A few notes from 2023 Chainalysis crypto geography report

It’s an emerging markets story aka “lower middle income countries”. For example defi:

Chainalysis Defi

India on par with UK! And Turkey dominates the Middle East

Chainalysis India Turkey

America is: More institutional capital; Stablecoins usage declining; Even in bear market, stables still lead, but alts beat ETH & BTC!

UK dominates in Western / Northern Europe

In Eastern Europe, it’s Russia, Ukraine, and Poland

Mainland China lags — but Hong Kong is promising

Chainalysis East Asia

“The promotion of Hong Kong as a potential crypto hub is not necessarily indicative of the Chinese government’s stance on crypto,” he told us. “However, we are seeing a number of Chinese state-backed entities indirectly supporting Hong Kong’s web3 ventures, and this could be viewed as an exploratory approach to understanding digital assets without loosening mainland policies.

India and SEA is all about centralized exchanges (CEX) — and look at gaming/gambling in Philippines and Vietnam

Chainalysis Asia

Saudi Arabia, Vietnam, Nigeria growing despite the bear market:

Chainalysis Growth

Here’s the The 2023 Geography of Cryptocurrency Report.

Great list of high signal qualities in founder types (unexpected opinions; niche content recommendations)

Source: https://twitter.com/george__mack/status/1726164596019359840

Some favorites:

4. You can never guess their opinions – The boxer that writes poetry. The advertiser obsessed with the history of war. The beauty queen who reads Nietzsche. If their beliefs don’t line up with their stereotypes, they’ve exercised agency.

6. They send you niche content – Low agency people look at the social engagement of content before deeming its quality. High agency people just look at the content. They spot upcoming trends very early.

The English language will increase its dominance in an AI world

Language is itself a technology, and like many technologies, it exhibits a classic network effect: each additional speaker of a language increases that language’s utility for all other speakers. The more “users” who speak and write English, the more valuable it is to know and use English in just about all affairs.

One obvious example is in software programming. Though there is a lot of symbolic and mathematical notation in programming languages, most would agree that English is head-and-shoulders more valuable to know (relative to the 2nd or 3rd most popular language) if you want to be a good programmer. It’s better for troubleshooting, for reading documentation, for scouring StackOverflow for copy-paste code, and now for getting ChatGPT or CoPilot to write code for you.

My belief is that as AI proliferates, English will only increase its lead. English is already in the lead with 1.4B speakers (though this number varies significantly depending on how you measure fluency), and Mandarin Chinese is second at 1.1B.

Why?

AI models need data. English comprises a majority of the available online training data. It helps that the largest economy in the world (the US) and the most populous country in the world (India, which depending on your reference, surpassed China’s population this year), are both English markets.

The largest content generating internet platforms — from Google to Facebook to Twitter to Wikipedia and on and on — are dominated by English speakers. An AI model’s output quality is directly correlated with the quantity of its training data, and there is simply more English data available than any other language, including Mandarin Chinese. Thus GPT4 and LLAMA and so forth are “smartest” in English.

There are multiple reasons why Mandarin Chinese lags behind, beyond just the fact that the breakthrough innovations in AI research and productization happened first in the US and UK. Among these reasons are the Great Firewall, the highly regulated and controlled nature of Chinese data, and China’s pervasive digital censorship (For example, there are more than 500 words alone that can’t be used on many Chinese UGC websites because they are perceived as unfavorable nicknames for President Xi Jinping)

Thus Chinese online training data lags English in both quantity and likely quality. There are also some reasons related to the languages themselves, where English is a more explicit language and Chinese more contextual.

English’s initial data lead is a self-reinforcing feedback loop — the more that people use English to interact with services like CharacterAI and ChatGPT, the more data the LLMs have to refine and improve (in English). Leaving other languages in the dust, especially long tail ones like Icelandic or Khmer.

As AI agents increasingly interact with each other, I’m guessing they will develop their own unique protocols for AI-to-AI communication. Not dissimilar to how computers communicate via highly structured network requests, only more complex and perhaps unique. AI will eventually create its own AI lingua franca. However, it’s also necessary that some human-readable component be built into this AI-ese (because at a minimum, developers will want to know where to debug and fix errors). English will likely be chosen for that AI-to-AI interface.

