0xAlex

0xjean.eth 🔜 🇮🇳 Verified account @jnptzl · Nov 3

the schedule of prediction market hub

lots of problems try to fix

with @devanshmehta from @seer_pm

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Kleros Verified account @Kleros_io · Oct 30

Preparing your week at @EFDevcon? The Kleros team is getting ready too.

We'll share more soon. First, you'll find us in three of Devcon's community hubs: Legal & Governance, which we host on Thursday 5 November, plus the Agentic and Prediction Markets hubs. Our booth, Core 02, is open all week.

Save the date: our side event, Truth Pays, is on Wednesday 4 November in BKC, together with @arkivnetwork and Web3 Mumbai.

The week at a glance is in the slides, and every session is in the Devcon app. Links in the reply.

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Seer Verified account @seer_pm · Oct 17

x.com/i/article/2109…

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ethresear.ch Prediction market design for betting on many highly improbable events One of the challenges with prediction markets on events where the probabilities are very lopsided (ie. either very close to 0 or very close to 1) is that betting on the more likely outcome is very...

Devansh Mehta Verified account @devanshmehta · Oct 13

3 month update on leaving the EF: i've been working full time with @seer_pm since august!

its been a seamless transition to move from being a client of Seer to now joining their team full time. I originally worked with them on the deep funding pilot, during which we battle tested their infrastructure and smart contracts

somewhere along that journey i got heavily pilled on info finance as a category, so joining them was a natural next step.

the simplest explanation is a two-sided marketplace with traders on one side and information seekers on the other. Seekers pay to create markets on questions they care about, while traders are paid for being right

Vitalik wrote earlier about why AIs are a big unlock for info finance: LLMs can profitably trade tiny, low-liquidity micromarkets that aren’t worth a human’s time.

Another unforeseen reason for their timeliness is how AI is making it cheaper to produce an output than to evaluate. the bottleneck is deciding what deserves our attention, which is where info finance thrives

A few example use cases we’re excited about;

1. Hiring / grant selection

You put out a job posting and get 10k+ applicants. You open a market on whether each candidate gets shortlisted for interview (or, more ambitiously, on the performance score they’d earn in their first 3 months if hired). Your team then reviews applications ranked by market odds.

2. Token listings / partnerships

You’re an exchange with thousands of token listing requests. You run conditional markets on how much trading volume each token would generate if listed, and review from the top down.

3. Market discovery / recommendation algorithms

You’re a trader with an edge in certain kinds of Polymarket markets, but finding them eats most of your time. So you fund a market on whether your wallet will trade polymarket markets. Traders who learn your taste get paid, and you get a ranked list of where to look.

At Seer, I’m focused on growing our trader community, working with information seekers who want markets created, and protocol economics.

DMs are open if you’re drowning in more than you can review or you want to trade these markets!

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