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Bankless Interview: Private Equity Insiders Reveal the Inside Story of Anthropic's Primary Market Trading

**Bankless Interview: A Private Equity Veteran Exposes the Dark Side of Anthropic's Pre-IPO Trading** In a Bankless podcast, Patagon founder Dio Casares reveals the opaque inner workings of the massive secondary market for shares in pre-IPO giants like Anthropic. The market, driven by private SPVs (special purpose vehicles), brokers, and even informal networks, sees hundreds of billions in notional value changing hands, with single-deal fees as high as 10%. However, an estimated 10-20% of transactions involve fraud or fabricated share certificates. Intermediaries often profit more from these deals than from their core investment businesses. Two types of "secondary" exist: company-sanctioned trades (like employee tender offers) that bring new money to the company, and disruptive "gray market" trades on platforms like Hive or Forge, which companies like Anthropic actively fight. The latter creates pricing chaos and complicates primary fundraising. A major risk involves multi-layered, nested SPV structures. When a company like Anthropic finally IPOs, delays in distributing shares down these chains, combined with discretionary powers of fund managers (GPs) to hold or sell, could trigger a wave of lawsuits and settlement nightmares lasting years. For small investors in "tokenized" versions of these assets, transparency is minimal, and due diligence is often impossible. Casares advises extreme caution, suggesting investors trust their gut and exit if something feels wrong. He warns that the post-IPO period will be a major "reckoning" for this wild and largely unregulated market.

marsbit05/15 09:44

Bankless Interview: Private Equity Insiders Reveal the Inside Story of Anthropic's Primary Market Trading

marsbit05/15 09:44

Is Elon Musk Actually the Victim?

"Victim or Vindicator? Inside the OpenAI Trial That Shattered the Myth." In May 2026, the federal court in Oakland became the stage for deconstructing the carefully curated narrative of OpenAI. The trial revealed a complex reality far removed from its founding ideals. The core dispute centered on whether OpenAI, founded in 2015 as a non-profit dedicated to benefiting "all of humanity," had betrayed its mission by shifting towards a lucrative commercial structure, particularly after its 2019 capped-profit affiliate (OpenAI LP) was established and Microsoft invested $13 billion. Elon Musk, a co-founder and early funder, sued, claiming the organization was "stolen" and turned into a de facto Microsoft subsidiary for private gain. OpenAI countered that Musk's funds were unconditional donations and his lawsuit was driven by a desire for control and regret after leaving to found his own AI venture, xAI. The trial exposed early fractures. Evidence from 2017, years before ChatGPT's success, showed the founders were already grappling with the immense financial demands of pursuing Artificial General Intelligence (AGI). Musk himself had proposed having Tesla fund OpenAI. The court scrutinized whether the founders knowingly crossed a moral line. Greg Brockman's personal diary, entered as evidence, contained entries about wealth goals and anxieties over the company's revenue path, alongside self-reminders about the moral bankruptcy of "stealing" the non-profit. Brockman later testified his OpenAI stake was worth nearly $30 billion. The character of CEO Sam Altman was a key battleground. Musk's legal team cited five individuals, including co-founder Ilya Sutskever and former board members, who had described Altman as dishonest. This highlighted a recurring "trust debt" within OpenAI's leadership, exemplified by the chaotic 2023 boardroom coup and subsequent reinstatement. Altman defended his position, arguing Musk sought to absorb OpenAI into Tesla and that commercial success amplified OpenAI's charitable impact. Testimony from Microsoft CEO Satya Nadella underscored how commercial realities now dominated. While framing Microsoft's massive investment as a way to enlarge the non-profit's funding "pie," texts revealed Nadella pressuring Altman to launch ChatGPT's paid version quickly. Nadella also revealed that during the 2023 crisis, Microsoft was prepared to hire Altman and his team, showcasing the board's diminished power against the gravity of capital, talent, and infrastructure. Ultimately, the trial depicted OpenAI not as a singular act of betrayal but as a gradual, systemic transformation. Its grand AGI mission required a "heavier machine" to sustain it—a machine of computing power (largely from Microsoft), capital, and commercial obligations that inevitably reshaped its priorities. The non-profit board, tasked with guarding the mission, found itself unable to control the commercial juggernaut it had enabled. For the public, the proceedings served as a sobering window into the making of a foundational technology. The AI tools increasingly integrated into daily life—from writing and coding to customer service—are not born from a transparent, purely altruistic process. They emerge from a tangled web of personal ambitions, private negotiations, control struggles, and cloud computing bills. The trial's legacy is the stark realization that as AI becomes societal infrastructure, its steering wheel remains in very few, and very human, hands.

