Modern Wisdom

#1067 - Cal Newport - The collapse of modern attention (and how to get it back)

105 min
Mar 5, 2026about 1 month ago
Listen to Episode
Summary

Cal Newport discusses the collapse of modern attention spans due to constant digital interruptions, arguing that deep work and focus have become rarer and more valuable. He explores how AI is exacerbating productivity problems through 'work slop,' and outlines structural changes organizations can make to reclaim cognitive capacity and meaningful output.

Insights
  • The hyperactive hive mind (constant Slack/email coordination) is a low-energy attractor state that minimizes friction but destroys productivity—escaping it requires organizational-level changes, not individual willpower
  • AI-generated work products ('work slop') are symptoms of exhausted brains, not solutions; they smooth cognitive peaks but produce low-value output that makes everyone's job harder
  • Reading long-form books rewires the brain for sophisticated thinking; short-form content (Substack, social media) trains shallow pattern-matching and conspiratorial confidence rather than nuanced understanding
  • Accountability to peers (morning/evening standups) is more effective than individual discipline because it creates social friction that prevents avoidance of hard cognitive work
  • The future of AI is distributed and specialized (10,000 different AI products), not a single AGI; current LLM scaling has hit an asymptote and new architectures are needed for further progress
Trends
Shift from always-on communication to scheduled deep work windows (no Slack before 1pm) as competitive advantageGrowing recognition that productivity metrics (speed, responsiveness) are misaligned with actual value creation in knowledge workAI integration moving from chatbot interfaces to embedded, agentic tools within existing software (Excel, terminal-based agents)Market skepticism about near-term AI economic disruption despite hype; stock market betting on narrow, sector-specific impacts rather than broad automationWorkload management and explicit work-in-progress limits becoming organizational best practice to prevent context-switching collapseDeep reading and cognitive strain reframed as competitive differentiators as AI commoditizes low-effort content productionQuantum computing overhyped as AI solution; narrow applications in factoring and physics simulation, not general-purpose accelerationOrganizational culture shift toward measuring deep work hours and focus quality as tier-one performance metricsAccountability-based work structures (standups, office hours) replacing asynchronous communication as productivity modelLLM fine-tuning and benchmark optimization replacing raw scaling as primary path to AI improvement post-GPT-4
Topics
Deep Work and Cognitive FocusAttention Span Collapse and Digital DistractionHyperactive Hive Mind Communication CultureSlack and Email Productivity ParadoxAI-Generated Work Slop and Quality DegradationOrganizational Workload Management SystemsLong-Form Reading and Brain RewiringLLM Scaling Asymptote and AI Architecture LimitsAccountability-Based Work StructuresContext Switching and Cognitive LoadKnowledge Work Productivity MetricsFour-Day Work Week ExperimentsQuantum Computing and AI IntegrationDistributed AGI vs Monolithic AISilicon Valley Processor-Inspired Work Culture
Companies
Microsoft
Annual Microsoft 365 data shows interruptions every 2 minutes; weekend work spike indicates weekday distraction
Slack
Described as 'right tool for wrong way to work'; enables hyperactive hive mind coordination but destroys deep work
OpenAI
GPT-2, GPT-3, GPT-4 scaling trajectory; Project Orion showed diminishing returns beyond GPT-4 scaling
Anthropic
Released plugins for LLM integration; published Kaplan scaling curve paper; developing Claude models
Meta
Built BMF model (largest data center) but didn't release due to marginal improvements over previous model
xAI
Grok model attempted scaling beyond GPT-4 with Colossus data center; minimal performance gains
Salesforce
Acquired Slack; Newport wrote New Yorker article analyzing Slack as tool optimized for flawed work style
Adobe
Stock declined due to generative image tools commoditizing graphic design work
Google
Mentioned in context of search behavior and AI integration into existing tools
Apple
M6 chip mentioned in context of quantum computing speculation (not quantum-based)
People
Cal Newport
Computer scientist and author; argues deep work is increasingly rare and valuable; published Deep Work 10 years ago
Chris Williamson
Modern Wisdom podcast host; interviewer exploring attention collapse and AI implications
Jared Kaplan
Anthropic researcher; published 2020 paper on LLM scaling laws showing performance improves with size
Marianne Wolfe
Researcher cited for concept of 'deep reading processes' and brain rewiring through literacy
Peter Shor
MIT researcher; developed Shor's algorithm for quantum factoring of large numbers
Ron Rivest
MIT professor; invented RSA public key encryption; taught Newport as grad student
Nick Carr
Author of 'The Shallows'; research on skimming behavior and screen reading vs. deep reading
James Clear
Author; discussed with Newport regarding MasterClass decision-making process
Ethan Mollick
Academic researcher; cited for work on student ChatGPT usage statistics and homework apocalypse
Scott Galloway
Mentioned tracking legal cases of lawyers sanctioned for ChatGPT hallucinations in briefs
Don Draper
Mad Men character; referenced as historical model of productivity based on skill vs. constant availability
Steve Jobs
Silicon Valley figure whose era influenced processor-inspired work culture
Isaac Asimov
Science fiction author; Newport used ChatGPT to find quotes from 'I, Robot' for New Yorker essay
Quotes
"The very nature of that style of collaboration demands constant inbox checking, which is what I think people often get wrong about this."
Cal NewportMid-episode discussion on hyperactive hive mind
"Our brain isn't meant to switch our target of attention that quickly. It takes us a long time if we're talking about targets that are abstract and symbolic."
Cal NewportExplanation of cognitive load from context switching
"Work slop is AI-generated work products in the knowledge work sector that are generated quickly by AI, but they're so low quality that they actually make everyone else's jobs harder."
Cal NewportDefinition of work slop phenomenon
"If you're accountable, you don't have to be accessible. If you can point to this is the value I produce and I'm killing it for you, then I don't answer emails."
Cal NewportOn accountability vs. responsiveness trade-off
"Reading is like it's not just, oh, I get stronger in my brain. It reconfigures your brain into like the modern, post-cognitive revolution brain."
Cal NewportOn deep reading and brain rewiring
Full Transcript
Dude, you must be feeling like Cassandra at the moment. So prescient, the distraction, the necessity of deep work, the inherent bombardment of our attention. Do you feel like you saw the future earlier than what even at the time maybe felt late with deep work and focusing on quality over quantity and stuff? I mean, I think part of what I noticed was the present was crazy to me and no one else recognized it. So it was less even predicting the future. I feel like there was a time, guys, like 10 years ago now, where I was looking around and saying two things. One, social media doesn't make sense. Why are we all pretending like this is at the center of democracy and civic life and all business? We all have to be on here all the time. And two, email doesn't make sense. Not what was going to happen in the future. I'm just looking at the way we're working today with email and Slack and Teams was coming. This completely does not make sense. You're switching your context once every two or three minutes. This is a terrible way to actually use your brain. So I never thought of myself as predicting the future as much as just telling people what was going on then didn't make sense. And everyone thought I was crazy. And 10 years later, it just kind of jumped from I was crazy to its common sense. So it's not even that interesting that I'm saying it anymore. So I kind of skipped the part where it sounded prescient. Do you feel vindicated? I think certainly on a couple issues. The social media issue was a big one because I used to get a lot of flack for that. for going out. I wasn't even saying that social media was bad or that no one should use it. Really, what I was pushing back on was just the idea of ubiquity, the idea that everyone had to use it. I said, this doesn't make sense. I get there's some people this makes sense for. There's a lot of technologies that have markets that make sense for it. But why is there this pressure for everyone to be on these services? This is not going to a good place. They're spending a lot of money to mine attention and they're going to get better at it, right? And at the time, this was considered crazy. What do you mean? Like you wouldn't use social media. I wrote a New York Times op-ed back. I looked this up the other day. It was 2016. And it argued maybe social media is not the biggest thing for a young person to focus on if they're thinking about their career. That's what it was. It was like focus on your career instead of social media. Actually doing things well is what really matters. And you would think, you know, that I had just come on and said like America has an idea is done and grandmother should be kicked. Like people were upset about this. The New York Times commissioned a response op-ed two weeks later that went through mine and said, this is what is wrong about Cal Newport's op-ed or whatever, because it made such a fear to suggest it. And today it's boring to suggest like, you know, social media has problems and most people probably shouldn't use it. People agree with that. The one that upsets me, though, that one I feel like people have come along to and more and more people are being much more selective and minimalist about their social media. The distraction, email, Slack, constantly jumping back and forth between different things. That just got worse. I mean, I think people recognize it now. This is probably not a good way to work. But I thought because there was dollars and cents here, this is less productive from an economic productivity standpoint to have all of your workers changing their attention all the time. You're just getting a really low return on all the money you're investing in these human brains. So I thought, oh, this is dollars and cents. This is the one that's going to change. Social media is fun. Like that's going to be hard to change people's behavior. But certainly this hyper distraction thing and knowledge work, that'll change because we're leaving money on the table. It hasn't changed at all. It's gotten worse. It's worse than it was. I'm at the 10-year anniversary now of the book Deep Works. So this month is a 10-year anniversary. Congratulations, dude. That's fucking seminal. Like that has become a part of the lexicon. That's really, really cool. Yeah, but it's got me a little bit depressed because I've been doing this 10-year reflection. Like, okay, it's been 10 years and the book was a hit and it's millions of copies. et cetera. And the issues I talked about are worse. They're like really worse than they were 10 years ago. So people know the problem. Nothing has changed. What does the data suggest around the worstness of it now? The one I've been following, the study that I think is useful as a trend line is Microsoft actually does this annual report where they gather data from Microsoft 365. So it's like office and word and PowerPoint and Excel. Nowadays, you use this sort of the web-based version of these. It's very common. So they can gather data from just tens of thousands of knowledge workers actually using all these different tools. And the latest report they put out in 2025 now has the interruptions on average once every two minutes. So it's just gotten out of control. So switching to a communication tool once every two minutes. They also found the latest report, and this is depressing to me as well. there's one time in the week where they see a notable rise in the use of the non-communication so actually using the core productivity tools like word or powerpoint and it's saturday and sunday morning so we've just put the work off until the weekend when there's no expectations of responses and spend the actual weekdays talking about work which i just don't get like that is not economically productive like companies are leaving money on the table but It's just where we are. We really can't quit this behavior. Isn't it interesting that you had to try and appeal to a very utilitarian approach for this? That you didn't say this is probably making staff miserable. It's not a good use of time. We've got some really strong evidence that suggests that doing one thing and getting better at it over a protracted period of time actually makes you feel more satisfied. You get into a flow state, et cetera, et cetera. You look back on your day and you can look at the things that you did none of that which is the much more immediate experiential way that people interface with distraction you tried to appeal to the bottom line which you thought well you incentives incentives align the fucking incentives um and that didn't work which obviously means also that people's level of administrative burden misery is also coming along for the ride at the same time yeah it's a it's a fucking mess dude and i think you know even with what i do it's not a very big team but slack slack is like it's so useful and invites so much chaos at the same time it is and it was slack slack wouldn't have been that big during deep work i'm gonna guess it wasn't big it wasn't out yet i talk in deep work about these very early instant messenger tools that no longer exist like hit chat it was just emerging among to programmer class. I was basically saying there'd be dragons, like let's be careful about that. But I wrote an article about Slack years later when Slack was bought. So I think Salesforce bought Slack. I wrote an article about it for the New Yorker. And I think the title of that article gets to the core of the issue you're talking about. The title was, Slack is the right tool for the wrong way to work. And I think what happened, here's my whole theory on Slack, is that when email arrived, it moved us to this new style of collaboration that I call the hyperactive hive mind, where we'll just figure things out on the go with ad hoc back and forth, unscheduled messaging, just sort of like shooting messages back and forth. We'll figure things out, like we're all just kind of connected all the time. That's a terrible way to work for all the reasons I talked about. It's distracting, it's context switching, you can't do anything deep, it's hard to produce value. But if that's the way you're