Sensitive content

This media may contain sensitive content.

Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Average vs Massive the difference is huge 🍆📏 SIZE WINS 🍆📏 #sph #sizematters #bnwo #bbc ,big dick sex ,size queen huge cock , cuckold , cheating, hotwife ,monster cock , size comparison, small dick, k1nk , size difference gap

SPHsizewins's profile picture

SIZE WINS 🍆📏

7,282 subscribers

11,146 görüntüleme • 5 gün önce •via X (Twitter)

NSFW#sph#sizematters#bnwo#bbc
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

The huge size difference between a lion and a lioness 🦁📏
0:20

The huge size difference between a lion and a lioness 🦁📏

Nature Unedited

174,305 görüntüleme • 7 ay önce

This cock exemplifies the difference between the technical average dick size, which is pathetically small and laughable, and the REAL hot sexy dick size which is a normal 8 inch cock. To be honest I almost never see small cocks IRL. Hot boys have big hot cocks. FACTS
0:26

This cock exemplifies the difference between the technical average dick size, which is pathetically small and laughable, and the REAL hot sexy dick size which is a normal 8 inch cock. To be honest I almost never see small cocks IRL. Hot boys have big hot cocks. FACTS

StacySizeQueen SPH

24,929 görüntüleme • 2 yıl önce

Posh British Size Queen Explains Dick Size, Good Dick vs Bad Dick. I do enjoy explaining it from the female POV, so you small peen losers can understand better LOL. 🤗 #fail #sph #humiliation
0:35

Sensitive content

Posh British Size Queen Explains Dick Size, Good Dick vs Bad Dick. I do enjoy explaining it from the female POV, so you small peen losers can understand better LOL. 🤗 #fail #sph #humiliation

StacySizeQueen SPH

15,266 görüntüleme • 2 yıl önce

Stacy Size Queen Shames Small Cock Loser for Masturbating Instead of Getting Laid. Does this sound like you? Just shamelessly masturbating your tiny little dick nub? Disgusting! #sph #humiliation #dickrate
0:29

Stacy Size Queen Shames Small Cock Loser for Masturbating Instead of Getting Laid. Does this sound like you? Just shamelessly masturbating your tiny little dick nub? Disgusting! #sph #humiliation #dickrate

StacySizeQueen SPH

13,967 görüntüleme • 2 yıl önce

Stacy Size Queen Flaccid Cock Shames and Humiliates Your Small Cock Existence. Your dick might look passable when hard... but what about when it's soft? Sometimes it can look outrageously terrible 😩😂 #sph #humiliation
0:23

Sensitive content

Stacy Size Queen Flaccid Cock Shames and Humiliates Your Small Cock Existence. Your dick might look passable when hard... but what about when it's soft? Sometimes it can look outrageously terrible 😩😂 #sph #humiliation

StacySizeQueen SPH

12,529 görüntüleme • 2 yıl önce

I liked the original PuttOUT Golf AirBreak… the new AirBreak Max is even better. - better design with the standing platform going right up to the green and no gap. Small but makes a big difference. - larger size and 2 cups makes it so much more versatile!!
1:59

I liked the original PuttOUT Golf AirBreak… the new AirBreak Max is even better. - better design with the standing platform going right up to the green and no gap. Small but makes a big difference. - larger size and 2 cups makes it so much more versatile!!

Cordie Walker | GolfWell

10,320 görüntüleme • 3 ay önce

Dick Summer is Here! We’ve been edging you for a while… Now you can finally enjoy the full load! Here are all the details: We’re launching a huge campaign running for the whole summer. It’s focused around the “Dick Rising” SocialFi Tech built by our own dev wizard You probably know how it works from giants like Portal or BlockGames. They paid agencies 100k+ to pull it off. And now we've made it even better. With our own twist. Here are the rules: Increase ‘Dick Size’ & earn $DICK by posting, and interacting with tweets that contain dickbrAIn. • Engagement on TWEETS: Reply - 30 cm Retweet - 20 cm Like - 10 cm • Engagement on REPLIES: Reply - 15 cm Like - 5 cm The dick will grow to the aggregate size of all dicks combined. Now let’s hear the spice: Each week the community will have a chance to reach the weekly goal, and unlock next rewards. We’ve been building 8 bombs for this campaign, and will release them each week, when the community goal is hit. They consist of games, utilities, and big updates. And let’s just say for now - You’re gonna love them! Fuck the scammers. Let's have some fun. Stay Hard! IT’S dickbrAIn TIME!
0:39

Dick Summer is Here! We’ve been edging you for a while… Now you can finally enjoy the full load! Here are all the details: We’re launching a huge campaign running for the whole summer. It’s focused around the “Dick Rising” SocialFi Tech built by our own dev wizard You probably know how it works from giants like Portal or BlockGames. They paid agencies 100k+ to pull it off. And now we've made it even better. With our own twist. Here are the rules: Increase ‘Dick Size’ & earn $DICK by posting, and interacting with tweets that contain dickbrAIn. • Engagement on TWEETS: Reply - 30 cm Retweet - 20 cm Like - 10 cm • Engagement on REPLIES: Reply - 15 cm Like - 5 cm The dick will grow to the aggregate size of all dicks combined. Now let’s hear the spice: Each week the community will have a chance to reach the weekly goal, and unlock next rewards. We’ve been building 8 bombs for this campaign, and will release them each week, when the community goal is hit. They consist of games, utilities, and big updates. And let’s just say for now - You’re gonna love them! Fuck the scammers. Let's have some fun. Stay Hard! IT’S dickbrAIn TIME!

dickbrAIn

27,070 görüntüleme • 2 yıl önce

TSN’s Josh Lewenberg with some huge updates: -The Raptors are NOT looking to replace Jakob Pöltl, but rather bring in size and depth behind him. -The likelihood of making a move between now and the TD is “pretty high”, with the goal of being under the tax and to add a big. -The more realistic Mavericks target for the Raptors, is not AD, but rather Daniel Gafford. The Raptors are interested in DG, and have “already checked in on.” -Another potential trade candidate is Orlando’s Goga Bitadze. -The Raptors have a surplus of wings, and potential players that could be traded are Ochai Agbaji and Gradey Dick. - The Raptors have all of their picks available to as potential trade assets for “something bigger.”
2:04

TSN’s Josh Lewenberg with some huge updates: -The Raptors are NOT looking to replace Jakob Pöltl, but rather bring in size and depth behind him. -The likelihood of making a move between now and the TD is “pretty high”, with the goal of being under the tax and to add a big. -The more realistic Mavericks target for the Raptors, is not AD, but rather Daniel Gafford. The Raptors are interested in DG, and have “already checked in on.” -Another potential trade candidate is Orlando’s Goga Bitadze. -The Raptors have a surplus of wings, and potential players that could be traded are Ochai Agbaji and Gradey Dick. - The Raptors have all of their picks available to as potential trade assets for “something bigger.”

