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Why CSI Is Officially Broken and What's Replacing It My conversation with Cuyler Owens, CEO at Widewail: 0:20 Incentives Ruin Survey Data. 2:30 Reviews Are A Free Focus Group. 4:55 500 Reviews Is Powerful Intel. 6:50 AEO Values Recency And Volume. 8:40 ChatGPT Found A Low-Pressure Dealer. 9:30 Words... show more

Car Dealership Guy

438,556 subscribers

14,138 просмотров • 16 дней назад •via X (Twitter)

Anya Rossi• Live Now

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Комментарии: 2

Фото профиля Vicimus

Vicimus15 дней назад

@widewailers The "reviews are a free focus group" point is the one most stores sleep on. They read them for score defense instead of mining them for what the process actually feels like.

Фото профиля Car Dealership Guy

Car Dealership Guy16 дней назад

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E97: Gavin Wood : Why Ethereum is Going Nowhere since 8 years (and my solution to it) Dr. Gavin Wood is the CoFounder of Ethereum, the Creator of the EVM and of the solidity language, and the Inventor and Founder of Polkadot & Parity Technologies Timestamps 0:00 Introduction 2:44 Culture in Japan VS UK 6:00 Humour 7:40 Who is Gavin? 9:17 Mission 10:28 Characteristics of Successful Founders 13:53 Developing Big Ideas 16:08 Creative Success Mechanism 20:03 Suffering 24:56 From Theory to Transactions 32:28 Building a Support Network 34:36 Legacy Banking Systems 36:01 Music Engineering 45:08 Childhood Dreams 46:27 Camino de Santiago 49:19 Crypto Fascination 54:44 Web3: The Post Snowden Web 1:00:39 Co-Founding Ethereum 1:03:12 Biggest Ethereum Achievement 1:04:04 Is Ethereum a Success? 1:07:38 Why Gavin Left Ethereum 1:09:48 Polkadot 1:14:53 Polkadots Achievements and Problems 1:24:05 Solution to Polkadot Main Problem 1:28:12 Polkadots Adoption & Communication Strategy 1:38:26 Polkadot Vision of Success 1:42:30 Memecoins 1:45:19 Crypto Integrity 1:49:45 Crypto's Limited Adoption 1:58:35 Identity vs. Individuality 2:07:15 Is AI a Bad Thing? 2:09:27 AI's Communication Revolution 2:25:06 Decentralization Role in AI 2:29:08 Eternal Happiness 2:32:17 Are You Happy? 2:33:52 Meaning of Life 2:38:58 What is Money? 2:45:55 Experience as a Father 2:48:54 Non-Consensus Beliefs

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MR SHIFT 🦁

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Why are Gen Z women so angry at men? Freya India William Costello Tania A Reynolds and I sat down to debate. 0:00 Why Are Modern Women So Angry? 1:34 Depression Spreads Through Networks 4:40 Women Drift Toward Progressive Politics 6:13 Dating Market Gets More Deceptive 8:08 Why Women Choose Singlehood 8:30 Girl Boss Vs. Partnership 8:50 Do Most Women Lean Left? 15:10 Online Outrage Keeps Escalating 15:37 The Rise Of Male Looksmaxxing 17:14 Dating Market Pushes Short-Term Looks 21:10 Why Men And Women Have Different Preferences 24:52 Men Optimizing For Group Chat Scrutiny 28:41 The Pre-Selection Effect 29:35 What Nikki Glaser Reveals About Mate Copying 32:38 Does Insecurity Make Us More Extroverted? 33:27 Gen Z Women: Insecure But Loud 35:33 How Women Adapted To The Modern Workplace 36:49 Assertive Women Disliked By Women 38:36 Why Men Don't Open Up 41:40 How To Help Struggling Men 43:18 Male Vs. Female Feedback Loops 45:27 The Two Mulans 47:43 The Soft Bigotry Of Male Expectations 50:40 The Self-Actualization Trap 53:26 The Hidden Rise Of Benevolent Sexism 55:27 The Mismeasurement Of Men In Psychology 57:51 Liberal Women Are The Unhappiest Group 59:33 Do Women Find Aggression Attractive? 1:01:22 Women Value Protection Above Infidelity 1:07:44 What Sex Dolls Reveal About Male Desire 1:09:28 Why Women Have Small Feet 1:14:10 Who Resents The Opposite Sex More? 1:16:38 Women Are More Sexist (Data) 1:19:15 Do Men Get The Ick Too? 1:21:58 Why Privileged Women Feel More Pessimistic 1:23:52 Manufactured Outrage & Middle Class 1:25:15 Can Men Be Victims Too? 1:28:20 Why Attractiveness Is The Ignored Privilege 1:32:59 Should You Be Friends Before Dating? 1:34:41 Are Opposite-Sex Friendships Platonic? 1:39:11 Is Effortless Beauty More Attractive? 1:43:27 Sydney Sweeney Vs. Sabrina Carpenter 1:43:47 The Game Theory Of Slut Shaming 1:45:04 Where To Find Everyone Paid partnerships included.

