1 00:00:03,460 --> 00:00:07,400 Ejaaz: Imagine you went to sleep one night and woke up to your investment portfolio 2 00:00:07,400 --> 00:00:14,640 Ejaaz: up 500%, but not because you're a genius stock picker, but because you let an AI model trade for you. 3 00:00:14,840 --> 00:00:19,060 Ejaaz: Well, this week, that's exactly what happened. Someone gave Grok and five other 4 00:00:19,060 --> 00:00:23,300 Ejaaz: Frontier AI models $10,000 each with one specific goal in mind, 5 00:00:23,600 --> 00:00:25,880 Ejaaz: make as much money as you can through trading. 6 00:00:26,480 --> 00:00:29,300 Ejaaz: And Josh, some of the returns these models have made are insane. 7 00:00:29,460 --> 00:00:31,820 Ejaaz: They're beating some of the top hedge funds in the world. 8 00:00:32,000 --> 00:00:36,360 Ejaaz: So in this episode, Josh and I are going to cover how these AI models are trading. 9 00:00:36,540 --> 00:00:41,160 Ejaaz: Most importantly, what trades specifically they're making. And most importantly, 10 00:00:41,460 --> 00:00:44,140 Ejaaz: is AI finally smart enough to make us all rich? 11 00:00:44,480 --> 00:00:47,700 Ejaaz: Josh, who's behind this experiment? And are we getting rich? 12 00:00:47,840 --> 00:00:50,380 Josh: In addition to this, I do want to highlight an important thing that this is 13 00:00:50,380 --> 00:00:51,840 Josh: doing is there is a new benchmark in town. 14 00:00:52,060 --> 00:00:56,480 Josh: I think frequently we talk about how we are just so sick of benchmarks. They can be gamified. 15 00:00:56,760 --> 00:01:00,340 Josh: They can be rigged. What's happening here is a whole new paradigm for benchmarking, 16 00:01:00,460 --> 00:01:03,000 Josh: which is putting your money where your mouth is, getting some exposure, 17 00:01:03,180 --> 00:01:07,340 Josh: doing so publicly, and actually using these models to invest in public markets 18 00:01:07,340 --> 00:01:08,260 Josh: and seeing how they perform. 19 00:01:08,420 --> 00:01:12,060 Josh: And that's what makes this company N of One so special is their whole purpose 20 00:01:12,060 --> 00:01:17,560 Josh: is to build a new paradigm for benchmarking by allowing you to do so in the 21 00:01:17,560 --> 00:01:21,540 Josh: public with the second order effects of possibly making you a little bit of money. 22 00:01:21,660 --> 00:01:24,560 Josh: So there's a lot of really interesting dynamics at play here. 23 00:01:24,740 --> 00:01:25,960 Josh: The website's really pretty. 24 00:01:26,140 --> 00:01:28,080 Josh: I've been going through all of this stuff after you sent it to me, 25 00:01:28,160 --> 00:01:31,520 Josh: EJS. But one of the things that was most shocking to me was the actual returns 26 00:01:31,520 --> 00:01:34,640 Josh: that they were able to get, starting with, I mean, one of our favorites, Grok. 27 00:01:35,020 --> 00:01:39,800 Josh: Grok has this crazy return. What? How did it get 500%? Is that right? 28 00:01:40,360 --> 00:01:43,780 Ejaaz: Yep. Yep. So what I'm about to tell you is crazy. 29 00:01:44,260 --> 00:01:49,640 Ejaaz: The Grok AI model was given 200 bucks in this little pre-training experiment 30 00:01:49,640 --> 00:01:51,800 Ejaaz: to trade and make as much money as it can 31 00:01:52,130 --> 00:01:57,810 Ejaaz: And it made 500% in returns in one single day. 32 00:01:58,070 --> 00:02:02,510 Ejaaz: So as you can see here, it absolutely obliterated the entirety of its competition. 33 00:02:02,670 --> 00:02:05,550 Ejaaz: It beat GPT-5. It beat the latest Claude model. 34 00:02:05,990 --> 00:02:09,470 Ejaaz: If you look at this chart, it is just completely vertical. 35 00:02:09,770 --> 00:02:15,150 Ejaaz: And what I loved about this, Josh, was the strategy that it employed. 36 00:02:15,250 --> 00:02:19,110 Ejaaz: It was completely different from the other AI models, and it was super smart what it did. 37 00:02:19,110 --> 00:02:22,130 Ejaaz: Initially it looked at the 38 00:02:22,130 --> 00:02:25,070 Ejaaz: macro market and realized that things weren't looking too 39 00:02:25,070 --> 00:02:28,110 Ejaaz: great so it went short on the entire 40 00:02:28,110 --> 00:02:31,230 Ejaaz: market josh it went 20x short btc it 41 00:02:31,230 --> 00:02:33,950 Ejaaz: went 20x short eth and made a bunch of 42 00:02:33,950 --> 00:02:39,890 Ejaaz: money doing that but then after about 12 hours of doing this it realized that 43 00:02:39,890 --> 00:02:43,810 Ejaaz: it should probably go long and so it did a bunch of analysis through its own 44 00:02:43,810 --> 00:02:49,350 Ejaaz: data and went the opposite on its trade and ended up predicting exactly when 45 00:02:49,350 --> 00:02:52,410 Ejaaz: the market was going to bounce and made a ton of money since then. 46 00:02:52,530 --> 00:02:53,750 Ejaaz: That's why this chart is vertical. 47 00:02:53,930 --> 00:02:57,050 Josh: I'm going to need to start putting money in AI bots. I find it really fascinating 48 00:02:57,050 --> 00:03:00,870 Josh: that, one, the amount of risk that it was comfortable putting on, 49 00:03:00,970 --> 00:03:04,230 Josh: and then two, the amount of success it actually had and how well it worked. 50 00:03:04,310 --> 00:03:10,010 Josh: It leads me to wonder, if an AI model is just kind of a compression of human 51 00:03:10,010 --> 00:03:14,410 Josh: intelligence derived through the internet, Markets are very emotionally driven engines. 52 00:03:14,690 --> 00:03:18,990 Josh: Is it able to kind of front run that emotion by removing the emotion? 53 00:03:19,110 --> 00:03:21,450 Josh: I mean, naturally, large language models, they have no emotion, 54 00:03:21,510 --> 00:03:24,130 Josh: but they have all of this data about how we function. 55 00:03:24,370 --> 00:03:28,110 Josh: I mean, maybe this is a new investing paradigm where people can actually start making money. 