Raoul Pal: "$80k Is Just the Beginning! Many Bitcoiners Don't Know What's Coming" | New Prediction

Añadido: 2026-05-17

[00:00:00]AI is now generating more information than humans can process and crypto markets are starting to react to that overload in real time. Raul Pal describes a world where AI output is scaling vertically, creating an information overload problem that can only be solved by AI systems compressing noise into signal. At the same time, he points to improving global liquidity conditions with global M2 near all-time highs and financial conditions stabilizing again. A backdrop that has historically fueled strong expansions in risk assets even when sentiment is extremely negative. Tom Lee focuses on a deeper structural shift inside markets and infrastructure. He highlights Bitcoin's long-term outperformance versus inflation and gold, but argues the biggest story is institutional adoption of blockchain. Wall Street is moving toward tokenization. Stable coins are enabling ultra- lowcost global payments, and AI agents are beginning to rely on blockchain rails for microtransactions that traditional systems cannot support. Together, these forces point to a convergence of AI, liquidity, and blockchain that is quietly reshaping the entire market structure. In this video, we're going to break down what Raul Pal and Tom Lee are really signaling beneath the surface.

[00:01:15]We'll also unpack how AIdriven liquidity shifts and tokenization trends could impact Ethereum and the broader crypto market from here. And before we jump into it, just a quick reminder, only a small percentage of you watching are actually subscribed. If you're getting value from the videos, hit that subscribe button. It's free. It supports the channel and you can always change your mind later. Now, let's begin.

[00:01:39]Show the speed. The most ridiculous graph I've ever seen in all history is the graph that arc put out of there was two graphs. One was annual output of words by humans.

[00:01:52]How they estimated that not sure but really you know it accelerates when the Gutenberg press comes right then the computer and the internet and so it's this kind of steep curve and then there's AI annual output is just a vertical because it's three years old and it just does pure vertical and it's now creating more words than humans in a year. Then the other graph was all words ever created by humanitative humanitative humanity cumulatively and AI vertical and by 2028 it will have surpassed the entire corpus of human writing.

[00:02:35]So I mean that is [ __ ] staggering the speed of what this is happening what the world looks like. you know, the economic singularity idea I've had for a long time. It's looking like that's going to be dead right beyond 2030. We have no [ __ ] clue where any of this stuff's going to work. Um, but the other thing is it's going to create another set of problems which is already happening which is there's going to be too much.

[00:02:59]Somebody has the arc chart to show you.

[00:03:01]Yeah, show that arc chart just popping up in the chat. It's this. It's stupid.

[00:03:07]There's no chart in existence like this.

[00:03:12]And so what we're going to see is a complete overwhelm of information.

[00:03:23]>> There's no way we can deal with it. So we're going to have to compress all this information via AI into useful stuff. I mean, right now, everyone's building dashboards, but everybody's got like 30 of these [ __ ] things.

[00:03:35]>> So you're you're before you know it, there's going to be five billion dashboards in circulation. And that's of no use to anybody. So we have to compress that all down. So the next phase is getting AI to distill down from all of the information sources, all of these extra words and everything the things that matter the most. Like you're scraping X to try and find signal is what are the conversations that matter that are engaging that matters more than scrolling your X feed because in the end there's too much noise and not enough signal. So it's a really AI is really good at a compression engine and god we're going to need it because of what's happening.

[00:04:13]>> Raul Pal highlights a shift where artificial intelligence is now producing information at a pace that is starting to overwhelm human processing limits.

[00:04:22]The growth is no longer gradual. It is accelerating sharply with machine output expanding into levels that were not possible in previous cycles. That creates a structural problem for markets. Prices depend on information being absorbed and interpreted before it gets acted on. When the volume becomes too large, that process starts to break.

[00:04:42]Instead of clear signals, markets get fragmented reactions across competing narratives and fast-shifting sentiment.

[00:04:49]Raul Pal frames this as a shift from information scarcity to information overload. The challenge is no longer finding data, but filtering what actually matters. Most participants are left reacting late because they are processing in too many inputs at once without a clean signal. Crypto reacts faster in this kind of environment. It is more sensitive to flows, attention, and narrative rotation, which means it tends to reflect shifts in sentiment before traditional markets fully adjust.

[00:05:17]AI is not just another input into the system. It is accelerating the production of all inputs at the same time. that raises the speed of the entire market structure and increases noise across every asset class. The result is a market where interpretation lags movement and price becomes the fastest available reflection of what survives the noise.

[00:05:37]>> How are you feeling about the market these days, Ralph? you know, I you know, it's very difficult to explain to people when you've just had, you know, a big down market like this is I it doesn't none of these phase me because it's just part of the pattern that I've been used to since 2013. I don't think it's the end of the cycle. I think it's a midcycle correction. I know there's a raging debate about that, but when I look at the things that matter to me, I see global M2 all-time highs, global liquidity had a pullback because of the dollar. Now the dollar's weakening. It's looking like it's going to go back to all-time highs. Um, our financial conditions index corrected somewhat, but that's looking okay as well as the dollar and rates back off. Um, we're seeing the ISM going up. We're seeing US liquidity conditions um rising. It's like everything is green here in front of us. Um and that's a decent backdrop for the market considering the market's sentiment is literally some of the worst I've ever seen. We've had the longest period in history where the fear and greed index has been below 10.