Omer Osman

97,327 görüntüleme • 7 ay önce

507 baby marched straight up to Saruyama boss Akira and sat right in front of him like a tiny VIP visitor. 😂😂 Akira looked down at this little bean and seemed to be thinking, "Umm... am I supposed to groom this? Is it legal to touch something this small?" 🤔😂 After a long moment of careful consideration, the giant finally gave a gentle groom. The size difference was hilarious Akira looked like a huge gorilla, while the baby looked like a tiny rat sitting in front of him. 😂🐀🦍 Then the Orange Sisters rushed over like babysitters on emergency duty: "Hoo! Sorry, old man! Don't worry, this is our adopted baby. His mother stepped out for some personal business. By the way iam a personal incharge😂😂. #akira #newbabymonkey #ivhikawazoo
0:41

507 baby marched straight up to Saruyama boss Akira and sat right in front of him like a tiny VIP visitor. 😂😂 Akira looked down at this little bean and seemed to be thinking, "Umm... am I supposed to groom this? Is it legal to touch something this small?" 🤔😂 After a long moment of careful consideration, the giant finally gave a gentle groom. The size difference was hilarious Akira looked like a huge gorilla, while the baby looked like a tiny rat sitting in front of him. 😂🐀🦍 Then the Orange Sisters rushed over like babysitters on emergency duty: "Hoo! Sorry, old man! Don't worry, this is our adopted baby. His mother stepped out for some personal business. By the way iam a personal incharge😂😂. #akira #newbabymonkey #ivhikawazoo

Animal Love

41,407 görüntüleme • 1 ay önce

🚨🚨Jamie Carragher says Manchester United are far much behind in terms of ambition among the Big Six. “Manchester United are a shambles of a football club right now. I look at the way they are operating in the transfer market and I just don’t understand it. This is Manchester United — they should be going after the biggest players, the best talent available, but instead they keep walking away from deals because they don’t want to pay the money. “You look at the names they’ve been linked with — Mateus Fernandes, Sandro Tonali, Morgan Rogers and other top players — and time after time they seem to step back when the deal becomes difficult. I understand you have to be smart in the market, but there’s a difference between being smart and lacking ambition. “They’ve got Champions League football next season, and this was the moment to show everyone that Manchester United are back. Instead, it feels like they’re more focused on saving money than building a team capable of competing. For a club of this size, that’s a huge concern.”
0:43

🚨🚨Jamie Carragher says Manchester United are far much behind in terms of ambition among the Big Six. “Manchester United are a shambles of a football club right now. I look at the way they are operating in the transfer market and I just don’t understand it. This is Manchester United — they should be going after the biggest players, the best talent available, but instead they keep walking away from deals because they don’t want to pay the money. “You look at the names they’ve been linked with — Mateus Fernandes, Sandro Tonali, Morgan Rogers and other top players — and time after time they seem to step back when the deal becomes difficult. I understand you have to be smart in the market, but there’s a difference between being smart and lacking ambition. “They’ve got Champions League football next season, and this was the moment to show everyone that Manchester United are back. Instead, it feels like they’re more focused on saving money than building a team capable of competing. For a club of this size, that’s a huge concern.”

CFC F_Boy

244,515 görüntüleme • 4 gün önce

How to spot "WHALES & INSIDERS" using Arkham. Inspired by Movez , I spent the last 60 minutes putting together a straightforward tutorial on how to find Whales and Insiders on Polymarket. No coding, no bots, no complex strategies. Just manual labor. 👇 Step 1: Go to Arkham( and search for the main Polymarket contract: "0x4bFb41d5B3570DeFd03C39a9A4D8dE6Bd8B8982E" Step 2: Filter the Noise. Look at the live transactions list. Filter by value. The bigger the number, the bigger the whale. Step 3: Pick a transaction you like, copy the wallet address. Step 4: Search their address on and copy the handle of the wallet. Step 5: Search their handle on Polymarket and explore their activity. 🚨 Here is the Alpha (How to spot the difference): The Insider: • Usually has very few trades. • Bets BIG amounts on plays that look "strange" at first. • Look for New Creation Dates + Low Activity. That is your insider. The Whale: • Just a high-conviction player with deep pockets and a huge risk appetite. If you spot a fresh wallet dropping heavy size on a random outcome? Pay attention. Always adjust your moves to your risk appetite. Let me know how it goes. 🥂
0:32

How to spot "WHALES & INSIDERS" using Arkham. Inspired by Movez , I spent the last 60 minutes putting together a straightforward tutorial on how to find Whales and Insiders on Polymarket. No coding, no bots, no complex strategies. Just manual labor. 👇 Step 1: Go to Arkham( and search for the main Polymarket contract: "0x4bFb41d5B3570DeFd03C39a9A4D8dE6Bd8B8982E" Step 2: Filter the Noise. Look at the live transactions list. Filter by value. The bigger the number, the bigger the whale. Step 3: Pick a transaction you like, copy the wallet address. Step 4: Search their address on and copy the handle of the wallet. Step 5: Search their handle on Polymarket and explore their activity. 🚨 Here is the Alpha (How to spot the difference): The Insider: • Usually has very few trades. • Bets BIG amounts on plays that look "strange" at first. • Look for New Creation Dates + Low Activity. That is your insider. The Whale: • Just a high-conviction player with deep pockets and a huge risk appetite. If you spot a fresh wallet dropping heavy size on a random outcome? Pay attention. Always adjust your moves to your risk appetite. Let me know how it goes. 🥂

Jayden ⛩️

13,612 görüntüleme • 7 ay önce

most Polymarket bots die the same way they quote symmetrically around mid-price price moves they absorb the loss repeat until account is empty the fix has been in academic papers since 2008 Stoikov figured it out studying stock market microstructure the math translates directly to prediction markets here's what actually matters: mid-price is a bad signal it's the average of best bid and ask on thin Polymarket orderbooks that number is almost meaningless what you want is VAMP Volume Adjusted Mid Price you walk into the orderbook depth and calculate the weighted average price for a given volume filters out the gaps, gives you a real reference point then you stop quoting symmetrically the reservation price formula: r = Mid - β × Q Q is your current inventory if you're long YES contracts, r shifts down automatically your bot starts selling YES cheaper and stops buying aggressively target is always flat inventory the spread isn't static either it has two components: volatility premium (widens when market moves fast) microstructure premium (depends on how often orders actually fill) if Polymarket odds start swinging fast, spread widens in real time static spread = guaranteed adverse selection - one more thing Stoikov points out: small tick size markets are where this model actually works large-tick markets (CME futures, liquid ETFs) have massive queues you can't nudge your price by a fraction of a tick without losing your place Polymarket is small-tick by nature binary markets, USDC pricing, sparse orderbooks that's exactly the environment this model was built for the P&L comparison between naive bots and inventory-controlled bots is not close naive strategy: wide distribution, occasional huge wins, regular wipeouts inventory control: tight distribution, consistent positive drift, rare catastrophic losses the "pennies in front of a steamroller" problem doesn't go away but you can see the steamroller coming if you're watching orderbook imbalance when bid volume heavily outweighs ask volume price is about to move up your bot should already be adjusting before the move happens that's the wealth still building the inventory control layer myself using for live execution in the meantime it handles the market scanning and order management while i finish the rest
0:51