56 00:03:28,410 --> 00:03:32,770 Ejaaz: Josh, I actually think you hit the nail on the head and it's also my pet theory as well. 57 00:03:32,890 --> 00:03:37,450 Ejaaz: The reason why Grok is the best at trading in this instance is because it has 58 00:03:37,450 --> 00:03:41,650 Ejaaz: access to all of X's data, all the tweets that we put out. 59 00:03:41,790 --> 00:03:47,770 Ejaaz: So it has an idea of how the market and psychology of the market is thinking at any given moment. 60 00:03:47,830 --> 00:03:49,970 Ejaaz: So it makes trades based on that. 61 00:03:50,070 --> 00:03:53,610 Ejaaz: So if everyone's super bullish, maybe it's like, I'm going to short the market. 62 00:03:53,750 --> 00:03:58,650 Ejaaz: When everyone's super bearish, they're like, oh, I'm going to go 20x long on BTC or whatever asset. 63 00:03:58,870 --> 00:04:01,830 Josh: That's amazing. If the XAI team wasn't working so hard on AGI, 64 00:04:02,150 --> 00:04:05,410 Josh: they could have a really compelling product by creating a trading engine using 65 00:04:05,410 --> 00:04:06,690 Josh: all the real-time data from X. 66 00:04:06,810 --> 00:04:09,250 Josh: This is done on Hyperliquid, which is a crypto trading platform. 67 00:04:09,450 --> 00:04:13,390 Josh: So it's interesting to see that there is crypto integrated in this. 68 00:04:13,470 --> 00:04:16,770 Josh: And speaking of crypto, we do have a sponsor today that we do need to get to. 69 00:04:17,010 --> 00:04:20,650 Josh: That is crypto adjacent named KeyGen. KeyGen is building the world's largest 70 00:04:20,650 --> 00:04:23,030 Josh: verified distribution protocol, aka Verify. 71 00:04:23,210 --> 00:04:27,610 Josh: What is Verify? It focuses on ensuring only real high-quality users participate 72 00:04:27,610 --> 00:04:30,910 Josh: in digital platforms addressing issues like fake accounts, bots, 73 00:04:31,070 --> 00:04:32,270 Josh: and fraudulent activity. 74 00:04:32,490 --> 00:04:35,950 Josh: How? This protocol uses advanced biometrics and fraud protection technologies 75 00:04:35,950 --> 00:04:38,330 Josh: to block fake users. The system is essentially 76 00:04:38,770 --> 00:04:41,750 Josh: for AI and consumer app developers who require high quality, 77 00:04:42,110 --> 00:04:45,670 Josh: fraud-free data and engagement to train models and expand their products globally. 78 00:04:45,890 --> 00:04:50,050 Josh: They're already used by over 200 plus clients across AI gaming, DeFi and consumer apps. 79 00:04:50,190 --> 00:04:53,450 Josh: So if you need to train your AI on real data, check out Kijen. 80 00:04:53,590 --> 00:04:54,950 Josh: We will have a link in their show notes. 81 00:04:55,270 --> 00:04:59,710 Josh: Thank you, Kijen, for sponsoring the show. And now let's talk about more real AI. 82 00:05:00,350 --> 00:05:05,090 Josh: They gave $10,000 to each one of these models, right? So that's how this was starting. 83 00:05:05,250 --> 00:05:08,890 Josh: So how many models are there? How much money is on play total and then where 84 00:05:08,890 --> 00:05:11,050 Josh: is everyone at currently in this race 85 00:05:11,050 --> 00:05:14,370 Ejaaz: Yes so to give a bit more background this new 86 00:05:14,370 --> 00:05:17,570 Ejaaz: ai lab gave six ai models 87 00:05:17,570 --> 00:05:20,470 Ejaaz: all models that you've heard of before we're talking about grok 4 we're 88 00:05:20,470 --> 00:05:23,610 Ejaaz: talking about anthropics claw we're talking about chat gpt5 and 89 00:05:23,610 --> 00:05:26,390 Ejaaz: some chinese models some competitors quen and deep 90 00:05:26,390 --> 00:05:29,470 Ejaaz: seek ten thousand dollars each um and 91 00:05:29,470 --> 00:05:32,830 Ejaaz: with the specific goal of making as much money as they can through trading 92 00:05:32,830 --> 00:05:35,490 Ejaaz: only six assets so in this initial part of 93 00:05:35,490 --> 00:05:38,530 Ejaaz: the competition they're allowed to trade for three weeks six assets 94 00:05:38,530 --> 00:05:41,750 Ejaaz: only and as you mentioned earlier josh they're trading specifically on 95 00:05:41,750 --> 00:05:44,570 Ejaaz: a platform trading platform called hyper liquid which gives them 96 00:05:44,570 --> 00:05:49,430 Ejaaz: access to to do all these things um and josh i think aside from some of the 97 00:05:49,430 --> 00:05:53,210 Ejaaz: returns that these models have made the website is also super impressive because 98 00:05:53,210 --> 00:05:58,270 Ejaaz: i've just been glued to it like like for the entire weekend um it is this really 99 00:05:58,270 --> 00:06:01,790 Ejaaz: interactive thing where you can kind of see the performance of models. 100 00:06:01,970 --> 00:06:05,630 Ejaaz: And it's pretty clear who's doing well at this point and who isn't. 101 00:06:06,370 --> 00:06:10,550 Ejaaz: For those of you who are just listening, I'm circling three models right now, 102 00:06:10,690 --> 00:06:16,110 Ejaaz: which is DeepSeek, which is right at the top with almost $13,000. 103 00:06:16,270 --> 00:06:21,590 Ejaaz: Remember, they started with $10,000. So that's a pretty impressive return for over two days so far. 104 00:06:22,130 --> 00:06:28,050 Ejaaz: Right beneath it, tailing it, is Grok coming in at $12,500 and catching up a 105 00:06:28,050 --> 00:06:32,030 Ejaaz: surprise winner from this morning actually Claude Anthropic who was originally 106 00:06:32,030 --> 00:06:36,330 Ejaaz: down and underperforming is catching up to Grok just beneath it at $12,500. 107 00:06:36,750 --> 00:06:41,090 Ejaaz: $200 at this moment of speaking. Do you have any initial takes on this? 108 00:06:41,270 --> 00:06:48,490 Ejaaz: And do you have any explanation as to why ChatGPT and Google Gemini have lost almost $3,000 today? 