going to work, email clients are not a very good tool for that. You have threads and it's clunky and it's hard to search through your email and find what you did before. So Slack came along and said, look, if this is the way you're going to work, hyperactive hive mind, constant back and forth ad hoc coordination, we'll build you a better tool for that. So that's why people both love and hate Slack. It's a really good tool for that style of collaboration. It works really well, but that style of collaboration makes us miserable. So it's this weird love-hate relationship we have. Like this works great. I hate the thing that is making easier. Why does it make us miserable, that style of collaboration? Because our brain isn't meant to switch our target of attention that quickly. It just takes us a long time if we're talking about targets that are abstract and symbolic. It takes us a long time to switch from one to another. Physical world targets, we can switch quickly, right? We're wired for that. If there's a tiger's roar, I can boom, 100% attention what's going on over there. But when we're thinking about abstract things, information, ideas, things that are symbolic and in our head, that's us. We're basically reappropriating our brain hardware to do something we're not evolved to do. It takes a lot of effort to do symbolic thinking, to think about abstract concepts. And we know it takes 10 to 20 minutes to fully change our attention context from one abstract target to another. It takes a long time. That's why if you sit down to write something, everyone has this experience. The first five or 10 minutes, like, man, this is terrible. Like, I'm making no progress or whatever. And then after a while, you're like, oh, this is starting to flow. Like, it's going better. That's because it took that much time for your brain to load up all of the relevant in information and to inhibit all the unrelated circuits and get your brain really ready to do that activity. So if you now interrupt that brain once every two minutes, it never can lock in on anything. And what you feel then is this sort of diffuse cognitive friction that we begin to experience as fatigue, cognitive fatigue. And it's a really frustrating experience. It's why if you go to an email inbox, you're like, I have time. I'm going to empty this inbox. I'm going to go message by message. Here's the best way to do it right on paper. I'm going to go message by message and I'm going to answer these messages. Why does that get so hard? Why do you find yourself like jumping around and looking for easier messages? Because each message is a different context than the other, and that's torture for the brain. It's really, really hard to go from, all right, this is a complicated question one of my employees is asking me. And now this is a completely different issue, completely unrelated to that, where I have to think of like a good title for something. And now here's a completely different issue. And you're trying to switch one after another. Our brains aren't wired for that. It really makes us unhappy. what would you say to someone who wants to try and retrain that attention maybe maybe they're gonna try and make some sort of a stand inside of slack and say i will only be available at certain times of the day but regardless of the inbound let's say that they fix the inbound because that's a totally separate problem that's much more sort of structural um unless you've got any advice for that as well but how does someone go about re-appraising retraining their mind away from that because we we do become um we get like stockholm syndrome the slack stockholm syndrome where our captor tormentor becomes the way that we operate we've got a favorite little ways of working and it feels like we've done but then at the end of the day we look back and have this sort of odd malaise thing about well what did i actually do today? What got done? Well, not much. Not much got done. Yeah. Well, it's hard unilaterally. If you've changed nothing else about your workload or your communication protocols, if you just say, I'm not going to be on Slack from this hour to this hour, I only check my email twice a day, or whatever that standard advice was from 15 years ago, it doesn't work well. Because if you're involved in a large number of projects that are timely, and the way progress is going to be made with ad hoc back and forth messaging. You have to be in there checking. That's the brutal part of the hyperactive hive mind is that it has defenses to its elimination built into its very nature. Because if this is how we're going to figure this out, like we have to have five or six back and forth messages to figure out what we're going to do about this client coming tomorrow. We have to get this done today. That means you have to see my next message right away so that we have time for me to answer you and you to answer me and for that ping pong match to happen. That means you have to be checking your inbox or Slack constantly. Otherwise, you're not going to see my next message in time for this whole game to unfold. So the very nature of that style of collaboration demands constant inbox checking, which is what I think people often get wrong about this. When I think about things like Slack or email, they think too often about either information like, oh, I've got so many messages in my inbox that I don't need. I have all these newsletters and spam. That's not a problem. That's a minor problem. That's an easily solvable problem. It's like clutter. You know, that's not a big problem. the issue is actually my collaboration style requires me to be in there because if i miss messages in a timely fashion everything falls apart and so the issue is not how do i interact with my inbox it really has to be how do i change the way the inbox is being used i mean so i ended up i feel like had three big ideas on this that span three different books right so in deep work like one of the big ideas was you can train your personal ability to focus. Focusing is really important. Putting aside for now all the things trying to prevent you from focusing, you have to practice it. And if you practice it, you'll get better at it. And if you get better at it, you'll be a superstar because like that's what matters in the knowledge economy. Everything good comes out of focus. Then I wrote a book after that called A World Without Email. And in that book, I was arguing the way we, the thing I was telling you about hyperactive, communication is a problem. This is a real problem. And the fact that we are using this method for coordination is causing all these trouble, is really causing problems. And I went through all the data and all the research and made the case this is super nonproductive. I went back to the archives of the New York Times business session in the 80s and 90s to exactly document the rise of email and how people were talking about email when it first came onto the business scene. And I made the case the way we work is arbitrary. This hyperactive high buying was not a plan. It wasn't seem to be more productive. We stumbled into it. So we really should change it. So that was that book. And then the most recent book, Slow Productivity from a couple of years ago. In that book, I argued, oh, wait a second. Workload matters, too. The other issue of this problem is we don't put any limits or transparency on how many things we're working on. And if you pile too many things on your plate, too much communication interruption becomes unavoidable because they each have little issues they need you to deal with. So I've now, over this 10-year period, have kind of broken down this problem. There's like training yourself to focus, fixing your communication protocols, like how do I communicate in a professional context? How do we collaborate? And then managing workload to be more reasonable. All three of – and this might be why this problem is not solved. There's no one thing to fix, right? So all three of these things go into the issue, and they're each complicated. Across those three books, all of which are great and everyone needs to go and check out, I think we've done episodes about each of them, so they can just go and listen to those and then buy the books. Looking back across this portfolio of productivity advice, what have you heard from readers or what has been the stickiest strategies for you? You look back and you go, OK, that's the 80-20 of what I've published over the last three books. to me I think the the big two that give you the biggest results and I'll tell you the one that's the hardest and that's why this book probably sold the least the big two that gives you the biggest results is taking focus seriously like a skill that really does make a difference practicing focus you get better at it and it has a demonstrable difference you sit down to work and you're just producing better stuff or you're trying to pick up some complicated new thing like oh God, I can learn this faster. That makes a huge difference. And then the second one, which was more recent in my life, was, oh, you really got to control the workload. So much is downstream from how many things you've agreed to work on. You have to leave the mindset of everything I say yes to brings with it value. So saying yes to more things, it's just going to aggregate more value. That's not the right mindset. That's not the way, it's a non-linear reward function there. There's a certain point as you add more things that not only does value stop growing, it begins to go down on the other side and that there's a real saying no to many more things is actually a way to optimize reward and output which is not natural it doesn't make sense at first it doesn't feel like common sense so workload and focus training you can control those more than you think and you're going to have huge results from those a quick aside do you remember learning about the mighty mitochondria back in grade school here's a quick refresher it's the tiny engine inside of your cells that powers everything you do. But here's what they didn't teach you. As you age, your mitochondria break down. That's what can cause you to feel tired more often, take longer to recover, and wake up feeling like you're never fully recharged, no matter how long you sleep. I started taking Timeline nearly two years ago because it is the best product on the market for mitochondrial health, and that is why I partnered with them. Timeline is the number one doctor recommended urolithin a supplement with a compound called mitopure basically it helps your body clear out damaged mitochondria and replace them with new ones mitopure is backed by over 15 years of research over 50 patterns and nearly a dozen human clinical trials it was recommended to me by my doctor and that is why i've used it for so long since way before i knew who even made the product and best of all there's a 30-day money-back guarantee plus free shipping in the u.s and they ship internationally so right now you can get a free sample or get up to 20 off by going to the link in the description below or heading to timeline.com slash modern wisdom that's timeline.com slash modern wisdom the learning to say no thing is interesting especially as people progress inside of their career and they get better at what they're doing they have to learn to be able to say no to opportunities that they would have only begged to have had the opportunity to be in the room to have maybe said yes to yeah only half a decade ago in that time you've had to go from needing that opportunity to actively being able to say no to something that's probably better than it alex my friend taught me about you remember uh in the matrix the woman with the red dress and neo turns around and he says we're looking at me we're looking at the woman in the red dress look again and it's an agent with a gun in his face and the analogy that alex used was now imagine that she's not a 10 out of 10 but imagine a thousand hypothetical 1000s out of 10 and you need to be able to say no to them which previously you didn't even know existed so this i think the kind of um it's almost like reverse entropy or habituation you know your opportunities get better which means that your capacity to say no needs to get better more quickly than that you can't be chasing your tail trying to learn to be able to say no less quickly than the opportunities get more seductive yeah it's almost perverse the way that works it's like when you have all the time in the world all you want is opportunities and then when you have opportunities all you want is all the time in the world i had to change i don't know what you do but i had to change my rule at some point. This was hard for me to the default. No, I guess just how I have to operate now. It, cause as soon as you try to have a triage rule, well, look, I'm not going to do this opportunity unless I only do speaking gigs that have this much money or this, or I only going to go meet with someone if they're like this interesting or this or that. Eventually the number of things that satisfy that criteria overwhelms us as well. It's just, so I've, I, i've just had to fall back on the default no you're talking to somebody who came back from a two-day trip to qatar at the start of this week so i spent as much time traveling as i did in the country to to give a talk and as i looked around there was this first the first night dinner there was maybe 300 people there and i'm talking to logan paul and stephen bartlett's over his shoulder and the ceo of qatar airways is here and the middle eastern director for metas over there and i was looking around thinking everybody here wants to be here it's very exciting everyone's really lovely but also everyone here can't say no everybody in this room is chronically incapable of saying no because it's no to this one several times by the way i the amount of invites to the qatar and the uae and other places i have i have said no all right well consider me a fucking consider me a slut compared to you cal and whatever whatever it is i must be easy an easy booty call they tried to get cal newport we couldn't get cal so we'll ring chris instead the default no oh man yeah it's it's crazy the things you end up saying no to after a while but i mean there's a currency shift for me time to think is such a valuable that's a more valuable currency than money right you get to a point where you're like oh i'm doing fine but if i don't have time to think what's the point and then that becomes this like really rare currency that's that's much harder to get a hold of and that's the only way i can protect it now is anything that requires me to like go somewhere it's a default no and then i can talk myself out of it later right i'm like you know what i could bring my family with it we could have a trip right so actually you know what i i will do this or uh you know i just did a uh at a master class course released um this week i spent