most Polymarket bots die the same way they quote symmetrically around mid-price price moves they absorb the loss repeat until account is empty the fix has been in academic papers since 2008 Stoikov figured it out studying stock market microstructure the math translates directly to prediction markets here's what actually matters: mid-price is a bad signal it's the average of best bid and ask on thin Polymarket orderbooks that number is almost meaningless what you want is VAMP Volume Adjusted Mid Price you walk into the orderbook depth and calculate the weighted average price for a given volume filters out the gaps, gives you a real reference point then you stop quoting symmetrically the reservation price formula: r = Mid - β × Q Q is your current inventory if you're long YES contracts, r shifts down automatically your bot starts selling YES cheaper and stops buying aggressively target is always flat inventory the spread isn't static either it has two components: volatility premium (widens when market moves fast) microstructure premium (depends on how often orders actually fill) if Polymarket odds start swinging fast, spread widens in real time static spread = guaranteed adverse selection - one more thing Stoikov points out: small tick size markets are where this model actually works large-tick markets (CME futures, liquid ETFs) have massive queues you can't nudge your price by a fraction of a tick without losing your place Polymarket is small-tick by nature binary markets, USDC pricing, sparse orderbooks that's exactly the environment this model was built for the P&L comparison between naive bots and inventory-controlled bots is not close naive strategy: wide distribution, occasional huge wins, regular wipeouts inventory control: tight distribution, consistent positive drift, rare catastrophic losses the "pennies in front of a steamroller" problem doesn't go away but you can see the steamroller coming if you're watching orderbook imbalance when bid volume heavily outweighs ask volume price is about to move up your bot should already be adjusting before the move happens that's the wealth still building the inventory control layer myself using for live execution in the meantime it handles the market scanning and order management while i finish the rest

cryptovcdegen

19,483 görüntüleme • 5 ay önce

🚨SHOCKING EXPOSÉ: Systemic Failures in Georgia's 2024 Election! 🚨New report reveals MASSIVE errors in official scanner logs from 7 counties—Bibb, Cherokee, Fayette, Floyd, Grady, Gwinnett, Houston—analyzing 872,000 ballots. This isn't isolated glitches...this is systematic, a SYSTEM-WIDE BREAKDOWN! Georgian’s for Truth co-founder, Field Searcy, explains: - Insane Error Volume: Over 716,000 errors logged—nearly ONE per ballot! 49.32% of ALL ballots had at least one error. - Ballot Reversals Everywhere: 299,000 misfeeds/reversals, hitting 26.95% of ballots. Consistent across urban/rural, big/small counties—points to DEEP systemic issues in scanners! - Security Red Flags: 22,481 QR code signature mismatches—classified as SECURITY ERRORS by federal investigators. Tied to Dominion systems! - QR code not found: 126,000 cases - Unrecognizable ballot format/ID: 187,000 instances - Ballot size too big: 319,000 flags (biggest category!) - Scanner transport fails: 60,000 mechanical issues - Exceeding Standards by the Millions: tiny Grady County, errors blew past federal limits by 155,000x; in huge Gwinnett, 144,000x. Same patterns EVERYWHERE—not human error, but MACHINE FAILURE! 📉 Read the full report 📜🔍at and see the full press conference at
6:27

🚨SHOCKING EXPOSÉ: Systemic Failures in Georgia's 2024 Election! 🚨New report reveals MASSIVE errors in official scanner logs from 7 counties—Bibb, Cherokee, Fayette, Floyd, Grady, Gwinnett, Houston—analyzing 872,000 ballots. This isn't isolated glitches...this is systematic, a SYSTEM-WIDE BREAKDOWN! Georgian’s for Truth co-founder, Field Searcy, explains: - Insane Error Volume: Over 716,000 errors logged—nearly ONE per ballot! 49.32% of ALL ballots had at least one error. - Ballot Reversals Everywhere: 299,000 misfeeds/reversals, hitting 26.95% of ballots. Consistent across urban/rural, big/small counties—points to DEEP systemic issues in scanners! - Security Red Flags: 22,481 QR code signature mismatches—classified as SECURITY ERRORS by federal investigators. Tied to Dominion systems! - QR code not found: 126,000 cases - Unrecognizable ballot format/ID: 187,000 instances - Ballot size too big: 319,000 flags (biggest category!) - Scanner transport fails: 60,000 mechanical issues - Exceeding Standards by the Millions: tiny Grady County, errors blew past federal limits by 155,000x; in huge Gwinnett, 144,000x. Same patterns EVERYWHERE—not human error, but MACHINE FAILURE! 📉 Read the full report 📜🔍at and see the full press conference at

Holly Kesler

23,301 görüntüleme • 6 ay önce

Chinese student used AI from Anthropic to turn $1,000 into $1,500,000 He studies at Tsinghua University in Beijing. His account is k9Q2m In such a young age he already make a million simply knowing the right formulas and being able to use Claude Result: $1,430 → $1,550,750 44,364 trades Win rate 100% The biggest win $23,600 on a single bet k9Q2m profile: How it bots work: The bot runs 6 formulas hedge funds use simultaneously, every tick. Most traders guess. This bot calculates. Formula 1 - LMSR Pricing Polymarket prices move on a logarithmic curve. The bot knows the exact price impact before entering. Market says 31¢ for BTC up in 5 minutes. The model sees the curve is mispriced. The bot enters before the correction. Formula 2 - Kelly Criterion Renaissance Capital uses it. Two Sigma uses it. Now your bot uses it. Every bet is sized exactly right. Never too big to blow the account. Never too small to matter. $1,000 bankroll. Consistent edge. Kelly compounds it into something real. Formula 3 - EV Gap Detection The bot scans every BTC market looking for one thing: - Where is the market price wrong by more than 5%? - Market says 30¢. Real probability is 55¢. EV = +0.52. The bot enters. Most people never see this gap. The bot never misses it. Formula 4 - KL-Divergence BTC 5-minute and 15-minute markets are correlated. When they drift apart - that's an arb. The bot measures the statistical distance between them every second. When it crosses 0.2, it flags the trade. This is how hedge funds extracted $100K+ on correlated election markets. The same logic runs here. Formula 5 - Bayesian Updates New block confirmed. Volume spike. Price movement. The bot doesn't ignore signals - it updates. Prior probability was 54%. New data comes in. Posterior jumps to 71%. The bot re-prices in real time while the market is still asleep. Formula 6 - Stoikov Execution Entering at the wrong moment kills the edge. The bot calculates the reservation price-the exact point where the risk-adjusted entry makes sense. It doesn't chase. It doesn't panic. It waits for the right tick, then fills What this means in practice: - Every few seconds the bot runs all six formulas in parallel. - If LMSR confirms mispricing - EV gap is above 5% - Kelly says the bet size is justified - Bayesian posterior agrees - KL-divergence flags the correlated drift - Stoikov clears the execution price Only then does the bot enter. Six filters. One trade. This isn't a trading bot. It's a hedge fund strategy running on a prediction market. The edge is real. The math is public. The difference is most people never build it. Just insert all these formulas into Claude and create your own bot Add this post to bookmarks so you don’t lose it Soon I will publish another bot with working formulas
0:38