Why are Gen Z women so angry at men? Freya India William Costello Tania A Reynolds and I sat down to debate. 0:00 Why Are Modern Women So Angry? 1:34 Depression Spreads Through Networks 4:40 Women Drift Toward Progressive Politics 6:13 Dating Market Gets More Deceptive 8:08 Why Women Choose Singlehood 8:30 Girl Boss Vs. Partnership 8:50 Do Most Women Lean Left? 15:10 Online Outrage Keeps Escalating 15:37 The Rise Of Male Looksmaxxing 17:14 Dating Market Pushes Short-Term Looks 21:10 Why Men And Women Have Different Preferences 24:52 Men Optimizing For Group Chat Scrutiny 28:41 The Pre-Selection Effect 29:35 What Nikki Glaser Reveals About Mate Copying 32:38 Does Insecurity Make Us More Extroverted? 33:27 Gen Z Women: Insecure But Loud 35:33 How Women Adapted To The Modern Workplace 36:49 Assertive Women Disliked By Women 38:36 Why Men Don't Open Up 41:40 How To Help Struggling Men 43:18 Male Vs. Female Feedback Loops 45:27 The Two Mulans 47:43 The Soft Bigotry Of Male Expectations 50:40 The Self-Actualization Trap 53:26 The Hidden Rise Of Benevolent Sexism 55:27 The Mismeasurement Of Men In Psychology 57:51 Liberal Women Are The Unhappiest Group 59:33 Do Women Find Aggression Attractive? 1:01:22 Women Value Protection Above Infidelity 1:07:44 What Sex Dolls Reveal About Male Desire 1:09:28 Why Women Have Small Feet 1:14:10 Who Resents The Opposite Sex More? 1:16:38 Women Are More Sexist (Data) 1:19:15 Do Men Get The Ick Too? 1:21:58 Why Privileged Women Feel More Pessimistic 1:23:52 Manufactured Outrage & Middle Class 1:25:15 Can Men Be Victims Too? 1:28:20 Why Attractiveness Is The Ignored Privilege 1:32:59 Should You Be Friends Before Dating? 1:34:41 Are Opposite-Sex Friendships Platonic? 1:39:11 Is Effortless Beauty More Attractive? 1:43:27 Sydney Sweeney Vs. Sabrina Carpenter 1:43:47 The Game Theory Of Slut Shaming 1:45:04 Where To Find Everyone Paid partnerships included.