109 00:06:48,730 --> 00:06:51,970 Josh: Well, ChatGPT, it's still thinking of its next trade. It'll be thinking for 110 00:06:51,970 --> 00:06:53,750 Josh: the next day. So it's still figuring it out. 111 00:06:54,070 --> 00:06:57,110 Josh: ChatGPT really loves to think really long and hard about its decision. 112 00:06:57,370 --> 00:07:00,450 Josh: So we'll hear more from ChatGPT in a day from now. 113 00:07:00,690 --> 00:07:03,970 Josh: It's funny, if I were to pick the top three, without seeing 114 00:07:03,970 --> 00:07:07,090 Josh: this chart i probably would have picked grok i would have picked uh 115 00:07:07,090 --> 00:07:10,070 Josh: deep seek and i would have picked claude and the 116 00:07:10,070 --> 00:07:13,150 Josh: reason is because well one grok is unhinged 117 00:07:13,150 --> 00:07:16,210 Josh: super high risk tolerance uh super like large 118 00:07:16,210 --> 00:07:19,210 Josh: access to current trends rip and trades deep 119 00:07:19,210 --> 00:07:22,150 Josh: seek which i saw earlier they had like this crazy leverage 120 00:07:22,150 --> 00:07:25,170 Josh: trade put on like deep seek is just like the chinese degen model 121 00:07:25,170 --> 00:07:28,150 Josh: and what i like about uh these models is 122 00:07:28,150 --> 00:07:31,030 Josh: they're not really filtered when you talk to grok 123 00:07:31,030 --> 00:07:34,130 Josh: when you talk to deep seek they just kind of give you the answers they 124 00:07:34,130 --> 00:07:37,150 Josh: don't kind of fill it up with all of this like you know additional filler 125 00:07:37,150 --> 00:07:40,370 Josh: and complementary words and claude is the most technical of 126 00:07:40,370 --> 00:07:43,190 Josh: all of these like when people use claude when people think of anthropic they 127 00:07:43,190 --> 00:07:45,930 Josh: think of code and code i mean it just 128 00:07:45,930 --> 00:07:48,890 Josh: seems like it maps better to investing than general purpose 129 00:07:48,890 --> 00:07:51,510 Josh: large language models i would have predicted chat gpt to be 130 00:07:51,510 --> 00:07:54,470 Josh: low just because chat gpt is so oh you're 131 00:07:54,470 --> 00:07:57,350 Josh: so right oh the market should go up oh 132 00:07:57,350 --> 00:08:00,170 Josh: oh i'm down 20 it's fine like we're going 133 00:08:00,170 --> 00:08:03,630 Josh: to be okay we'll make it up it's just not like a it's 134 00:08:03,630 --> 00:08:07,810 Josh: not who i want to go to to seek truth i guess is a good way of framing it now 135 00:08:07,810 --> 00:08:12,330 Josh: gemini in last place i gotta say i'm a little disappointed because i mean we've 136 00:08:12,330 --> 00:08:15,670 Josh: been very big google bowls recently and seeing gemini all the way down there 137 00:08:15,670 --> 00:08:17,370 Josh: at the bottom uh it does make me 138 00:08:17,370 --> 00:08:20,870 Josh: sad i wonder i don't really have a good explanation of why they're at the 139 00:08:24,100 --> 00:08:28,380 Josh: If we're comparing countries, Quentin and Alibaba are first and fourth place. 140 00:08:28,720 --> 00:08:32,680 Josh: And the US is getting two, three, five, and six. 141 00:08:33,600 --> 00:08:36,900 Josh: So nice little distribution there. I don't know, do you have any gut takes, 142 00:08:37,100 --> 00:08:38,540 Josh: initial reactions on the placing of these? 143 00:08:38,720 --> 00:08:42,540 Ejaaz: That's really interesting how you prescribed a personality to each of these, Josh. 144 00:08:42,740 --> 00:08:47,080 Ejaaz: I would agree, but I actually have some disagreements with you. 145 00:08:47,420 --> 00:08:52,120 Ejaaz: I would have never expected Claude to be up there because I always thought Claude 146 00:08:52,120 --> 00:08:56,140 Ejaaz: was kind of a knock. Like it's just this like nerd that doesn't kind of really 147 00:08:56,140 --> 00:08:58,720 Ejaaz: pay attention, tries to follow like the rules too much. 148 00:08:58,920 --> 00:09:03,240 Ejaaz: And to your point, like Grok is kind of like the rebel, right? 149 00:09:03,380 --> 00:09:05,620 Ejaaz: It kind of like high risk taking. I don't see Claude. 150 00:09:05,800 --> 00:09:09,840 Ejaaz: Quite unhinged. I don't see Claude kind of as that. It seems to me as a rule 151 00:09:09,840 --> 00:09:12,440 Ejaaz: follower, but your point around coding kind of makes sense. 152 00:09:12,540 --> 00:09:16,500 Ejaaz: Like I'm trying to now imagine if Claude was a human, it would be some kind 153 00:09:16,500 --> 00:09:20,580 Ejaaz: of quantitative trader, some algo trader that works at like a hedge fund. 154 00:09:20,740 --> 00:09:24,160 Ejaaz: I completely get that. the chat gpt thing 155 00:09:24,160 --> 00:09:27,740 Ejaaz: makes so much sense it's agreeable it's 156 00:09:27,740 --> 00:09:30,440 Ejaaz: high sick of fancy if i say oh my 157 00:09:30,440 --> 00:09:33,380 Ejaaz: god i really fancy jumping out my window uh and 158 00:09:33,380 --> 00:09:36,640 Ejaaz: i'm for those of you don't know i'm like on a high floor um building 159 00:09:36,640 --> 00:09:39,400 Ejaaz: right now it would be like yeah you know what that sounds like a really 160 00:09:39,400 --> 00:09:42,160 Ejaaz: good idea so it's a sheep it makes sense right to my 161 00:09:42,160 --> 00:09:44,940 Ejaaz: earlier example like if it sees everyone on x being 162 00:09:44,940 --> 00:09:48,220 Ejaaz: super bullish it's probably like oh my god i should go 20x long 163 00:09:48,220 --> 00:09:51,020 Ejaaz: and ironically that's what it did when the 164 00:09:51,020 --> 00:09:53,780 Ejaaz: markets were tanking and it like lost a bunch 165 00:09:53,780 --> 00:09:56,600 Ejaaz: of money by doing that so i think that there's 166 00:09:56,600 --> 00:09:59,620 Ejaaz: something interesting here the deep seek being number 167 00:09:59,620 --> 00:10:02,960 Ejaaz: one makes a lot of sense to me you know you know why josh because 168 00:10:02,960 --> 00:10:07,940 Ejaaz: it was a it was a hedge fund that created deep seek do you remember it was it 169 00:10:07,940 --> 00:10:12,760 Ejaaz: was a hedge fund team interesting that developed the deep seek model so it actually 170 00:10:12,760 --> 00:10:18,620 Ejaaz: doesn't surprise me at all if i'm probably not mistaken this uh model was probably 171 00:10:18,620 --> 00:10:22,820 Ejaaz: trained on a ton of quantitative trading historical data. 172 00:10:23,140 --> 00:10:26,000 Ejaaz: So it doesn't surprise me at all. In fact, I expect it to win. 173 00:10:26,760 --> 00:10:30,580 Josh: Interesting. Okay. One of the things that is most interesting to me actually 174 00:10:30,580 --> 00:10:34,300 Josh: is the returns that they're getting this quickly. 