Chinese student used AI from Anthropic to turn $1,000 into $1,500,000 He studies at Tsinghua University in Beijing. His account is k9Q2m In such a young age he already make a million simply knowing the right formulas and being able to use Claude Result: $1,430 → $1,550,750 44,364 trades Win rate 100% The biggest win $23,600 on a single bet k9Q2m profile: How it bots work: The bot runs 6 formulas hedge funds use simultaneously, every tick. Most traders guess. This bot calculates. Formula 1 - LMSR Pricing Polymarket prices move on a logarithmic curve. The bot knows the exact price impact before entering. Market says 31¢ for BTC up in 5 minutes. The model sees the curve is mispriced. The bot enters before the correction. Formula 2 - Kelly Criterion Renaissance Capital uses it. Two Sigma uses it. Now your bot uses it. Every bet is sized exactly right. Never too big to blow the account. Never too small to matter. $1,000 bankroll. Consistent edge. Kelly compounds it into something real. Formula 3 - EV Gap Detection The bot scans every BTC market looking for one thing: - Where is the market price wrong by more than 5%? - Market says 30¢. Real probability is 55¢. EV = +0.52. The bot enters. Most people never see this gap. The bot never misses it. Formula 4 - KL-Divergence BTC 5-minute and 15-minute markets are correlated. When they drift apart - that's an arb. The bot measures the statistical distance between them every second. When it crosses 0.2, it flags the trade. This is how hedge funds extracted $100K+ on correlated election markets. The same logic runs here. Formula 5 - Bayesian Updates New block confirmed. Volume spike. Price movement. The bot doesn't ignore signals - it updates. Prior probability was 54%. New data comes in. Posterior jumps to 71%. The bot re-prices in real time while the market is still asleep. Formula 6 - Stoikov Execution Entering at the wrong moment kills the edge. The bot calculates the reservation price-the exact point where the risk-adjusted entry makes sense. It doesn't chase. It doesn't panic. It waits for the right tick, then fills What this means in practice: - Every few seconds the bot runs all six formulas in parallel. - If LMSR confirms mispricing - EV gap is above 5% - Kelly says the bet size is justified - Bayesian posterior agrees - KL-divergence flags the correlated drift - Stoikov clears the execution price Only then does the bot enter. Six filters. One trade. This isn't a trading bot. It's a hedge fund strategy running on a prediction market. The edge is real. The math is public. The difference is most people never build it. Just insert all these formulas into Claude and create your own bot Add this post to bookmarks so you don’t lose it Soon I will publish another bot with working formulas

AdiiX

718,045 görüntüleme • 4 ay önce

Leaving Citadel & launching a $1B AI hedge fund — how Renee Yao built NeoIvy Capital from scratch Renee Yao walked away from two of the most elite hedge funds on Wall Street — Citadel & Millennium — and built a quant fund on a fundamentally different model: modern AI instead of human-powered alpha generation. The result: $1B+ in regulatory AUM, uncorrelated returns through COVID, & a fund Business Insider named one of the top transforming investing in North America. We cover: - Why large multi-manager quant firms rely on massive global researcher headcounts — & why Renee saw that as a model worth disrupting - The 3 barriers to entry in AI-driven quant — & why legacy sequential infrastructure can be a disadvantage compared to modern parallel distributed systems - How NeoIvy's self-evolving models adapted in real time during the March 2020 crash — while traditional quant managers had a nightmare month - The difference between beta returns, factor returns & pure alpha — & why size is the enemy of true idiosyncratic returns - Why the "black box" reputation of quant funds has been the #1 fundraising obstacle - How a 4-year-old girl visiting her uncle's room-sized supercomputer in China set the foundation for all of this - The edge/breadth/constraint framework from Grinold & Kahn — & how it shaped Renee's thinking on diversification - Renee's raw advice on staying disciplined when everyone around you is chasing beta in a bull market Transcript: 00:00 Intro 01:14 Renee Yao’s journey to founding Neo Ivy 02:28 Joining Citadel after the financial crisis 04:13 Hedge fund diversification and breadth of edge 04:45 Why Neo Ivy trades with AI strategies 07:50 How self-learning AI adapts to markets 09:40 Causation vs correlation in AI hedge funds 10:33 Barriers to entry for AI hedge funds 14:47 Risks of crowded factor bets explained 16:39 Why big funds struggle with AI talent 17:29 From PM at Citadel to hedge fund founder 18:47 Challenges of launching a quant hedge fund 20:25 Biggest constraint for AI hedge fund startups 22:08 How AI hedge funds adapted during COVID 24:04 Modern AI tools used in quant trading 25:13 Building hedge fund infrastructure from scratch 26:26 Career advice for aspiring quants and traders 28:55 Adapting career goals to changing job markets 31:57 Life lessons from trading and risk management 32:51 Staying disciplined while running a hedge fund 34:38 Obsession and belief in AI hedge funds 35:41 Closing thoughts on hedge funds and life
35:59

Leaving Citadel & launching a $1B AI hedge fund — how Renee Yao built NeoIvy Capital from scratch Renee Yao walked away from two of the most elite hedge funds on Wall Street — Citadel & Millennium — and built a quant fund on a fundamentally different model: modern AI instead of human-powered alpha generation. The result: $1B+ in regulatory AUM, uncorrelated returns through COVID, & a fund Business Insider named one of the top transforming investing in North America. We cover: - Why large multi-manager quant firms rely on massive global researcher headcounts — & why Renee saw that as a model worth disrupting - The 3 barriers to entry in AI-driven quant — & why legacy sequential infrastructure can be a disadvantage compared to modern parallel distributed systems - How NeoIvy's self-evolving models adapted in real time during the March 2020 crash — while traditional quant managers had a nightmare month - The difference between beta returns, factor returns & pure alpha — & why size is the enemy of true idiosyncratic returns - Why the "black box" reputation of quant funds has been the #1 fundraising obstacle - How a 4-year-old girl visiting her uncle's room-sized supercomputer in China set the foundation for all of this - The edge/breadth/constraint framework from Grinold & Kahn — & how it shaped Renee's thinking on diversification - Renee's raw advice on staying disciplined when everyone around you is chasing beta in a bull market Transcript: 00:00 Intro 01:14 Renee Yao’s journey to founding Neo Ivy 02:28 Joining Citadel after the financial crisis 04:13 Hedge fund diversification and breadth of edge 04:45 Why Neo Ivy trades with AI strategies 07:50 How self-learning AI adapts to markets 09:40 Causation vs correlation in AI hedge funds 10:33 Barriers to entry for AI hedge funds 14:47 Risks of crowded factor bets explained 16:39 Why big funds struggle with AI talent 17:29 From PM at Citadel to hedge fund founder 18:47 Challenges of launching a quant hedge fund 20:25 Biggest constraint for AI hedge fund startups 22:08 How AI hedge funds adapted during COVID 24:04 Modern AI tools used in quant trading 25:13 Building hedge fund infrastructure from scratch 26:26 Career advice for aspiring quants and traders 28:55 Adapting career goals to changing job markets 31:57 Life lessons from trading and risk management 32:51 Staying disciplined while running a hedge fund 34:38 Obsession and belief in AI hedge funds 35:41 Closing thoughts on hedge funds and life