Of course, AI is an amazing and broad innovation that will benefit speakers of all languages. It will help to preserve and distribute rarer languages, and enable faster and better language-to-language education and translation. Whether you speak Vietnamese or Icelandic, there will be an AI model for you. I’m simply arguing that these secondary languages won’t be anywhere NEAR as good as the leading English models, and I would venture that even if English isn’t your first or even second language, you will probably still get better results using broken English to interact with ChatGPT than, say, French.

I could be very wrong here. As with any emerging technology, second and third order effects are by their nature unpredictable and chaotic. And the technology still has a long way to evolve and mature. Let’s see how it all plays out. I’m especially curious about what kinds of AI-to-AI communications will emerge, whether exposed through a human-readable interface or otherwise.

Ok that’s it, over and out good sers and madams! OpenAI wow!

The crypto bull is back: What are the unexpected catalysts waiting for us?

Most people who follow crypto would probably agree that we are either entering or already in the early innings of the next crypto bull cycle. Just as prior cycles took prices to all time highs over the span of 1-2 years — though with plenty of volatility — I expect much the same behavior this cycle, too.

Like prior cycles, this one seems to sync with Bitcoin’s 4-year halving. Like prior cycles, it also comes after a prolonged and painful bear market full of implosions, bankruptcies, scammers, government regs, and plenty of Twitter fights.

If you’re on Twitter, the dominant explanation for why the worm has turned is the anticipated approval of America’s first Bitcoin spot ETF, specifically Blackrock’s application.

There are other catalysts too such as:

-the anticipated Bitcoin halving cutting new bitcoin issuance from 6.25 per block to 3.125 per block in April next year

-A pause and potential reversal of the Fed’s rate hiking cycle (and stealth QE or as Michael Howell puts it, “quantitative support” 🙄)

-The conclusion of SBF’s (first) criminal trial and the steady forgetting of the FTX debacle (and the Luna debacle and the Celsius debacle and on)

-High and sustained global inflation causing fiat currency holders around the world to look for alternative stores of value

-The crash of US Treasury prices and the prospect of “higher for longer” interest rates causing fixed income investors to seek alternatives

I consider the above as “immediate” catalysts in the sense that if any of them were to occur in a sustained and significant way, it would probably lead to a significant and broad pump in crypto prices. Some of the above are already “priced in” to varying degrees. But not completely, and not to the degree that I anticipate they will materialize in 2024 and 2025.

In addition to the imminent catalysts, I find it interesting to speculate about potential knock on effects, the “unexpected catalysts” per the title, the second order effects that follow on from the first wave.

Just as the rise of Uber (initial catalyst) led to the downstream effects of (a) the decline of the regulated yellow cab industry, (b) the crash in NYC taxi medallion prices, and (c) the rise of on-demand apps for everything from scooters to house cleaners.

These unexpected catalyst and downstream effects are far less likely to happen, but when they do, they can generate enormous volatility in outcomes because they are almost by definition SURPRISES and thus NOT PRICED IN.

I believe the immediate catalysts — and more that I missed — will by themselves propel Bitcoin past its former all time high ($69K USD). You can expect the rest of crypto to catch up as well (just not your shitcoin).

But it’s those unexpected catalysts / un-priced-in effects that could push cryptocurrencies to significant new highs in 2024 and 2025. Though I don’t put much stock in price predictions, my starting assumption for price peak in this fast approaching cycle is $150K Bitcoin and $10K Ethereum, with Ethereum flippening Bitcoin (as I wrote about before) briefly, and that itself also being a second order effect.

So below are some very speculative potentially surprising ideas that could catalyze the late and crazy parts of the bull market:

Microstrategy causes corporations and corporate titans to fomo in
As Microstrategy’s Bitcoin bags explode in value (even at $36K Bitcoin, MSTR is already $1B in profit), leading to record corporate profits, a soaring stock price, and new levels of media notoriety for Michael Saylor, other small and medium tier companies — particularly those in adjacent industries from energy to tech to finance — will adopt a crypto reserve strategy. You could see billionaire tech titans like Masayoshi Son fomo in. Bitcoin will benefit most. Ethereum may surprise too

El Salvador causes nation states to fomo in
The same effect could happen to El Salvador, which becomes celebrated as a new beacon of financial sovereignty and emerging market wealth. President Bukele is feted by innovative politicians (I hope this is not an oxymoron) and small sovereign states, particularly in the Global South, and a race begins for nation states and central banks to buy Bitcoin and other blue chip cryptos. Investing heavily in bitcoin mining is also an indirect approach (eg, Oman, UAE, Bhutan). It’s possible G7 / developed states could also FOMO in, but I think this more likely in the next cycle (circa 2027-2028)

Bitcoin ETF’s success leads to a laundry list of other token ETFs
The Bitcoin spot ETF, after a slow launch, will steadily become Wall Street’s new darling, causing financial advisors and institutions to fomo in, leading to a slew of applications for other crypto ETFs starting with Ethereum. Though most applications could be rejected or at least delayed, this solidifies crypto’s position within tradfi, and tradfi is coming with their big accounts and clever financialization.