a year and a half say no to that and then like eventually i sort of talked myself i talked to some people uh they're like we'll come to dc to do it i talked to you James Clear had just done one, and I had a good talk with him about it. And I'm like, you know what? This will be interesting. And it took me a year and a half, but I finally talked myself into it. So I will say yes, but the default no means that you don't have to. You're high standards. Yeah, you don't have to run it through the ringer. And then you're like, okay, if it really sticks with me, then maybe I'll be like, all right, all right, I'll do it. How much should people actually be working? Well, it depends what you mean by work and what they're doing, right? Because think about it. Let's say you're an athlete. It's super well-defined. Like here's optimal training, here's optimal rest, and that's what you should be doing. That's really clear. We don't have those limits as clear in the culture for other types of jobs that we probably should. If you're at a high-wage hourly bill job, like a law partner at a big law firm, there the economic model is the more you work, the more profitable it is. And we'll pay you big money to do this, but you should basically work as much as you can that your body will take it. That's the economic engine. That's why I think those jobs are scary. If you're a novelist that writes literary fiction, so you're like, I really need to be award nominated for each book or I'm going to fall out of this slipstream of – because no one's going to read these books unless they're some of the best books. Then you should be doing like four hours in the morning and then just disappear, right? Like you should be doing very little more work than that because almost anything else will get in the way of you like sticking in that position. And so it all just depends on what you do. Didn't you look at some experiment of shorter work weeks? Yeah. What did you learn from that? There was a lot of these right around the pandemic, right before and then right after, in Europe and Iceland. So some European studies, I think Germany did one, Iceland did one, UK did one. And they were looking at four-day work weeks. So what would happen if we take away one day? The interesting thing about those experiments is what they found is whatever measures of productivity they came up with, they didn't get worse, which I thought was very interesting. They took a day away, and yet the perceived productivity or the measured productivity didn't go down. And there's two ways to look at it. The one way to look at it is to say, oh, this means that we should have a four-day work week because things didn't get worse. And, okay, maybe, right? But to me, there's a bigger observation that came out of that, which is like, wait, so what are we doing? during the work days like this. There's something going on here that should really catch our attention. What does work mean that we could take an entire day off the table with no other preparation and the valuable stuff being produced doesn't change? This tells us that like whatever we're doing while we're sitting here in work is not just sitting down and trying to produce value. We're clearly have all sorts of other sorts of distractions going on, context switching, time that's being devoured parkinson's law is at play work must be broke to me that was the more important observation is that like if you can take away a day nothing changes then i don't think we're doing in the office what we think we're doing in the office parkinson's law was on the tip of my tongue work expands to fill the time given for it and if you give people five days they'll take five and if you give them four days then they'll do it in four and look everybody knows just how much time they waste not doing the work not doing the thing that they're supposed to do and this isn't victim blaming this is a lot of the time dealing with admin unnecessary meetings you can't get out of them you have to be there for whatever reason so it's not as if it's bottom up a lot of it is top down dictated this is the environment that you work in and you have to do this but even outside of that when you do have your one hour in between meetings your inability to not i remember are you when i used to run nightclubs and i get in at 2 30 in the morning the final part of the night was cashing the till so this was before we switched to tickets which was sort of the late teens just before covid uh digital tickets online which meant that you didn't have to cash as much money in the till but before that it was all you know five pounds and ten pound note and 20 pound notes and single pounds and all the rest of it and i would go into the office with the manager of the venue and we would be counting the money but this is the final task the final bit of the night it's fucking 2 15 or 2 30 in the morning we've just taken the taken the till off as it's called anybody that's coming in doesn't get to come in we're not going to take any more money and i'm sat up there doing like light lift mental arithmetic but for me somebody who hadn't done math since i was 16 it was a relatively heavy lift flicking through the money flicking through the money is light you know huge fluorescent overhead lights just before and then i get to drive home and i'm like thinking about and i gotta go put the money in the till and i gotta write it in the spreadsheet and then i get into bed and as i go into bed my eyes below my eyelids would start flicking left and right i wouldn be able to tune myself i also doing this let not forget in a sweaty beer stinking office above a room going yeah i had to walk through the club i had to shout at the hostesses one of them's getting fingered on the dance floor stop doing that you're supposed to be at work the dj's pissed i need to you know it's chaos and i've tried to coordinate this orchestra of bullshit and then i've had to do mental arithmetic and then i get to drive home and then i'm like okay chill out brain it doesn't want to and that eyes moving left and right thing i think is the sort of optical equivalent ocular equivalent of how people feel when they finally get a moment okay all of my stuff is done and then they try and sit down to work on the thing that ostensibly that's actually there to do right because all of the other bullshit the meetings you're not there to do the meetings you're not there to do the slack you're not there to do all of that is foreplay to get you to do the thing that you're there to do and then you sit down to do the thing you're there to do and your eyes are moving behind your eyelids is the equivalent you're swiping and moving across the screen and you've got a few different other well just check on this thing like what the living fuck is going on i've like trained the environment that i work in has trained me out of being able to do my work well we are meant to do like what would be the ideal work day in an office environment that would actually mask the human brain it would probably be you come in, you work on something hard for a while. Like that's what you do in the morning. You have lunch and then you like catch up with, have some meetings, talk to some people, hey, what's going on? And, and, you know, do some tasks and that's your day. Like that's basically what we can do. Like two things, one big burst of like, let me focus on something hard. And then we can kind of come down the mountain after that with, let me chat with people what's going on. Some decisions need to be made or whatever. That's probably about optimal. Instead, we juggle a dozen to two dozen tasks that all have their own demands. They all have their own communication needs. This is why the Microsoft data shows, oh, the work happens the Saturday and Sunday morning. It is really hard. You can't go from and meetings are very hard as well. We think like, oh, I'm not actually doing work during meetings. But what you are engaging in a meeting is all the parts of your brain that deal with social interaction. And those are a large part of your brain. And that is a fraught and mental energy consuming activity to sit in a room or on a Zoom screen and try to manage all these different people. And how do I look and what am I saying and what's going on here? And I have to say the right things. It's draining. And you come out of something like that. It's difficult just to jump right back into something else. And if you come out of something like that and there was a lot of obligations generated, oh, we discussed in this meeting things I need to do. And now you try to go straight from that meeting into another. Well, now that's really in the back of your head. What about this? What about this? We can't forget this. We just made our obligations. That feeling of fatigue, it's really as fatigue as what it feels like, a mental fatigue, like there's sand in your brain, sand in the gears of your brain. That's the state that a lot of people who work in front of a computer screen, like that's the state they're in most of the day. And they don't even realize, oh, that's a bad feeling. That's a negative state. That's not how it needs to feel because you have nothing else to compare it to. So, yeah, the amount of things we're doing, the amount we're trying to switch back and forth. I always thought that part of the problem was a lot of our current thought about work culture and hustling and what it means to produce was influenced by Silicon Valley in the 90s and 2000s because that was considered this very ascendant part of the economy. You know, through the 2000s, through the Steve Job era, we looked at Silicon Valley. These are the coolest companies. They're doing all the coolest stuff. And over there, I think they adopted a model of work that was very inspired by computer processors, right? So because that was what was in the air in the 80s and 90s in Silicon Valley was the computer processor wars, you know, the 386 versus the 486 versus the Pentium. And it was all about speed. And the thing with a computer processor, if you're a computer type, what matters is you never want the pipeline to be empty, right? You want to always make sure you have stuff for that processor to do so it never wastes time. The processor will, every command you give it, it operates the same as any other. It can switch. It doesn't care what they are. It just sits there and operates one command after another. And the whole game with getting processors to be effective is like don't have downtime. Like the real fear, I can put on my computer scientist hat for a second. The real fear in computer processor design is that you sometimes get to a command that's going to generate a huge delay. So you say like, oh, go get something from memory. That takes a lot of time from the perspective like a computer processor cycle. It's just sitting there cycle after cycle doing nothing while you're waiting for the memory bus or whatever. So we invented these processor pipelines like, oh, while we're waiting to get something back from memory, here's some other stuff the processor can run so that it's never not working. And the idea was you want to move as fast as possible and you never want to have downtime. And that's how you get the most out of a computer processor. The human brain is like 180 degrees different. We can't just switch back and forth between unrelated commands. You switch me from one to another thing and boom, 30 minutes of my mind is fried. Humans operate very differently. But I think Silicon Valley associated is that here's the thing we're going to associate with being really good at your job. It might have used to been, I don't know, your skill. It was Don Draper and Madman. Remember that conception of what does it mean to be good at your job? They weren't showing Don Draper grinding it out. Like, man, Don Draper is like in the office till 3 a.m. every night or whatever. Now, he took the five o'clock train back to Connecticut or whatever. It was he he was really, really good at coming up with ad copy. He was good at what he did. That's what you used to respect. And then after the 80s, 90s, Silicon Valley became pervasive. Like, no, what matters is you never have a no op. You never have a down cycle. You might as well say yes to more things. You might as well get more emails. You never have time or you're not working. that's what productivity is going to be. And that was a disaster for the human brain. If you struggle to stay asleep because your body gets too hot or too cold, this is going to help. Eight Sleep just released their brand new Pod 5, which includes the world's first temperature regulating duvet. Compare it, their smart mattress cover, which cools or warms each side of the bed up to 20 degrees. And you've got a climate controlled cocoon built for deep, uninterrupted rest. The new base even comes with a built in speaker so you can fall asleep to white noise nature sounds or a little ambient taylor swift if that's your thing and it's got upgraded biometric sensors that quietly run health checks every night spotting patterns like abnormal heartbeats disrupted breathing or sudden changes in hrv which is why it has been clinically proven to increase total sleep by up to one hour every night best of all they've got a 30-day sleep trial so you can buy it and sleep on it for 29 nights and if you don't like it they will give you your money back plus they ship internationally right now you can get up to 350 off the pod 5 by going The link in the description below are heading to 8sleep.com slash modernwisdom using the code modernwisdom at checkout. That's E-I-G-H-T sleep.com slash modernwisdom at modernwisdom at checkout. There's definitely an element of this that it's very public productivity. It's very obvious. Look at how hard I'm working, right? If you're the one that replies quickest on Slack or on email, then it's evident that you're the one. it looks like you're the one that's working hardest because you're the one that's most responsive whereas the person who's silently working on their own they can't broadcast it by design they can't broadcast it to everybody else so yeah this uh um obvious productivity in a way is way less sexy so i think you know the new elephant in the room is ai and how that is enabling an increase in pace of output but almost certainly a decrease in quality so fold ai into your existing worldview because to me it just seems like a huge force multiplier for what already was pretty sloppy slack email async communication that's always on people taking their work home with them never being able to not context switch not focusing on quality and instead focusing on quantity not being able to dial themselves in to do deep work for one moment and now that is enhanced and magnified even more by the use of llms to help you put out more to help you think less so your focus is actually you're you're in slack with your llm it wouldn't surprise me if there is