and you're able to rip out those pages and place them out in front of you so you can see them all very clearly the context window is the amount of those pages that you can see in clear view without having to actually turn the page and find something it is just quick access data to whatever you want to query so imagine it's like not your eyes but it's an AI and it's a camera and it could see everything that's laid out in front of you that's kind of the context window and it's helpful to have more pages because it can see more things quickly and it's also more accurate it

doesn't have to infer what the next token is because the next token is clearly visible in that context okay okay so if I'm may maybe a human way to turn this into a metaphor is like say I'm doing mental math and I'm holding numbers in my brain and I'm manipulating the numbers i'm thinking about the numbers i'm retrieving numbers differently in a sequence a context window means I can think about a larger array of numbers all at once uh before I like lose them in my mental space would that was that a a good analogy yeah that's right um and you can store a lot more so if it is a very complex model where there is a lot more numbers you can store them all in one place and you don't have to guess it is all very clear because it is all seen out in the

general view is is that the big reason why this a uh llama for the new release from meta that's why this is such a big deal or was it more of a collection of things maybe a jaws I'll I'll throw this one to you what were the big standout uh components of this release from meta sure so the first standout was what Josh just mentioned which is the 10 million context window actually to to build off your example Josh it's not just one big book it's the case or equivalent of 75 novels or another way to look at it 75 novel of a context window in a single context window or you could think of it as 1 million lines of code right so that's like one of the major things you know it's it's easy to recall memory

data etc the second most important feature of these models and and I say models because they technically released three models um two which are kind of like basic and then one gigantic model which is like a two trillion parameter um beast uh but the second most important thing is it's a mixture of experts design David which means that at any one point when you're querying the model you're only quering around 14 to 17 billion parameters so it's hyperffic efficient when you're like quering it and for the bigger model it's obviously a larger uh query so it's going to probably hit around 250 billion parameters which is a lot more computationally heavy but it's still way

more efficient than how OpenAI runs their models where they just query the entire trillion parameter model uh and it takes a while to like come back to you and stuff yeah we've defined um parameters on the show before but uh maybe it's worth it just to take some time since we're in the mode of defining things like to me a parameter is a specific uh like node of information or a neuron like a it's a unit of information or a node of information or a or a neuron neural connection in the brain and when you have more parameters you just have like a higher resolution camera pointed at the internet which all of these AI models are uh trained on you have a higher resolution camera pointed at knowledge at the internet and these

parameters with their weights are set to a specific number to actually be a map of knowledge that is digested from the internet and so if you have a higher parameter knowledge uh uh higher parameter model you simply just have a more knowledgeable model there's truly just knowledge is contained in these parameters that's kind of how I think about it does anyone want to amend that definition or add to it yeah that's pretty good um I think with parameters they're also known as weights uh the way it works and this was a big debate early on is is does it actually improve with scale so does it actually increase directly exponentially with the amount of data you feed it and so far it's been yes so so far the more data you can feed

into this the higher resolution the model will be so in the case of of weights it kind of goes through this pre-training phase where it's it's fed just a ton of data a ton of information and then each one of those training runs that happens actually alters those parameters just slightly and then it compares the results of the new run to the previous run and it gets better and better and better and that's kind of how they tune it um and generally speaking the more parameters the smarter it is so the fact that this has I mean the largest one has two trillion parameters that is huge that is a tremendous amount of training data i don't know where they found it from i don't know how they saw two trillion things but hopefully that will result in very very high quality answers okay okay so now we have a 10

million token context window uh and again a token is just like a a unit it's like a syllable of sorts is almost a word uh and then we also have an increase in parameter size but also three different models came out uh so between all of those things that's kind of sum summarizing why the why this announcement from Meta is what it is but there was some follow on controversy downstream of this announcement uh because, people, met Meta, maybe, to, just set the context Meta has been lagging as a model as as an AI lab like met the no one really uses the the llama models as far as I understand it to be like everyone's using either chat GBD4 or claude uh and so Meta has been just like losing this this game uh and with these

release of their new models they are hopefully trying to leaprog their place into number one number one that would be the easy way to like talk about this announcement but Jaz um you're telling me that there's been some controversy with the release of this uh model can you can walk me through that okay so to to summarize this every AI model that is released doesn't matter which company uh produces it are typically uh graded across what we call benchmarks right and uh they're known as sota sa benchmarks or stateofthe-art benchmarks and typically every model producer attributes it to this um the reason why they do this is you know how do you know whether one model is better than the other you can't really kind of you know test or query it you can ask them the

same questions but you're going to get different answers but how do you really know well there's a measurement of different things like parameters like you know we just discussed weights etc um and then there's the actual output of the actual model right so when meta released these three models uh this week um they had all these different grades across their benchmarks and they were claiming uh David and Josh to be as good if not better than deepseeek v3 and v1 or r1 uh and openai's 03 model which is like a really high performative reasoning model right um but for the first time ever there was a huge amount of backlash about these benchmarks um for two reasons number one uh it was

stated uh and there's like a few screenshots that we've seen that you can share on the screen here David um that they had blended test results across different models to basically give a falsified or rather skewed result for their benchmarks across their models so basically they kind of blended data sets to give a falsified answer just so that they looked clearer or nearer to the actual state-of-the-art benchmarks the second thing was and this is the time uh tested trial is people just used the model and was like this is kind of [ __ ] and it isn't it isn't as good as OpenAI's reasoning model or it's not as good as Claude's model or etc and so people were just like is meta lying

about this now there was a lot of back and forth a lot of rumor fear-mongering etc um their head of generative AI armored actually came out and stated that this isn't got anything to do with their benchmark their benchmark testing is you know to a high quality or high grade however there is an implementation issue so if you look at this tweet that he says here it says you know we've also heard claims that we've trained on um test sets that is simply not true and we would never do that that our best understanding is that the variable quality people are seeing is due to needing to stabilize implementation so he's putting it down to the fact that you know inferencing is taking a while our models are overheating etc that's the the kind of like equivalent of what