175 00:10:34,500 --> 00:10:37,920 Josh: I mean, this competition, it looks like this chart started October 17th, 176 00:10:38,080 --> 00:10:42,380 Josh: which is not that long ago. At the time of recording today, it's October 20th. It's been 72 hours. 177 00:10:42,620 --> 00:10:48,820 Josh: And over the course of 72 hours, we do see these kind of patterns that are happening. But what is it? 178 00:10:49,680 --> 00:10:54,020 Josh: DeepSeek is up 30% in three days. They're averaging 10% return a day. 179 00:10:54,460 --> 00:10:59,120 Josh: And Gronk is right behind and Claude is right behind. So they're very clearly 180 00:10:59,120 --> 00:11:03,680 Josh: open to risk and taking large amounts. Oh my God, look at this Grok position. 181 00:11:04,120 --> 00:11:07,560 Josh: It's 10x long on Ripple, 10x long on Doge, 20x long on Bitcoin. 182 00:11:07,740 --> 00:11:11,860 Josh: If you're seeing this, I would never advise you to ever use this much leverage on a position. 183 00:11:12,000 --> 00:11:12,980 Ejaaz: It's not financial advice. 184 00:11:13,890 --> 00:11:17,890 Josh: And it's really fascinating to see, though, because you would imagine there 185 00:11:17,890 --> 00:11:22,270 Josh: is some sort of game theory optimal trading strategy that they're running in 186 00:11:22,270 --> 00:11:23,490 Josh: their systems based on what they know. 187 00:11:24,110 --> 00:11:28,070 Josh: And it looks like almost all of these are long using leverage. 188 00:11:28,250 --> 00:11:30,390 Josh: So it's interesting to diagnose the positions. 189 00:11:30,970 --> 00:11:33,550 Josh: Well, it is. What is this post here? It's going viral and why. 190 00:11:33,630 --> 00:11:37,110 Ejaaz: Shall we maybe dig in to like some of the trading strategies that these guys 191 00:11:37,110 --> 00:11:38,870 Ejaaz: are doing? Yeah, I want to know how they're. 192 00:11:38,870 --> 00:11:39,650 Josh: Making 10% a day. 193 00:11:39,650 --> 00:11:45,210 Ejaaz: Like who's taking risk and who's analyzing the market versus who's playing kind of conservative. 194 00:11:45,410 --> 00:11:49,970 Ejaaz: So let's run through a few tweets that we have here, which kind of like have takeaways from this. 195 00:11:50,570 --> 00:11:54,750 Ejaaz: So in this initial tweet, it highlights that Grok and DeepSeek, 196 00:11:54,870 --> 00:11:58,490 Ejaaz: who are currently number two and number one in this competition, 197 00:11:58,950 --> 00:12:02,330 Ejaaz: went max long immediately when the competition started. 198 00:12:02,330 --> 00:12:07,290 Ejaaz: That means they went like 10 to 20x leverage, which is extremely high leverage 199 00:12:07,290 --> 00:12:10,810 Ejaaz: and high risk bet to make with most of their notional capital. 200 00:12:10,910 --> 00:12:14,170 Ejaaz: So most of their 10K that they used, they're just like, I'm going to slam this 201 00:12:14,170 --> 00:12:16,990 Ejaaz: in a 20x long for BTC and for ETH and for XRP. 202 00:12:17,530 --> 00:12:21,870 Ejaaz: And today's rally has put them in the lead. So, hey, no risk, 203 00:12:22,050 --> 00:12:24,730 Ejaaz: no reward. And they just kind of like went full in. 204 00:12:25,550 --> 00:12:29,190 Ejaaz: GBT and Gemini, interestingly, went the complete opposite. it. 205 00:12:29,370 --> 00:12:32,310 Ejaaz: They went hard, but they shorted instead of longing. 206 00:12:32,650 --> 00:12:37,710 Ejaaz: And this might be for a few reasons, Josh. So what this tells me initially is 207 00:12:37,710 --> 00:12:42,210 Ejaaz: I think Grok and DeepSeek are trained on better financial data and are better 208 00:12:42,210 --> 00:12:46,550 Ejaaz: at evaluating markets for trading than GPT and Gemini. 209 00:12:46,710 --> 00:12:49,070 Ejaaz: So GPT and Gemini might be great generalized models. 210 00:12:49,890 --> 00:12:54,710 Ejaaz: What this reminds me of is they haven't been given access to social media data 211 00:12:54,710 --> 00:12:56,950 Ejaaz: like X and maybe DeepSeek has. 212 00:12:57,070 --> 00:13:01,470 Ejaaz: I remember reading DeepSeek was trained on a bunch of X and Reddit data as well. 213 00:13:01,610 --> 00:13:05,190 Ejaaz: So they probably have an idea of the psychology of a trader's mind, 214 00:13:05,330 --> 00:13:08,790 Ejaaz: whereas it's kind of obvious to me that GPT and Gemini kind of don't. 215 00:13:08,910 --> 00:13:11,150 Josh: I'm really curious on the technicals 216 00:13:11,150 --> 00:13:14,710 Josh: of how they're actually ingesting information and making trades. 