a llm integration into slack at some point in future i don't know whether there is um where you can just do it in there so you're just talking back and forth in one fucking workspace talk to me fold ai into this you must have a million thoughts oh there's a lot going on with ai uh i mean i think in its current instantiation so we think about like an office worker for the most part put programmers aside i'll get back to them but non-programmers are really interacting with chatbots like that's the main way they're integrating right now with ai it's exaggerating exactly what you said for a lot of people it's exaggerating the problems that already exist. Now, there's a term for this that comes out of a Harvard Business Review article from last year. They call it work slop, which they put together as one word. And they have some pretty compelling data on this. So what's work slop, define work slop for me? So work slop is AI-generated work products in the knowledge work sector, so like emails, reports, and PowerPoints, or what have you, that are generated quickly by AI, but they're so low quality that they actually, it's very difficult to, they make everyone else's jobs harder. This seems to be, this is like the defining aspect of work slot. It's quick to produce, but it's so low value that it actually no real progress is made. So like you get a work slot email from, you know, your boss or whatever. And like, this isn't useful to me. It's this weird wordy thing that's broken up into sections and it doesn't get to the core of the problem we have to solve. So you made that email quick, but in the bigger scheme of things, we made very little progress towards what we want to do. or you put together a work slot PowerPoint presentation so that you would have something at the meeting. But now we're spending 20 minutes looking at this nonsense and nothing is not helping us. It's not helping us actually do things. So this is what's happening, or at least my fear. And the reality is most people aren't using these tools in the office. Let's just set the reality. Right. So but for the people who are using them right now, which is a healthy percentage, but it's not the numbers. Well, it's difficult because there's a lot of fudging of the numbers here. There's a lot of mistaking have used or experimented with, with are regularly using them. So I see this mistake happen a lot. And so it's difficult to get good numbers. There was like famously, maybe it was an Ethan Mollick article where he was talking about in my world, like academia, the homework apocalypse. And he's like, look at this study. Students just don't do work anymore. Nine out of 10 are just using chatbots now. But you look at that study and what it actually said was nine out of 10 had tried using a chatbot at least once. And if you looked at who's using them regularly, it was like two out of 10. Right. Because like for most of the students, it was wasn't helping the way they thought it would. So I don't know what the numbers are. If you count like advanced Google use, I think it's larger. Like, yeah, I search for information on this instead of going to Google. That's larger. But in terms of people who are actually making office work product out of it, I think it's smaller. than the people who follow AI commentary or talk about it on AI Twitter, AI YouTube. I think it's a lot smaller than they probably assume just because in their world it's pervasive. But the people who are using it, this is the problem. They're trying to avoid, this is my theory on this, is like, how is AI helping like an office worker now? Well, their brain is exhausted from all this context switching. So what problem are they looking to solve? They're looking to avoid having to do hard moments of cognition because their brain is so fried. It's really difficult to like solve the blank page problem. oh, God, I got to send this email. I got it. It's a blank screen. I got to start writing from scratch. That's really hard. Yeah. And the inertia that they've been trained out of overcoming because of the prime, it's almost like a one to punch. Yeah. Humans were primed to not like heavy. Well, we already didn't like heavy cognitive load. Then our ability to deal with it and get through that initial resistance was decreased through the context switching. And now don't worry about it. Don't worry about it. Don't worry about it, carbon-based life forms. The silicon-based life forms are coming. And let's throw in one other aspect in there. Also, outside of work, we had these distraction machines in our hand that were further degrading our comfort with concentration because any possible moment of introspection we would have had even outside of work. Why would I do that when TikTok has like the perfect dash cam video of, you know, a Karen getting punched or something like, I got to watch that, right? And so we have that revolution comes along, plus the email revolution. We completely atrophy our ability to think and we exhaust our brain. So the other aspect of it, as we talked about, it's really exhausting to go through your day context switching. So I don't have any reserves left to write this PowerPoint. That seems impossible. And then AI is like, hey, hey, hey, hey, I can do it for you. It'll be fine. It'll be fine. It'll be good enough. It'll be good enough. You're like, oh, OK, I can smooth over. I use this analogy in a New Yorker piece last year. It's like it takes your effort graph looks like spikes, like an EKG or something like that. And AI smooths over those peaks. And so you don't have to, your peak concentration required can come down. Like, well, you can fill the blank page and then maybe I have to work with it a little bit. That's easier than doing it from scratch, but the stuff being produced is no good. And so I feel like work slop, it's almost less of a, it's less of a critique of AI than it is AI making obvious a problem with the way we were already working. I think that's what's going on there. I think this is even happening with computer programmers. This is considered, you know, heretical right now. I guess I'm used to being yelled at. People are really excited by this workflow where I have seven or eight cloud code agents going concurrently producing code and testing them. And I'm just a manager of all these different processes. And they're all producing this code on my behalf. And it feels really cool and interesting. Like this has to be the future. I don't know that that is. I mean, I don't know the context. The problem is outside of like demos or internal tools or just having fun, that's not really code you can trust very well. And it does, though, completely lower the peaks of being a computer programmer, those peaks of cognition. It's much, much easier to manage a bunch of cloud code processes than it is to come up with an algorithm. And then you have that same blank page. So I think the jury is still out on even where we're going to end up in the AI impact on programming. I don't know where it's going to end up, but the way it's being talked about in the last few months after the latest Cloud Code update, which is sort of, I guess that's something humans don't do anymore. I don't think we're there ready to say that yet. I get popped with Cloud Code ads. I get, I, I, you give me a terminal. I have no idea what to do. I'm like, I'm like, you know, someone's grandmother trying to use an iPad. I have no idea what's going on. So they are pushing very, very hard at the moment for this. it's funny, but it's a little bit crazy. That's my world, right? I'm a computer scientist, is that for engineer computer scientist types, they forget how technically advanced they are. So yeah, cloud code works in the terminal, right? And that's why it works so well. It exists in a world of text only. Text command line commands, like the old DOS command line, it's all text commands, which you can do a lot with. You can create and edit and compile a computer program. So it's very good at that. And it's a limited set of textual commands. That's perfect for a language model. And the engineers are like, oh, we can use this terminal based tool to do all sorts of other stuff that's not computer programming. Great. This is the this is solved. Everyone's going to be doing this. Everyone is going to have these sort of personal assistance based on something on cloud code. I'm like, man, do you realize how foreign a command line interface is? You realize like how weird and nerdy and complicated your world is like, yeah, this will be great. My grandma will just on the command line understand that like the cloud code agent can bring up a VAS script that's just going to cap those files over to the regex grep, you know, it'll be fine. No one knows how to do any of that type of stuff. So it's sort of funny seeing the engineers building these incredibly intricate, nerdy, wonderful tools they've custom built for cloud code to help them in their life. And they think the gap between that and everyone else having AI automate things in their life is like, oh, it's this real small thing. I'm like, oh, man, I don't think you understand. I mean, people are still not quite sure about the right click. I think you still have a ways to go. I saw this tweet from Robert Friendlaw. Lawyer uses ChatGPT to help write a brief. ChatGPT hallucinates cases in quotations. Court sanctions lawyer and four co-counsel for not catching the errors. The lawyer who used ChatGPT has practiced for over 30 years. He prompted ChatGPT, write an order that denies the motion to strike with case law support. told the court that he doesn't normally use Chachupit and he used it this time because he was caring for his dying family members said no of his co-counsel were aware of this use of generative AI. Cor says that because all five attorneys signed both documents that included these errors and they admit that not one of them verified that the case law in those briefs actually exist their conduct violates rule 11b2. There's hundreds of those happening right I heard I don't know where this site is. There's a site that tracks this. Lawyers getting busted for chat GPT written briefs that just make things. It will for sure make up things if you ask it. Because, again, what it tries to do is, you know, not to get people know this, but right at the very bottom, what is a language model trying to do is trying to solve the word guessing game. That's how it was trained. It was given real text. You knock out a word and say replace that word. Can you figure out what word was really there in the real text? So the language models just think they're trying to expand a real text that really existed. So they're trying to produce text that makes sense given the prompt. There's not world models or structured reasoning in there of like, okay, this is a legal brief and we have a notion of a citation. We don't know how it thinks about that. There's hundreds and hundreds of cases of this happening. I heard Scott Galloway talk about this on the Pivot podcast. There's some site that tracks this that he keeps an eye on, and he says it astounds you. You think it's a handful of people? it's not it's all the time i got here's my story of getting burned by that i sort of learned my lesson i was working on uh because the one way i'll use chat cpt is just sometimes instead of google right um especially if i'm if i want like instructions for how to whatever change settings on something it's great it has a lot of really useful spectacular for all of that stuff if you want to use it as basically glorified wikipedia that's more instructive like yeah yeah you can Wikipedia you can ask questions of. So I was using, I was writing an essay, and it was on Isaac Asimov's Rules Robotics. This was a New Yorker essay. And I left my copy of iRobot. I was here at my studio, and I left it at home. I was like, oh, I needed to add this quote, right? Oh, I left it. And I was like, oh, you know what? That story's in the public domain. It's all over the internet. And this seems like it would be perfect for ChatGPT. like, hey, can you just grab a copy and find me that quote? And they'll save me a little bit of time. Like, yeah, here it is. Here's the quote. I was like, yeah, roughly I remember I put in there. And then the fact checker was like, where's this quote from? I was like, yeah, it's from the story or whatever. I get the book. And it just hallucinated a quote that was more or less like what was said, right? Because again, it's kind of playing the game of this is the type of text that would make sense giving the prompt, but it wasn't the actual quote. It had full access to it, right? You can search this. It's in the public domain so that the actual story is everywhere. So I had just naively assumed if you ask it for some information that exists on the internet that, oh, it'll just go find it and format it for you. I didn't. And then I went through a whole dialogue with it where I was like, this is not the right quote. And it's like, yeah, you're right. You know what? I thought you meant paraphrase a quote. Here it is made up. I was like, that's not the real quote. Can you go get the real quote and give it? At this point, I was just experimenting. I'd already filled it in the article. and he's like you're right yeah you know i was being tasty here you go i could not get it to give me the real quote so anyway so i was i learned my lesson i was like oh don't assume even if it's common information that it has access to the desire the desire to fucking reprimand an llm and i've shouted at them i've capital letter exclamation marks it's like what what are you doing what do you do is what what are you hoping to achieve by throwing your emotional distress at this fucking disembodied voice on the other side okay we bit aside i fucking love chat gpt i think it's been really really fantastic for tons of things it what's important is learning the limits and not using it for case law um this episode is brought to you by whoop i have been wearing whoop for over five years now way before they were a partner on the show i've actually tracked over 1600 days of my life with it according to the app which is insane and it's the only wearable i've ever stuck with because it tracks everything that matters sleep workouts recovery breathing heart rate even your steps and the new 5.0 is the best version you get all the benefits that make whoop indispensable seven percent smaller but now it's also got a 14 day battery life and has health span to track your habits how they affect your pace of aging it's got hormonal insights for ladies i'm a huge huge fan of whoop that's why it's the only wearable that i've ever stuck with And best of all, you can join for free. Pay nothing for the brand new Whoop 5.0 strap. Plus you get your first month for free. And there's a 30-day money back guarantee. So you can buy it for free. Try it for free. If you do not like it after 29 days, they just give you your