Jesse Honigberg

504 posts

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Jesse Honigberg

Jesse Honigberg

@jessedh

living the dream(ish)

Nyack, NY Katılım Mayıs 2008
204 Takip Edilen121 Takipçiler
Jesse Honigberg
Jesse Honigberg@jessedh·
@VitalikButerin - I know it’s a longshot that you’ll see this but I’ve been thinking about this problem but from the Asset pricing side versus the liability side (if you are a bank, they are inverted). Prediction markets would actually be a great to price granular lending risk
vitalik.eth@VitalikButerin

Recently I have been starting to worry about the state of prediction markets, in their current form. They have achieved a certain level of success: market volume is high enough to make meaningful bets and have a full-time job as a trader, and they often prove useful as a supplement to other forms of news media. But also, they seem to be over-converging to an unhealthy product market fit: embracing short-term cryptocurrency price bets, sports betting, and other similar things that have dopamine value but not any kind of long-term fulfillment or societal information value. My guess is that teams feel motivated to capitulate to these things because they bring in large revenue during a bear market where people are desperate - an understandable motive, but one that leads to corposlop. I have been thinking about how we can help get prediction markets out of this rut. My current view is that we should try harder to push them into a totally different use case: hedging, in a very generalized sense (TLDR: we're gonna replace fiat currency) Prediction markets have two types of actors: (i) "smart traders" who provide information to the market, and earn money, and necessarily (ii) some kind of actor who loses money. But who would be willing to lose money and keep coming back? There are basically three answers to this question: 1. "Naive traders": people with dumb opinions who bet on totally wrong things 2. "Info buyers": people who set up money-losing automated market makers, to motivate people to trade on markets to help the info buyer learn information they do not know. 3. "Hedgers": people who are -EV in a linear sense, but who use the market as insurance, reducing their risk. (1) is where we are today. IMO there is nothing fundamentally morally wrong with taking money from people with dumb opinions. But there still is something fundamentally "cursed" about relying on this too much. It gives the platform the incentive to seek out traders with dumb opinions, and create a public brand and community that encourages dumb opinions to get more people to come in. This is the slide to corposlop. (2) has always been the idealistic hope of people like Robin Hanson. However, info buying has a public goods problem: you pay for the info, but everyone in the world gets it, including those who don't pay. There are limited cases where it makes sense for one org to pay (esp. decision markets), but even there, it seems likely that the market volumes achieved with that strategy will not be too high. This gets us to (3). Suppose that you have shares in a biotech company. It's public knowledge that the Purple Party is better for biotech than the Yellow Party. So if you buy a prediction market share betting that the Yellow Party will win the next election, on average, you are reducing your risk. Mathematical example: suppose that if Purple wins, the share price will be a dice roll between [80...120], and if Yellow wins, it's between [60...100]. If you make a size $10 bet that Yellow will win, your earnings become equivalent to a dice roll between [70...110] in both cases. Taking a logarithmic model of utility, this risk reduction is worth $0.58. Now, let's get to a more fascinating example. What do people who want stablecoins ultimately want? They want price stability. They have some future expenses in mind, and they want a guarantee that will be able to pay those expenses. But if crypto grows on top of USD-backed stablecoins, crypto is ultimately not truly decentralized. Furthermore, different people have different types of expenses. There has been lots of thinking about making an "ideal stablecoin" that is based on some decentralized global price index, but what if the real solution is to go a step further, and get rid of the concept of currency altogether? Here's the idea. You have price indices on all major categories of goods and services that people buy (treating physical goods/services in different regions as different categories), and prediction markets on each category. Each user (individual or business) has a local LLM that understands that user's expenses, and offers the user a personalized basket of prediction market shares, representing "N days of that user's expected future expenses". Now, we do not need fiat currency at all! People can hold stocks, ETH, or whatever else to grow wealth, and personalized prediction market shares when they want stability. Both of these examples require prediction markets denominated in an asset people want to hold, whether interest-bearing fiat, wrapped stocks, or ETH. Non-interest-bearing fiat has too-high opportunity cost, that overwhelms the hedging value. But if we can make it work, it's much more sustainable than the status quo, because both sides of the equation are likely to be long-term happy with the product that they are buying, and very large volumes of sophisticated capital will be willing to participate. Build the next generation of finance, not corposlop.