Ethan Kho

138,224 görüntüleme • 5 ay önce

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.
18:48

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.

ConsistentlyInconsistent

50,687 görüntüleme • 11 ay önce

I Cracked Polymarket Using Claude Opus 4.6: The 96,000 Dollar Script For 5 Minute High Leverage Windows most traders are currently sitting at their desks fighting a losing battle against a digital wall because they do not realize the house always wins against human emotion. while the crowd is busy chasing the next meme coin or getting washed out in a single wick an automated agent just pulled nearly a hundred thousand dollars out of thin air using nothing but raw logic. i have seen people blow their life savings in these five minute windows because they treated a high leverage prediction market like a playground instead of a laboratory i am moon dev and i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself which was a massive waste of my time and resources. with bots you must iterate to success so i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated by the market the five minute markets on polymarket are essentially a high speed game of musical chairs where the person left standing is usually the one with the fastest script. leverage makes these markets extremely dangerous because it amplifies every mistake you make until your account is completely empty. the only way to survive this environment is to stop trading based on a gut feeling and start trading based on a stress tested mathematical edge the real breakthrough happened when i started using claude opus four point six to write the execution code for these specific five minute windows. having an ai agent that can analyze microstructure data means you can find trends that are completely invisible to the naked eye. it is essentially like having a team of twenty engineers working for you around the clock without the communication lag or the massive overhead costs some of our back tests show a sixty four percent win rate which sounds like a dream to anyone who has ever spent a night staring at a red screen. however the return on these tests varies wildly based on a few specific changes to the strategy parameters and histogram filters. i found that a return of forty one thousand dollars can jump to nearly double that just by adjusting how the bot handles the macd histogram threshold the trap that most people fall into is thinking that a good back test is a license to print money immediately without any further validation. this is a dangerous lie that leads to huge losses because the market in the past is not a perfect mirror of what is going to happen today. that is why i never launch a bot with full size until it has survived the incubation phase where it trades with ten dollars at a time incubation is the ultimate reality check for any trading strategy regardless of how good the numbers look on a computer screen. it is nerve wracking to watch a bot enter its first real trade even if the size is small because that is the moment theory meets reality. most of the bots that pass a back test will fail during the first forty eight hours of incubation and that is exactly why this step is non negotiable the data i use to build these systems covers over two hundred weeks of historical one minute candles to ensure the results are robust and not just luck. we are currently moving toward a machine learning approach where the system can adapt to changing market conditions without me having to intervene. this means the bot will eventually be able to recognize when a high leverage window is too risky and simply wait for a better entry the strategy itself relies heavily on macd variations which is a well known indicator but it is used here with a very specific and proprietary twist. by filtering for trades that hit a specific threshold we can ignore the random price noise that usually liquidates manual traders. we look for an edge of at least six percent which is enough to cover all platform fees and still leave a significant profit on the table i used to think that being a successful trader meant being a genius who could predict the future with a magical crystal ball. the truth is far more boring because success is just about researching an idea and testing it until the data proves it works in the past. then you just let the bot do the work while you go live your life instead of being a slave to the candle sticks and charts this world is changing fast and the people who learn to leverage ai to automate their thinking are going to be the ones who win the next decade. i am not asking you to trust a back test or a screenshot from a website because i want you to trust the process of testing it yourself. code allows you to take your life back from the screens and finally stop the cycle of over trading and emotional liquidations the difference between the traders who make it and the people who blow up is simply the willingness to iterate on their ideas daily. you might fail on your first ten bots but the eleventh one might be the script that changes your entire financial trajectory forever. it is about staying in the game long enough for the math to finally work in your favor and removing the human heart from the execution every day i am back testing and researching new ideas to see if they can survive the stress of real market data. i launch these live bots and let them run for seventy two hours to see if they can handle the pressure of the current market trend. while everyone else is coping and complaining about market volatility we are just adjusting our parameters and letting the ai find the next profitable window vibe coding with claude opus four point six has changed the speed at which i can deploy a new strategy from weeks down to just a few minutes. you can give the ai a general strategy idea and it builds the entire trading infrastructure for you while you focus on the logic. this speed is the ultimate advantage in a market that moves as fast as a five minute prediction window on the blockchain the future of trading is not found in a chat room or a paid signal group but in the code you write and the data you process. i believe that everyone has the ability to become an automated trader if they are willing to put in the work to learn the scripts. it is the only way to escape the trap of the nine to five and the anxiety of manual hand trading in a manipulated market i want you to understand that the ninety six thousand dollar returns i see are the result of hundreds of failed tests that never saw the light of day. you have to be willing to look at a failing bot and kill it without emotion so you can move on to the next research project. that is the quantitative mindset that separates the winners from the people who are just gambling with their savings if you are ready to stop being the liquidity for the big players then it is time to start building your own automated army of bots. for the cost of a few cups of coffee you can get access to the road map and the scripts that are driving these results. i am here every day showing you the process because i want to see more people use code to find their financial freedom and beat the house at its own game
11:04