[00:06:44]>> Um and even in the equity markets, which didn't really correct a lot, some stocks did. The equity markets have been massive kind of sentiment, negative sentiment, you know, record put buying, um, you know, record underweights, all sorts of weird stuff going on. So, the market was primed for something.

[00:07:05]Then, you know, the news out of Iran has helped the situation. It was something I thought was likely going to be the outcome and I still think the outcome may be more positive than people expect which is a a more broader longerterm resolution to the Iran situation where you know if you play out the game theory it's in everybody's interest to reach an agreement where Iran has no nukes they stop funding Hezbollah and stuff like that in exchange they get the removal of sanctions over time which means their economy can boom because Iranian economy is full of great business people and they've always been a big part of that region. It means that oil prices come down which is a win for everybody because everybody's using as much energy as possible to generate as much intelligence as possible right now in the AI wars. So, it's kind of a win-win.

[00:07:58]Saudi wants it, Israel wants it. Um the US wants it, Iran probably wants it. Um, but there was part of the Iranian regime that didn't and maybe that'll change.

[00:08:12]So, so I'm I'm pretty optimistic here over everything.

[00:08:18]Raul Pal focuses on the macro backdrop where liquidity conditions are starting to stabilize again after a period of tightening. Global money supply trends remain elevated compared to historical cycles and financial conditions have begun to ease at the margins. This matters because liquidity is one of the main drivers of crypto cycles even when sentiment is weak. At the same time, positioning across markets is extremely defensive. Fear readings have spent extended periods at deeply negative levels and risk exposure has been reduced across both crypto and equities.

[00:08:52]In past cycles, this kind of setup has often appeared closer to midcycle corrections rather than true structural breakdowns. The key tension is between weak sentiment and improving liquidity conditions. That mismatch is what creates volatility. Markets can stay heavy for longer than expected, but when liquidity stabilizes, price tends to move quickly because positioning is already light. Raul Pal frames this kind of environment as familiar across previous cycles. Liquidity expands in waves, sentiment collapses during corrections, and then markets repric sharply once conditions shift again. The timing is uncertain, but the structure tends to repeat. Crypto is highly sensitive to this dynamic because it sits at the far end of the risk curve.

[00:09:36]When liquidity improves even slightly, crypto often responds faster and more aggressively than traditional assets.

[00:09:43]What matters here is not just the correction itself, but the conditions building underneath it. And if you want to stay ahead of these signals and know exactly when the market's heating up or when it's giving you those rare buying windows, I break it down every day in the Crypto Nutshell, my free 5-minute daily crypto newsletter. It's built to give you quick, actionable insights so you can make smarter decisions without spending hours buried in charts or headlines. You'll get clear signals on when to buy, when to take profits, and the latest news that could move markets, all delivered straight to your inbox.

[00:10:18]Just click the first link in the description, enter your email, and you're in.

[00:10:22]>> I think Bitcoin uh now it's Bitcoin is 15 16 years in existence. Um and over any rolling period, uh Bitcoin has outperformed every asset class. Like as much as gold's done great, you know, um you've never lost money owning Bitcoin, holding it for three years. But here's another interesting stat. If you look at Bitcoin's relative performance to gold, I'm sorry, to inflation since 20 2009, it's outperformed inflation 97% of the time. So, it's actually stored your value better than inflation. Gold in that exact same period of time only beat inflation 52% of the time. So in other words, Bitcoin has hedged you better on inflation than gold, even though gold least last couple years has done great.

[00:11:21]Is Bitcoin important, more important today than before? One, people are worried because of quantum, and I think it's a true problem for Bitcoin, but it's not a problem for blockchain. um blockchain has proven itself to be uh actually a better solution and that's why we're seeing uh two really important trends really build on the blockchain. The first is Wall Street is tokenizing things. I mean it's not just Robin Hood like cutting edge companies, it's Black Rockck and the JP Morgans. They're building digital coins, tokenizing funds, uh, and actually arguably rebuilding their business on ledgers. I mean, look at ICE. I mean, ICE just made an investment into OKX, a crypto exchange. I mean, that's a huge deal.

[00:12:12]Um, and the second is AI because a AI agents, you know, and if people are building Claudebot, if you send that into the world to collect payments, the most secure way to do final finality on payments at the lowest cost with fractions of a penny. You can't do it with PayPal or banking systems. you know, they they only go two digits, but you might want to collect a microp payment of a millionth of a penny, but you do it a million times. Stable coins have six like tether and USDC, which is circles, they have 16 zeros. They can collect microp payments even for tax authorities. So, and then private keys, agent systems can easily deal with crypto wallets. So I I think AI is going to be building especially as it starts to do commerce a lot on the blockchain.

