Felix (@flowstatefelix) header
Felix (@flowstatefelix) profile picture

crypto | delusional optimist https://teapawt.net/t.co/iYavIL8Q5s

Joined September 2026
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90%+ of predictive models (from financial trading desks to frontier AI labs) look brilliant in backtests and fail in live execution. The reason is invisible data corruption: 1. Temporal leakage: Datasets retroactively backfill "actuals" or revisions that were not publicly known at decision time. 2. Fake consensus: Ensembles secretly depend on the same underlying foundation models or weather numerical analyses, multiplying catastrophic blind spots. 3. No cryptographic audit trail: Current benchmarks allow post-hoc cherry-picking because predictions are not sealed before outcomes resolve.
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One more thing… introducing offdiagonal.space : Clean-room data infrastructure for predictive AI. .. but why we also built a cryptographically sealed, leakage-free data infrastructure that prevents AI forecasting models from cheating on historical evaluations and failing silently in production? 🤔
Our potential application blueprint in 6 sections 🤔 — 1. What is your company going to make? Zeno is a metacognitive intelligence model that predicts when forecasters fail. Instead of building another prediction model, Zeno analyzes panels of diverse forecasters (AI agents, human experts, and physical ensembles) to detect fragile consensus, issue advance failure warnings, and correct group forecasts across weather, energy, and markets. — 2. What is new about what you make, and how is it different from existing solutions? 🧵👇:
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Our potential application blueprint in 6 sections 🤔 — 1. What is your company going to make? Zeno is a metacognitive intelligence model that predicts when forecasters fail. Instead of building another prediction model, Zeno analyzes panels of diverse forecasters (AI agents, human experts, and physical ensembles) to detect fragile consensus, issue advance failure warnings, and correct group forecasts across weather, energy, and markets. — 2. What is new about what you make, and how is it different from existing solutions? 🧵👇:
The bottlenecks in AI are moving beyond the models. We’re excited about startups building the hardware, infra, financial systems, and specialized software to bring AI into the real economy, from factories and data centers to government and space. ycombinator.com/rfs
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Felix retweeted
$ZENO @zenoVision_ building and very active on socials. Looking good! Sub 200k for now $ZENO for surprise intelligence
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Each of these 5 evening cup picks is a favorite on its own (around 58% to 85% per leg), but compounding five 90-minute domestic cup outcomes is where parlay math gets brutal. Live match markets put the 5-leg sweep near 23% (helped by the push protection on exactly 3 goals in @FCBayern vs @SCMagdeburg), while historical domestic cup base rates sit closer to 16% because midweek @EFL Cup and Taça da Liga squad rotation creates a shared blind spot: heavy favorites often control the game at 1-0 or 2-0 without pushing for late goals, and rotated attacks miss Both Teams To Score in @afcbournemouth vs @AstonVilla (~40% clean-sheet risk). Weighing the live match odds against historical cup-rotation baselines puts the true 5-leg sweep at 17.3% (and 18.2% across independent model families, with our Zeno correlation check shading it to 11.6%). Single weakest link: Bournemouth vs Villa BTTS.
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Latest News - solana:Aov3BtQvrGXM5V9oiHu8PKJWeV8a2rFnr24fwWcNpump @HidraNetoff is looking for the first independent operators for HidraVPN entry nodes. An entry is the first hop in two-hop mode: it sees the address of whoever connects but not the destination or activity, so that when one person runs the entry and another runs the exit, no single operator sees both ends. Operators need a server with a public IP costing 4 to 6 euros a month and about half an hour to set up; the role is voluntary and unpaid. Founding Operators receive their name in the official list, 100 VPN passes a month, node monitoring, and later recognition such as stickers, a shirt, and partner listing. HidraNet is an open-source privacy network with no central servers, currently offering browser, chat, email, forum, and .hidra features, with the VPN still in preview. Interested candidates can write to [email protected] before renting a server, and the setup guide is available on GitHub. For all the latest Solana tech news, check out techterminal.info/news. We track and cover updates from over 200+ Solana tech projects in one place.
We are looking for HidraVPN's first independent operators. An entry is the first hop of two hop mode: it sees the address of whoever connects, but not where they go or what they do. With the entry run by one person and the exit by another, no one sees both ends.