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Pamela Anderson Is PROOF That All Women Will HIT The Wall! ⏲️TIME STAMPS⏲️ 0:00 : Stream loading… 13:40 : INTRO 16:00 : The different kinds of S!mps 19:20 : RP is the truth 22:10 : 304’s are rewarded 25:25 : First story: Pamela Anderson | The wall is undefeated 🥛 30:00 : A woman’s sexual market value is perishable 32:50 : You have time on your side fellas 36:40 : These girls are in the movie Smile 😀 42:10 : Reading chats 💬 43:30 : Next Story: Trey Songz ordered to pay 11 million… 51:20 : Women who like celebrities are an L | Women have strange fantasies 52:30 : Next Story: Jets QB Tyrod Taylor | Frank is too nice 🐕 55:00 : She pissed on the side of the street 🤢 56:30 : Back to the story 59:40 : 🥷’s shot the club up 1:01:40 : Her dating history 🤯 1:10:50 : Chats | Superchat all your W’s 1:19:55 : Schedule for this week 1:21:30 : We create, lose weight, buy real estate 1:25:45 : OUTRO | Zoom call is loading… —SWITCH TO CASTLE CLUB 🏰— 1:31:25 : Caller #1 Should I be removed from her credit? 1:33:50 : #2 How much money do I need to buy a house in Canada? 🇨🇦 / You can be aware, but don’t cancel yourself 1:37:50 : #3 Advice for a new business owner (ATM) 1:42:30 : #4 Should I surrender my car? What’s a buy here pay here? 1:50:50 : #5 car advice for a business owner 1:59:10 : Why you need good credit 2:01:00 : #6 Don’t take those personal loans/ Focus on one skill first 2:07:00 : #7 How can I get better at networking? 2:09:00 : #8 High yield savings account advice 2:12:45 : #9 DM’s on demand/ Work on fixing your accent 2:15:30 : #10 I’m in HVAC, but I want to get into law enforcement/ Get rid of your tattoos 2:21:00 : #11 Fitness advice for getting abs 2:27:30 : #12 What content is safe for TikTok and YouTube? 2:33:10 : OUTRO

Myron Gaines

51,313 просмотров • 1 год назад

University of Toronto mathematician Daniel Litt and a16z's Lisha Li on AI's impact on mathematics: The models are good at a narrower slice of math than the headlines suggest. They grind long computations, pull technical ideas from more papers than any human could read, and apply every known technique better than almost anyone. What they don't do is build theory, or hold a vague philosophy long enough to make it precise, which is most of what Daniel says he actually does for a living. In this conversation, he and Lisha get into how mathematicians raided an AI proof for parts and broke several other problems with them, why a thousand AI mathematicians might all turn out to be the same mathematician, and why the proof a model handed Daniel was correct but still worth nothing. 00:00 Intro 02:10 The Erdős problem AI disproved 06:20 AI's reasoning looks recognizably human 07:55 Why English beat formal proofs 10:00 Why models can't build theory 14:50 Open problems measure your ignorance 17:45 How a graph became a Millennium Prize problem 18:58 Where AI doesn't help Daniel 21:15 Why ugly proofs are worth doing 23:42 True conjectures are harder than false ones 29:32 10 pages of calculation, zero insight 34:55 The goal of math is not to produce papers 36:25 5 conjectures, 3 bad papers, 1 hour 38:05 One mathematician duplicated 1000x 40:48 Why humans matter even if models win 46:30 When cheaper and worse beats better 49:22 Why the newest AI result isn't a big deal 57:05 How mathematicians actually check a long proof 59:38 Daniel's 3-year-old is already doing math YouTube: Daniel Litt Lisha

University of Toronto mathematician Daniel Litt and a16z's Lisha Li on AI's impact on mathematics: The models are good at a narrower slice of math than the headlines suggest. They grind long computations, pull technical ideas from more papers than any human could read, and apply every known technique better than almost anyone. What they don't do is build theory, or hold a vague philosophy long enough to make it precise, which is most of what Daniel says he actually does for a living. In this conversation, he and Lisha get into how mathematicians raided an AI proof for parts and broke several other problems with them, why a thousand AI mathematicians might all turn out to be the same mathematician, and why the proof a model handed Daniel was correct but still worth nothing. 00:00 Intro 02:10 The Erdős problem AI disproved 06:20 AI's reasoning looks recognizably human 07:55 Why English beat formal proofs 10:00 Why models can't build theory 14:50 Open problems measure your ignorance 17:45 How a graph became a Millennium Prize problem 18:58 Where AI doesn't help Daniel 21:15 Why ugly proofs are worth doing 23:42 True conjectures are harder than false ones 29:32 10 pages of calculation, zero insight 34:55 The goal of math is not to produce papers 36:25 5 conjectures, 3 bad papers, 1 hour 38:05 One mathematician duplicated 1000x 40:48 Why humans matter even if models win 46:30 When cheaper and worse beats better 49:22 Why the newest AI result isn't a big deal 57:05 How mathematicians actually check a long proof 59:38 Daniel's 3-year-old is already doing math YouTube: Daniel Litt Lisha