marsbit05/15 09:06

Is Elon Musk Actually the Victim?

marsbit05/15 09:06

Pump.fun with Built-in Leverage? A Deep Dive into Hyperliquid's New Project alt.fun

"Hyperliquid's 'Pump.fun'? Decoding alt.fun, a New Project with Built-in Leverage" alt.fun is a new dApp launchpad on HyperEVM, described as Hyperliquid's version of "Pump.fun." It allows anyone to permissionlessly launch meme/altcoins backed by leveraged perpetual contracts (perp-backed altcoins). Instead of a standard bonding curve with spot reserves, each token is directly tied to a leveraged token (LT) representing a Hyperliquid perp position. The token price is driven by both trading activity and the underlying perp's leveraged P&L. Key mechanics: Creators choose an underlying asset (HYPE, BTC, ETH, etc.), direction (long/short), and leverage (2x, 5x). All tokens launch with a fixed $4000 market cap. The bonding curve uses BounceTech's LTs as reserve assets. A "graduation" mechanism automatically migrates tokens to HyperSwap AMM once a USD threshold is met or the curve sells out, with LPs permanently locked. The platform token is $ALT. The project saw over $1M volume in its first hour and brought 300+ new users to HyperEVM. The whitepaper highlights significant risks: leverage exposure (LTs can go to zero), volatility decay for high leverage in sideways markets, and reliance on Hyperliquid/BounceTech infrastructure. It represents an innovative fusion of meme coin virality and real leveraged financial exposure, positioned as an "altcoin factory" and potential traffic gateway for the HyperEVM ecosystem.

marsbit05/15 09:00

Pump.fun with Built-in Leverage? A Deep Dive into Hyperliquid's New Project alt.fun

marsbit05/15 09:00

Behind the Coinbase Acquisition of USDH: Hyperliquid’s Interest-Driven Choice

The article discusses the transition of the Hyperliquid ecosystem's native stablecoin, USDH, following its acquisition by Coinbase. Last September, USDH, issued by Native Markets, was a focal point in the ecosystem. Recently, Coinbase announced it will become the official USDC treasury deployer on Hyperliquid. Native Markets granted Coinbase the rights to purchase the USDH brand assets, leading to the gradual phase-out of USDH. Users can convert USDH to USDC or fiat without fees during this period. USDC is now Hyperliquid's official stablecoin. The move is framed as a three-way win: * **Coinbase & Circle:** Deepen ties with Hyperliquid's on-chain economy. Both companies are staking HYPE tokens. Circle had already invested in HYPE previously. * **Hyperliquid:** Becomes the primary beneficiary, set to receive the vast majority (estimated ~90%) of the reserve yield income from the ~$5.16 billion in USDC on its platform. This could translate to significant daily HYPE buybacks. The alliance with Coinbase may also offer regulatory advantages in the US. * **Native Markets:** While exiting the stablecoin business, the team reportedly received economic compensation from Coinbase for the USDH brand assets, framing it as a successful conclusion to USDH's role. However, the article notes criticism from some Hyperliquid community members. They view the shift as a step back for decentralization and argue that the original USDH issuer vote was driven by internal interests rather than user benefit, leaving regular users with nothing. The conclusion reflects that the eventual partnership between Hyperliquid and the giants (Coinbase/Circle) underscores a reality of利益分配 (interest distribution) over initial ideals of community and ecosystem advocacy.

