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real titty lovers appreciate small titties
A small thing— found its way into the day.
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A small thank you to our community 💚 To celebrate Higgsfield’s $1 Billion revenue run-rate, we’re resetting the subscription credits you’ve used this month. Keep making things you love. This one’s on us.
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Crypto space really has a choice - grow the f up or get sidelined with random regulations. Saying we can not do anything when we are programming decentralized system is just untrue. Banks run AI for fraud detection but are inherently centralized and require KYC. At the same time KYC doesn't solve any of real problems as we know. We have better data and talent to create systems that don't require KYC and actually deter criminals while giving full freedom to real users. By working together we can totally weed out crypto of criminal activity. Criminal TAM is way smaller than all of economy moving onchain we are targeting. Decentralization != disorganization
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Small-town Ohio: we’ve got your back.
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New on 🧵 Smart-account transactions (ERC-4337) and an Events tab on every contract. Here's what changed. (1/7)
I'll smack you with these : D
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Why Tokenization Could Be the Most Important Economic Innovation of Our Lifetime | Bruce Fenton @BruceFenton is a longtime Bitcoin advocate since 2012, securities professional, and one of the early pioneers of tokenized securities. He is the founder and CEO of Chainstone Labs and founder of Atlantic Financial. Alongside Overstock founder @PatrickByrne, Bruce was involved in some of the earliest efforts to bring securities and financial-market infrastructure onto blockchain rails. In 2018, he tokenized equity in his own company, Chainstone Labs, on the Ravencoin blockchain—years before tokenization became one of Wall Street’s biggest narratives. In this episode, Bruce breaks down naked short selling, the plumbing behind traditional securities markets, and why he believes much of the problem is ultimately a ledger problem. We dive into questions such as: Who actually owns the stocks sitting in your brokerage account? How can shares be lent and rehypothecated? What role do brokers, clearing firms, DTCC, and Cede & Co. play in determining who owns what? And could blockchain replace an opaque system of claims and intermediaries with a transparent ledger showing exactly where an asset is and who owns it? We unpack what “tokenized stocks” actually means—and the important distinction between a token that simply gives you exposure to a stock’s price and a security issued natively onchain, where the token itself represents the actual share and the ownership rights that come with it. Bruce discusses how tokenization could allow smaller businesses to tokenize ownership and have their stock traded globally without needing to be listed on a traditional exchange like the NYSE, as well as what a future without KYC could look like. Finally, we get into Wall Street’s embrace of tokenization, the SEC’s evolving approach to tokenized securities, and one of the biggest questions surrounding the future of this technology: who ultimately controls these new financial rails? Remember to subscribe and hit the bell “🔔” icon to get notifications 0:00 Bruce Fenton & Patrick Byrne: Pioneers of Tokenized Securities 3:36 Naked Short Selling Explained 6:28 Who Actually Owns the Stocks in Your Brokerage Account? 12:00 Tokenization Solves Wall Street’s “Ledger Problem” 15:48 What Are You Actually Buying With Robinhood’s Tokenized Stocks? 16:48 Real Tokenized Stocks: When the Token IS the Share 21:46 Tokenization Could Open U.S. Markets to the Entire World 22:52 Why Companies May No Longer Need the NYSE 26:29 Could Tokenized Markets Exist Without KYC? 29:31 Bruce Tokenized Equity on Ravencoin in 2018 30:53 Will Blockchain Make Clearing Houses & DTCC Obsolete? 33:17 Could Tokenization Have Prevented the GameStop Crisis? 38:19 Wall Street Is Embracing Tokenization — Who Gets the Power? 40:20 The SEC’s New Tokenized Securities “Innovation Exemption” 42:57 Why Robinhood’s Tokenized Stocks Don’t Qualify 47:01 Could Everything Eventually Be Tokenized? 51:02 The Dystopian Side of Tokenization: Surveillance & Asset Seizure
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woke up a sweet beautiful smart angel with incredible boobs again…
Higgsfield is the most untold story in tech. $1BN in ARR in 18 months. Faster than everyone other than OpenAI and Anthropic. They spend $4M a month on models. They expect this to be $100K per person per month. They have 150 people working in a content machine. They will breed more millionaires than any other company in Kazakh history. For the first time, @alexmashrabov on the journey to $1BN in ARR. (below) 1. The Power of the Immigrant Founder Coming from Uzbekistan, Alex was pushed into competitive programming at age eight as his single path to reach the United States. For international founders, placing top in global competitions serves as the ultimate social elevator, instilling the relentless work ethic required to build breakout companies. 2. My Biggest Lessons in the Journey to Finding Product-Market Fit @higgsfield burned over $10 million of its $16 million seed round chasing hype and narrative rather than product quality. With under $5 million left, the team pivoted to product-led growth, solving camera control for creative directors, which immediately triggered organic hypergrowth without paid ads. 3. The 150-Person Content Team Powering Higgsfield's Billion in ARR Nearly half of Higgsfield's workforce consists of 150 in-house creative professionals producing tutorials, ads, and cinematic projects. Generating 90 minutes of TV-quality AI video requires 100 hours of raw output, proving human taste and curation remain the primary drivers of distribution. 4. We Spend $4 Million per Month on Models Higgsfield spends $4 million monthly on internal model usage, averaging $10,000 per employee so teams can freely vibe code and test workflows. Uncapped inference compute acts as a force multiplier, allowing top talent to discover breakthroughs at maximum velocity. 5. Why Chasing Benchmarks Is Bullshit and the Corporate Misalignment Occurring Public benchmarks have devolved into corporate psyops where lab researchers overfit test data to secure bonuses before job-hopping. Text-to-video benchmarks ignore real production workflows requiring 3,000-word prompts, proving direct customer iteration beats artificial leaderboards. 6. Why Team Sizes Won't Be Impacted as Much as People Think While AI handles over 60% of basic support requests, complex B2B environments cannot eliminate human teams. High product velocity constantly shifts rules and context, requiring smart, coordinated operators across legal and customer success. 7. Americans Are Way More Promiscuous When It Comes to Leaving Companies Silicon Valley workers routinely jump jobs every two years, prioritizing short-term trends over deep commitment. This transactional market gives international hubs an advantage, where cultural loyalty and team stability build compounding technical moats. (links in comments)
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