Prithvir

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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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Biggest Prediction Market movers in the last 24 hours
1. Jordan Bardella wins French presidential election: 39%
2. Fed cuts rate 25 bps at April meeting: 31%
3. Paramount takeover of Warner Bros before July: 34%
(filtered out markets w less than $100k liq and $10k vol)
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Remotion was a mistake. Roll it back\n\nTimeline now:\nai-slop-launch-vid\nai-slop-launch-vid\nai-slop-launch-vid\n.
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To everyone who said prediction markets are just sports, here’s the CEO of a $110b company:\n\n1. Weather and temperature contracts are the most frequently traded\n2. Utilities will soon hedge electricity and natural gas contracts using these markets\n\nPrediction markets are already institutional\n\nYou’re just not paying close enough attention
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WSJ and NYT will give you emotional opinion pieces on Greenland.
Prediction markets will give you unbiased odds.
1. US takes control of a part of Greenland by 2029 = 42%
2. Trump acquires Greenland before 2027 = 20%
3. Greenland acquired for $600b to $899b = 17%
4. Trump invades Greenland in 2026 = 11%
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