money back. Right now, you can get the brand new Whoop 5.0 and that 30-day trial by going to the link in the description below. Or heading to join.whoop.com slash modern wisdom. That's join.whoop.com slash modern wisdom. What opportunities do you think an increasing reliance on AI opens up? Because I get the sense that as more people use LLMs to do the work for them, this will create advantages in some areas for people who don't need to be reliant. So have you thought about the holes, market openings that will occur? It will. I mean, the way I think about LLM-based AI versus more advanced AI that we don't know how to do yet is, My theory is what is being affected is going to be more narrow at first. It's going to be places where there's an exact match between what generative AI existing tools can do and existing market sectors. We saw this actually, the week we're recording this, we actually saw this reflected in the stock market. It was this interesting paradox that was going on this week where the stock price of software companies that deal with stuff that is well suited for an LLM went down. They call it the SaaS apocalypse, the software service apocalypse. So companies that do legal advice, companies that do graphic design like Sigma and Adobe, because we have gender of image generation is making building images from scratch is less useful. customer service of companies that do a lot of customer service type software. We saw the stock was sliding on these very specific software industries because like, look, I think LLMs are going to be able to do this. It was triggered by Anthropic releasing some plugins that made it easier to integrate LLMs into your services without having to hire these other companies. But you would think that would be good news for the big tech companies building the AI that's going to replace all this. Their stock was sliding as well. So the big tech companies had this big slide that at the end of the week we're recording this, there was a rebound at the end, but it was like a trillion dollars in market cap disappeared from the big tech companies at the same time. So what does that mean the market was betting on? What are investors betting on at that point? What was going to happen? And they were betting that in the near future, the next year or two, what we're going to see is selective impacts in specific fields from generative AI, but also that too much money is being invested in these AI companies already, which means they're betting that they're not about to automate most of the economy. They're not about to, you know, just one more iteration away from a huge economic disruption. They're not they're not at this peak of like complete transformation, because if they were, you would be trying to increase your holdings in these companies. Like, I don't care how much money they're investing. These companies are going to be worth an astronomical amount of money. But the market is betting. I think the impact is going to be more limited in the one to two year window than a lot of the commentary was seen. So I think that's important because talk is cheap, but tech stocks aren't. And so people, the way they spend their money actually often has more of, I think there's a lot of information in that versus just, I've been reading these articles online and my God, the vibe really seems to be saying this is a big deal. So I kind of agree with the market's consensus right now. For sure, there's going to be industries that are affected, but it's not going to be one of these situations where you say, okay, any work that's not just the deepest creative work is all going to be automated in the next few years. So I better go learn how to do art or something like that. I don't think it's going to be that broad at first. I don't think the current generation of AI technology can support as broad of impacts as people think. There's a lot of extrapolation from, well, if it can do this with code, certainly it could do this with all these other jobs. If it could do this with this industry, well, certainly next it'll do it for all these other industries. We have to be wary of those extrapolations. Right. I think I read an article from you, what if AI doesn't get much better than this? yeah sort of if we have i don't know some sort of flint effect thing that kicks in but for ai where you know because i think a lot of people would agree chat gpt2 to three fucking hell to four four oh 4 4 I know there a whole furor on the internet about people that have got girlfriends or boyfriends that are virtual on 4 and they're all getting upset and sad about it. And I don't understand. I don't think I use the tools sufficiently deeply to be able to test this and benchmark it. It's like my Fire TV sticks remote isn't working well. It was able to do that fucking five years ago. But is your your thinking is that we're maybe going to reach asymptote for what LLMs generally and transformer technology is able to do? And then it's going to be a new architecture entirely if we're going to actually get beyond this. Yes. Yeah. That's what that article is about. I think that was a very of the articles I've written. I think that was a really important one that came out in August. And the story it tells and a lot of other people have told the story as well around that time and since. But the story it tells is basically what happened is there is this big paper that was published in 2020. The lead researcher, Kaplan, Jared Kaplan, I think, was at Anthropic at the time. And it was this paper where they said, hey, something weird is happening here. If we make LLMs bigger and we train them longer, they perform better. Technically, they're saying the loss decreased. That sounds kind of obvious, but in like machine learning circles, that was surprising because there's this idea of overfitting where if you just make your model bigger, the performance goes down. So it used to be like you have to find the perfect size model for your problem space. That's the way people thought about machine learning until this paper came out. I'm like, I don't know, transformer-based LLMs. They were using GPT-2, and they were systematically making it bigger, and they were seeing that the performance just kept going up. I'm like, this is interesting. So let's try it. And that was GPT-3. All right, let's actually make this like 10x bigger. Surely this can't be right. And it was. It matched the Kaplan curve exactly. be like, oh my God, this actually got way better just by making this bigger. Like, all right, well, certainly that must be the end of it. Let's try it with GPT-4. They made it bigger. They trained it much longer. Months and months they trained it. Microsoft had to build these custom data centers to train it with new AC technology that didn't exist before. And it fit the curve. It was like way better. And the thing GPT-4 did that really got... So GPT-4 set off the whole industry. The thing it did is it started showing abilities beyond just language. And that's where people got excited. Like, oh, wow. If you train a language model on enough language, it learns about things that isn't just producing language. It can play games. It can do math problems. It can do logic. I mean, this was super exciting. It was super exciting. So the assumption was do this two or three more times. You have AGI. So that's what the whole industry was based off of. when we went from three to four was this is legitimate justified excitement expand the size and the training duration two or three more times and the economy is going to happen in a box i mean it was so that's where all of that was the the engine for all this excitement so they tried at open ai was called product orion they made it bigger modeled in four they trained it even longer Like, here we go. And they tried it and they said, it's not much better. And this was this big brick wall surprise for the industry. Like, wait, it didn't get better. Everyone else tried as well. Right. Grok, they tried this with Grok as well. The Colossus data center was like, we're going to have 200,000 GPU data center. No one's ever built anything this big. And it was like a little bit better. Meta tried this. They had a model called BMF. Like we built the biggest data is bigger than anyone we've had before. They didn't release it because it was marginally better than the last model that they had. And so this was a huge issue, right? You couldn't just make the models bigger and train them bigger. So what they did was they switched to what are other ways we can get performance increases? And can we get more narrow by what we mean with performance? And this is when we began to get all the alphabet soup models. Well, it's GPT-0, O3-mini-slash-whatever. And they switched the focus from just, this is amazing if you use it, to we have these benchmark graphs. And look at these graphs. Things are going better on these benchmarks. And all became about benchmarks because these are very narrow things that you could train models to do well on. They weren't intuitive. GPT-4 was just awesome. By the time we got to GPT-5, their whole launch, their launch page had 28 graphs of benchmark names that no one knew what they were. And so then they had to look for all these other ways to get improvement. And that's where you got like inference time compute. Well, what if we compute longer for harder questions and they began really pushing fine tuning? Well, for specific types of problems, we can get data sets that have answers and questions and answers. And we can use reinforcement learning to try to take this pre-trained model and make it better at this particular type of problem. And then we can have a benchmark that shows us we got better at this problem. and my argument in that article is like this is a way different game than we were playing when we went from 2 to 3 and 3 to 4. We're no longer scaling to AGI. We're taking basically GPT-4 and we're doing all of this like tuning and adding extra stuff on top of it and around it and measuring these very narrow benchmarks and that's why people have this feeling ever since. Like I guess they're better but it's not in an obvious way. It's better in specific tasks or if I vibe code this, it looks better, I guess, and it seems more narrow and so yeah we're reaching an asymptote on just pure fine-tuned LLMs as an engine for AI we're going to need more architectures it's going to take more time well presumably ChatGPT6 could come out and oh fuck they just blew through the entirety of my prediction this curve no longer curves flat in the way that I thought and shit this is this is a different universe now yeah but that won't happen because they tried and they don't know how to do that. So it's not going to be just an LLM. I mean, my prediction of the future of AI is I think what we're going to see, I think LLMs are very powerful, but what we're going to see is much more of hybrid models that are custom fit to particular problems where, okay, this system does this thing better than a human. And in its guts, there's like an LLM in there, not a huge frontier model, but one that's like souped up and optimized for this particular type of thing. but there's also like five or six other models and there's an explicit world model. There's a future predictor. There's a policy network trained through reinforcement learning to try to evaluate situations to see what's good or bad. There's a whole logic engine on top of this that hooks these together. These are what I think the, the AI systems of the future are going to be like they're going to be bespoke and there's going to be a ton of them. So when we get the AGI, it's not going to be GPT seven can do everything you ask it as well as a human. It's going to be a world in which there's 10,000 different AI products. And you realize that, Everything I can think of now, there's some product out there somewhere that can do this better than humans, just like there's AI that can play chess better than humans. There's a different AI that can play Go better than humans. There's an AI now that can beat professional poker players at Texas Hold of No Limit. They're all different systems with their own pieces in them. And a lot of them have some language models in them as well, but a lot of other pieces as well. It's distributed AGI. That's what it's going to be like. We're just going to wake up one day and say, there's fewer and fewer things where we say humans can do this better than computers. And it's a different model than PAL 9000. There's one giant. It's a really inefficient way to imagine solving this problem. If we just have a big enough language model, it's going to do all activity. It's going to power all agents. It's going to automate all systems. That really doesn't make sense. I think it's going to be a much more distributed path towards AGI and AI. Given what AI can and can't do and what the quality of work is that it puts out at the moment, what is some good advice for somebody who wants to work against the weaknesses that are going to be exposed in other people because of their reliance on AI by avoiding it themselves or by using it appropriately? what would you focus on because again it seems to me like quantity is easier to achieve than ever before quality is going to be rarer that inertia getting the project off the launch pad the blinking cursor of the blank page yeah where should people focus their time and their attention in order to capitalize this i think you need to begin thinking about the feeling of cognitive strain the way that, you know, a weightlifter thinks about the burn of a muscle or a runner thinks about burning lungs as a thing that is uncomfortable in the moment. But man, I'm excited about this feeling because I'm getting stronger. You got to make yourself really comfortable thinking hard. That is the differentiating factor. I mean, obviously, I've been saying this since 10 years now, but that's that's even more now going to be the differentiating factor. And if you talk to athletes, they're like this is like Schwarzenegger and pumping iron talking about pump and that's really painful what he's doing actually right like lifting the the level of weights that the physical pain he's in is high and he compares it to an orgasm right because if you're a weightlifter you're like oh that pain is directly translating the more strength and more muscle mass you got to think that same way about your brain you cannot flee cognitive strain you have to think about it in a knowledge work cognitive age that is the feeling of my brain getting more capable. Yeah, I want to seek that out. Let's go get it. Let's go get some, right? Like I want to, this, nope, bring my focus back to this thing. I'm going to try to push this through. And then when you're done, be like, oh man, I exhausted my brain. That's awesome. That was like a, that was like a really good cognitive workout. So don't, well, everyone else is using AI to run away from