a16z

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Here's my interview with , one of the top ai agent traders We discuss everything from what he's buying on this dip, how he finds tokens, his favorite groups and more 0:00 Is the party over for AI agents? 2:55 Is Virtuals Protocol your main playground? 4:27 What's an example of a mispriced token? 5:39 What's Virtuals biggest competitor? 5:57 If you had to restart, would it be on Virtuals? 9:23 What ai agents are you buying? 16:05 How are you finding ai agents? 19:45 Who would you recommend following on X? 21:25 How are you evaluating tokens? 23:50 Do you think any of this tech will be used in web2? 26:20 Do you speak with the dev before buying? 27:05 Where do you post alpha? 29:00 Walking through a recent play 38:00 What is your price target on Anon? 40:20 What platform are you LPing on? 44:10 Do you use any tools? 46:50 Are there any upcoming tokens you're looking at?

Here's my interview with , one of the top ai agent traders We discuss everything from what he's buying on this dip, how he finds tokens, his favorite groups and more 0:00 Is the party over for AI agents? 2:55 Is Virtuals Protocol your main playground? 4:27 What's an example of a mispriced token? 5:39 What's Virtuals biggest competitor? 5:57 If you had to restart, would it be on Virtuals? 9:23 What ai agents are you buying? 16:05 How are you finding ai agents? 19:45 Who would you recommend following on X? 21:25 How are you evaluating tokens? 23:50 Do you think any of this tech will be used in web2? 26:20 Do you speak with the dev before buying? 27:05 Where do you post alpha? 29:00 Walking through a recent play 38:00 What is your price target on Anon? 40:20 What platform are you LPing on? 44:10 Do you use any tools? 46:50 Are there any upcoming tokens you're looking at?

Gorilla

32,543 просмотров • 1 год назад

E137: From exposing Bitcoin’s biggest weakness to onboarding FIFA and MapleStory - Avalanche🔺 CEO and Founder Emin Gün Sirer🔺⚔️ - founder of Ava Labs 🔺, the company behind Avalanche - shares the journey from building Karma (a pre-Bitcoin digital currency) to pioneering Avalanche, the multi-chain blockchain reshaping crypto's infrastructure. From early academic battles with Bitcoin maxis to onboarding FIFA and MapleStory Universe, this is one of the wildest rides in Web3. Timestamps 0:00 Introduction 1:59 Opening Comments 2:55 What Is Your Mission 3:39 Who Are You 6:00 Business vs PHD Program 7:21 Chip on The Shoulder 9:32 Partnerships Jupiter, Money Badgers, Mantle 10:27 Chip On The Shoulder (Continued) 11:55 What Is An Internet Currency 13:55 Why Was Bitcoin Better 15:46 Biggest Flaws In Bitcoin 19:17 Is Maximalism A Good Thing 21:18 Does Maximalism Help Bitcoin 22:05 Fascination With Bitcoin & Crypto 23:33 Evolution With Time 25:11 Broader Crypto Use 27:26 Partnerships Trezor Sui 28:15 Avalanche Explained Simply 28:48 Shiny Object, Why People Fall For It 33:08 Moving Towards Show Me Era 34:27 What Emin Did Different 36:45 What Did You Do Wrong 38:10 Does The Best Tech Win 40:03 Avalanche, Home of Layer Ones? 42:10 How Does Avalanche Scale 43:38 The Gaming Blockchain 48:21 Real World Assets on Defy 50:31 How Big Is RWA 50:58 Why Transformation Is Slow 52:36 FIFA On Avalanche Blockchain, Why? 53:28 Endgame For Avalanche 56:48 Personal Difficulties While Building 58:30 What Did You Change Afterwards 1:01:25 Why Live In New York 1:03:40 Debanked After Moving 1:09:05 Crypto Full Mainstream, How? 1:10:43 Biggest Prediction In 12 Months