he's saying yeah so a big amount of controversy as to whether this is real or not if it is true that is a huge dark mark on Meta's not just brand but the entire AI model josh what do you think is going on here it also feels kind of like a dark mark on the industry i'm not super uh well up to date on the meta situation in terms of benchmarks but benchmarks as a whole very much feel like they're broken because they can be gamified i think benchmarks early on were were really effective way of measuring, AI, models, because, so so, much of it was new and they were actually challenging problems to solve but now that AI models have gotten so so advanced it's difficult to generate these benchmark problems and standardize them because the process of standardizing them makes them cheatable um so I think it just it starts a

broader conversation of how you actually measure the intelligence of these models as they get better because there is the option where people can gamify them and when they do gamify them it looks great on paper but when you use them you're like this doesn't quite match up so that's kind of how I've been gauging the models that I've been using is mostly through either my own use or just smart people who use them differently and how they react to them i don't think benchmarks are a super reliable way and I think there's a lot of work trying to figure out how to make them better but in this case I don't know if meta did them but I think a conversation needs to be had um about how we actually benchmark these models properly i think that's just fundamentally true for benchmarks as a concept there's

something out there called Goodart's law which is just often stated as when a measure becomes a target it ceases to become a good measure as in when if we are comparing whose model is best using this particular test then all of these AI labs are incentivized to make a model that's good for that test and not really care about whether that thing is actually useful or not there was a a blog post on less wrong uh less wrong.org or less wrong is um kind of this like rationalist corner of the internet it's where a lot of AI safety people come from here leazer Yukowski comes from here uh and there a blog post was posted um uh on the 24th of March so actually not not terribly recently uh but this also goes to show that this actually has been a growing conversation

in the AI industry the blog post is titled recent AI model progress feels mostly like [ __ ] uh and it starts off with two main claims that either AI labs are cheating and they are cheating their way to find a good benchmark number to report a good number uh or they are just uh accidentally testing they're actually accidentally gearing their AI models to be good at taking that test to be good at that benchmark and it also kind of goes through some of the incentives here uh one that really stood out to me was uh talent acquisition because there's not that much talent AI talent to go around uh and attracting very good talent for your AI model is very very valuable and no good AI talent wants to work for the

fourth or fifth or sixth best AI model and so if you if Facebook can show who again we started off this conversation saying Facebook has been lagging they have been showing poor performance on their models now they're number one now their performance is number one but people are looking at these models being like this is not a useful tool for me uh and, so so, just, there's, a, big, a, growing conversation about like yo benchmarking sucks and also there's just a ton of warped outcomes and warped incentives around this whole benchmarking complex did anyone any of you guys read this blog i did not no trust me okay i haven't told you everything you need to know yeah but it sounds um it sounds right and the what the re like to

benchmark a model that's supposed to be reflective of the collective intelligence of humanity by using a few math problems it just seems wrong so yeah something needs to be changed i mean would you both agree that the best way to just assess a model's capability is whether it makes material impact on your life i feel like that's that's pretty much it right like what if we just had a test bed of people across a variety of different uh economic standards and professions and we just said "Here's a new model let me know uh what you think about it or what the general feedback is give me a rating of one to 10 is that a dumb idea yeah yeah yeah it feels closer it's more subjective a dumb idea okay no no no sorry that was a Yeah I was agreeing with you yeah i was like yes I agree

with your point because it is it's increasingly subjective how people use models how they how it affects their lives most people don't use them for code or math problems they want them for general purpose stuff so yeah I'm all in favor of that the way that we benchmark GPUs I think is actually genius where if you want to compare like the next higherend GPU the Nvidia like 590 to the 4090 you actually just benchmark it using real games like highintensity uh what what are the most like AAA graphically intensive games and then you just do a frame rate comparison on how like how good that GPU is for that game which that is true usefulness because if it spits out higher frame rates on a higherend game Well that is useful for gamers who want exactly those

properties and so I think we we are need some sort of benchmarking system like that where it we're actually testing against uh things that people want rather than like standardized test because we all know they the failures of standardized testing in in in the school in the school system right like anyone who's just like wealthy or has the means will practice the ACT or the SAT 10,000 times and then they will get a good SAT score but they're actually just an idiot who has money yeah and Yeah i I actually just thought of a a specific distinction between that David which is and the standardized tests that we're used to they're normally theoretical or paper questions right it's like hypothetically what if this happens you know or or give

me the answer to this you know random equation um but with AI it's actually actually practical you can see it happen immediately in real life right so it's like it's not like you know uh tell me the weight of these 10 oranges and then use that to calculate the mass of the sun it's like no I'm going to show you right now whether that makes sense and if you're wrong you're really wrong and it's, going to, taint, your, reputation almost entirely and it and also I'm going to do this calculation in like 15 seconds here we go right so I think people aren't really ready for that feedback loop and it's obviously showing with meta right any last comments on the subject before we move on no all right, moving, on, to, one, of, the, big, uh releases of the week I would say is this

uh website which is kind of just an interactive document uh the document titled AI 2027 and these are it was authored by a collection of just AI legends um Scott Alexander is a notable one to me he is the author behind the Slatear Codeex blog which is this uh very wellrespected well- read uh for nerds blog that Silicon Valley tech leaders read um and if bankless listeners are familiar familiar with the concept of Moolok Moolok came out of this late star codeex blog a bunch of other things came out of there um and so Scott Alexander and four other people read wrote this AI 2027 uh model for how they think a plausible model for how AI development goes from here and they give

dates right so mid 2025 stumbling agents is where we are in current AI uh landscape and I think anyone who just came out of the AI slot meta understands exactly where we are with stumbling agents uh and then they kind of give a prediction late 2025 what that looks like uh early 2026 coding automation mid 2026 China wakes up late 2026 AI takes some jobs january 2027 uh agents never stop learning and they give this predictive idea for where this could go and they also talk about incentives from they they bring in anything that's relevant they talk about uh AI copycatting uh Silicon Valley Tech Labs they talk about Department of Defense uh