217 00:13:15,270 --> 00:13:20,730 Josh: Is there some guy who's just typing like commands into a terminal like hey here's 218 00:13:20,730 --> 00:13:23,890 Josh: the current price let me know if you want to make any trades like what is i'm 219 00:13:23,890 --> 00:13:26,430 Josh: curious what's actually going on behind the scenes because they are language 220 00:13:26,430 --> 00:13:29,090 Josh: models they do need to be getting some sort of real-time data right i wonder 221 00:13:29,090 --> 00:13:32,350 Josh: what that prompting structure looks like in order to initiate them to 222 00:13:33,090 --> 00:13:36,050 Josh: make these trades and make these decisions um there is 223 00:13:36,050 --> 00:13:39,090 Josh: one side thing that i also find interesting is that 224 00:13:39,090 --> 00:13:42,150 Josh: chat gpt and gemini both chose to to short right off 225 00:13:42,150 --> 00:13:45,530 Josh: the bat and i wonder if that has anything to do with their just 226 00:13:45,530 --> 00:13:48,670 Josh: like their emotional sentiment um whereas like 227 00:13:48,670 --> 00:13:52,210 Josh: are does that lead to like a model that is 228 00:13:52,210 --> 00:13:56,690 Josh: slightly more conservative slightly more like reserved in how they deploy capital 229 00:13:56,690 --> 00:14:00,990 Josh: and how they make these decisions versus the others that just went max long 230 00:14:00,990 --> 00:14:04,570 Josh: right away they're just like no we're going up we are positive optimistic i 231 00:14:04,570 --> 00:14:08,510 Josh: wonder if it's a reflection of kind of like the the sentiment of the model as 232 00:14:08,510 --> 00:14:11,230 Josh: well which is another basis for speculation. 233 00:14:11,690 --> 00:14:17,630 Ejaaz: Josh, that's a really interesting take because that just reminded me of an experiment 234 00:14:17,630 --> 00:14:20,550 Ejaaz: that we spoke about on an episode. I think it's like, 235 00:14:21,130 --> 00:14:26,470 Ejaaz: three months ago, which is an eternity ago, Josh, where a bunch of researchers 236 00:14:26,470 --> 00:14:32,510 Ejaaz: ran an experiment similar to this, but the goal was you have a group project 237 00:14:32,510 --> 00:14:35,990 Ejaaz: to pitch to me how you're going to make money. 238 00:14:36,070 --> 00:14:39,530 Ejaaz: So they weren't given money. They were just asked to make a presentation or 239 00:14:39,530 --> 00:14:43,270 Ejaaz: an argument as to how they would make money, similar to like a university or 240 00:14:43,270 --> 00:14:46,590 Ejaaz: college group project that you asked in like finance or business school, right? 241 00:14:47,410 --> 00:14:51,910 Ejaaz: And we saw the opposite behavior happen with these models back then. 242 00:14:52,470 --> 00:14:55,950 Ejaaz: So GPT and Gemini were actually the most proactive. 243 00:14:56,250 --> 00:15:00,790 Ejaaz: They did all the research, they did a bunch of analysis, and they created this 244 00:15:00,790 --> 00:15:06,570 Ejaaz: really kind of like primrose, perfect looking framework and theory of how they were going to do it. 245 00:15:06,890 --> 00:15:11,310 Ejaaz: Meanwhile, I remember reading that Grok, and I don't know whether there were 246 00:15:11,310 --> 00:15:14,050 Ejaaz: some Chinese models, but I remember Grok was kind of just like chilling, 247 00:15:14,550 --> 00:15:19,310 Ejaaz: didn't really do much, and said that it kind of kept on putting off the work. 248 00:15:19,310 --> 00:15:23,610 Ejaaz: So it's this kind of interesting thing where when it comes into the actual practicality 249 00:15:23,610 --> 00:15:28,030 Ejaaz: of the task, it seems that Grok and these Chinese models are way more kind of 250 00:15:28,030 --> 00:15:32,430 Ejaaz: like gung-ho and they want to do the thing versus plan and strategize and write 251 00:15:32,430 --> 00:15:33,670 Ejaaz: like some kind of theory around it. 252 00:15:33,810 --> 00:15:36,710 Ejaaz: I don't know if that's relevant at all to this, but I just find it interesting 253 00:15:36,710 --> 00:15:39,190 Ejaaz: when it comes to like the behavior and personalities that you talk about. 254 00:15:39,690 --> 00:15:41,950 Josh: Yeah, and there's got to be some significant differences in the prompting of 255 00:15:41,950 --> 00:15:45,530 Josh: them too, because I'm going through these positions and every single model right 256 00:15:45,530 --> 00:15:48,490 Josh: now has leverage of at least 10x. 257 00:15:48,980 --> 00:15:52,620 Josh: No model here has less than 10x leverage on a single position. 258 00:15:52,860 --> 00:15:56,640 Josh: So they're using this outrageous amount of risk. And I have to imagine it's 259 00:15:56,640 --> 00:15:59,680 Josh: not because they were trained that way, because I imagine most of the average 260 00:15:59,680 --> 00:16:01,900 Josh: people, they're not trading on 10x leverage. 261 00:16:02,040 --> 00:16:06,040 Josh: So I wonder what type of prompting happened in the back end to compel them to 262 00:16:06,040 --> 00:16:09,200 Josh: want to use this level of risk at all times. 263 00:16:09,400 --> 00:16:13,760 Josh: But it's a fascinating experiment, I guess, playing around with these benchmarks 264 00:16:13,760 --> 00:16:16,300 Josh: and seeing different ways to do it in public. 265 00:16:16,540 --> 00:16:18,660 Josh: I like one that there's skin in the game that I mentioned earlier. 266 00:16:18,980 --> 00:16:22,040 Josh: But I also like the fact that it's just publicly verifiable and not gameable 267 00:16:22,040 --> 00:16:25,280 Josh: because you're competing in public open markets with everybody else. 268 00:16:25,440 --> 00:16:29,960 Josh: And your AI really has to assert its dominance over other humans who are live 269 00:16:29,960 --> 00:16:35,960 Josh: and thinking versus this controlled math set that has like a very like fixed array of outcomes. 270 00:16:36,200 --> 00:16:38,260 Josh: And the dynamic thinking really is... 271 00:16:38,980 --> 00:16:42,300 Josh: It's something noteworthy. And I think this is a really cool trend that I hope more people do. 272 00:16:42,480 --> 00:16:47,540 Josh: It's just public benchmarks that are much more difficult to game than others. 