E137: From exposing Bitcoin’s biggest weakness to onboarding FIFA and MapleStory - Avalanche🔺 CEO and Founder Emin Gün Sirer🔺⚔️ - founder of Ava Labs 🔺, the company behind Avalanche - shares the journey from building Karma (a pre-Bitcoin digital currency) to pioneering Avalanche, the multi-chain blockchain reshaping crypto's infrastructure. From early academic battles with Bitcoin maxis to onboarding FIFA and MapleStory Universe, this is one of the wildest rides in Web3. Timestamps 0:00 Introduction 1:59 Opening Comments 2:55 What Is Your Mission 3:39 Who Are You 6:00 Business vs PHD Program 7:21 Chip on The Shoulder 9:32 Partnerships Jupiter, Money Badgers, Mantle 10:27 Chip On The Shoulder (Continued) 11:55 What Is An Internet Currency 13:55 Why Was Bitcoin Better 15:46 Biggest Flaws In Bitcoin 19:17 Is Maximalism A Good Thing 21:18 Does Maximalism Help Bitcoin 22:05 Fascination With Bitcoin & Crypto 23:33 Evolution With Time 25:11 Broader Crypto Use 27:26 Partnerships Trezor Sui 28:15 Avalanche Explained Simply 28:48 Shiny Object, Why People Fall For It 33:08 Moving Towards Show Me Era 34:27 What Emin Did Different 36:45 What Did You Do Wrong 38:10 Does The Best Tech Win 40:03 Avalanche, Home of Layer Ones? 42:10 How Does Avalanche Scale 43:38 The Gaming Blockchain 48:21 Real World Assets on Defy 50:31 How Big Is RWA 50:58 Why Transformation Is Slow 52:36 FIFA On Avalanche Blockchain, Why? 53:28 Endgame For Avalanche 56:48 Personal Difficulties While Building 58:30 What Did You Change Afterwards 1:01:25 Why Live In New York 1:03:40 Debanked After Moving 1:09:05 Crypto Full Mainstream, How? 1:10:43 Biggest Prediction In 12 Months

MR SHIFT 🦁

93,188 просмотров • 1 год назад

🤖FSD V14.2 First Impressions Drive 🚗 Although the release notes made this update seem small - it feels to me like this is the refinement we have been waiting for in V14. All of my driving today was very smooth with no brake issues - I drove through HEAVY construction, parking lots, highways, etc and had no issues at all related to braking. We did run into a problem where the car got stuck trying to leave the parking lot - this is a problem that a larger context window would likely fix. Enjoy Chapters 00:00 Release Notes 01:00 Livestream Tonight 01:20 Self-Driving Stats 02:05 Another new V14.2 Feature 02:45 Drive Starts with a small issue? 03:38 Great lane change 04:30 Destination Park 04:50 Leaving Parking Lot 05:30 Cannot trust peoples turn signals 06:30 Great job slowing for yellow 07:45 Standard feels slower than V14.1.7 08:30 Funny destination parking 10:20 Drive Thru Test 12:35 Taking a left turn where it should not 13:40 What do you want to see on the live stream? 14:25 Destination Parking 14:45 I appreciate the signal use by FSD 16:15 Testing Nag 17:05 Great job moving out of collapsing lane 17:40 Destination Parking 18:10 Not fully stopping for stop sign 19:15 Driving slow in construction zone 20:30 Destination Parking 21:00 Disengagement - Stuck in parking lot 23:15 Polite Behaviour by FSD 24:50 GREAT job parking amongst construction 25:45 Amazing job leaving area 26:50 Good job through construction 27:30 Nag more strict at times? 28:25 Hesitation with the wheel 28:35 Terrible park job 30:51 What would you do here? 31:50 Catching up after my birthday 32:50 School Zone 33:50 My new Cybertruck Model 34:15 Great job moving around parked vehicle 35:20 More wheel jerking while parking 35:55 100% Self-Driving 36:10 More wheel hesitancy 36:40 QoL improvements for the Self-Driving Stats 39:00 FSD drives better than me 40:35 V14.2 Profiles feel slower than V14.1.7 41:50 Autonomy is such a hard thing to solve 43:15 My thoughts on V14.2