realizing that they need to pair with their own domestic AI labs as a matter of national security they talk about uh China trying to figure out their ways around the chip uh shortage uh and really where this ends up at is where they think this is going is like, a a, super, intelligence, explosion, by the end of 2027 where the governments of the world have all of their resources pointing to because this is the most valuable thing that's how I I'll summarize this in just a sentence uh Jazz how how would you summarize what's going on here what do you think about it yeah I I mean so it reminds me of um what a bunch of the top CEOs in AI have said right so CEO of Open AI Google Deep might have all said that um AGI will

arrive within the next 5 years and I think Sam Alman's kind of said this in 2023 right which is what's kind of like set up the kind of four fiveyear timeline to 2027 uh and so what we basically have here is a band of like cracked AI builders and researchers have got together and said "Okay well how will that actually kind of pan out how do we actually get to ASI artificial super intelligence as they reference it here right?" Um it kind of before I I dig into it this uh if this sounds familiar it's probably because you read um Leopold Ashen Brener or however you pronounce his names uh famous piece situ situational awareness which was I think released sometime last year where he details his prediction for AGI by the same date 2027 and it's important to

note that like you know a lot of these uh pieces are technically you know opinionated and they get a lot of things wrong but they also creepily get a lot of things right and the band of people that have put together this particular prediction are you know very in tune yeah yeah exactly and so you kind of hit some of the key themes uh on the head David but I want to kind of like stack it across to the timeline that you mentioned right so next 12 to 18 months you mentioned there's going to be these kind of basically mid agents kind of like semi-autonomous kind of unimpressive they kind of automate a few things but whatever right um and these AI agents are expected to like drive their own research a developmental process you know automate complex tasks

so you know we see these with OpenAI's operator agent or Claude's coding agent or Anthropic's computer use agent you know uh we see these releases of agents that do basic tasks for you like hey I'm going to book you a holiday or predict you know where your next uh food shopping trip should be or how much it's going to, cost, right, kind, of, not, that impressive but useful right and the article predicts that over the next 12 to 18 months we'll see these generative AI models and early forms of agents kind of automate a bunch of these general tasks but the main goal of this is it's going to accelerate us towards artificial super intelligence so the question is well how is this supposed to be feasible given that the agents today don't do jack [ __ ] right and well it's

the whole point that they make is these agents are going to be tactically developed to accelerate AI research itself so instead of just releasing models that make you know us pathetic humans clap excitedly and be like "Oh wow." You know that's a cool Gibli image um the models themselves will conduct research on itself to make itself better including discovering new forms of training itself to be smarter etc which would lead to basically an exponential curve for development of AI and we're already seeing the seeds of this foundation kind of be planted today we've got you know um reasoning data tracers we've got reinforcement learning and rag we've got uh Claude's coding

tool which is you know all of this is happening behind the scenes right it's not very front-facing because it's kind of like too technical or boring for the public audience to really care about but of course if we do end up getting AI then we might be in quite a bit of trouble when all of this comes to fruition but that's that's kind of like the general takeaway and then later on the article goes on to kind of discover like or like look into the secondary effects of what this is going to have like geopolitical impacts like an AI arms race right you know how do major powers like the US and China uh interact with each other does China just go for the throat and take over Taiwan all these kinds of different things so yeah Josh I know you uh read this article

what was going through your brain when you read it uh the I encourage everyone to read this because the presentation and the quality of the ideas are so high these are not just some random schmash off the street these are very impressive people who have a good track record of predicting stuff and did a really good job of packaging it the really startling thing to me was the timelines because everyone kind of talks about oh yeah AGI is coming ASI is coming quickly but they really, lay it, out, month, by, month, of, how this is going to happen and the reality is it's coming very soon and Verizon they they are giving quarter like quarterlong time frames for when they think things are going to arrive yes and if you have that level of clarity um then we are getting closer than I think a lot of people realize there's another

blogger not Slatesar Codex but uh Tim Urban who has the way but why um blog and he was on a podcast recently talking about his new book which was the history of the world from the beginning of time the big bang till now and he said the the very last chapter he had to make AGI because once you kind of solve AGI artificial super intelligence nothing else really matters so the rest of history doesn't really matter because the rate of acceleration once this one problem gets solved once we have this super level of intelligence It makes every other problem seem useless and meaningless and that was the startling realization of this is oh wow this is actually something that will happen this decade and what does this world look like when all of our menial problems today are actually useless because ASI

is able to solve all of these these difficult things and I loved how they mapped it out how specific they were about their examples and just the repercussions it's it's pretty mind-blowing it's a little unnerving it's um it's happening quicker than than I expected you know what I you know what I want to know is what happens after the point of fact like what happens after ASI is created i think it's fair like have you noticed like all these prediction forecasts have told us how we get to ASI but no one's talking about what happens after it well no one knows what happens after the infinite kaboom is that the end of the world like what actually happens you know are we just do we become slaves to our laptops like it's kind of like this ambiguous

thing I think like what happens after afterwards depends on who you asked uh so economists will tell you that productivity goes to infinity and GDP also goes to infinity but money doesn't go necessarily to humans and capital doesn't necessarily go to humans broadly and so this is partly going back into kind, of the, conver, the, current, comm conversation that we see with like global trade and manufacturing uh that's that's somewhat relevant uh and then it'll also go into just the conversations of like where do humans humans get value from because humans it's like sociologists will tell you that humans need to do work in order to feel good about themselves and not be