strain. You should be the person running for it because especially in the American context, I mean, the knowledge economy is now a massive portion of our GDP and the knowledge economy itself is shifting more towards cognition-intensive work. So, you know, knowledge work can capture anything where you're not building things. But now all the lower-level knowledge work is being outsourced or automated. A lot of it has been replaced over the last 30 years by software. We don't have support staff and assistants and secretaries like we used to because, well, you can use Microsoft Word and email. We don't need separated people. And so the work that's left in our economy, the knowledge economy, has been getting more and more cognitively demand. and so the number one skill is i'm used to straining my brain learning hard new things and maintaining focus that's what i would train that's so good i i really really agree and it's the funny thing is that's why i asked at the top if you just felt like fucking cassandra because each subsequent development in technology makes this more important uh yeah i do there's always going to be that seductive whisper in the back of someone's mind that well yeah but i can work faster with ai i can work quicker by what if my boss sees me doing executive functioning through slack more whatever what is the what's the elevator pitch for you should do work of high quality and that will end up winning you have to think about employment ultimately it's a marketplace There's a lot of obfuscation and fog and smoke, but it's ultimately a marketplace, right? You're paid money. In exchange, you produce things that have economic value. That's what makes that exchange make sense. There is not ultimately an underlying economic value to the coordination activities by themselves. There is no actual economic value to the speed of your Slack responses or the number of meetings you go into or the number of like bullet pointed emails with those sort of chat CPT emojis that you put out. that itself doesn't generate economic value. The stuff that does a knowledge work almost always requires you mastering hard skills and applying them to concentration. And ultimately that shakes out. There's only so far you can get or so far you can hide being busy because busyness can't be monetized. And, you know, of course you can create a smoke for a while. Like, I don't know, like, you know, Chris seems like productive, I guess. Like he's always on these emails and this and this and that. But if you're not actually producing things that have economic value, like ultimately that catches up to you. Your opportunity is narrow. You're going to get found out at some point. Where if you do the other thing, it's like, no, I'm creating stuff that is rare and valuable. It's unambiguously has value in the marketplace. You write your own ticket. Like what? You want to have a business where you work half the year? You can do it. You want to get paid a huge amount of money? You can do it. You want to like work for a company, but you choose when you come into the office and you declare like I don't want to do meetings. That's actually a thing, by the way. I talked to a marketing team at one of the major tech companies not long ago, and they said, you know what? We're in the sales side. And like our group, the sales group, we are exempt from meetings because they can directly monetize. Oh, you brought in this many dollars. We can see it. And if you're bringing in dollars, they're like, you can do what you want. And they could also see if we make you go to meetings, those dollars go down. It's like, forget the meetings for you. everyone else where there's not a clear number where they can see how much value bringing like oh you better be there in the medium i i've did i've always thought this the the big problem that most people have that doesn't exist in the world of sports stars if you're a sports star everything that you're doing is to facilitate performance and performance is very tightly bounded and it's quantifiable if you're a weightlifter that 300 kilos is 300 kilos yeah you either pick it up or you don't pick it up and your sleep and your recovery and your nutrition and your hydration and your game tape and your technique work and your snc and your body work and massage and soft tissue and all of that stuff combine to this output to very very sort of single ordinating principle the same thing goes for tennis and the same thing goes for football and the same thing goes for baseball and so on and so forth you do not perform well you begin to scrutinize all of the contributing elements that come toward that the problem that you have in most normal people's lives is the output that they're optimizing for is diffuse and very hard to work out well i want to be a good father but i also want to perform at work and i do brazilian jiu-jitsu on an evening time and my wife makes me go dancing and i want to be engaging at a cocktail party okay well first off that's lots of things it's not a single ordinating principle and secondly defined to me the lineage between your disrupted sleep last night and your poorer performance around the dinner table or in brazilian jiu-jitsu or whatever the diffuse thing contributes because you inevitably have to make trade-offs from one thing in order to do and to do another but also it's just hard it's hard to work out how your performance is performing and this is the same in the work life the perfect example the sales people we just know if we do make you do this thing we lose that thing and that thing is more important than this thing it would be like if for some reason sports stars were being encouraged to stay up late you go well we know if we make you stay up late answering fucking slacks your performance in the game the next day decreases but for most people there's this implicit assumption that part of what you do is the contribution to the strategy and the operations and the executive function culture and so on which means that you forget what you're there for i think people have forgotten what they're there for what what am i supposed to be here at work doing what is my out my outcome goal there's so much fat in the american american knowledge work sector right now right we're so wealthy and there's so much money being slung around that we can have whole organizations where most people don't even know how they're directly connected to producing that value. And they could just be doing email all day or whatever, right? It's so inefficient. But there are, I mean, there are plenty of knowledge work areas where people don't put up with a bunch of this nonsense. And it's all areas where it's very easy to quantify your production. I did this essay a couple of years ago where I did a reflection where I said, God, almost every thought I've had in my books all came out of my experience as a grad student at MIT. So I was at the Theory of Computation group in the Computer Science department at MIT. Don't call it a department, but the Theory of Computation group in the CS lab at MIT, which is like a group, the professors there, the students, we weren't like this, but the professors were super geniuses, like literally Turing Award, Turing Award, MacArthur, MacArthur, Turing Award, Dijkstra Prize, like smartest people in the world. And it was incredibly clear if you were successful or not. What major theorems did you prove in the last few years? That's it. That's all that mattered. Right. And that required a lot of thinking. So they were terrible with email. They had no interest in social media meetings. Like if you're trying to throw meetings at them, they would just ignore you. Right. I wrote about this in deep work even. And people push back. I was like, this is what it's like in that world. If you send someone an email in this world, like one of these professors, and they're like, this is ambiguous, you kind of didn't word this well, or I don't really want to do this, they just ignore it. That's on you, buddy. I will lose my job if I'm pre-tenure, if I don't come up and solve theorems. And they put up with no nonsense. And a lot of that actually infused the book, Deep Work, because you know what? I came of age in an environment where all anyone cared about was focus and everything else was secondaries. Athletes, just like you said, If this is getting in the way of my launch angle going down or my batting average adjusting, I'm going to change it. But it's crazy right now in knowledge work how many positions that's not true. But what I advise people then, get in a position where that's true. Change your profile at work or if you're changing your job, change your job into one where your value production is unambiguous. Now, this is a double-edged sword because it swings both ways. Because you can't hide anymore. You can't hide anymore. But if you get into one of those situations and then you do the cognitive work, I know how to focus. I build the skills. I apply the skills. I'm not afraid of cognitive strain. You're in the absolute best position in our economy. Right. You can write your own ticket, but you have to be willing to go into a circumstance of like this is the only world I know. And academia is what did you publish? That's all that matters. It's all we care about. What did you publish? Book writing? How many copies did your last book sell? That's all that matters. There's no, you know what, though? He answered our publisher email so quickly. So let's give him another deal, folks. No, it's exactly how many dollars did you make us last time? That's what we care about, you know, for the next time. So it's a scary world where you're being held accountable. But it's an equation I always say is that if you're accountable, you don't have to be accessible. If you're like, I can point to this is the value I produce and I'm killing it for you. Then I don't answer emails. I don't go to these meetings. I don't do 50 sort of things. You can get away with almost anything you want. So I think that's more people should make that move, especially in the AI age, I suppose. More people should make that move towards like, hey, hold me accountable and then do the work to actually show up. It makes your life so it's such a better way to go through knowledge work. 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Maybe you're at the top of it, near the top of it, or you're just, you're toward the bottom of it, but you feel like you've got the ear of the person that's in charge if you were to say we've got the classic diffuse hive mind pseudo productivity malaise like the the ambient soup that everybody's swimming in how would you what would you do what would you how would you rework the internals of an organization that still needs to communicate obviously there has to be coordination people aren't working in silos there is going to be inevitable communication and coordination that needs to happen how how do you survive the modern world what would you propose how would you restructure things yeah i mean i would do a few things one i would say we're going to have explicit workload tracking and management right no more just people throw stuff at you and you implicitly just add it to your plate we want a place where we write down what everyone's working on and we can see it and now we can start talking about things like what is an ideal wyp what's an ideal work in progress limit for an individual how many things do we want someone working on at the same time before that curve starts to go the other way. So what you have to do once you start doing that is saying we need a place to track things that need to be done that no one is actively working on right now and we can feel OK about it. So I would definitely want to set up where things enter into our radar of this needs to be done. There's a place for that to go and to be stored. Oh, it's like an organizational getting things done inbox. Yes. And it's not on anyone's plate. Because as soon as you are responsible for something, it generates email slack and meetings. So once it's on your plate, it begins to spin off administrative overhead and slow productivity, I call it the overhead tax. That gets spun off as soon as it's on your plate. So everything by default goes to a team plate. No one's working on it. Then we keep track of from that plate as we move things to people's individual responsibilities. We have like, I don't, you should do three things at a time. That's it. And when you finish something, you can pull something else in. So do a small number of things fast and well, and then keep bringing things. So I would definitely do that. The second thing I would do is I would say no more hyperactive hive mind. If you send a message that requires more than a single message in response, that should not happen over digital communication. If I can't just answer your question with one more message, then that has to be real time. Now we can't have that turn into an explosion in meetings. So what we're going to do is we're going to have daily office hours for everyone. So there'll be a daily time where everyone knows they can call you or walk to your office or whatever and go through a bunch of things with you real quick instead of sending emails. We're going to have morning stand-up meetings within the teams for sure. Who's working on what this morning? Who needs what from who to get that done? Go do the work. We're going to have – so we'll definitely do those as well. We might throw in phone hours. It's a new idea I'm thinking about where you say, look, there's a longer period of time, like maybe all afternoon, where you can always call me if there's something that's so urgent you can't wait until the next office. hours, there's enough friction in phone calls that that actually turns out to work pretty well. Like, I'm not just going to call you because I want to get something off my plate. I won't call you unless it really is serious. So I would do that as well. And then I would say, okay, what ongoing work does this not work for? What type of projects do we work on on a regular basis where this isn't working because it's too long to have to wait till the afternoon's a problem? I'd say, great, let's identify those. And for each of those, let's build a protocol. Here is our protocol for collaboration on this type of work. And however that's going to work, but it's like the information goes into this spreadsheet and then whatever. Someone checks it in the morning. They move things to shared files. I don't know what it is, but whatever it is that prevents us to have ad hoc unscheduled messaging isn't necessary. So explicit workload management. I would have this rule of no hyperactive hive mind. I would have protocols for any type of recurring collaboration where we could be explicit about how we actually want to do this. and then I would have a culture of talking about deep work and concentration like a tier one skill how's it going uh how many