I Cracked Polymarket Using Claude Opus 4.6: The 96,000 Dollar Script For 5 Minute High Leverage Windows most traders are currently sitting at their desks fighting a losing battle against a digital wall because they do not realize the house always wins against human emotion. while the crowd is busy chasing the next meme coin or getting washed out in a single wick an automated agent just pulled nearly a hundred thousand dollars out of thin air using nothing but raw logic. i have seen people blow their life savings in these five minute windows because they treated a high leverage prediction market like a playground instead of a laboratory i am moon dev and i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself which was a massive waste of my time and resources. with bots you must iterate to success so i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated by the market the five minute markets on polymarket are essentially a high speed game of musical chairs where the person left standing is usually the one with the fastest script. leverage makes these markets extremely dangerous because it amplifies every mistake you make until your account is completely empty. the only way to survive this environment is to stop trading based on a gut feeling and start trading based on a stress tested mathematical edge the real breakthrough happened when i started using claude opus four point six to write the execution code for these specific five minute windows. having an ai agent that can analyze microstructure data means you can find trends that are completely invisible to the naked eye. it is essentially like having a team of twenty engineers working for you around the clock without the communication lag or the massive overhead costs some of our back tests show a sixty four percent win rate which sounds like a dream to anyone who has ever spent a night staring at a red screen. however the return on these tests varies wildly based on a few specific changes to the strategy parameters and histogram filters. i found that a return of forty one thousand dollars can jump to nearly double that just by adjusting how the bot handles the macd histogram threshold the trap that most people fall into is thinking that a good back test is a license to print money immediately without any further validation. this is a dangerous lie that leads to huge losses because the market in the past is not a perfect mirror of what is going to happen today. that is why i never launch a bot with full size until it has survived the incubation phase where it trades with ten dollars at a time incubation is the ultimate reality check for any trading strategy regardless of how good the numbers look on a computer screen. it is nerve wracking to watch a bot enter its first real trade even if the size is small because that is the moment theory meets reality. most of the bots that pass a back test will fail during the first forty eight hours of incubation and that is exactly why this step is non negotiable the data i use to build these systems covers over two hundred weeks of historical one minute candles to ensure the results are robust and not just luck. we are currently moving toward a machine learning approach where the system can adapt to changing market conditions without me having to intervene. this means the bot will eventually be able to recognize when a high leverage window is too risky and simply wait for a better entry the strategy itself relies heavily on macd variations which is a well known indicator but it is used here with a very specific and proprietary twist. by filtering for trades that hit a specific threshold we can ignore the random price noise that usually liquidates manual traders. we look for an edge of at least six percent which is enough to cover all platform fees and still leave a significant profit on the table i used to think that being a successful trader meant being a genius who could predict the future with a magical crystal ball. the truth is far more boring because success is just about researching an idea and testing it until the data proves it works in the past. then you just let the bot do the work while you go live your life instead of being a slave to the candle sticks and charts this world is changing fast and the people who learn to leverage ai to automate their thinking are going to be the ones who win the next decade. i am not asking you to trust a back test or a screenshot from a website because i want you to trust the process of testing it yourself. code allows you to take your life back from the screens and finally stop the cycle of over trading and emotional liquidations the difference between the traders who make it and the people who blow up is simply the willingness to iterate on their ideas daily. you might fail on your first ten bots but the eleventh one might be the script that changes your entire financial trajectory forever. it is about staying in the game long enough for the math to finally work in your favor and removing the human heart from the execution every day i am back testing and researching new ideas to see if they can survive the stress of real market data. i launch these live bots and let them run for seventy two hours to see if they can handle the pressure of the current market trend. while everyone else is coping and complaining about market volatility we are just adjusting our parameters and letting the ai find the next profitable window vibe coding with claude opus four point six has changed the speed at which i can deploy a new strategy from weeks down to just a few minutes. you can give the ai a general strategy idea and it builds the entire trading infrastructure for you while you focus on the logic. this speed is the ultimate advantage in a market that moves as fast as a five minute prediction window on the blockchain the future of trading is not found in a chat room or a paid signal group but in the code you write and the data you process. i believe that everyone has the ability to become an automated trader if they are willing to put in the work to learn the scripts. it is the only way to escape the trap of the nine to five and the anxiety of manual hand trading in a manipulated market i want you to understand that the ninety six thousand dollar returns i see are the result of hundreds of failed tests that never saw the light of day. you have to be willing to look at a failing bot and kill it without emotion so you can move on to the next research project. that is the quantitative mindset that separates the winners from the people who are just gambling with their savings if you are ready to stop being the liquidity for the big players then it is time to start building your own automated army of bots. for the cost of a few cups of coffee you can get access to the road map and the scripts that are driving these results. i am here every day showing you the process because i want to see more people use code to find their financial freedom and beat the house at its own game

Moon Dev

10,921 görüntüleme • 4 ay önce

** Sega Genesis 3D Engine Update 8 ** Significant improvements all round as you can see and hear from the last update !! Foremost - A huge thanks to Toni Gálvez - Megastyle - BG. who has joined the project to create a bit of 16bit low poly magic. Toni's an Amiga fan but also crazy about game dev in general, he's worked on GBC, GBA, PC, MD, PSP, C64, CPC, MSX... and others. Gaming titles include War Times, Metal Gear, Rocketman, Tintin & Asterix to name a few. He's provided the great new ship model you see on screen - new striped buildings, all the backgrounds / palettes etc. There's a lot of models he's given me which need to be added, also he will be planning a lot of the level design. Very happy to have him help me turn this into something more than a tech demo as I have my hands tied pushing the MD as far as it can go haha - there is no cpu cycle to be spared. Also many thanks to my good friend CYBERDEOUS - Crouzet Laurent for the Music for this showing , I wanted to have the music load occurring so we have a realistic benchmark for performance and he was only too obliging. If you're into MD chiptunes check him out !! Since last update : New player model , substantially more detailed than the Arwing. Last update had a 23 triangle Arwing , this update has a 39 triangle custom model from Toni. We had several to choose from , others will be used for enemies . 3D Buffer size increased 25% to 256x160. This was quite tricky as I'm close to the DMA limit even with an extended vblank . Spent a few days thinking of how to do this as like anything retro every solution has a drawback, finally got a workable solution. It makes a big difference to have a bit more vertical height . Z Rotation added ( the screen tilting left to right ) , small hit to vertex transform on cpu thanks to look up tables doing the heavy lifting, saving 4 multiplies per vertex. Multiple speed ups in rendering code. Onscreen paths with no range checking used until Z is close enough to cause clipping , partial onscreen drawing pathes that need to check boundaries, quad rendering completely rewritten - was very very painfull to get right . I found out the hard way that things are great when they are not rotating in the Z axis haha . Partial buffer draw optimisations - which have helped with the massive dma load , sending up to a 20kb buffer in a single frame needs a lot of optimisation. Min / Max tile lines are analysed and only sent if dirtied , reducing most buffer swaps substantially. Still some issues to sort out , at times you can see the flicker near top of screen when frames are near full height . I need to optimise that a bit. Due to the onscreen buffer system a full Sprite background had to be implemented almost Neo Geo style. This flips the usual MD rendering system on its head as it uses both foreground and background layers for a foreground 3d plane and sprites for the background. This presents a few issues, one is to get a tilt effect on the background by using narrow sprites (16x32) we run out of sprites when trying to cover the screen. Thankfully the MD is not limited to 80 sprites, to fix this a 114 sprite multiplexor is used to draw the background, its completely made up of 16x32 sprites ! Why do things this way ? speed . Its the interleaved foreground/background layers that allow a double buffered ram system writing to write to vram using dma in a completely linear fashion - virtually no tile translation needed. The negative is you have no planes for the background, that's where the sprites come in . Thanks to H40 mode we still have a few sprites we can use for effects in the forground also . Thankfully we can implement a fairly good tilt still for the background using sprites, in future updates this will be able to move horizontally also and a bit of vertical movement. XGM1 music driver in use to simulate music cpu load, XGM2 unfortunately with the massive DMA needed to shift the 3d buffers would slow down at times rendering it unusable, XGM1 plays at full speed - albiet with a bit more of a cpu hit. Together with the sprite multiplexor and the music driver active theres a 10 % hit to cpu so I've had to play around with draw distances / object heights and other optimisations to offset that. Not to mention the larger buffer takes more cpu to fill also. Everything is placeholder so will be changed with proper stage design. We are averaging 20 FPS in the current video, I'll push for more as always !! Progress continues on my other projects , updates soon on those - retirement can't come quick enough . #SGDK #SegaGenesis #SegaMegadrive
1:17