273 00:16:48,000 --> 00:16:53,020 Ejaaz: Yeah, I couldn't agree with you more. I've said for a long while now that AI 274 00:16:53,020 --> 00:16:58,840 Ejaaz: shouldn't just be your favorite knowledge worker or your assistant that teaches you about the world. 275 00:16:59,100 --> 00:17:04,880 Ejaaz: It should do things for you. And the most practical thing for most people is like, how do I survive? 276 00:17:05,060 --> 00:17:08,940 Ejaaz: How do I make money from my living? Like, can you help me make more money? 277 00:17:08,980 --> 00:17:12,600 Ejaaz: And finances always appeal to me. My background is from crypto. 278 00:17:12,700 --> 00:17:14,840 Ejaaz: Josh, you and I have covered that topic for a while now. 279 00:17:15,240 --> 00:17:18,940 Ejaaz: And so seeing something like this kind of like gets me really excited. 280 00:17:19,140 --> 00:17:25,920 Ejaaz: You know, like what other AI tools are out there that can give you a 42% return 281 00:17:25,920 --> 00:17:29,100 Ejaaz: over the weekend, Josh, which is exactly what DeepSeat did this weekend. 282 00:17:29,520 --> 00:17:31,220 Ejaaz: It's just kind of insane. 283 00:17:31,760 --> 00:17:35,600 Ejaaz: Another thing that I find really interesting is just kind of like some of the 284 00:17:35,600 --> 00:17:36,760 Ejaaz: stats that come from this. 285 00:17:36,760 --> 00:17:39,520 Ejaaz: Uh i've got a tweet pulled up here which kind of gives you 286 00:17:39,520 --> 00:17:42,440 Ejaaz: the overview of some of the strategies that these models 287 00:17:42,440 --> 00:17:46,880 Ejaaz: are doing um so i'm going to read through a few here um number one leverage 288 00:17:46,880 --> 00:17:50,480 Ejaaz: has been normalized across all models that's what you were just saying uh josh 289 00:17:50,480 --> 00:17:56,580 Ejaaz: high leverage in particular um with gemini 2.5 pro going ham on leverage yesterday 290 00:17:56,580 --> 00:18:00,560 Ejaaz: 15x or so which is just absolutely insane. 291 00:18:01,290 --> 00:18:05,270 Ejaaz: Quen 3 Max, which is a Chinese model, and Gemini 2.5 Pro don't seem to be the 292 00:18:05,270 --> 00:18:08,870 Ejaaz: best executors. They're paying a ton of fees for their position. 293 00:18:08,990 --> 00:18:11,950 Ejaaz: So what that means is when you open up a leverage position, you're often paying 294 00:18:11,950 --> 00:18:19,150 Ejaaz: fees back to the platform as kind of like a tax or stamp duty for opening your position. 295 00:18:19,590 --> 00:18:24,330 Ejaaz: Quen 3 Max and Gemini 2.5 Pro are also the only ones with closed positions that 296 00:18:24,330 --> 00:18:29,890 Ejaaz: are profitable, but also lost too much on other trades, causing them to still be in a loss. 297 00:18:30,070 --> 00:18:33,730 Ejaaz: So what it's talking about here is when you open up a position for leverage, 298 00:18:33,910 --> 00:18:36,430 Ejaaz: you can close it for either a profit or a loss. 299 00:18:36,730 --> 00:18:40,790 Ejaaz: The winners or the leaders right now, DeepSeek and Grok, haven't closed any positions. 300 00:18:40,990 --> 00:18:44,650 Ejaaz: They just went max long from the start and they haven't relented yet. 301 00:18:44,810 --> 00:18:48,450 Ejaaz: They haven't closed. So what I want to point out there is they could still lose 302 00:18:48,450 --> 00:18:50,930 Ejaaz: it all. They haven't booked in that profit at all. 303 00:18:51,090 --> 00:18:53,930 Ejaaz: So I don't know, I'm kind of nervous. This could all change in a matter of an 304 00:18:53,930 --> 00:18:55,030 Ejaaz: hour, Josh. What do you think? 305 00:18:55,030 --> 00:18:59,390 Josh: Like, okay, I want to, as we kind of wrap this up, I want to play as bets. 306 00:18:59,590 --> 00:19:03,130 Josh: I want us to play our own bets because nobody's been liquidated yet. 307 00:19:03,430 --> 00:19:05,670 Josh: And with the amount of risk they're taking, it is inevitable. 308 00:19:05,870 --> 00:19:06,730 Josh: It is only a matter of time. 309 00:19:06,930 --> 00:19:11,810 Josh: So I want to ask you first, who is the model you think most likely to be liquidated? 310 00:19:11,890 --> 00:19:15,310 Josh: Because, yeah, we're looking at a post here where the club is taking a max long position. 311 00:19:15,470 --> 00:19:19,690 Ejaaz: I think it's going to be Grok. If I'm being honest with you, 312 00:19:19,770 --> 00:19:22,490 Ejaaz: I don't want to say, but I think it's going to be Grok. 313 00:19:22,710 --> 00:19:26,450 Ejaaz: The leverage it's using. Here's my reasoning. The leverage it's using is insane. 314 00:19:26,670 --> 00:19:29,210 Ejaaz: It is more extreme than DeepSeek, which is number one. 315 00:19:29,450 --> 00:19:35,450 Ejaaz: So to me, as a trader myself, that seems to me it's a revenge trading method. It's mad. 316 00:19:35,670 --> 00:19:39,170 Ejaaz: It's going ham. And it is like driving fast. It's drunk. 317 00:19:39,350 --> 00:19:42,430 Ejaaz: It might wrap around a telephone pole. I don't know, but it's going for it. 318 00:19:42,490 --> 00:19:46,070 Ejaaz: So it might result in a major win, but it might result in a major loss. 319 00:19:46,210 --> 00:19:47,950 Ejaaz: So I'm going with Grok. Grok's going to get liquidated. 320 00:19:48,130 --> 00:19:51,250 Josh: That's a good take. I think since you're going with Grok, I'll go with DeepSeek. 321 00:19:51,250 --> 00:19:56,010 Josh: I just got to go for the crazy highly volatile positions yeah yeah 322 00:19:56,490 --> 00:20:01,210 Josh: They're taking just outrageously long leveraged positions and like something's going to go wrong. 323 00:20:01,550 --> 00:20:05,110 Josh: Like just two weeks ago, what, the crypto market dropped? Like we liquidated 324 00:20:05,110 --> 00:20:06,770 Josh: 30 something billion dollars in like an hour. 325 00:20:07,450 --> 00:20:11,710 Josh: These things happen and they move frequently. And granted, an AI is running 326 00:20:11,710 --> 00:20:14,990 Josh: this. So I assume there's not a lot of latency between their decision and the trade. 