depressed uh and so I think like you can get a bunch of different answers depending on who you ask and I think every discipline has perspective to add about like what happens after super intelligence that that what happens after humans are not the most productive the most intelligent entities on the planet josh what do you think it's almost I think we don't know because it's just not comprehensible to us like you were talking about decades of progress in any given industry happening in minutes um and you're just going to unlock so many things that are unforeseen that will change the like fabric of reality around us it just seems so mindboggling to even try to guess because it is so all-encompassing what it can do um so I don't know i have no Okay okay okay but to to push back on both of you I think it's super important

to like try and broach the topic at least right so like one thing that kind of pops to my head is um a material removal of humans from economic impact on society right so what does that look like you know is that the universal basic income world where we just all like kind of slaves and we walk on our treadmills at home and we can only leave when Papa says "Okay go on go grab your food cuz I still need you to to execute some physical tasks for me." You know until the robots go up until scale like it's it's just like a super weird world and I can't really grasp my head around it i don't think I think it's a it's a quadrillion dollar question at Jaws and you can actually see this in the

existential angst of the Zoomer generation uh where a lot of them are trying to make very big decisions right now about do they go to college what do they study uh do they like what do they invest their time and what does a career look for like for them and all of most of them as a as a generation are reporting being [ __ ] confused about what to do with their lives because they don't know where to spend their time yeah it's a tough question i would I would encourage people to look to sci-fi for the answers to this they generally have the most creative things that are are right on the correct time scale they're not always right but on a long a long enough time scale they are ready Player One is a fun example of that where like if things do just get

commoditized in our world and it's there's not much productivity we can do can we just put ourselves into a digital world and do we just live into slums into slums in real life uh and that's like that is a plausible reality which is scary and that's why there's so it's such a wide array of plausible outcomes that could happen from this do we escape the world of Adams do we just put these headsets on and are we gone for good or do we try to um align ourselves with the AI and do we put chips in our brain and are is that how we coexist um how do we peacefully coexist with this form of intelligence it's a weird question to ask yeah uh in this article Josh you were talking about just how good the layout is i want to just emphasize double click on this idea that this

article is a is an interactive article they have these like graphs and metrics uh that when you scroll down and are reading the article the graphs change because you're going forward in time and you just see these this curve of capabilities just go increasingly up and up and up and up and up as you read it and then they also have different uh actual like vectors of AI capabilities including coding coding hacking boweapons robotics forecasting and politics you know and each one of these things grows in capability as we as you scroll down and read the article to the point where AI just becomes hyper capable in all of them uh and just give a big plus one to just like getting your head wrapped around why this is

significant is conveyed by this article and also con it's also like why I think we are doing these podcasts because like yo future is weird man and I would like to have at least a little bit more foresight of it coming down the pipe I don't think people are locked in dude okay you want you know what's crazy I asked some of my uh non-crypto non AI non tech friends uh how often do you guys, use, chat, GBT, and, all of, them, are like I I don't use it i don't use chat GBT and I was going to bring up this exact point um oh bro my friends either don't use chat GPT or believe that AI is chat GBT like that is the entire existence of AI and it's normally to each's point earlier it's it's used as

if it was an enhanced Google query so it's used as a search box instead of an actual tooling utility and a lot of that is just there's people are not educated on how to actually extract value from these machines like you're just given a text box and say like here's the collective knowledge of humanity like do what you want with it and that's a difficult well well it's also like optionality as well right it's like Netflix subscription or chat GPT like I'm going to go with Netflix cuz I want to watch the latest series of blah blah blah right so it's like um and the whole Google, query, thing, really, annoys, me, I I think we're going to get into it later but I I just think you're massively underusing these models like the whole point of these models is to make you smarter

and just using it as a simple Google query function isn't going to get you anywhere in fact it's probably going to remove you from the race entirely i'm also mad at the designers for for making it the single text box i feel like that's such a terrible form factor for this type of intelligence where they are like deferring the hard design choices to the user they're like "Here's a text box do what you will." Instead of guiding them through the process of how to effectively extract value so I I don't necessarily blame my friends for that yeah well there should be an addictive app layer don't you agree Joshua well I think we've discussed this kind of like offline as well it's like like what's the Tik Tok for a LLM usage right like what are like trends that I can just get involved in and ask or talk

to it you know to me that's one of the biggest opportunities is how do you package this into ways that are exciting and accessible to the average person who would choose this over Netflix because still Netflix wins most times because it's too challenging to use but can you handle that design decision can you create something that is better more addictive than Netflix better more addictive than Tik Tok but gives you these leverage tools to actually do something productive versus just consuming all the time and that's a really fun problem for people to solve oh hang on let me ask you this though right do you genuinely think people are going to ear more on the productive use of AI versus consumptive i would argue it's the opposite i would say there's going to be um chat GPT image gen in the future for video and people are going to

be like "Huh I'm going to watch a bunch of these videos that people created." I don't, think, they're, going to, be, I, don't think they're going to go on and be like "Hey here's a video David create a series of us you know I don't think people are going to do that they're going to be like I'm just going to scroll through some of these like both will definitely happen because we saw when YouTube came out Tik Tok came out Instagram reels came out Instagram generally everyone got more access to creativity and to producing stuff easily uh and also you just created a thousandx in consumption so you'll get both yeah i just think it'll lean more on consumption i'll place a bet with you right now

place a bet with you right now people on that one yeah that one scares me because I mean imagine Tik Tok if you can get hyper custom videos just made for you every time you swipe because image is getting very good very quick and that's a scary future like are we just going to brain rot ourselves away is that is that Darwin Darwinian's like final is that a future or is that a present we're there i think it just gets worse well to go to Josh's earlier point he he said to relate to sci-fi most of them are lowkey kind of depressing do you know what, I, mean, like, look, at, like, Dune look at like [ __ ] Star Trek and all all these like wars and [ __ ] it's not going to be easy i don't think so this is this is like Darwinism's final

frontier is if if like the human race can survive the addictive increasingly addictive nature of AI content then we can survive as a population if we lose like that's it asi just runs the world global warming it's brain rot that's the existential threat we're cooked it's over so we'll see who makes it through introducing Uni Chain built for DeFi and powered by Uniswap uni Chain is the fast decentralized layer 2 designed to tackle blockchain speed and cost challenges with this mainet now live you can enjoy transactions that up to 95% cheaper than the ETH layer 1 all while benefiting from an impressive 1second block time that will be getting even faster very soon uni Chain is the first layer 2 to launch as a stage 1 rollup on day one that means it comes with a fully functional permissionless proof system

