Indepth Research

Provide in-depth research reports and independent analysis, leveraging data, technology, and economic insights to deliver a comprehensive examination of the blockchain ecosystem, project potential, and market trends.

After the Developer Count Halved: Crypto Is Not Dead, It's Just Ceding Talent to AI

Following a significant decline in the total number of open-source crypto developers, from a peak of 45K in 2022 to approximately 23K by 2026, this article argues the industry is undergoing a "talent deleveraging" rather than a collapse. The exodus primarily consists of newcomers who entered during the bull market, while the core of experienced developers (2+ years) has grown to a record high, contributing around 70% of code. These established builders are concentrating in ecosystems with real users and revenue, like Bitcoin and Solana. The article posits that crypto has cultivated a unique skill set in building trustless, autonomous systems with near-zero tolerance for error—a capability now finding high demand in the AI era. As AI scales, it faces structural gaps in decentralized compute aggregation, multi-agent coordination/incentive alignment, and autonomous payment infrastructure. Crypto builders are transitioning their expertise to address these exact problems. Examples include CoreWeave (mining to AI compute), Hyperbolic (decentralized compute verification), EigenLayer (extending restaking mechanisms to AI agent governance), and the x402 protocol (enabling AI agent micro-payments via stablecoins). The role of the crypto builder is evolving from writing smart contracts to designing the rule-based, trust-minimized frameworks necessary for AI-native systems. Venture capital is increasingly funding this convergence, viewing it as a structural opportunity rather than a narrative shift. The core talent and systemic design principles from crypto are not disappearing but being re-priced and applied to the foundational challenges of scalable AI.

链捕手05/18 13:37

After the Developer Count Halved: Crypto Is Not Dead, It's Just Ceding Talent to AI

链捕手05/18 13:37

A Quick Look at the Latest Moves of the 24-Year-Old 'AI Stock God': Sixty Percent of the Portfolio Hedging Against Semiconductor Downturn

24-year-old AI investing prodigy Leopold Aschenbrenner's fund, Situational Awareness LP, has disclosed its Q1 2026 13F holdings. The fund's total portfolio nominal value surged 148% to $13.7 billion, driven by both investment gains and significant new capital inflows. The most striking move was the establishment of massive short-term hedges against potential volatility in the AI semiconductor sector. Over 60% of the fund's nominal exposure is now in put options (bets on declines) targeting major AI hardware stocks like NVIDIA (NVDA), VanEck Semiconductor ETF (SMH), Broadcom (AVGO), and AMD. Notably, the fund also holds call options (bets on rises) on some names like Micron (MU) and TSMC, indicating it expects extreme price swings in these stocks. Alongside these hedges, the fund remains a long-term bull on AI infrastructure. It significantly increased its equity stakes in companies like GPU cloud provider CoreWeave (CRWV) and added to positions in power/energy infrastructure firms like Bloom Energy (BE), albeit after taking substantial profits on the latter. The fund also exited positions in optical communication hardware (LITE, COHR) and reduced leverage by clearing out large call option positions on Intel and CoreWeave. In essence, the portfolio reflects a dual strategy: cautious on near-term semiconductor valuations and potential over-extension, while maintaining a conviction that the true long-term bottlenecks and value will be in the underlying infrastructure powering the AI revolution—such as energy, data centers, and compute availability.

marsbit05/18 13:31

A Quick Look at the Latest Moves of the 24-Year-Old 'AI Stock God': Sixty Percent of the Portfolio Hedging Against Semiconductor Downturn

marsbit05/18 13:31

BNB Chain Releases Research Report, Exploring the Path to Post-Quantum Cryptography Migration for BSC

BNB Chain has released a new research report exploring a potential migration path for BNB Smart Chain (BSC) to post-quantum cryptography (PQC). The study assesses the feasibility and performance impact of replacing traditional blockchain cryptography with quantum-resistant alternatives, aiming to ensure long-term network security. Key areas evaluated include post-quantum transaction signatures (proposing ML-DSA-44), validator signature aggregation, transaction verification, public key storage, and cross-regional network performance under increased data loads. A major finding is that while technically feasible now, achieving PQC-readiness involves significant scalability trade-offs. Test data showed transaction size increased from ~110 bytes to ~2.5 KB, block size grew from ~110 KB to ~2 MB, and native transfer TPS decreased from 4,973 to 2,997. The primary performance bottleneck was identified as increased network transmission overhead due to larger data volumes, rather than the signature verification process itself. Notably, the pqSTARK aggregation technique proved efficient, compressing validator signatures at a ~43:1 ratio, which helps manage consensus layer overhead. The report clarifies this is a research-oriented exploration, not a response to an imminent threat, and notes that areas like P2P handshakes and KZG commitments require further study and broader ecosystem coordination.