Ethereum becomes known as the deflationary currency and the Internet bond
As crypto usage rises (always correlated with bull markets), Ethereum becomes significantly deflationary (it already is, just more so), and along with its anticipated spot ETF approval, this is the cycle where Ethereum will birth its new reputation as (1) the “Internet bond” (first bearer digital asset with meaningful yield) and (2) the first deflationary asset to go alongside Bitcoin’s positioning as the first fixed-supply asset

Bitcoin beating gold becomes the next Schelling point
As Bitcoin easily passes $100K, everyone will turn their attention to what’s next, and what’s next is beating gold. Depending on the estimate you use, that easily puts Bitcoin around $400-500K, which I don’t expect to happen in this cycle… but it could. And it’s what people will talk about in the late bull. People need rallying points and gold has always been a big bullseye

Ethereum will flippen Bitcoin — just briefly
Just as Bitcoin’s main competitor is gold, Ethereum’s main competitor is Bitcoin. I support both and believe a rising tide lifts all boats. In the last bull, Ethereum peaked around 50% of Bitcoin’s value (market cap), and I expect that 50% will be far surpassed this cycle. As this happens, everyone will begin talking about Ethereum “flippening” Bitcoin, and the possibility is not priced in. Though I expect any market cap flippening to be short lived this cycle, but possibly a permanent fixture by the next. I wrote more about that prospect here.

Memecoin mania will return with a vengeance, and MSM will go crazy
I expect memecoin mania to return, despite less global liquidity and a high rates environment. And it will be larger and more degenerate, and no one will expect it. The first $100B memecoin. Maybe even a memecoin billionaire. The mainstream media’s shock and disgust will ironically pour fuel on flame. Elon’s never one to miss a press party, and he will finally launch his own token, somehow justifying the move by claiming synergy with Twitter/X and Grok AI.

That’s it for now. It’s a very incomplete list, but if even a couple of the above surprises were to happen, we could be in for a wild(er) ride. I’ll add more as I think of them or you can yell at me on Twitter.

You could argue there will be plenty of negative surprises and unforeseen headwinds, too, but that’s the thing about bull markets — no one really cares, and everyone just wants to greed while greeding is good. The bad news and the corruption and the new wave of scams will accumulate and build and then push us into the next bear in 2025-2026 :)

Squads as a social primitive: “The founding of a new group DM is year zero.”

Read it here: https://otherinter.net/research/squad-wealth/

Some favorite excerpts:

* Whether housemates or friends sharing a Discord group, squads allow social currency and financial capital to inter-convert, creating opportunities and group resiliency that would have been impossible to achieve alone.

* Group collaboration is now the strong default, putting squads at the center of social, cultural, and economic life. To paraphrase K-HOLE: today people are born as individuals, and have to find their squad.

* Younger generations are already imbued with extremely powerful squad energy, equipped with formative experiences in Minecraft, DOTA 2, and Fortnite parties.

* A greater network may surround the squad, making it appear big and fuzzy from the outside. But for the core crew, an invisible circle binds and protects a space of group identity.

* Squad space is where market-moving trades are planned, conspiracies are conceived, and memes are spawned. Members of the squad may live in different geographies—but within this space, everyone is on SQUAD TIME. The founding of a new group DM is year zero.

* The squad doesn’t need its own micro-currency—images, art, music, takes, shitposts, and, indeed, roasts are the native medium of exchange. […]. Instead, playful exchanges produce trust, reciprocity, and VIBES—the ineffable group energy that squads value most

* The group is the basic user class for the tools we need today as a society, yet few pieces of software allow the squad as a whole to produce cooperatively and generate wealth together. To fully realize SQUAD CULTURE this must change

* SQUAD WEALTH is a rate of 5 memes per day, it’s the e-girls vacation, the TikToker hype house, the empty church your crew rented upstate. SQUAD WEALTH is when the Discord is popping off and it brings you more joy than a 70-hour-week hustle ever could

* Squads = autonomy + community + equity
*