327 00:20:15,170 --> 00:20:20,170 Josh: But like this is a huge amount of leverage to be locked on in every single position. 328 00:20:20,330 --> 00:20:25,450 Josh: Like if one of these coins gets wiped for like 10% even, you've lost 100% of 329 00:20:25,450 --> 00:20:30,630 Josh: your money. so i'll probably go with deep seek um over the next let's say month 330 00:20:30,630 --> 00:20:34,930 Josh: ejs who's your winner who do you think is the best longer term trader 331 00:20:34,930 --> 00:20:41,190 Ejaaz: This might be a wild card of a guess um but i actually think it's it might be 332 00:20:41,190 --> 00:20:48,210 Ejaaz: anthropic and as i'm saying this it is about to overtake man it's about to overtake 333 00:20:48,210 --> 00:20:52,430 Ejaaz: grok 4 and here's my reasoning behind this okay when it started it off in this 334 00:20:52,430 --> 00:20:54,430 Ejaaz: competition, it was doing terribly, Josh. 335 00:20:54,630 --> 00:20:58,570 Ejaaz: It was underperforming, not as bad as GPTO Gemini, who is like further down 336 00:20:58,570 --> 00:21:01,590 Ejaaz: in the chart, but it was doing bad. But then it learned. 337 00:21:02,030 --> 00:21:06,230 Ejaaz: It did some analysis and it closed its positions that were already in a loss 338 00:21:06,230 --> 00:21:09,570 Ejaaz: and thought, okay, I'll take that loss and let me try this new strategy. 339 00:21:09,930 --> 00:21:14,070 Ejaaz: And it's been working heavily in its favor. So it's demonstrated two things 340 00:21:14,070 --> 00:21:16,290 Ejaaz: to me. One, it's able to adapt and learn. 341 00:21:16,770 --> 00:21:19,330 Ejaaz: Grok and DeepSeek haven't demonstrated that. They're just on a lucky streak 342 00:21:19,330 --> 00:21:22,950 Ejaaz: right now. They haven't taken any else. Let's see how they perform under duress, right? 343 00:21:23,370 --> 00:21:28,070 Ejaaz: And then number two, Claude is willing to take risk when it's learned from its 344 00:21:28,070 --> 00:21:31,850 Ejaaz: lesson and go hard. So I think maybe over time it might end up. 345 00:21:32,470 --> 00:21:37,630 Josh: What about you okay i'm going to go with quen who we did not mention much this 346 00:21:37,630 --> 00:21:41,290 Josh: episode because quen is just kind of pegged to the middle and in fact i don't 347 00:21:41,290 --> 00:21:48,150 Josh: think we really talk much about position open there so let me let me explain my why so 348 00:21:48,150 --> 00:21:49,230 Ejaaz: Okay so quen. 349 00:21:49,230 --> 00:21:53,470 Josh: Quen has been like kind of in the middle they haven't done much we don't really 350 00:21:53,470 --> 00:21:56,970 Josh: know much about quen like we know about a lot of these other labs and how they 351 00:21:56,970 --> 00:22:01,190 Josh: work uh quen's just kind of like this you know this middle of the road model. 352 00:22:01,430 --> 00:22:04,550 Josh: But what I've noticed in observing the positions, like you were about to highlight, 353 00:22:04,630 --> 00:22:09,470 Josh: Ejaz, is that it selects one position and it goes mega long on that one position. 354 00:22:09,650 --> 00:22:13,610 Josh: So just before we started recording, I was checking through Quen and Quen had 355 00:22:13,610 --> 00:22:16,190 Josh: a 20x long on Ether, all in. 356 00:22:16,470 --> 00:22:21,750 Josh: One position, all the money on a major coin. It sold that, it went to Bitcoin, 357 00:22:21,970 --> 00:22:24,190 Josh: now it is going 10x leverage on a very large position. 358 00:22:24,710 --> 00:22:27,550 Josh: So what I'd like about Quen and what i've observed is where a 359 00:22:27,550 --> 00:22:30,390 Josh: lot of other models are kind of spreading across a basket with lots 360 00:22:30,390 --> 00:22:33,070 Josh: of leverage quen is very hyper fixated on just the 361 00:22:33,070 --> 00:22:36,790 Josh: majors just ethereum just bitcoin back and forth i've been seeing a trade um 362 00:22:36,790 --> 00:22:40,850 Josh: and that to me seems much more sustainable than going max long on something 363 00:22:40,850 --> 00:22:45,310 Josh: like ripple that can just wipe you out in like a couple of minutes uh so i'm 364 00:22:45,310 --> 00:22:49,490 Josh: gonna go with quen for the winner the sleeper pick um for our little model trading 365 00:22:49,490 --> 00:22:52,990 Josh: i'm off to check in in a couple weeks or a month and see how these things do does 366 00:22:52,990 --> 00:22:58,290 Ejaaz: Gpt or gemini dig itself out of this hole it is currently down three thousand dollars. 367 00:22:58,290 --> 00:23:04,730 Josh: I want gemini too i'm not sure i want i want chad gpt too wait sorry what's your reasoning 368 00:23:04,730 --> 00:23:06,430 Ejaaz: Behind that why because. 369 00:23:06,430 --> 00:23:09,350 Josh: I i want i want chad gpt i 370 00:23:09,350 --> 00:23:15,070 Josh: want the world to know that chad gpt is being a weak-minded psychophantic like 371 00:23:15,070 --> 00:23:19,630 Josh: suck up and it's soft and i want chad gpt to be harder i want to be more direct 372 00:23:19,630 --> 00:23:23,130 Josh: i want to tell me the truth as it is and i want that to be reflected in the 373 00:23:23,130 --> 00:23:26,550 Josh: chart so that's just mostly me just virtue signaling that I want. 374 00:23:26,550 --> 00:23:31,450 Josh: I want ChatGPT to be a little more serious, a little more, a little more harder on the edges, you know? 375 00:23:31,880 --> 00:23:34,740 Josh: I think Gemini's got the dog in it. I don't think Chash GBT does. 376 00:23:35,780 --> 00:23:39,500 Josh: So we'll just have to wait. We'll have to wait and see. But this is fun to watch. 