链捕手05/18 13:24

BNB Chain Releases Research Report, Exploring the Path to Post-Quantum Cryptography Migration for BSC

链捕手05/18 13:24

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market?

When Compute is Commoditized: How Far Away is a GPU Futures Market? The article explores the potential emergence of a futures market for computing power ("compute"), akin to markets for commodities like oil or electricity. It uses a five-dimension framework to assess the market's maturity for sustaining robust futures trading. **Current Market Assessment (Scorecard):** * **Supply Fragmentation:** 🔴 **Red.** Supply is highly concentrated, dominated by a few hyperscale cloud providers. * **Price Volatility:** 🟢 **Green.** GPU pricing is already highly volatile. * **Physical Settlement Infrastructure:** 🟢 **Green.** Early infrastructure exists at the OTC/broker level. * **Standardization:** 🔴 **Red.** Compute lacks a standardized, tradable unit (e.g., an H100 hour is not uniform). * **Lack of Substitutes:** 🟡 **Yellow.** Vertically integrated players can hedge internally, while others are forced to be long. **Conclusion:** The overall scorecard suggests a robust futures market is premature. The market has volatility and early settlement infrastructure but lacks the necessary supply fragmentation and standardization for large-scale price discovery. Most activity remains OTC. **Key Unanswered Questions & Hypotheses:** The article posits that the market could evolve in the next 1-2 years: 1. **Supply:** May become *moderately more fragmented* due to new cloud providers, cheaper power locations, and demand from long-tail users (e.g., startups running open-source model inference). 2. **Standardization:** Could emerge from the growing **inference** workload (expected to be >65% of AI compute demand by 2029), which has more homogeneous hardware requirements than custom training workloads. Widespread adoption of **open-source model weights** is seen as a key catalyst for democratizing inference and driving infrastructure standardization. 3. **Traded Unit:** The most viable layer for trading is likely the **"chip-instance-hour"** (powered, usable compute time), traded similarly to electricity in regional contracts with spot/futures overlays. Trading at the upstream "chip" layer is unlikely due to supply concentration, while the downstream "token" layer faces challenges due to lack of uniformity across AI models.

链捕手05/18 09:04

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market?

链捕手05/18 09:04

Annual Loss Rate Only 0.03%: Data Disassembles the Real Risk of DeFi Lending

DeFi lending's real-world annual loss rate from hacks and exploits is approximately 0.03% of the Total Value Locked (TVL), excluding cross-chain bridge incidents. This analysis, based on data from DeFi Llama, shows that while lending protocols are frequent targets due to their concentrated assets, the actual financial impact relative to the sector's massive scale is minimal. The overall DeFi hack total of $77.51B is heavily skewed by cross-chain bridge breaches. Removing those, losses drop to $45.18B, with lending and AMM protocols being the most affected non-bridge categories. Risk has significantly improved as the ecosystem has matured. For the year leading to May 2026, net losses in EVM and Solana lending protocols were $30.1 million against an average daily TVL of $99.6 billion, resulting in the 0.03% loss rate. Notably, the industry's asset recovery capability, exemplified by the full recovery and surplus from the Euler Finance hack, mitigates net losses, with a ~20% recovery rate for non-bridge lending incidents. Attack scale follows a log-normal distribution, meaning most incidents are small, and catastrophic losses are rare. This demonstrates that diversification across protocols is an effective risk mitigation strategy. The data indicates that DeFi lending has evolved into a measurable, compartmentalized, and relatively low-risk sector within the broader digital asset landscape.

marsbit05/18 07:46

Annual Loss Rate Only 0.03%: Data Disassembles the Real Risk of DeFi Lending

marsbit05/18 07:46

Vitalik: We Shouldn't Oppose AI, But Create Sanctuaries

Summary: In a podcast, Ethereum co-founder Vitalik Buterin discusses the human response to advancing AI. He argues the core risk isn't AI's intelligence, but humanity's passive reliance on centralized systems and AI, which erodes privacy and personal agency. His solution is not to fight AI, but to build "sanctuary technologies"—tools like Ethereum that offer safe, optional spaces where individuals can retain sovereignty and freedom of choice without being forced into a single system. Buterin reflects on his shift from an "autopilot" mode in his youth to actively "piloting" his life and work. He stresses the importance of maintaining "manual mode" activities—like learning actively and performing tasks without AI assistance—to prevent mental atrophy and preserve independent thought. For builders, his advice is to prioritize technologies that protect human agency, avoid outsourcing all strategic thinking, and actively engage in serendipitous, real-world interactions. He repositions Ethereum/crypto not as a fix for legacy systems like the dollar, but as a parallel, voluntary option. In an era of increasing centralization, the freedom to opt-in or opt-out becomes invaluable. The key takeaway is that the AI era demands greater human proactivity; the scarcest resource will remain actively thinking, sovereign individuals.