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basically a medium length memo that punchline is you as a employee of Shopify are now expected to use AI in your job so he lays out uh five six points uh number one using AI effectively is now a fundamental expectation of everyone at Shopify two AI must be part of your GSD prototype phase, i, don't, know what, that, means, three we will add AI usage questions to our performance and peer review questionnaire four learning is self-directed but share what you learned uh five before asking for more headcount and resources team must demonstrate why they cannot get what they want done using AI wow uh and then six everyone means everyone this applies to all of us including me and the executive team so

CEO of Shopify stating AI is an expectation inside the company since he released this on Twitter on X for everyone to read many other CEOs chimed in saying yes we have also implemented this expectation or we are going to implement this expectation even at bankless uh we have a internal just server uh server like channel that we just titled AI lab and it's all every member of the company just talking about how they use AI in their workflow so I think this is already becoming like the industry status quo of just like yo use AI share how you use AI we're all trying to figure this out together uh but Toby I think kind of just made this shot across the bow for all uh tech company

leaders to say like yo uh it is an expectation to be using AI and if you don't use AI you're out uh Josh when you read this memo what did you think um I was really excited about it and I think it's one of those cases where he's just saying the quiet part out loud because a lot of people don't want to scare other people who are looking for jobs but he's basically saying we are going to stall hiring and we are going to try to increase the leverage of our employees as much as possible and I love the the collective exploratory thing that he has because I think that's the most valuable thing going back to what we were talking about in the last segment no one really knows how to maximally extract value from this especially in narrow use cases like a particular company like Shopify

so collectively getting everyone together saying you must use this and you must share your findings I think is very productive i forget the specific numbers i think it was um Shopify is getting 40% growth is I believe the number and the expectation is that the employees can match that growth using this leverage tool so he's expecting a 40% growth of production from individual employees just by leveraging these tools i think it's super exciting um it is a little scary because this is a large company who is now saying "Hey we're not going to hire anyone unless you can prove that we really need them because AI is able to and this is after they had a pretty large layoffs in the last 12 months." So it's it is a new world order it is a shift that is permanent i don't see this changing um the opposite

direction anytime soon so let me just go ahead and look there are 11,600 employees at Shopify uh and so the CEO of of a almost 12,000 employee company saying hey we are not hiring anyone unless you can prove that you cannot do that job with AI i think that is pretty alarming from a jobs market perspective because that means that maybe maybe you're not cutting anyone but adding new jobs I think is not going to be a thing is going to start to de diminish inside inside of Silicon Valley well well I I also think um a stat that goes underlooked in this memo is he's essentially asking every employee to 10x

themselves so he uses the example of you know you're all in your teams and then comes across that one golden employee that just 10xes the entire team right he says well now the tools that each of you use and have access to has the ability to 10x yourself so you know it's not just a matter of like we're not going to hire employees and you guys maintain the 20 to 40% which is as he states here i think he kind of wants people to like 10x the ability of each of themselves which would mean you know what does a potential 100,000 plus uh version of Shopify look like right it's a hundred billion dollar company as it sits right now and Toby is I think due to his history definitely been one to push with

these frontier technologies do you guys remember when NFTTS were the craze shopify, was, one, of the, first, ones, to, to test it out you know token gated access to A B and C service right and you know as necessary as they were they canned it but, like, I, I, feel, like, it, I I, feel, like AI is just a little bit of a a different point and then the second thing to to your that I want to kind of emphasize Josh's earlier point which is there's a slight nuance here because people have been afraid that AI is going to replace them but he is saying the quiet part out loud but doing it himself and I think CEOs are actually and this is the subtle nuance here going to push AI onto their employees and like ou

their employees first so it's like a human enforced displacement versus AI you know creating this like tool that just replaces you entirely and then you just kind of like slot it in do you know what I mean we'll see approaches from both you know you've seen customer support agents replace people so far but I think top down kind of like pushing of AI tooling to replace individuals or stop hiring people is definitely going to become more of a trend mhm it feels like that rift is growing and this is kind of the trend from the last segment which was are you going to use it for the Netflix version or for the productive output version it's the same thing with Shopify and all these other companies where these are high leverage tools where if you are a person of high agency who uses them and leverages them

you will get very far ahead but if you don't you will be left behind by that amount of leverage so it creates this very large gap that might not necessarily exist today but will become increasingly large very quickly and that probably causes a lot of concerns for people too because now there are the people who leverage it and now they are 10x employees and there are the people who do not and now they are just one and that's a much larger divide than someone who's like 5x versus 2x or whatever it may be we can even go back to the AI 2027 document that we were talking about earlier down at the bottom of the document you know towards the end of times closer to 2027 uh this this hypothetical AI lab which you could just think of chat GPT or Open AI they just

didn't want to uh use OpenAI specifically they even talk about all of the AI developers by the time that we approach the super intelligence uh explosion in 2027 that they think they think is coming all of the AI developers that are working for the AI labs have all made themselves redundant and they're all kind of just there doing loose oversight without actually doing much of the work uh and so even the a maybe even the AI labs will be the first people to actually fully AI their workforce because they are the ones who are uh intimately aware they know how to use these things the best and so maybe the canary in the coal mine is that actually AI labs start to use their own models as their own employees and all

employees of like OpenAI or Anthropic or Deepseek or whatever they actually end up being AI managers more than actual like laborers themselves that's kind of the model that that AI 2027 gave in in their document yeah I would say that's the whole point right what is ASI what is AGI it is replicating human intelligence but not just replicating it just accelerating it completely um it just reminded me Open AAI didn't OpenAI tease their uh agents that they're releasing soon and it goes through different tiers with the top one being $20,000 a month and it's like a PhD level uh employee that can come and work