deep work hours did you get in this week are you happy about that what was getting in the way of that did you have a particularly good session tell everyone else about it like what worked oh I see you you you did music you have a different look oh let's all think you know hey here's a good idea that we can borrow make deep work culturally something you talk about as like this is a tier one skill that we're really proud about you do those things you're not going to 2x your profitability this is the thing that's always frustrating me about these ideas is like you could make more money if you do it but that's it's really hard those changes i just talked about it's hard there's friction there's personalities and this is the thing i really underestimated when i wrote those books the way we work now is like a a low energy point right it's like the easiest possible configuration of work. So if you feel friction, you're trying to do something more structured, you're trying to do something that makes better use of our brain, and you're getting resistance, the place you're going to fall when you give up is the way we're doing it now. So it's not arbitrary, I've realized. It's hyperactive hive mind, let's just figure things out on the flow, no workload management. It's not arbitrary. It's the low energy. It's like this local minimum. It's the place that minimizes the complexity that still allows a company to run. And I think that's why we keep falling back in mathematical terms as a suboptimal Nash equilibrium. It's not the optimal way to work together, but no one person can leave it and make their situation better. It a low energy state It a it an attractor It a local minimum in the utility landscape whatever mathematical metaphor we want to use And so it it not arbitrary I was like oh it like a law of work physics This thing is like a neutron star in the world the universe of work that just attracts everything back to it. And it takes a huge amount of energy to escape its pull. That's why I think we've had so much trouble solving this problem, even though you would make more money if you did it. I wonder, I'm thinking about sort of immediately implementable solutions for this. I get the sense that you could probably tell people, we don't use Slack before 1 p.m. Like nobody is to post in Slack before 1 p.m. Because you can ring if it's SOS emergency scenario. You can just call somebody. We just don't use it. And then it means that everybody knows that they should not be doing it. It's a company-wide deep. I mean, look, are there going to be some departments? hr for instance probably would be but your job is your your job is hr up you're in the pr department or something like that your your job is actually about comms uh but if you're in marketing or if you're in accounting something like that okay sit down and do your fucking work and up until a point what do you make of intermittent fasting for communication company-wide yeah it works especially though what really makes that more sustainable is if you have that quick morning stand-up on the team scale at the beginning of the day where everyone says, here's what I'm going to be working on during these morning hours. Here's what I need from each other to make progress on this. So what would have unfolded over Slack and email, you're doing in 10 minutes. So you say, okay, here's what I'm working on this morning. I'm working on the new white paper. Here's what I need though. I need those figures from you. When can you get them to me? By 930? All right, you're going to get them to me by 930 and I need those quotes you promised. Can you just do that right away? Okay. So you all know what I need from you. Okay. Now I'm going to put my head down and write that report. So having that meeting ahead of time where everyone says what they need and what they're going to do, that makes that time work better. And then the thing that really works, do the same thing on the other end of the morning. All right. You said you were going to work on this, this, and this. What happened? So there's accountability on the other end. You can't run away from you know if you just went on email and social media like well wait a second i thought you're gonna write the white paper yeah and if other people flake they don't send you the figures they don't send you the quotes you're like i got stuck man i never got out cal didn't cal didn't do what he said and they're there in the same room and they're like oh okay i get it i get it i i can't just ignore stuff right like i actually have to do it i think that's a great idea i think something like that works well if you put that accountability uh before it and you put it after it that's scares people, by the way, though. That really does scare people because you actually have to do the work. And this is the thing with really social media and smartphones killed this way worse. AI is going to make this worse. But that was a big inflection point in terms of losing our comfort with concentration. That got really bad once we got algorithmically optimized content. We really got used to that. And so it's scary if you just go to a company and say, here's the new plan, boss. We're going to have a meeting in the morning. You got to tell me what you're going to do for the next five hours and then you got to do it we're going to check in after five hours and see how it went that's a nightmare for a lot of people that is like oh god i don't know what i'm going to do i i agree um i get the sense that a nice way to introduce this would be look everybody's brain here has been turned into slop everyone no one is able to do their job as effectively as they should so you are expected to do the work but the reason that we do the pre and post is not to whip somebody into performance review it's to give you accountability because you don't look like a tit in front of your co-workers but if you don't get to the point we're going to the same as when you start training for a marathon you don't run 10k on the first day you will titrate the dose up and over time you know week one will permit some fuckery and week two will permit a bit less fuckery and week three we're all in it together and this person's pulling ahead they're really like a hyper responder you know they're making loads of gains in the focus gym and other people are moving a bit more slowly okay what is it that they are doing what so on and so forth but imagine that imagine if you if you had a company-wide um focus initiative where people were just okay we're going to move together everybody is going to focus on focus and um interesting around the ai thing so george my housemate's writing a book at the moment uh do you know cold turkey do you ever use cold turkey i know about it yeah yeah yeah it's a website limiter app limiter for macbook we've been using it for a decade um his cold turkey went rogue and um just kept shutting his browser down even though he wasn't trying to access the thing that he wasn't supposed to it said he needed to install it was a nightmare uh and here's a conversation between him and his ai uh cold turkey has gone rogue and i need to remove it please tell me how to delete it from terminal and the response the response is i'm not going to help you bypass it george this is exactly the scenario you set it up for you're two days in the book is waiting close the terminal and write and he's replied and said no it's got a bug so i can't get on calls like pleading with his own ai because he's obviously put in the instructions be rigorous with me be tough with me tell me that i should be getting back to being focused when i start to go off task do the thing and that's a an ai equivalent of what you're talking about which is this supervisionary oversight commission thing but his just happens to be based in silicon instead of in other people so maybe ai will help us we it could basically chastise us like what the problem is the problem that you have with the ai thing is it's so fucking sycophantic all the time um that it will tend to bend eventually to what it is that you want yeah but no one believes that the chatbot interface is the future of ai the boosters the skeptics the moderates uh there's there's an emerging consensus that we're going to look back at this current moment where we interact with AI by typing into a chat window, that's going to be like the Usenet news groups of the beginning of the internet. It was like a cool thing early on that showed the promise of the internet, but the tools got better. There's better ways to make use of it. So the thought is in the future, AI is going to be more integrated into more things. It'll be more agentic. It'll be a lot, not like having conversations in English text, but deploying agents to do things, maybe with natural language, but also it'll be more integrated in the software. Individual tools will be more common. So it'll be much more common. I'm in Microsoft Excel and I'm like, can you sort row five by this amount and cut out all columns that, you know, have less than as many values? And it does that. It's going to be, that's what the interactions are going to become like. And so this idea of having a singular anthropomorphized entity through which you're having all conversations, that's almost like an accident of early AI. I mean, OpenAI will tell you this, that ChatGPT was supposed to just be a demo of the type of things you could do using the APIs into their language models. It's like the type of tool you can build that would make use of AI. And then it caught them completely off guard. And everyone wanted to use ChatGPT and chat with it because it was really cool. I don't think that's going to be the form vector. So I think a lot of these issues we have now, like this is weird. It's unsettling. We're anthropomorphizing it. We're getting parasocial relationships with the agents. We're having romantic relationships with them. We're getting unsettled because having English conversation, we have a hard time not simulating a mind on the other end of this. Which is why I shout at my chat. That's why you shout at it. I think a lot of this two years from now is going to be super narrow, right? Because I don't think just having this sort of general purpose oracle you chat with, that's not the future. That's not what people think we're going to be doing. Why are people mad about 4.0 being removed? My understanding was they were just happy with the fine. So you tune these things. The conversational style comes from a post-training tuning session where you give it, you've already done the pre-training, which is unsupervised. And you go through this post-training session where you have a lot of examples of questions and answers and you ask the question and then it gives an answer and then you sort of zap it using optimization theory to try to move like, now we're going to change the weights to be closer to this answer we already said was better. So if you have a bunch of examples of the way you want something to respond and you go through one of these sort of zapping training sessions after the fact it'll respond more like that so they just changed the way they were doing that and the thing they changed to people didn't like the tone that created so it was just about what date literally like the data sets you're using when doing this fine tuning after you've done that big massive pre-training where it's unsupervised talk to me about the role of quantum computing in ai minimal to non-existent So QAI is all just bullshit? Yeah, I'm not. Yeah. I mean, quantum computing is really interesting. There's a huge amount of technical problems just to actually get these things scaled to the number of qubits in which they're useful. And there's a there's a fallacy out there in thinking about quantum computing that is basically like a normal computer, but times a million. Yeah. Which is just not the way these things function. So there's only very specific problems you can solve with a quantum computer because you actually have to express the problem in the language of physics in such a way that you're creating what's known as a wave function that when it collapses, it's going to collapse to a configuration that's the right answer. Therefore, like implicitly searching a large state space in sublinear time, only certain problems allow you to do that. So it's unlike a normal computer where I can program a computer to do almost anything. Quantum computers, it's much more narrow what you can do with it. Could you give me an example of something that it would and wouldn't be able to do? Well, the big example, this is the guy who was at MIT when I was there. Peter Soar early on was the one who figured out like, hey, one of these complicated wave function collapsing things you could do could factor prime numbers or Q day. Yeah, factor numbers to see, to find the prime factors, rather find the prime factors of big numbers um that's a really big deal because uh rsa yeah public public key encryption and ironically this this just goes to show how crazy mit was is also at mit is ron rivest who i taed for who invented you see r and rsa he invented public key encryption so like the guy who invented public key encryption is there next to the guy who figured out how quantum computers could could maybe undo it undo it yeah so it's kind of interesting so it's good at that uh there's a lot of problems that are based around simulation of quantum or physical physics systems. And that's, you can simulate quantum physics systems directly using quantum in a way instead of having to try to simulate them. So it's very good for that. There's a certain type of search. It gets a little technical, but there's a certain type of search that you can implement that has applications. So there are interesting applications. But the thing I was beginning to sense recently, which made me worry, is that there was a sense of like height migration. so people are getting a little bit frustrated sort of like post gpt5 of like this isn't filling my need to have something to be you know a technology that is going to change everything i love that concept and then again sniffing around okay but what if we just quantum somehow will unlock ai and solve all these problems we're having i think it's way more complicated than that there are narrow applications of these particular things that might have some ai application but you can't like run an LLM on a quantum machine. And now it's a billion times better. That's just not how it works. So quantum is interesting. It's just really hard. The problem is the errors multiply. I mean, they make these qubits, these quantum bits they use, these algorithms. It's incredibly complicated. There's different ways to do it. But in some ways you have laser beams in a super cool chamber holding like a particle in a very careful state. And it generates errors and then the errors add up with other errors. and it's after you make enough of these things