marsbit05/17 03:03

Vitalik: We Shouldn't Oppose AI, But Create Sanctuaries

marsbit05/17 03:03

Conversation with Patagon Founder: Revealing the Inside Story of Anthropic's Secondary Market

**Summary: Inside Anthropic's Massive, Opaque Secondary Market** In a revealing interview, Patagon founder Dio Casares pulls back the curtain on the booming, high-risk secondary market for shares in companies like Anthropic. This private market, fueled by companies staying private longer and massive funding rounds, is estimated to involve hundreds of billions of dollars. Casares distinguishes between two types of "secondary" trading: 1. **Company-approved SPV (Special Purpose Vehicle) sales:** Where new capital flows into the company, often facilitated by select private equity firms. Anthropic supports this to manage liquidity and pre-IPO selling pressure. 2. **The "gray" market:** Platforms like Hive and Forge that match buyers and sellers, often creating pricing confusion and competing with official funding rounds. These intermediaries are widely disliked by companies. The market structure is complex and fragmented, relying heavily on personal connections. Brokers connect buyers and sellers, often layering multiple SPVs to pool capital, with single transaction fees as high as 10%. Strikingly, some finance professionals earn more from this trading than from their primary investment roles. **Key risks highlighted include:** * **High Fraud Rates:** An estimated 10-20% of transactions involve fake stock certificates or sellers who take payment without having the shares. * **Complex, Risky Structures:** Nested SPVs, "forward contracts" on employee equity, and tokenized private equity create layers of opacity. This is exemplified by a recent incident where an xAI employee's shares were revoked after an espionage allegation, leaving buyers empty-handed. * **Post-IPO "Settlement Hell":** After an IPO, delays in distributing shares through multiple SPV layers and decisions by fund managers to hold onto shares could trigger years of lawsuits as downstream investors are locked out. **For small investors** holding positions through tokenized vehicles or layered SPVs, it's often impossible to verify the underlying asset. Casares advises caution: if the investment feels wrong, consider exiting. As the private market now surpasses IPO fundraising, this "wild west" ecosystem faces a looming reckoning. While it will likely professionalize, the post-IPO period for a company like Anthropic could unleash a wave of disputes, exposing the vulnerabilities built into this frenzied, largely unregulated marketplace.

marsbit05/17 01:08

Conversation with Patagon Founder: Revealing the Inside Story of Anthropic's Secondary Market

marsbit05/17 01:08

Ford's stock price surged 20% in a single day: The traditional automaker is also pivoting to AI

Ford's stock surged 20% after it announced the creation of a new subsidiary, Ford Energy, investing $2 billion to build a 20 GWh energy storage system plant. Morgan Stanley valued this business at $10 billion, betting its margins could far exceed Ford's traditional auto division. The valuation is tied to a projected 49 GW U.S. power shortage by 2028, driven by booming data center demand concentrated in four key corridors. However, the massive subsidies funding this AI infrastructure boom, like a $3.3 billion package for a Meta data center in Louisiana, face growing scrutiny. Public opposition to local data centers (70%) now exceeds that for nuclear plants due to their strain on grids, limited job creation, and high fiscal cost. Ford's $8 billion market cap gain hinges on the continuation of this ecosystem: sustained subsidies, unmet power demand, and manageable public backlash. If any of these constraints—physical power shortages, state budget limits, or voter opposition—tightens, a widespread repricing could follow.

marsbit05/15 11:45

Ford's stock price surged 20% in a single day: The traditional automaker is also pivoting to AI

marsbit05/15 11:45

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

Raoul Pal: What Does Kevin Warsh Becoming Fed Chair *Really* Mean?

The Senate narrowly confirmed Kevin Warsh as the 17th Fed Chair. This analysis argues his appointment is part of a strategic economic framework, not a partisan shift. Warsh, a tech investor, uniquely believes in an AI-driven productivity boom. His mandate is to enable this by avoiding restrictive monetary policy, unlike conventional models that would hike rates against inflation. He is expected to shift Fed focus from headline to core inflation, signaling tolerance above 2%, and initiate a formal policy review. The goal is a coordinated "Fed-Treasury Accord" with Secretary Bessant, mirroring the 1990s Greenspan playbook. Bessant's international deals aim to secure foreign demand for U.S. debt, while Warsh's Fed ensures policy supports this structure through lower rates and dollar depreciation. Key implications: lower rates by 2027, a weaker dollar, and outperformance for assets linked to AI, crypto, and gold. The critical variable is the bond market; if long-term yields rise too sharply, the entire framework could fail. The next six months will test whether the market gives Warsh the space to implement this plan.

marsbit05/15 07:06

Raoul Pal: What Does Kevin Warsh Becoming Fed Chair *Really* Mean?

marsbit05/15 07:06

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