🤖FSD V14.2 First Impressions Drive 🚗 Although the release notes made this update seem small - it feels to me like this is the refinement we have been waiting for in V14. All of my driving today was very smooth with no brake issues - I drove through HEAVY construction, parking lots, highways, etc and had no issues at all related to braking. We did run into a problem where the car got stuck trying to leave the parking lot - this is a problem that a larger context window would likely fix. Enjoy Chapters 00:00 Release Notes 01:00 Livestream Tonight 01:20 Self-Driving Stats 02:05 Another new V14.2 Feature 02:45 Drive Starts with a small issue? 03:38 Great lane change 04:30 Destination Park 04:50 Leaving Parking Lot 05:30 Cannot trust peoples turn signals 06:30 Great job slowing for yellow 07:45 Standard feels slower than V14.1.7 08:30 Funny destination parking 10:20 Drive Thru Test 12:35 Taking a left turn where it should not 13:40 What do you want to see on the live stream? 14:25 Destination Parking 14:45 I appreciate the signal use by FSD 16:15 Testing Nag 17:05 Great job moving out of collapsing lane 17:40 Destination Parking 18:10 Not fully stopping for stop sign 19:15 Driving slow in construction zone 20:30 Destination Parking 21:00 Disengagement - Stuck in parking lot 23:15 Polite Behaviour by FSD 24:50 GREAT job parking amongst construction 25:45 Amazing job leaving area 26:50 Good job through construction 27:30 Nag more strict at times? 28:25 Hesitation with the wheel 28:35 Terrible park job 30:51 What would you do here? 31:50 Catching up after my birthday 32:50 School Zone 33:50 My new Cybertruck Model 34:15 Great job moving around parked vehicle 35:20 More wheel jerking while parking 35:55 100% Self-Driving 36:10 More wheel hesitancy 36:40 QoL improvements for the Self-Driving Stats 39:00 FSD drives better than me 40:35 V14.2 Profiles feel slower than V14.1.7 41:50 Autonomy is such a hard thing to solve 43:15 My thoughts on V14.2

Devin Olsen

117,054 просмотров • 10 месяцев назад

Andrew Kang turned a few early stage robotics investments into a $500 Million publicly traded empire RoboStrategy He is widely considered THE leading investor in robotics Andrew Kang believes the ChatGPT moment for Robotics is happening RIGHT NOW and it will be BIGGER THAN BITCOIN This interview is a masterclass on Robotics investing in 2026 1:18 – Why robotics today feels like crypto in 2015 4:23 – Is robotics a bigger opportunity than Bitcoin? 10:30 – Robotics 101: players, problems & bottlenecks 16:40 – Who's leading the race: Tesla vs Figure 23:10 – China's 100+ robotics companies & the real investment risk 25:28 – US vs China: who's actually ahead? 33:40 – How many human jobs will be replaced? 38:00 – The "ChatGPT moment" for robotics 43:55 – UBI & the new social contract 46:30 – Why Andrew built Robo Strategy 51:20 – Lessons from Bitmine, MicroStrategy & Saylor 1:07:50 – The Boston Dynamics question 1:12:09 – His most contrarian bet: avoid model-only companies 1:19:55 – Tesla or Figure? 1:23:26 – Figure's valuation in 5 years: bear, base & bull 1:29:20 – Final words of wisdom

Andrew Kang turned a few early stage robotics investments into a $500 Million publicly traded empire RoboStrategy He is widely considered THE leading investor in robotics Andrew Kang believes the ChatGPT moment for Robotics is happening RIGHT NOW and it will be BIGGER THAN BITCOIN This interview is a masterclass on Robotics investing in 2026 1:18 – Why robotics today feels like crypto in 2015 4:23 – Is robotics a bigger opportunity than Bitcoin? 10:30 – Robotics 101: players, problems & bottlenecks 16:40 – Who's leading the race: Tesla vs Figure 23:10 – China's 100+ robotics companies & the real investment risk 25:28 – US vs China: who's actually ahead? 33:40 – How many human jobs will be replaced? 38:00 – The "ChatGPT moment" for robotics 43:55 – UBI & the new social contract 46:30 – Why Andrew built Robo Strategy 51:20 – Lessons from Bitmine, MicroStrategy & Saylor 1:07:50 – The Boston Dynamics question 1:12:09 – His most contrarian bet: avoid model-only companies 1:19:55 – Tesla or Figure? 1:23:26 – Figure's valuation in 5 years: bear, base & bull 1:29:20 – Final words of wisdom

EllioTrades

333,331 просмотров • 3 месяцев назад