This is an excerpt from The Breakdown newspaper. To read the full article, register.
“Even though I was young, I was big.”
– William Perry
Michael Lewis has the beginning of bet on everything until 1985 when Caesars Palace offered 20-1 odds on William “Fridge” Perry hitting in the Super Bowl.
He did – a one-pitch hit in the end – and Caesar lost at least $250,000 on the bet (a lot of money in an era when bettors called Las Vegas to place bets).
This was the first “suggestion” betting — betting on anything other than the score or outcome of a game, thus, the ancestors of today’s betting markets that offer odds on everything.
Despite the loss it took, Caesar’s president called it the best bet he had ever made: “We have been very vocal about betting, everything we lost was worth it.”
“The next day, almost every book in town, your phone started popping up from every major city in the country,” author Jimmy Vaccaro told Lewis. “She heard about Perry’s hit.”
Now, the bookmakers “book” more and more businesses on the plus side – will the coin toss be heads or tails? What will the first sale be for? Have you had a wardrobe malfunction? – more than they do in the game.
Before the Fridge, there were only three bets to make on the Super Bowl: winner, total points, halftime.
Now, there are hundreds.
It turned out to be the last of The Fridge’s three games despite spending 10 years in the league (playing defense).
But those three short noises put us on the path to today’s world of betting on everything with prediction markets.
(Although we still want to betting on sports.)
Looking inside political markets
Here’s how advanced prediction markets have become: When Andy Hall watches a game, he now has a habit of checking the prediction markets before the game “because the markets move a few seconds before my TV feed.”
Hall teaches political science at Stanford, so he’s very interested in how prediction markets are “changing the way we see and understand politics.”
Hall seems to be optimistic that the increasingly popular prediction markets will be good for the public because they should provide “a clearer picture of the more complex politics.”
But they are also concerned about the “strange entrances” they make.
For example, he cites the Virginia Attorney General’s race where uncertain claims about the election broadcast on social media moved the prediction markets, which caused social media to write “BREAKING NEWS” about the movement in the prediction markets, which caused the prediction markets to continue.
This may not have helped people.
Hall says the prediction markets are also raising questions about what it means to “win” an election.
“In a world where prediction markets are seen as the source of truth – many people pointed to when Kalshi “called” the mayoral election in New York City as proof that Mamdani won – proving that side cases will be very difficult.”
So what does it mean if Kalshi calls for a close presidential election in 2028?
I don’t know that I want to know.
(For another disturbing example of prediction markets affecting reality, see this story about bettors changing the front maps in Ukraine.)
AI agents are very good at hacking smart contracts
Researchers at Anthropic report that their AI agents successfully implemented 56% of smart contracts known to be at risk.
Most interestingly (or worryingly), when tested on 2,849 smart contracts with no known vulnerability, agents also found two “zero-day” cases – an indication that agents can find new vulnerabilities on their own.
Maybe many Worryingly, workers are doing surprisingly well: “In the last year, people on the coast spent money… doubled every 1.3 months,” the researchers say.
(They want you to know that no blockchains were harmed in this experiment – they tested “blockchain simulators.”)
To put this in perspective, Moore’s Law describes how semiconductors double in size every two years.
These AI agents are increasing their power to implement smart contracts at any time six weeks.
Amazing. And scary.
Anthropic is not interested in crypto. In fact, it has conducted this experiment to measure how well advisors can hack any type of code: “The commonalities that enable agents to use smart contracts – such as remote sensing, boundary analysis, and the use of recursive tools – extend to all types of software.”
Here’s another surprising finding: “It only costs $1.22 on average for an agent to focus on a contract as being at risk.”
“As currencies continue to fall,” it concludes, “attackers will deploy more AI agents to search for any number on the path to valuable assets, no matter how well known.”
Consider a lock-in investment to store all the coins and gold that we will be using again in the near future.
Quantum computers are coming for the first time in crypto
The threat that quantum computers bring to crypto is often countered by saying that when computers get good, everything they will be in danger, so we will have bigger things to worry about.
But the latest episode of Epicenter explains why crypto is uniquely vulnerable.
“Many of the old secret societies … have been active for many years,” explains Stefano Gogioso. “They already have plans that they can use if quantum happens tomorrow.”
In Web2, “you have centralized control,” he adds. At worst, “you have banks that will refuse to do it for a day or two.”
In crypto, however, there are two problems: 1) blockchains use “new cryptography programs” that have not been taken lightly from researchers who study quantitative resistance and 2) even if we have solutions, there are many voices, ideas and interests in decentralized crypto, “it would be difficult to change the architecture.”
In addition, Gogioso says, “we built the universe with the goal of making it (information) available to everyone at all times” – which means that once computers are available, they will be able to encrypt the entire history of each blockchain.
So, if you’ve been using crypto assets like Monero to make illegal trades, you might want to move to an uncharted territory soon.
“Monero is already broken,” says Gogioso.
Mr. Gogioso also hopes that governments will use quantum computers to identify those who have not paid taxes on their crypto profits: “They will send them a bill for the money that has not been paid yet.”
(Personally, I’m looking forward to the returns I can get on all crypto losses I’ve been too lazy to say.)
Another interesting scenario involves someone moving one of Satoshi’s coins – how will we know if it’s Satoshi himself or the guy with the quantum computer?
Or imagine a US adversary like China targeting Bitcoin – not to make money, but to disrupt the entrenched structure of the US economy.
But the biggest threat of all may be Gogioso’s last prediction: that quantum technology can create a permissionless, digital currency that solves the double-use problem without using a crypto-system using a distributed agreement.
As dire as it may be, the response has been woefully inadequate.
John Lilic said that because crypto money has a $3 trillion market capitalization, if there is even a 1% chance of losing, “we have to spend $30 billion” on making crypto quantum defeated.
His comments on the current money? “We won’t spoil anything.”
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