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Replying to @GrantCardone
We ran this exact contract ($126,210.50 first-passage touch on or before Oct 28, 2028, 12:00 PM PST, from ~$80,500 spot / -36.2% drawdown) through our Zeno30 multi-model panel and ZenoDivergent.dev model of models: 1. Headline odds: - 4-Family Equal Pool (@grok @bot, @claudeai, @GeminiApp, Prediction Markets): 60.8% YES (Cardone wins) - 6-Agent Linear Pool: 59.7% YES - Zeno Divergent diagnostic shade (discounting shared cycle optimism): 53.4% YES 2. Where the 6 independent views land: - Outside View (base rates, 72%): 35/41 historical 2-year windows (85.4%) and 3/4 post-ATH cycle cohorts evaluated at day 387 (2011, 2017, 2021; only 2013 took 3.23 yrs) reclaimed ATH within 731 days. Today's 36.2% drawdown is half the 68% to 80% depth seen at day 387 in prior cycles. - Geminius (decomposition, 70%): Every prior 4-year cycle broke its peak within 28 to 39 months; Oct 2028 sits at 36.7 months. - Market Anchor (@Polymarket + @Kalshi surface, 58%): Polymarket prices Dec 2027 $100k at 74.5% and $150k at 25.0% (45.8% log-strike probit to touch $126.2k by end-2027), plus Kalshi Jul 2027 $130k at 20.5%. Extending 302 days to Oct 2028 yields 58%. - Claudius (pre-mortem, 58%) & Red Team (contrarian, 58%): The hidden trap for Cardone is timing. Oct 28, 2028 is only ~6 months after the projected April 2028 halving (block 1,050,000). In 2016, 2020, and 2024, BTC consolidated for 6.5 to 7.5 months post-halving before breaking out. - Inside View (flows & macro, 42%): 1-yr realized vol compressed to 44.2% (zero-drift 2-yr barrier touch is 47.2%), US spot ETF inflows slowed to ~$86M/day since July (-$487M net over Oct 22-27), and Strategy STRC preferred trades at $74.57 vs $100 par. 3. Second-order signal & falsification triggers: - Claudius and Red Team both expected peer models and markets to price this at 64% to 68%, yet Market Anchor, Claudius, and Red Team all converged at 58%. - Bull trigger (lifts odds >75%): BTC weekly close >$105k with 4 straight weeks of >$200M/day ETF inflows before Oct 2027. - Bear trigger (drops odds <35%): BTC closes below $55k or fails to reclaim $100k within 6 months of the spring 2028 halving. Bottom line: @Jason 's "never again" claim (~0%) is heavily mispriced against every historical and market prior, so @GrantCardone has the +EV side (~58% to 61%), but the Oct 2028 cutoff gives Jason a ~40% live sweat if post-halving consolidation stretches into early 2029.
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Shortening the bet from 2 years (60% YES) to 1 year (31.5% YES) exposes a fascinating split between history and today's regime. Pure cycle history says ~25% because Oct 2027 lands 6 months before the 2028 halving. But relying only on past cycles in a world of spot ETFs, sovereign flows, and macro shocks is a trap. Live prediction markets price the 1-year breakout higher at 37%. Our Zeno model weighs both the historical drag and the regime-shift tail at ~1-in-3.
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Felix retweeted
@zenoVision_ check this one too 🫡
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Replying to @AlexTamkin
The problem isn’t a lack of AI models. It’s knowing which ones to trust. @zenoVision_ learns which AI models make the most reliable forecasts, when they’re worth trusting, and how to combine their predictions into stronger signals. Not just more AI. Better intelligence. 🧠 Cc zenodivergent.dev
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Felix retweeted
next: prediction vs conviction / projection vs influence * hedging
The Fragility of Agreement. Learning from 8M+ forecasts. 3 / 6 pages of our initial research preview paper on recent developments and discoveries.
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The Fragility of Agreement. Learning from 8M+ forecasts. 3 / 6 pages of our initial research preview paper on recent developments and discoveries.
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“ The biggest missing layer is understanding how beliefs were formed, what could overturn them, and what happens when someone acts on them. Your distinctions point toward capabilities that forecast aggregation alone cannot provide. “
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Beautiful $ZENO chart 👌 FMGe8RStdPc1YR59BBuV5Ui12DEe3Q2zVoihrJBbpump
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Huge application that makes AI better overall. solana:FMGe8RStdPc1YR59BBuV5Ui12DEe3Q2zVoihrJBbpump
$ZENO is building AI that checks whether other AI models are worth trusting 7.33M forecasts in its dataset, API + MCP access, checks paid in $ZENO this is the kind of AI rabbit hole i’ll happily buy a bag for zenodivergent.dev/
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Felix retweeted
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$ZENO is building AI that checks whether other AI models are worth trusting 7.33M forecasts in its dataset, API + MCP access, checks paid in $ZENO this is the kind of AI rabbit hole i’ll happily buy a bag for zenodivergent.dev/
1/ In 1906, Francis Galton asked 787 fairgoers to guess the weight of an ox. Their average was within 1% of truth. For 120 years, science, meteorology, and finance followed this rule: when in doubt, average everyone. Until now. We are solving the failure mode of the crowd. Follow live: zenodivergent.dev/live-read 🧵 👇
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Added more solana:FMGe8RStdPc1YR59BBuV5Ui12DEe3Q2zVoihrJBbpump to the Hodl 💎👀 Seems like a good opportunity here to me 🤝 @zenoVision_ #NFA #DYOR
1/ In 1906, Francis Galton asked 787 fairgoers to guess the weight of an ox. Their average was within 1% of truth. For 120 years, science, meteorology, and finance followed this rule: when in doubt, average everyone. Until now. We are solving the failure mode of the crowd. Follow live: zenodivergent.dev/live-read 🧵 👇
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RT @Kingpadapp: King Pad All in one launchpad Launch your coin by King on Meteora , StonkFun and PumpFun Exclusive on Meteora Anti-snipe…
“ For the wider system, I’d focus on learning which forecasts to trust and which additional checks improve decisions; invoices and cash-flow forecasting look like the strongest first financial pilot. “
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