at your company and then you had like a something stupid like a 200 bucks a month and it's meant to be a high knowledge worker which is basically like most people at like Fang companies or the bank yeah most people um I I definitely think that that's the case and like to to go to the point of um the uh AGI or AI 2027 um they want to one of the key themes is they want to use AI to improve itself iteratively over time so it seems like that will be the main place that it gets displaced first okay let's turn to education uh because uh this is something that came out this week claude uh Anthropic just released Claude for education uh and this is basically trying to AI you know higher

education up to the college level uh and so this is this is what it looks like and they're basically um part of this part of this announcement comes a couple of different things uh learning mode a new claude experience that guides students reasoning process rather than providing answers helping develop critical thinking skills uh universitywide claude availability full campus access agreements with Northern University London School of Economics and Political Science a few other colleges um making claude available to students academic partnerships and student programs uh and so uh basically uh Claude is making a university as a product or a school as a product to help educate and and it's not just g I think the important difference is if you go and type into chatbt hey what's this

answer it'll give you the answer but here uh Claude education is is working through how to arrive at the answer for people that are querying it uh and then I think maybe one big headline that I think everyone should reflect on uh is this uh this one here from foxnews.com texas private school's use of new AI tutor that's cloud for education rockets to student test scores to top 2% in the country uh so a a Texas private school started using Claude for education uh and, then, all, of a, sudden, their, students start start testing at the top 2% in the country uh and so this has massive implications we already know the uh the university structure is already under threat universities have been leaving

being the going out of vogue for a while now uh because they are just entrenched ideological systems without any sort of like actual educational value students are taking in like quarter millions dollars of debt to become like a a speech therapist uh things like this and so education has already been like needing a revamp and now here we have AI which for a use case that I think is just a match made in heaven AI becoming your tutor your teacher uh in this very streamlined way uh it what are your thoughts i just don't see the point of universities within the next two decades going forwards and I'm probably being generous i'm probably being super generous, with, that, timeline, to, be honest

right if we're getting AGI in two years why is that you know crazy to say um I I I think there's a few points I want to make around this number one um the way it's packaged this product Claude education makes it seem like it's meant to aid lecturers and to use your analogy earlier um David you know maybe employees become the coach of the AI right i don't think that's going to happen when it comes to education i think, it's, going to, become, incredibly personalized heck YouTube has already accelerated that massively i've learned a ton of stuff that I wouldn't have normally learned uh via school college university or any kind of prestigious degree that I would have ever attained and I think personalized education just makes sense everyone is different everyone learns and comes from a

different background why would it make sense to you know use this arbitrary person and sorry I'm reducing professorship massively but who has been you know honing their work and craft very you know commendably for decades to then be expected to teach each individual in a certain or specific way it just seems like AI is meant to scale this kind of thing the Texas data point kind of proves that but the second wider trend that I'm noticing here David is that I just don't think people are using AI effectively like I would love to like contest and see what is so special about Clawude education i would bet you that it's the exact same model it's just being crafted and curated in an

educational circumstance so behind the scenes they've just given a longass prompt which says you are a professional university educator now and you are going to specialize in economics 101 um please uh identify and analyze the London School of Economics syllabus for 2025 uh term 1 and create an agenda and schedule lectures etc etc right and then it's just being fed straight to the people there um so I I put out this tweet uh recently um I don't know if you can um pull it up but I basically caught up with some friends and they were telling me how they spent um four plus hours just this week alone prompting chat GPT uh within a single chat room to

improve their life and how they learn now if you look through this this tweet um you know uh when I asked why they were doing this they said so that they can tell me what job I should do next you know and this is in response to why me asking him why he put his entire career history into Chat GBT and then another guy said he logs his entire set of notes from therapy and asks Chat GBT to give him life advice i said "What what do you mean like what what qualifies ChatGpt for this?" But he goes "It doesn't matter who Chat GBT is i just tell ChatGpt who to be." So I said "Who did you ask him or it to be?" And he goes I simply said chat GBT you are now Carl Jung one of the forefathers of

psychology modern day psychology and I Carl Jung is Sigman Freud's Sigman's Freud so he's hot Freud that's a that's a good way to describe him um and he basically said "Here are all my therapist notes also you have the entire history of my chat log with you talking about random arbitrary recipes and random Star Trek scenes that I missed and then random hypothetical situations that you know I never ended up getting into but I wanted your opinion on can you create an identity or personal personification profile of me and then tell me what's wrong with me how can I improve should I have broken up with that girlfriend or should I get back together with her you know it's this crazy thing and then the third kind of like subtle point is like we are just

giving troves of our personal data to this thing you know I I asked him like how how did you on earth did you focus for 2 hours giving career or your career history he said oh I just spoke to it i just put it on voicemail and I spoke to it i'm talking to another person there and I think um you know there's a dark side of it which is like you know we're giving away all our data we're going to you know give away all control to this AI but then there's the positive side which is like if you use this very well you could end up having similar effects to that Texas school that shot to the top 2% right and it maybe had no business being there without AI right I don't know Josh do you have any thoughts on this yeah I I am in love with this

headline because I have been at war with school for for so long it is such an abomination how people are educated and it's it's the AI segment is just the acceleration on the gasoline that has already been happening uh with self-education in the case of High school classrooms are pretty crappy most of them fall to the quality of the most disorderly student it's a lot of disciplinary stuff it's not very custom the customization part when you get to high or college is the same thing it's the same system for every single person it's the same lectures the same classes everyone learns differently there is no reason why it shouldn't be hyper customized to you and why you should not just have your own AI that understands your preferences understands everything about you and is able to deliver this information and educate you in the way