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vitalik.eth
vitalik.eth@VitalikButerin·
Recently I have been starting to worry about the state of prediction markets, in their current form. They have achieved a certain level of success: market volume is high enough to make meaningful bets and have a full-time job as a trader, and they often prove useful as a supplement to other forms of news media. But also, they seem to be over-converging to an unhealthy product market fit: embracing short-term cryptocurrency price bets, sports betting, and other similar things that have dopamine value but not any kind of long-term fulfillment or societal information value. My guess is that teams feel motivated to capitulate to these things because they bring in large revenue during a bear market where people are desperate - an understandable motive, but one that leads to corposlop. I have been thinking about how we can help get prediction markets out of this rut. My current view is that we should try harder to push them into a totally different use case: hedging, in a very generalized sense (TLDR: we're gonna replace fiat currency) Prediction markets have two types of actors: (i) "smart traders" who provide information to the market, and earn money, and necessarily (ii) some kind of actor who loses money. But who would be willing to lose money and keep coming back? There are basically three answers to this question: 1. "Naive traders": people with dumb opinions who bet on totally wrong things 2. "Info buyers": people who set up money-losing automated market makers, to motivate people to trade on markets to help the info buyer learn information they do not know. 3. "Hedgers": people who are -EV in a linear sense, but who use the market as insurance, reducing their risk. (1) is where we are today. IMO there is nothing fundamentally morally wrong with taking money from people with dumb opinions. But there still is something fundamentally "cursed" about relying on this too much. It gives the platform the incentive to seek out traders with dumb opinions, and create a public brand and community that encourages dumb opinions to get more people to come in. This is the slide to corposlop. (2) has always been the idealistic hope of people like Robin Hanson. However, info buying has a public goods problem: you pay for the info, but everyone in the world gets it, including those who don't pay. There are limited cases where it makes sense for one org to pay (esp. decision markets), but even there, it seems likely that the market volumes achieved with that strategy will not be too high. This gets us to (3). Suppose that you have shares in a biotech company. It's public knowledge that the Purple Party is better for biotech than the Yellow Party. So if you buy a prediction market share betting that the Yellow Party will win the next election, on average, you are reducing your risk. Mathematical example: suppose that if Purple wins, the share price will be a dice roll between [80...120], and if Yellow wins, it's between [60...100]. If you make a size $10 bet that Yellow will win, your earnings become equivalent to a dice roll between [70...110] in both cases. Taking a logarithmic model of utility, this risk reduction is worth $0.58. Now, let's get to a more fascinating example. What do people who want stablecoins ultimately want? They want price stability. They have some future expenses in mind, and they want a guarantee that will be able to pay those expenses. But if crypto grows on top of USD-backed stablecoins, crypto is ultimately not truly decentralized. Furthermore, different people have different types of expenses. There has been lots of thinking about making an "ideal stablecoin" that is based on some decentralized global price index, but what if the real solution is to go a step further, and get rid of the concept of currency altogether? Here's the idea. You have price indices on all major categories of goods and services that people buy (treating physical goods/services in different regions as different categories), and prediction markets on each category. Each user (individual or business) has a local LLM that understands that user's expenses, and offers the user a personalized basket of prediction market shares, representing "N days of that user's expected future expenses". Now, we do not need fiat currency at all! People can hold stocks, ETH, or whatever else to grow wealth, and personalized prediction market shares when they want stability. Both of these examples require prediction markets denominated in an asset people want to hold, whether interest-bearing fiat, wrapped stocks, or ETH. Non-interest-bearing fiat has too-high opportunity cost, that overwhelms the hedging value. But if we can make it work, it's much more sustainable than the status quo, because both sides of the equation are likely to be long-term happy with the product that they are buying, and very large volumes of sophisticated capital will be willing to participate. Build the next generation of finance, not corposlop.
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Jesse Honigberg
Jesse Honigberg@jessedh·
@arshbot @mikulaja 100% - @mikulaja - shouldn’t Evolve have to clear the marketing materials and this should have been caught. I’ve seen programs get in trouble for less than this, especially if they’re targeting underBanked populations.
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Harsha Goli
Harsha Goli@arshbot·
@mikulaja Don’t think you can legally call it a bank like this
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Akshay 🚀
Akshay 🚀@akshay_pachaar·
this is huge. ollama is now compatible with the anthropic messages API. which means you can use claude code with open-source models. think about that for a second. the entire claude harness: - the agentic loops - the tool use - the coding workflows all powered by private LLMs running on your own machine.
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Rimsha Bhardwaj
Rimsha Bhardwaj@heyrimsha·
BREAKING: I stopped reading textbooks cover to cover. NotebookLM now teaches me directly from PDFs and notes. Here are 6 prompts that turned documents into lessons 👇
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MIT Sloan Management Review
AI investments are exploding, but enterprise returns remain mediocre. The core issue? Leadership deploys intelligence as if it were automation. But intelligence — human or machine — can’t simply be inserted into workflows; it must be architected into environments. Most organizational designs manage effort and enforce alignment — they do not orchestrate reasoning, learning, or adaptive value creation. This is their AI strategic blind spot. Yet this is precisely where Wolfram’s computational philosophy offers essential and actionable clarity: Unlocking AI’s value requires leaders to ask not what tools can do but what architectures and infrastructures let intelligence emerge, evolve, and flourish. Organizations that treat intelligence as a designable infrastructure — not as an emergent property of tools — are likely to obtain faster, higher-quality decisions; reduced systemic risk; and enhanced adaptive capacity. Read the full article >> mitsmr.com/4lCLN9Z
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Jesse Honigberg
Jesse Honigberg@jessedh·
@KathyHochul quick idea - make the NYS HudsonLink bus service free by refunding the cost of monthly pass if you use it more than 15 times a month - I see these buses leave mostly empty from the Palisades Mall and it costs the same if it is empty or full! Reward use!
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Lincoln Tunnel
Lincoln Tunnel@PANYNJ_LT·
The Lincoln Tunnel to NY has all lanes blocked due to a vehicle fire. Updates are posted when situations change.
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Phil Goldfeder
Phil Goldfeder@YPGoldfeder·
End of an era!! In every job, there are people that you just gravitate to because they make you better! At @crossriverbank that’s @jessedh, one of the smartest and greatest guys I have ever known and will miss him as he moves on to his next adventure changing the world!
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Jason Mikula
Jason Mikula@mikulaja·
The proliferation of scams, accelerated by gen AI and now agentic AI, risks undermining the benefits of "real-time" payments, if there is no recourse and you have to double- or triple-check before sending funds. (Yes, below is re: wires, not Zelle, RTP, crypto, or stablecoins)
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Jesse Honigberg
Jesse Honigberg@jessedh·
@waltrcox There’s actually a better way to do this using an RfP without the receiving bank having to support send on the RTP network
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walt
walt@waltrcox·
know a FinTech who cracked the code (with a bank sponsor) for Zelle pull payments (ie near real time account funding). if keen to learn more, slide into DM's (should be fixed) or raise hand ✋
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