** Sega Genesis 3D Engine Update 8 ** Significant improvements all round as you can see and hear from the last update !! Foremost - A huge thanks to Toni Gálvez - Megastyle - BG. who has joined the project to create a bit of 16bit low poly magic. Toni's an Amiga fan but also crazy about game dev in general, he's worked on GBC, GBA, PC, MD, PSP, C64, CPC, MSX... and others. Gaming titles include War Times, Metal Gear, Rocketman, Tintin & Asterix to name a few. He's provided the great new ship model you see on screen - new striped buildings, all the backgrounds / palettes etc. There's a lot of models he's given me which need to be added, also he will be planning a lot of the level design. Very happy to have him help me turn this into something more than a tech demo as I have my hands tied pushing the MD as far as it can go haha - there is no cpu cycle to be spared. Also many thanks to my good friend CYBERDEOUS - Crouzet Laurent for the Music for this showing , I wanted to have the music load occurring so we have a realistic benchmark for performance and he was only too obliging. If you're into MD chiptunes check him out !! Since last update : New player model , substantially more detailed than the Arwing. Last update had a 23 triangle Arwing , this update has a 39 triangle custom model from Toni. We had several to choose from , others will be used for enemies . 3D Buffer size increased 25% to 256x160. This was quite tricky as I'm close to the DMA limit even with an extended vblank . Spent a few days thinking of how to do this as like anything retro every solution has a drawback, finally got a workable solution. It makes a big difference to have a bit more vertical height . Z Rotation added ( the screen tilting left to right ) , small hit to vertex transform on cpu thanks to look up tables doing the heavy lifting, saving 4 multiplies per vertex. Multiple speed ups in rendering code. Onscreen paths with no range checking used until Z is close enough to cause clipping , partial onscreen drawing pathes that need to check boundaries, quad rendering completely rewritten - was very very painfull to get right . I found out the hard way that things are great when they are not rotating in the Z axis haha . Partial buffer draw optimisations - which have helped with the massive dma load , sending up to a 20kb buffer in a single frame needs a lot of optimisation. Min / Max tile lines are analysed and only sent if dirtied , reducing most buffer swaps substantially. Still some issues to sort out , at times you can see the flicker near top of screen when frames are near full height . I need to optimise that a bit. Due to the onscreen buffer system a full Sprite background had to be implemented almost Neo Geo style. This flips the usual MD rendering system on its head as it uses both foreground and background layers for a foreground 3d plane and sprites for the background. This presents a few issues, one is to get a tilt effect on the background by using narrow sprites (16x32) we run out of sprites when trying to cover the screen. Thankfully the MD is not limited to 80 sprites, to fix this a 114 sprite multiplexor is used to draw the background, its completely made up of 16x32 sprites ! Why do things this way ? speed . Its the interleaved foreground/background layers that allow a double buffered ram system writing to write to vram using dma in a completely linear fashion - virtually no tile translation needed. The negative is you have no planes for the background, that's where the sprites come in . Thanks to H40 mode we still have a few sprites we can use for effects in the forground also . Thankfully we can implement a fairly good tilt still for the background using sprites, in future updates this will be able to move horizontally also and a bit of vertical movement. XGM1 music driver in use to simulate music cpu load, XGM2 unfortunately with the massive DMA needed to shift the 3d buffers would slow down at times rendering it unusable, XGM1 plays at full speed - albiet with a bit more of a cpu hit. Together with the sprite multiplexor and the music driver active theres a 10 % hit to cpu so I've had to play around with draw distances / object heights and other optimisations to offset that. Not to mention the larger buffer takes more cpu to fill also. Everything is placeholder so will be changed with proper stage design. We are averaging 20 FPS in the current video, I'll push for more as always !! Progress continues on my other projects , updates soon on those - retirement can't come quick enough . #SGDK #SegaGenesis #SegaMegadrive