that you most effectively learn and I think the the privacy thing is a concern but even if the illusion of privacy is given that's probably good enough because that's the reality we live in today um where like all of your cookies are tracked your online traffic is tracked your your GPS location on your cell phone is tracked it's not very obvious the average person wouldn't know that but it still happens so the privacy is a concern but if you can get around that and give people these hyperpersonalized AIs it is so much more effective than college the only tricky part is if people do start self-educating using AIS and if they do get these hyper custom models they lose these social elements of colleges and education and socializing in general which contributes to this increasing trend of people just being a little more

quirky uh socially but we have the internet right we have a little digital avatar friends right but to me it seems like there's absolutely no reason why it shouldn't be hyper customized and it's reflected in this this headline which is like the people who are using AI are now in the top 2% in the country and that this is very early AI it will only ever get better from here and get more personalized as it understands your preferences so I am all for it and very excited about it okay okay so if we were to take the other side of that Josh uh I some immediate thoughts that come to mind and I'm curious what you both think is number one alignment of these models need to be super important and governed very well can you imagine if the creator of a model came in with an agenda you know to

sway the masses into a particular educational st political stance for example or just you know teaching basic math completely incorrectly obviously that's a more extreme example what happens when humans lose oversight basically right and they stop fact-checking uh which leads me to my second point which is do we just become incredibly lazy it sounds super productive right it's like hey we're going to learn all these different things but then do we just stop trying to pioneer it goes back to the what hap what do we do when AGI manifests right do we just become incredibly lazy and just said uh you know let AI discover who God actually is and and figure that out you know where do we end up imagine verifying yourself without handing over personal data no hacked databases no

unnecessary personal exposure for airdrops and no AI bots ruining community governance meet Self the onchain identity verification protocol built for privacy and control self protocol uses a zero knowledge proof to confirm your identity safely users prove key details like age or citizenship without revealing sensitive personal information self never stores your data it only generates cryptographic proofs here's how it works in three steps first register and verify use the Self app to scan your biometric passport's RFID chip self-verifies authenticity with zero knowledge proofs each passport creates one unique identity second you can share proofs privately third party apps request identity proofs like confirming you're over 18 you can also link proofs

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teaches you public school just teaches you the basic modicum of like knowledge but really just puts you in a place where you won't get into trouble for like eight hours six hours of the day uh and that is so homogeneous because we are all going through this extremely homogeneous school program all across the the country all across the United States like yeah it differs from state to state but like not really um and I think what we are what we will see with education is the same thing as what YouTube or Instagram reels did to mainstream media where there were just like seven news channels and then that exploded into 70,000 YouTubers all giving their takes on the news some terrible some great some way better than mainstream media but it's really you

know choose your own adventure uh and now we are going to see that fragment even further into just every single student has their school it's one school per student i don't know if you guys went to public school but I remember class sizes were a huge issue in high school where like they were packing in 35 kids into a classroom and it always got bigger every single year and this is the exact opposite of that where you get one hyperpersonalized teacher professor who's the best at their job to teach you exactly what you want to want to learn have you guys ever asked chat GPT uh generate an image of me based on everything that you know about me you guys done that yeah okay so it comes it

is you you first you forget you re you first realize how much data you have given chattpt about yourself in ways that like you have not given any data to any other application before cuz like it's truly friendly it's a friendly chatbt especially is very supportive uh and so you I anyone who's using chatbt go open it up ask generate an image of me based on everything that you know about me and it'll generate an image of you and you will realize how much it knows knows about you and your style uh and think about how highfidelity that relationship that it has with you and now now it's your professor right it already knows you all of your interests and your style and your quirks and now

it's now it's your school system to carry you or or your child from like six years to 16 years old uh I think it's I think it's really cool uh I'm not really in my learning years anymore but nonetheless I'm still looking forward to like learning some university level education from ChachiBT i just got rejected excuse me i just got rejected david I don't have any personal details about your appearance or characteristics so I can't create a tailored image of you if you'd like you can provide me with some descriptive details blah blah blah blah blah what do you mean i've given like my entire life to this thing you just you just force it to make an image just say you make your best guess okay I'm gonna give it a go we'll see how it goes i I have seen this come out wrong where like my you know

generic looking white friend came out as like a black overweight female i was like "Well that's that's different." Mine was startling to the point where it hadn't the actual view out my window was correct it knew what I was looking at and everything i was like "Wait this did I ever tell you this?" Wait wait wait what do you mean what do you mean and I had the William but yeah no it had it had the bridge in the background of my image and I was like "Wait that's the exact Did you ever ask it about moving?" Um well we must have spoken about it cuz it didn't just learn this on its own so we were talking about something moving whatever I was looking at trying to figure out the name of whatever street it was but it it knew and it was very

accurate it had a little drone in the background and a camera and a microphone i, was, like "Wait, this, is, weird.", That's like kind of like my room okay you guys want to see mine my image oh please i'd love to all right here we go here's me uh for for the listener we have we have a guy who's definitely on the Brooklyn side of New York with the New York skyline in the background he's holding an espresso i I have a rock climbing rope slung around my shoulder uh an Apple Watch a climbing helmet and an espresso martini because I it knows that I ask how to make cocktails pretty frequently this is pretty good this is pretty good also it also works through its logic as well it just tells you its logic and its workflow and it's like pretty cool wait

can I can I share mine it actually surprisingly nailed it one second send me a picture and I'll put it on screen here we go nailed it um that's funny because I think we both look like generalized AI engineers yeah yeah for some reason I look entirely like you know an an even nerdier David Hoffman that's crazy much much nerdier yeah you are not the uh attractive Indian man that you see on screen maybe potentially a tech billionaire i can't quite tell like I know, he, has, this, guy, has, at least, 12 hoodies, yeah, wow, all right, let's, bring up the rear of this uh this AI rollup as we uh close this out the last big one is