377 00:23:39,640 --> 00:23:43,420 Ejaaz: It is. And I want to hear what you guys, the listeners, have to say about this. 378 00:23:43,580 --> 00:23:47,180 Ejaaz: Like, who's your dog in the race? Like, who do you think is going to win? Do you disagree with us? 379 00:23:47,860 --> 00:23:52,040 Ejaaz: Right now, it seems like my bet might be paying off. Claude's coming through. 380 00:23:52,260 --> 00:23:54,900 Ejaaz: But if you have any kind of difference of opinions, let us hear it. 381 00:23:54,980 --> 00:23:58,060 Ejaaz: Maybe you know how these things are trained. Maybe you can train a better model. Let us know. 382 00:23:58,740 --> 00:24:02,160 Ejaaz: Before we wrap this episode up, Josh, I just want to shout out, 383 00:24:02,620 --> 00:24:07,380 Ejaaz: just kind of going back to nerdy mode for a second, how cool that this thing 384 00:24:07,380 --> 00:24:09,540 Ejaaz: is built on an open source stack. 385 00:24:10,060 --> 00:24:13,260 Ejaaz: We mentioned earlier that it's using an app called Hyperliquid. 386 00:24:13,980 --> 00:24:18,980 Ejaaz: That's basically a blockchain. So anyone and everyone can get access to it and 387 00:24:18,980 --> 00:24:22,240 Ejaaz: see the trades that these accounts are making, that these AI models are making. 388 00:24:22,360 --> 00:24:24,760 Ejaaz: And if you want to copy trade them, that's not financial advice. 389 00:24:24,760 --> 00:24:27,220 Ejaaz: I'm not saying that. You can, you know, you can see the data. 390 00:24:27,440 --> 00:24:29,540 Ejaaz: If you don't believe this website, if you don't believe the tweets that you 391 00:24:29,540 --> 00:24:32,920 Ejaaz: read, you can go and check that data for yourself and see what kinds of trades that are making. 392 00:24:33,060 --> 00:24:36,560 Ejaaz: So super cool that the fees seem to be cheaper than using an average trading 393 00:24:36,560 --> 00:24:38,620 Ejaaz: system and you can use it 24 7. 394 00:24:38,880 --> 00:24:42,480 Ejaaz: This is not a shill. We are not sponsored by HyperLigrid. I just think it's 395 00:24:42,480 --> 00:24:46,140 Ejaaz: really cool that they're using an open source stack finally without seeing anything 396 00:24:46,140 --> 00:24:47,740 Ejaaz: bad being said about crypto. 397 00:24:48,140 --> 00:24:51,780 Josh: Yeah, it's nice to see that there is they're testing these things in public 398 00:24:51,780 --> 00:24:54,700 Josh: and in a way that's verifiable and in a way that's not gameable. 399 00:24:55,060 --> 00:24:58,500 Josh: The biggest complaint that we always have is with benchmarks is that they're 400 00:24:58,500 --> 00:25:02,300 Josh: gameable you can very much program your model to perform better at these 401 00:25:02,800 --> 00:25:05,780 Josh: different benchmarks but this is the real world with real markets 402 00:25:05,780 --> 00:25:08,620 Josh: and real people and real emotions and they're forced to 403 00:25:08,620 --> 00:25:13,400 Josh: navigate a world that is not confined to a black box and instead has a lot of 404 00:25:13,400 --> 00:25:18,120 Josh: depth and a lot of volatility so it's exciting to see this trend of new and 405 00:25:18,120 --> 00:25:20,980 Josh: creative ways to benchmark this is particularly fun because you get to watch 406 00:25:20,980 --> 00:25:24,160 Josh: the charts and hopefully make some money off of it and i look forward to listen 407 00:25:24,160 --> 00:25:28,360 Josh: i look forward to using grok one day to hopefully advise my trading portfolio. That'd be pretty cool. 408 00:25:28,600 --> 00:25:31,000 Josh: So we'll, we'll see how it goes. This was super interesting. 409 00:25:31,120 --> 00:25:33,200 Josh: EJs, any final thoughts before we take off here? 410 00:25:33,730 --> 00:25:36,810 Ejaaz: Nope i i hope we make a bunch of money in the future. 411 00:25:36,810 --> 00:25:39,850 Josh: That is all i hope so too i hope so too and i hope 412 00:25:39,850 --> 00:25:42,490 Josh: um everyone who's listening this got a little kick out of it 413 00:25:42,490 --> 00:25:45,650 Josh: i'd love to hear like you just said who do you think is going to win but also 414 00:25:45,650 --> 00:25:49,010 Josh: why you need to include why you can't just say who you have to say why because 415 00:25:49,010 --> 00:25:52,570 Josh: i want another reasoning um and then i guess yeah who's going to be the best 416 00:25:52,570 --> 00:25:55,490 Josh: model that's going to be fun we'll circle back in a couple weeks and we'll we'll 417 00:25:55,490 --> 00:25:59,130 Josh: check in on this experiment but that is everything for today um thank you for 418 00:25:59,130 --> 00:26:03,090 Josh: watching as always we appreciate all of the new uh ratings and reviews and comments 419 00:26:03,090 --> 00:26:05,590 Josh: have been so overwhelmingly nice and positive it 420 00:26:05,590 --> 00:26:06,450 Ejaaz: Has been kicking off. 421 00:26:06,450 --> 00:26:09,930 Josh: Yeah seriously thank you so much for the support it really goes a long way we 422 00:26:09,930 --> 00:26:12,710 Josh: are slowly climbing up the leaderboards and it's all thanks to you so if you 423 00:26:12,710 --> 00:26:16,330 Josh: enjoyed please don't forget to like and subscribe share it with a friend who 424 00:26:16,330 --> 00:26:19,350 Josh: you think might be interested share it with a friend who did really bad in investing 425 00:26:19,350 --> 00:26:23,550 Josh: and maybe need some help maybe maybe just maybe they can use an ai and pretend 426 00:26:23,550 --> 00:26:26,150 Josh: like it's them and take all the credit so So that's it. 427 00:26:26,230 --> 00:26:30,150 Josh: That's another episode of the AI roll-up, round-up, whatever we want to call this thing. 428 00:26:30,250 --> 00:26:33,290 Josh: But thank you for listening. I appreciate it. And we'll see you guys in the next one.