Odaily星球日报05/15 06:48

Behind the Coinbase Acquisition of USDH: Hyperliquid’s Interest-Driven Choice

Odaily星球日报05/15 06:48

Google and Microsoft Battle in the AI PC Arena: Is Local Computing Power an IQ Tax? Is the Cloud PC the Ultimate Form?

Google and Microsoft are competing in the AI PC arena, with the article questioning whether powerful local AI hardware is necessary. It argues that current "AI PCs" often rely heavily on cloud AI for complex tasks, making premium local AI silicon potentially less critical. Google recently unveiled "Android PCs," a new high-end productivity-focused product line. Unlike traditional AI PCs that add AI features to existing Windows systems, Android PCs position cloud-based AI, specifically Google's Gemini, as their core. The system deeply integrates AI, allowing context-aware assistance directly where the user is working, regardless of the underlying device hardware (x86 or ARM). The piece suggests that cloud computing might be the future for AI PCs. Unlike cloud gaming, which demands ultra-low latency, AI tasks are more tolerant of network delays, as users already expect some processing time. This makes the cloud-computing model well-suited for AI. Examples like Alibaba's "Wuying AI Cloud Computer" show how cloud services can offer robust AI capabilities without requiring powerful local hardware. This shift challenges the traditional PC model. With rising memory costs and limitations in consumer-grade local AI performance, the "light local, heavy cloud" approach offers an alternative. It could lead to devices that primarily need a good display and network connection, with heavy AI lifting done remotely. However, the transition is just beginning. Traditional players like Microsoft are pushing both local AI standards (e.g., 40+ TOPS NPU requirements) and deeply integrating cloud AI (Copilot with GPT) into Windows. Apple leverages its tight ecosystem and has found success with more affordable MacBooks, potentially positioning it well for AI integration later. Chipmakers like Intel and AMD, while promoting local AI, also benefit massively from supplying data centers for the cloud AI infrastructure. The conclusion is that AI is redefining the PC. The future battle will involve cloud integration, OS-level AI, and cross-device ecosystems. While questions about network reliability, data privacy, and user adaptation remain, the era of the AI cloud computer seems to be on the horizon.

marsbit05/15 06:35

Google and Microsoft Battle in the AI PC Arena: Is Local Computing Power an IQ Tax? Is the Cloud PC the Ultimate Form?

marsbit05/15 06:35

World Cup Approaches, Prediction Markets Face a Major Test

The 2026 FIFA World Cup represents a major public test for sports prediction markets like Polymarket and Kalshi, which have grown significantly by offering tradable markets on event outcomes. This global event, hosted by the US, Canada, and Mexico, concentrates risks related to sports integrity, cross-border operations, and gambling ecosystems. A key concern is the potential for insider trading on non-public information (e.g., injuries, lineups), which could be exploited in granular prediction markets. FIFA's choice of its official prediction market partner, ADI Predictstreet, has raised significant doubts. The platform, relatively unknown, has faced scrutiny over the integrity of its executives—including past insider trading allegations and associations with a major EU corruption scandal—its rapid licensing in Gibraltar, and the fact its product was not yet live at the time of the announcement. This partnership begins with a "trust deficit." FIFA itself carries historical corruption baggage, and its deepening ties with betting and data industries fuel concerns about maintaining sporting integrity. While FIFA has established monitoring systems, their effectiveness against potential insider trading across decentralized global prediction markets remains unproven. Major US-based prediction platforms have updated rules to prohibit trading based on confidential information. However, the World Cup's complex ecosystem of federations, teams, and officials makes enforcement far more challenging than in domestic leagues. The event will not determine the fate of prediction markets but will critically test whether they can be integrated as a regulated event-trading infrastructure or remain a high-risk gambling-adjacent activity within global sports.

marsbit05/15 05:11

World Cup Approaches, Prediction Markets Face a Major Test

marsbit05/15 05:11

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