Shannon Birt

33,145 görüntüleme • 15 gün önce

The Tokyo Game Show was a humbling yet uplifting experience. We booked early and got a pretty decent sized booth in the middle of the main hall, hoping we could make some noise in Asia's most prestigious web2 game show... But the moment I arrived to the venue, it made me realize just how small Apeiron and web3 gaming still really is. We were surrounded by the giants of the industry, their sheer size, quality and scope are next level, and I genuinely feel like a bucket in an ocean.💧 I was also hoping we would have gotten more to show by this time as well, that our mobile game would be ready and the game economy would be blossoming. Sadly, it's quite the opposite, and it made me wonder if we are ready for such a big stage. But times don't wait and opportunities always come and go, so we'll just have to present the work we've done so far with the doodiest attitude and let the show go on.🙌 Each morning there would be a giant rush as early participants run through the venue to collect time slotted entry tickets from giant publishers to make sure they can experience upcoming AAA titles like Monster Hunter Wilds (MH is actually where Apeiron normal attacks are inspired from). Most of the giant booths don't actually give out much merchandise or ingame rewards, and the only real offer they have is for their fans to playtest the latest games, watch unrevealed trailers or take photos with cosplayers/mascots/diorama. Having been in web3 for a while, this is a good reminder that, out there, there is a massive and genuine love for gaming beyond incentives. And this is the intrinsic value of games that we hope to deliver🥰 After the initial rush, the traffick will eventually disperse and trickle towards other booths, I remember watching our line build up each day, finding different ways to attract passerbys to get a leaflet, to pre-register and to playtest our game, it took 2 hours to fill up the lines on the first day, and by the 4th day the lines filled up in 30 minutes. We got a pretty good strategy going, the models posed for a wall of photographers to block the path, while the mascot and plushies drew people in. big sword | Apeiron found it more effective to wave sealed packaged plushies instead of opened plushies to let ppl know it is actually something they can obtain and take away, small but very effective difference!🧸 Our line extended each day, and the booth was constantly surrounded by curious passerbys asking what game this is...what is the name of that cute mascot... when is it launching... After each playtest our Japanese community doods, such as mino.ron 🍊 who helped us man the battle stations would ask the player for their feedback, many of whom had to que for over an hour to try our game... and the feedback we got were very positive! The emotions I see on their face as they play the game, fighting the first boss and winning their first pvp matches... were all of genuine excitement and happiness. I watched a lot of gamers from around the world play Aperion for the first time, and I have to say this gaming nation really does pick up Apeiron faster compared to other regions, or hopefully, its because of the new tutorial we put in place.🤞 We were visited by many of the major booth's representatives, countless PR/Broadcasting outlets and a handful of mobile game publishers. A lot of them told me they were attracted to our booth's colorful design. We would mention the crypto elements of the game but most of the interest is centered around the cute dood, the colorful artwork and the unique gameplay. I literally got over 200+ business cards during these 4 days (though bulk of them are marketing agencies lol) and my email and telegram is absolutely flooded.💦 We may be a bucket in the ocean, and there is still a lot of work that needs to be done, but amidst the giants out there, the appeal of Apeiron is still here. Our uniqueness and quality is what sets us apart even amongst web2 peers. I don't know how much longer it will take for Apeiron to be ready to compete with the giants up there, but I know I want to be up there one day, and I have a target I really want to aim for.🎯 During those 4 days, while I was giving out flyers and waving plushies towards smiling japanese doods in real life, I was also messaging back in omega channel to a group of upset holders who were concerned with our token performance. It's quite a surreal and contrasting experience. But yes I understand the performance of our token and assets also stands in stark contrast to what we are trying to present in real life. But with all the lesson we've learnt in crypto over the past 3 years... is that we must be patient and conserve ammunition during market downturns. We have not sold any APRS since TGE, we have only been accumulating steadily, we will stage our comeback when the mobile game is ready, when we have the means to acquire and onramp retail users (i beleive this is the sacred duty of web3 games), and hopefully but not absolutely necessarily, with healthier market conditions.💱 We are so close now, and as cheesy as it sounds, its darkest before dawn, we have witnessed this in Apeiron's ecosystem before the Ronin migration, we will build, we will survive, and we will thrive. What's most important now, is to focus on creating the best gaming experience for new users coming in. Our closed mobile beta testing on google play will begin next week, together with a new bug report flow, we will need all the help we can get to eliminate those bugs and issues and more suggestions to help build a better Apeiron.🙇‍♂️
0:35

The Tokyo Game Show was a humbling yet uplifting experience. We booked early and got a pretty decent sized booth in the middle of the main hall, hoping we could make some noise in Asia's most prestigious web2 game show... But the moment I arrived to the venue, it made me realize just how small Apeiron and web3 gaming still really is. We were surrounded by the giants of the industry, their sheer size, quality and scope are next level, and I genuinely feel like a bucket in an ocean.💧 I was also hoping we would have gotten more to show by this time as well, that our mobile game would be ready and the game economy would be blossoming. Sadly, it's quite the opposite, and it made me wonder if we are ready for such a big stage. But times don't wait and opportunities always come and go, so we'll just have to present the work we've done so far with the doodiest attitude and let the show go on.🙌 Each morning there would be a giant rush as early participants run through the venue to collect time slotted entry tickets from giant publishers to make sure they can experience upcoming AAA titles like Monster Hunter Wilds (MH is actually where Apeiron normal attacks are inspired from). Most of the giant booths don't actually give out much merchandise or ingame rewards, and the only real offer they have is for their fans to playtest the latest games, watch unrevealed trailers or take photos with cosplayers/mascots/diorama. Having been in web3 for a while, this is a good reminder that, out there, there is a massive and genuine love for gaming beyond incentives. And this is the intrinsic value of games that we hope to deliver🥰 After the initial rush, the traffick will eventually disperse and trickle towards other booths, I remember watching our line build up each day, finding different ways to attract passerbys to get a leaflet, to pre-register and to playtest our game, it took 2 hours to fill up the lines on the first day, and by the 4th day the lines filled up in 30 minutes. We got a pretty good strategy going, the models posed for a wall of photographers to block the path, while the mascot and plushies drew people in. big sword | Apeiron found it more effective to wave sealed packaged plushies instead of opened plushies to let ppl know it is actually something they can obtain and take away, small but very effective difference!🧸 Our line extended each day, and the booth was constantly surrounded by curious passerbys asking what game this is...what is the name of that cute mascot... when is it launching... After each playtest our Japanese community doods, such as mino.ron 🍊 who helped us man the battle stations would ask the player for their feedback, many of whom had to que for over an hour to try our game... and the feedback we got were very positive! The emotions I see on their face as they play the game, fighting the first boss and winning their first pvp matches... were all of genuine excitement and happiness. I watched a lot of gamers from around the world play Aperion for the first time, and I have to say this gaming nation really does pick up Apeiron faster compared to other regions, or hopefully, its because of the new tutorial we put in place.🤞 We were visited by many of the major booth's representatives, countless PR/Broadcasting outlets and a handful of mobile game publishers. A lot of them told me they were attracted to our booth's colorful design. We would mention the crypto elements of the game but most of the interest is centered around the cute dood, the colorful artwork and the unique gameplay. I literally got over 200+ business cards during these 4 days (though bulk of them are marketing agencies lol) and my email and telegram is absolutely flooded.💦 We may be a bucket in the ocean, and there is still a lot of work that needs to be done, but amidst the giants out there, the appeal of Apeiron is still here. Our uniqueness and quality is what sets us apart even amongst web2 peers. I don't know how much longer it will take for Apeiron to be ready to compete with the giants up there, but I know I want to be up there one day, and I have a target I really want to aim for.🎯 During those 4 days, while I was giving out flyers and waving plushies towards smiling japanese doods in real life, I was also messaging back in omega channel to a group of upset holders who were concerned with our token performance. It's quite a surreal and contrasting experience. But yes I understand the performance of our token and assets also stands in stark contrast to what we are trying to present in real life. But with all the lesson we've learnt in crypto over the past 3 years... is that we must be patient and conserve ammunition during market downturns. We have not sold any APRS since TGE, we have only been accumulating steadily, we will stage our comeback when the mobile game is ready, when we have the means to acquire and onramp retail users (i beleive this is the sacred duty of web3 games), and hopefully but not absolutely necessarily, with healthier market conditions.💱 We are so close now, and as cheesy as it sounds, its darkest before dawn, we have witnessed this in Apeiron's ecosystem before the Ronin migration, we will build, we will survive, and we will thrive. What's most important now, is to focus on creating the best gaming experience for new users coming in. Our closed mobile beta testing on google play will begin next week, together with a new bug report flow, we will need all the help we can get to eliminate those bugs and issues and more suggestions to help build a better Apeiron.🙇‍♂️

LoreKeeper

28,962 görüntüleme • 1 yıl önce