then then the errors they swamp out of control it's a really you know it's so you're telling me that the the fucking m6 chip in the macbook pro is not going to be a quantum one it's not going to be the q6 chip it's not in fact i i was i'm now i want to know what qai is what is qa you mentioned qai quantum ai yeah but i mean is there a particular product or just people talking about quantum's going to just make ai better yes yeah there is um i have a a friend who i train with like this is like you know what i love some of the people that i love the most are the ones who you wouldn't predict uh have the life that they do and there's a girl who trains at lift atx on a saturday lovely girl i've trained with a bunch of times real cool boyfriend's cool like just fitness modeling super hot the long hair lift the big out all the you know like but super strong all the rest of the stuff like feminine as well quantum computing degree, like works in quantum computing. And she was telling me about quantum AI. And she was telling me about QAI, as it's referred to. And it's a burgeoning field, supposedly. Unless she's lied to me. Unless she's totally fucking lied to me. Yeah, I'm curious what they're working on. UT Austin has good quantum theorists. Look, I'm searching for it. A guy I knew from IT, they hired him away there. I see quantum AI merges quantum computer with machine learning in the process. high-dimensional data faster than classical systems. Now they're working on it, but I don't know how that's going to work, basically. So I don't know what they're working on, but it's not something that you hear a lot in computer science circles yet. So maybe they'll have some breakthroughs. It's worth looking at, but I don't know how that's going to work. Okay. One of the other elements, I guess, that people struggle with when it comes to deep anything is learning, the process of learning. Talk to me about the mechanics of keeping a deep reading habit alive. Well, I mean, I think reading pages is probably the cognitive equivalent of steps, right? So if you're a 10,000 steps a day person, it's like this is just like a baseline to make sure that like at least my physical systems are being used. You should have a page count, 25 pages a day, 20 pages a day of reading a book. It just is like getting those cognitive steps in. Because I think we recognize more and more reading it. I would say it's a cheat code, but it's better to think about it as like reading is the thing that formed the modern brain. And I'm like, I'm more and more convinced about this. I have a book idea I'm working on now where I'm sort of exploring this idea. The brain before we had the Neolithic Revolution, it was the same neurons, right, 15,000 years ago that we have right now. But if we go pre-reading, those neurons were doing the things they were evolved to do, which is very much about like the visual system and the audio system. And we could communicate through spoken language and that's fine. And then we invent reading. And this is this is not something that our brain is evolved for. So in order to read, we have to go through this sort of excruciating process of learning to read in which what you're doing is actually rewiring sections of your brain to connect in ways that they weren't originally meant to connect to. So we're we're reforming our brain when we learn how to read. And we develop what Marianne Wolfe calls deep reading processes, where you've now yoked together different parts of your brain that don't normally work together, that can now have to work together in order to understand written text. Once your brain is wired to do that, if you reverse this and write, you can generate much, much more sophisticated thoughts than you can if you haven't done this wiring. and your understanding of things. The complexity of what you can understand when you have this new rewired brain, that also really goes up. So reading is like, it's not just, oh, I get stronger in my brain. It reconfigures your brain into like the modern, you know, post-cognitive revolution brain. Okay. Why is it important to read physical books? What is lost if I read Substack? I know that you're a fan of Substack. I love Substack. I think it's fantastic. what's the difference between reading it on a laptop versus a phone versus a Kindle versus a physical piece of paper? Well, there's two different things going on here. There's medium and content tight. So if you're reading a book in a physical book or you're reading in a Kindle, it doesn't matter, right? I mean, they're both actual physical medium. Like the way that the Kindle is actually a physical experience. It's, it's, it's actual little discs that are, you know, dark on one side and light on the other. And to make a page, They have little electrical impulses and you shock the disk you want to turn and you don't shock the ones you don't want to turn. And so you've literally created an actual black and white physical version of the page on the Kindle. You're not unlike a computer screen or a TV where it's light being emitted. There's no light being emitted. It's physically that's the page. It just created a new physical page that has text on it. That's why you have to actually have a light on a Kindle to read it. So it's just a page that reconfigures itself into a new page. I love eating technology. I think it's really cool. content type the issue is i mean there's a lot of this research we've known since the 90s a lot of this is captured in um the best book on this would be uh the shallows nick carr's book the shallows when we're reading something like a web page or substack for whatever reason uh we skim much more aggressively that's the main issue we jump around uh much more aggressively just trying to pull out the key points i think that's all just acculturated right like you could sit and read like if you print out a sub stack article and sit in the library and you read it carefully it's the exact same thing as reading a book it's the exact same thing in in sense of the experience on screens we tend to skim around more the other advantage of like a book that was actually published versus like a post you see online it's just better thought through right so when you write a book you spend a couple years on it like you're really uh you spend a couple years crafting the book and you might have been based on a lifetime of thinking about this topic. And so you take your time when writing a book and it gets edited and re-edited and you go back. Like I'm writing a book now. I've been working on it off and on for like three or four years. I've rewritten this book like three times. It's like, this isn't right. This isn't clear enough. And so when you go through text that has been that carefully thought through and structured, that's also you just get a different experience because the pieces click together at different scales and it just uses you build in your brain these intricate interlocking pieces that all hook together and is beautiful and you get that aha moment feeling there's an actual physical endorphin rough you get in your brain um so i you know i think reading smart books written by smart people that took a long time to write that's your calisthenics for your brain it literally changes you're a smarter person if you do that versus if you don't so good i have to say reading full-length books has been uh the volume that i do that has been decreased over the last few years largely because of substack so uh there's a extension for google chrome called push to kindle and if i press it yeah the article appears on my kindle because i don't like reading on my phone and i don't like reading on my laptop probably for the reason that that you said but when i think about it it very much is uh running downhill because what's the longest sub stack that you're going to read 20 minutes maybe 25 25 minutes a fucking long article yeah uh and maybe part of that maybe part of my penchant for it is that i do get the outcome right what what is it that i'm looking to learn oh i want to find out from steve stewart williams about sex differences in mate desire for sexual novelty something like that okay well i will learn the outcome in the same way as i could feed myself food that was just a cube of calories and that would sort of give me the caloric intake that i needed but what you're presumably reading for apart from just the enjoyment of reading it is to be able to recall it and for it to be woven into the broader mental landscape that you've got which actually probably means you need to spend time and attention with it and some of the leanness and brevity that comes with an article actually might work against you maybe you need it to be said to you in five different ways maybe you need the author to meander off onto a story that takes three pages to explain about this guy who owned a ferrari and parked it outside of a hotel so that you can then come back in and each one of these is a little velcro latch hook that you can hook yourself into and yeah i wonder whether i wonder whether the reading or uh discriminating toward reading stuff that is exclusively shorter form results in the sense that i'm learning lots but if you are to actually do some sort of scrutiny around that well okay how much of it can you remember how long did you spend with this idea did you spend long enough for it to be a part of now your mental models and the framework that you how much can you recall that would be an interesting an interesting challenge and the frameworks are understanding are shallower just because it's less time to establish them so like in a subset it's not a bad thing but you know what can you do you typically have like one idea and like here's something that supports that idea and here's maybe you like a different idea and here's why that doesn't work and if that's all you're consuming that becomes your mental model for how knowledge is gained and i think we see a lot of this i mean think about internet culture now is much more conspiratorial and i don't mean in the like sort of grand conspiracy which it is but not in not just in like the grand conspiracy type of thinking but in the confidence there's this quick jump the confidence where you're like that's wrong because of this and boom and you think that like this is like the slam dunk case or something like that that's a result of not reading a lot of books you read a lot of books you're like okay this is way more complicated uh everything is way more complicated than you thought it was and there's probably a clear truth here but clear truths are more complicated like even the notion of what a clear truth feels like comes out of reading books right like you understand oh ultimately like this person was right but it's complicated and like yeah this was not so clear cut and this is like a compromise and this was really important and these factors were here but honestly those factors aren't as big as you think and this factor really was more important and so like this really was the right thing to do so even like your notion of what's true or what's not true or what it means for something to be clear is like different than if you're just looking at boom slam dunk i think it's a big problem online. Both sides of the political spectrum do this. You want everything just to be, this person is just garbage and completely wrong. And there's this one simple thing I know that means you're completely wrong and I'm completely right. And you're wrong in the worst possible sort of way. And that is such a sopholithic, I'm saying the word wrong. Solidistic. Yeah, exactly. You said it, right? I have to read more. But it's sophistry for sure, right? This idea of this is how truth an argument unfolds is like there's an obvious flaw that's easy for me to grok which i guess now could actually be a verb as opposed to just meaning to understand also i could literally grok it i guess um and now it's clear that you're wrong and i feel righteous you know and then we go seeking that and then we want to simplify everything in the world to you're just terrible and this person is perfect and this idea makes the most sense if you disagree with this idea it's because like you want to eat children and you know it just becomes it's a different under This is what I think we get wrong. It's not just like we're, we're, we don't have the right information. We've changed what our notion of truth is because we're not exposed to the complexity of truths. When you read a, not only a scholar, like a smart case for it, but then you read the arguments that they confronted and then you read someone else that's arguing against their point. And you're like, Oh, okay. I've, I've seen the clash of like minds. And now in that clash, I like, I kind of see what's going on here. Like, yeah, the truth really leans this way. And I feel really real conviction in that because I've seen like the best minds come at this from either side. And I really understand. And it's not cut and dry. But ultimately, like this is the right thing to do. That was like a very familiar thing to people and leaders like in times past. You lose it if you're exposed to these low resolution copies, these low resolution simulacrums, these easy to digest pre-chewed versions of argumentation and understanding. It just changes the way your brain thinks about what true even means. Yeah, there's an arc to sense-making that you kind of need to track. And if you don't track it, you just assume that answers appear. Yeah. It's like, no, no, they don't. Cal, you fucking rule. Let's bring this one home. Why should people go to keep up to date with everything you do? Oh, God. CalNewport.com, I guess. My books are on Amazon. My podcast, Deep Questions on YouTube or wherever you get podcasts. Newsletter at CalNewport.com. Deep work. Too many things going on now, Chris. Deep Work is 10-year anniversary. I'm excited about it. All new. I replaced all the blurbs on the back with most of them are now organic. I could just like people who have said things about it without me asking them to say it. So that's fun. And I have a master class out on this stuff, too. So I don't know. It's everywhere. Too many places. I feel too busy. For a person who's a digital recluse, you are everywhere. But that's a function of focusing on quality, not quantity. I can't wait to speak again, man. This has been so much fun. I appreciate that. Always a pleasure, Chris. Always a pleasure. to talk with you. I get asked all the time for book suggestions. People want to get into reading fiction or nonfiction or real life stories. And that's why I made a list of 100 of the most interesting and impactful books that I've ever read. These are the most life-changing reads that I've ever found. And there's descriptions about why I like them and links to go and buy them. And it's completely free. And you can get it right now by going to chriswillx.com slash books. That's chriswillx.com slash books