[00:13:05]And so I would be overweight any of the blockchain stories out there today which includes Ethereum, you know, Salana and others.

[00:13:18]Tom Lee focuses on long-term performance data that frames Bitcoin as a consistent outperformer across asset classes. over rolling multi-year periods, Bitcoin has outpaced equities, commodities, and gold. Even through multiple cycles of extreme volatility, the argument is not about short-term direction, but structural trend over time. A key point he emphasizes is Bitcoin's relationship to inflation. Across longtime frames, Bitcoin has historically preserved purchasing power more effectively than traditional inflation hedges like gold.

[00:13:50]that positions it less as a speculative asset and more as a longduration store of value in a debasing currency environment. The more important shift, however, is institutional behavior.

[00:14:01]Large financial players are no longer observing blockchain from the outside.

[00:14:05]They are actively building on it.

[00:14:06]Tokenization of financial instruments is moving from concept to implementation with funds, assets, and settlement layers being rebuilt on chain by major institutions. Stable coins also play into this structure. They enable near instant settlement and extremely lowcost transfers, which opens the door for new forms of digital commerce. This becomes even more relevant as artificial intelligence systems begin interacting economically at scale, requiring fast and automated payment rails. Crypto in this context is not just a trade. It is becoming infrastructure for both finance and machine-driven transactions. Bitcoin captures the macro store of value narrative. While networks like Ethereum sit closer to the settlement layer that supports programmable activity, the shift being described is not just price driven. It is structural adoption across the financial system.

[00:14:56]>> In some ways, there's already been a bare market cuz uh software has had a draw down and uh the the withdrawal of liquidity, you know, the amount of selling and then the short positioning is what you usually see at the height of a bare market. And we know the mag 7 actually has become untouchable for many people. And we know uh everything correlated to software like crypto uh has declined. So I think basically half the stock market has been in a bare market already. Um but the the reason I don't think this is the bare market is uh too many people have turned bearish.

[00:15:34]Um, so you know, I I I think markets like if you think about late 2021 and that and we missed that decline, that was a time when people were quite optimistic and the market was falling in the face of pretty good news until it turned really bad. And uh I think that that's more likely happening later this year because, you know, we do have things that can cause investors to flip from being optimistic to scared whether it's a new Fed. Uh we still have a lot of AI spending. There could be new doubts emerging. Um so I'm kind of in the camp that we're going to be resilient through this war headlines and and make our way to 7,300.

[00:16:18]Tom Lee challenges the idea that markets are in a clean bare market phase. The argument is that parts of equities and crypto already went through their draw downs earlier with heavy selling, weak positioning and extended pessimism already playing out across multiple segments of risk assets. What stands out is how defensive positioning has become.

[00:16:38]Exposure has been reduced. Sentiment is heavily negative and in many areas of the market, investors are already acting as if the worst has passed or is still ongoing. That kind of setup is not typical of early expansion phases, but also not always consistent with deep structural collapse either. The key distinction he makes is that liquidity has not fully disappeared. Instead, it has shifted and tightened in waves, creating uneven pressure across different sectors. That produces what looks like a bare market in some parts of the system, while others remain more stable underneath. Crypto tends to exaggerate that effect. It reacts more aggressively to liquidity shifts because it sits higher on the risk curve. When liquidity contracts, it falls faster.

[00:17:20]When liquidity stabilizes, it tends to rebound faster as well. Tom Lee frames this environment as closer to a reset phase within a larger cycle rather than a full breakdown. The important factor is that sentiment has already turned extremely negative, which historically often precedes reversals once macro conditions stabilize. What matters next is not the fear already priced in, but how quickly liquidity conditions shift.

[00:17:44]Again, Raul Pal and Tom Lee are describing different angles of the same shift. One is focused on the speed of information, the other on the structure of financial infrastructure, but both are pointing toward a system that is changing at its core. On one side, artificial intelligence is accelerating information production to the point where human interpretation is becoming the bottleneck. Markets are being flooded with signals, narratives, and data faster than they can be processed. That forces a move toward compression where AI systems themselves begin filtering what matters and what does not. On the other side, liquidity conditions are shifting again after a period of tightening while sentiment remains heavily negative. Historically, that kind of setup does not resolve quietly.

[00:18:31]It tends to lead to sharp repricing once conditions stabilize and positioning is too defensive to absorb new flows. At the same time, financial infrastructure is being rebuilt. Tokenization is moving into mainstream institutions. Stable coins are becoming global settlement layers and blockchain systems are being integrated into traditional finance rather than sitting outside of it.

[00:18:53]Tomley frames this as a structural adoption phase rather than a narrative cycle. When you put both views together, the overlap becomes clear. AI is increasing the speed and chaos of information while blockchain and crypto systems are evolving into the infrastructure that can handle machine-driven economic activity.

[00:19:11]Liquidity acts as the fuel that connects both. The result is not a simple market cycle. It is a convergence of AI, liquidity, and tokenized financial systems with crypto sitting directly in the center of that transition. Anyway guys, that's all we have for today.

[00:19:27]Thanks for watching and I'll see you all in the next