the news of the week is A16Z's not AI6Z the actual A real A16Z raising a 20 billion dollar mega fund to invest in AI startups uh in the United States uh so that's pretty damn big um I mean this is A6Z's job it's not any surprise that they're raising 20 billion but I think it just goes to show how much juice there is left to grow out the AI industry j when you saw this headline $20 billion being raised not yet raised but being raised by A6Z to invest in United States AI what were your first thoughts so I had an initial kind of like gasp which I was like that's a a humongous number for a single fund but then I was like oh yeah no that

that that probably makes total sense right like it wasn't too long ago where you know Sam Alwin was prospectively you know trying to raise a trillion dollars or whatever crazy figure was it 8 trillion $7 trillion something crazy like that yeah so um I don't think this is you know out of turn especially given like some of the valuations that are coming do you remember I think like Curser literally last week got like a $10 billion valuation just based off its recent round so I think you know these numbers kind of make sense um I I I'm kind of curious where it's going into right and I think what's most interesting about this particular announcement is they didn't just they weren't kind of lazy about it they weren't kind of just like "Yeah we're going to dump a bunch of this into like

compute and data center companies and la create a model." They were like "No we want to own the app player of whatever this behemoth of technology ends up becoming." And they use the term uh vibe creation platform and so for those of you who are wondering what the hell that is think of Cursor which is a Vibe coding platform but instead it's a platform that can hit almost anything that you want to do right not necessarily coding it could be um I want to become the next biggest music artist and perform on my concerts all around the world well to start off with I need to be able to create some music right so what if I go on this vibe creation music platform and I can you know become the

next superstar right and what's the difference between like you know just like this and maybe I don't know Apple's garage studio where you can kind of like mix beats is one it uses AI so you can just like prompt and type in the kind of flow and you can edit your music and all that kind of stuff but then you could it also connects to your socials directly it also ties and brings in all your friends to listen to it in a really easy simple manner what they're trying to do is create this unanimous platform right or they're trying to fund founders that are building this unanimous platform to connect different things it doesn't doesn't have to be music it could be movie editing or whatever that might be and why I found this so interesting and I'm curious to hear whether you two have

the same take um obviously we've spent like a lot of our time in the web 3 world right and the whole promise of the web 3 world was to kind of connect all these different intermediaries and entities to create some kind of unanimous experience it kind of sounds like what they're trying to do and I am super happy to see this investment happen at the app player i mean Josh what do you what do you think i'm just so excited to see a lot of money going to something other than training i think all of the money that's been raised is going to GPUs and to building larger clusters and it's exciting to see smart people with a lot of money shifting away from that focus on cluster training to actual application layer it goes back kind of to what we were talking about

earlier where there is just this single text window and you're supposed to extract this value and they're slowly narrowing those use cases and I think that's the most valuable thing that you can do is just teach people how to get value out of this so using your example if you want to become a professional musician this is the narrow box that we have built that is optimized for allowing you to do that thing and so far those solutions don't exist it's still very broad so investing $20 billion into creating narrow but hyper useful AI for whatever you might be interested in is is so so exciting so I'm very pumped about this one i remember reading a tweet thread last week about how this one like mall uh commercial real estate investor uh had just revamped his entire process with architects that he would work with for his whole like mall

revitalization process so the the idea here is like he would buy up a cheap distressed mall uh he would work with an architect to plan a new design revitalize it and then increase the value of the mall that he uh bought he invested in uh and the architect design process he said would would be so much back and forth about how to make a goodlooking mall like six to nine months of back and forth and labor with his architect and he was able to take a picture of this mall prompt chat GPT to get something that was 90% of the way there and that was the new starting point that he had with this architect to go and and he said it just cut off like eight out of the nine months of time frame for that one development process

and saved like t tons man hours and the whole thing that I was thinking about when I was reading this is he is doing this inside of chat GPT which is unoptimized to do this job but it is still the right brain to do it so like just just like Josh has been harping on this entire episode where this form factor for how we engage with chatbt is so constricting because it's just this text box that looks like Google but nonetheless is doing incredible work it doesn't take that much more effort and labor from a startup to make a architect and design optimized interface for chat GPT just another wrapper of chat GPT for a more narrow but specialized application of this thing and you can

apply that across every single industry under the sun uh and we just there's just so much investment in L1 i see the same pattern here uh between the L1 investment or the fat protocol investment from the crypto space where people want to invest in the layer ones they want to invest in Ethereum they want to invest in Salana uh do they want to build a layer 2 or do they just want another build another layer one they just want to invest in the blockchains and they don't want to invest in the apps and that is the issue plaguing the crypto space and right now we have plenty of layer ones we have Enthropic we have uh Open AI we have DeepSeek we have all of these different godamn LG the television company came out with an AI model layer one uh and right now I

think what what Josh is saying is like yo we need the app layer of all these layer ones we need all these layer ones to become more expressive more opinionated more directed at specific outcomes and I think that's what what Josh is excited about with A16Z actually building out the app layer and not just funneling more money into just making chat GBT that much better in a very generalized broad diffuse sense and it goes back to the the benchmarks too is now you have these like predefined benchmarks across these categories that you can actively compare because it is a more narrow band of scope so you can see who can actually create the best architecture drawings and that is a clear benchmark that you can set once you have these narrow focused purposes so that's another way to solve the benchmarking thing is like

okay you could have your crazy good models but narrow it down into something that's actually useful for me and then we could compare how that helps me personally i love how we just went full circle with that i love that i think that's a great way to end it josh Jaws thank you for helping the Bankless Nation go through the the weekly news this week it was a big week next week will be even bigger and we'll be back in seven days to bring you the news in the AI space josh and Josh thank you guys so much awesome thanks for having me bankless Nation you guys know the deal we didn't even talk about crypto so I need to find a new sign off there i don't know if there's any disclaimers needed because you know crypto is risky but we didn't talk about

it so I guess uh this is the frontier it's not for everyone but we are glad you are with us on the bankless journey thanks a lot