Prithvir

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There’s been misinformation circulating about @tradefoxai's fee structure. Here are the facts.
Since launch, aggregate fees as a percentage of total volume traded have been 0.33%. That figure is before any cashback or referral fees are paid out.
How it works:
We do not use a flat fee. We use a Gaussian distribution. We believe this structure is better than any flat fee model.
In prediction markets, most uncertainty lives near the middle of the curve. That’s where price discovery happens. As price moves toward 0 or 100, uncertainty collapses quickly because the outcome is closer to being decide
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Prediction markets called the US striking Iran before the headlines did.
Now they’re pricing:
1. Khamenei out as Supreme Leader by March 31: 47.5%
2. By June 30: 61.5%
3. By 2026: 68.5%
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Remember folks
Marxist eschatologists reinvent how the end of the world is near every decade
Don’t fall for it
Neither war nor AI doom can take away your life’s meaning since none of you had any purpose in the first place
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Interesting piece in @business this morning
Transactions, volumes, and open interest continue to go parabolic.
But optics and mass market perception could still cap the ceiling.
The next unlock will be institutional markets with unambiguous resolution criteria and explicit hedging utility.
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Data Science skill levels in 2026
1. Ask AI to write a query and iterate until it works
2. += Optimize query efficiency for cost and performance
3. += Translate a business question into the right query
4. += Design and run hypothesis tests
5. += Design and execute A/B tests
6. += Allocate capital based on experimental evidence
Prompt operator to capital allocator
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Hyperscaler capex at $646B is
1. more than the combined military spending of Germany, France, UK, Japan, Italy, Canada ($350B)
2. equivalent to the GDP or Singapore, Sweden, Argentina ($600B)
3. Equivalent to the US bank loan growth ($700B)
4. Slightly smaller than US defense spend ($917B)
5. More than half annual growth in consumer spend ($1T)
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if you're inner circle isn't discussing
1. neg-risk
2. bonding markets
3. merge split arbitrage
4. approximate airdrop size
5. nonce-based order cancellation
congrats, you are blessed
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Key Takeaways from the Federal Reserve paper:
"@Kalshi and the Rise of Macro Markets"
The Fed just published a 41-page working paper evaluating Kalshi as a macro forecasting tool.
They compare prediction markets to:
- Fed funds futures
- Secured Overnight Financing Rate (SOFR) options
- Bloomberg consensus
- Blue Chip surveys
- Survey of Market Expectations (SME)
- Survey of Professional Forecasters (SPF)
1. Real-time, full distributions
Surveys give point forecasts. Infrequent. Often stale.
PMs give:
- Continuous updates
- Full probability distributions
- Intraday reactions to news
- Density
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Apple is the only adult in the room
1. AirPods alone generate more revenue than all of Anthropic’s products and services combined
2. OpenAI plans to spend $100b a year to generate $14b in revenue
3. Apple will spend $1b per year to license Gemini, which will likely increase hardware sales by $20–$80b
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Anyone paying attention can tell that
centibillion market cap neobanks and brokerage houses are being built on top of agentic abstraction in 2026.
financial apps that don't default to ai-native user interactions will die this decade.
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anytime an anon account tweets anything remotely positive about an onchain
project your default assumption should be that they were paid to do it
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anyone waxing on about ai replacing all swes has clearly never architected a low-latency system where one missed optimization costs real money while staring at a flame graph at 3am
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was at a cafe predictionmaxxing when i got brutally pnl-mogged by a 19yo latency demon running cross-venue arbs
bro was limit-sniping and copytrade-mogging me while i was jesterclicking 50/50 politics
told myself it’s just variance to stop the cortisol spike
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