# AI Investment Related Articles

HTX News Center provides the latest articles and in-depth analysis on "AI Investment", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Insiders Betting on Musk Are Reaping 'Historic Returns'

The largest IPO in history is imminent as SpaceX, led by Elon Musk, is set to price its offering on June 12. At a targeted valuation near $2 trillion, this event will mint new billionaires from Musk's inner circle of long-time allies, rewarding their loyalty with unprecedented returns. Key beneficiaries include Antonio Gracias, Musk's close friend and confidant, who holds a 7.3% stake potentially worth over $140 billion, making him the second-largest individual shareholder. Gwynne Shotwell, President and COO since 2002, holds shares valued at roughly $2 billion. Bret Johnsen, the CFO, holds stock worth approximately $1.4 billion. Luke Nosek, a PayPal co-founder and early investor, stands to gain about $5.3 billion. The IPO filing also reveals complex and controversial financial arrangements. SpaceX has guaranteed nearly $20 billion in payments from xAI's subsidiary to Gracias's Valor Equity Partners for AI hardware leases—deals auditors flagged as "failed sale-leaseback" transactions, forcing SpaceX to record them as debt. Despite rapid revenue growth, SpaceX is not profitable, posting a $49 billion loss in 2025 and a $4.3 billion loss in Q1 2026. Capital expenditures are soaring, with over 60% directed toward AI. Public investors will inherit these losses, significant debts, and a governance structure heavily controlled by insiders, including a provision granting Musk up to a billion additional shares if one million people live on Mars.

链捕手05/26 07:41

Insiders Betting on Musk Are Reaping 'Historic Returns'

链捕手05/26 07:41

Interview with the Founder of an AI-Focused Investment Fund: Forget the False Narrative of 100x Returns, What Crypto x AI Assets Are Worth Watching?

Interview with Austin Barack, founder of AI-focused fund Relayer Capital. He emphasizes prioritizing real value over hype, especially in the Crypto x AI sector. Key assets discussed include: * **Venice:** A private AI platform where user data isn't shared with model providers. Its unique two-token model (VVV and DM) provides sustainable, capped user incentives for computation. Rapid user growth (3M) and token usage (15x in months) suggest significant upside. * **Grass:** Sells high-quality, specialized web-scraped datasets to AI labs for model training. With ~$50M+ ARR and triple-digit growth, its ~$400M valuation is seen as undervalued. * **NEAR:** Praised for its superior cross-chain swap infrastructure via intents, positioning it as crucial infrastructure for AI agents and decentralized applications. * **Akash:** A decentralized GPU compute marketplace gaining traction, with visible usage on platforms like OpenRouter. * **Investment Framework:** Shift from generic "buyback-and-burn" narratives to analyzing the "net token value flow"—whether token holders genuinely capture value from the underlying business. Markets are consolidating around a smaller set of quality projects with strong fundamentals like Venice, Grass, and NEAR, making targeted investments more effective.

marsbit05/26 01:56

Interview with the Founder of an AI-Focused Investment Fund: Forget the False Narrative of 100x Returns, What Crypto x AI Assets Are Worth Watching?

marsbit05/26 01:56

Bezos, Schmidt, Powell Jobs: The Three AI Investment Philosophies of Silicon Valley's Old Money

Jeff Bezos, Eric Schmidt, and Laurene Powell Jobs, three prominent figures from Silicon Valley's "old money," are deploying massive personal fortunes into AI, but with distinctly different investment philosophies reflecting their visions for the future. Eric Schmidt, the former Google CEO, approaches AI as a geopolitical and infrastructural arms race. Through his family office, Hillspire, he invests heavily in defense AI companies, energy infrastructure (like Bolt Data & Energy to power data centers), and space launch capabilities (Relativity Space). For Schmidt, the ultimate AI advantage lies in physical resources—energy, transport, and military application—framing it as a national competition requiring state-level strategy and endurance. Jeff Bezos is building a vertically integrated, full-stack AI empire. His bets span the model layer (via Amazon's massive investment in Anthropic), the application layer (through investments like Perplexity), and now, the physical execution layer. His new venture, Project Prometheus, with $6.2 billion, aims to inject AI into manufacturing, creating a closed loop from AI chips and cloud compute (AWS) to real-world production, potentially for Amazon's own ventures like the Kuiper satellite network. In contrast, Laurene Powell Jobs adopts a more subtle, human-centric approach through her Emerson Collective. Her AI investments focus on specific, positive-impact applications—such as AI for healthcare (Proximie, Atropos Health), education (Curipod), and European AI sovereignty (Mistral AI). A key, high-profile bet was her early backing of Jony Ive's design firm LoveFrom and its spin-off, io, an AI hardware device company later acquired by OpenAI. Her philosophy prioritizes improving human-machine interaction and addressing societal needs over sheer scale or control. These three strategies—Schmidt's focus on state-level infrastructure and security, Bezos's pursuit of end-to-end industrial integration, and Powell Jobs's emphasis on human-centered design and applied solutions—represent fundamentally different wagers on what will define the next decade of AI. While the eventual winner is unknown, the sheer scale of this capital migration from internet-era giants is already reshaping the industry's trajectory.

marsbit05/14 08:11

Bezos, Schmidt, Powell Jobs: The Three AI Investment Philosophies of Silicon Valley's Old Money

marsbit05/14 08:11

a16z Weekly Chart: Tech Giants Rely on 'Side Hustle' Investments for Income, Great AI Products Can Sell Out in a Day

a16z Weekly Charts: Four Counterintuitive Signals in Tech 1. **Super Platforms' "Other Income"**: Amazon and Google recorded exceptionally high "other income" in Q1, largely from unrealized gains in their private investment portfolios (e.g., Amazon's Anthropic stake). This contributed to over one-third of their net profit, far above the historical 5-10%. The broader trend shows tech capital expenditure is now the primary driver of US GDP growth, accounting for 55% of all business investment. 2. **AI-Generated eBook Proliferation**: Since ChatGPT's launch, monthly eBook releases on Amazon have tripled to over 300,000, flooding the platform with AI-generated content. However, research indicates this has also increased the volume of "decent" books, providing a net gain in consumer surplus by 2025. AI tools have particularly boosted productivity for established authors. 3. **Call Center Jobs Defy AI Replacement**: Contrary to predictions, call center employment in the Philippines has grown steadily from 1.15 million in 2016 to 1.9 million in 2025, with further growth projected. In the US, customer service job postings are outperforming the overall market. The key reason: the full cost of voice AI agents remains roughly equal to human agents (~$92 vs. ~$90 per day). Cases like Klarna show initial replacement can lead to quality issues and re-hiring. 4. **Rapid Adoption of AI Mobile Apps**: AI app downloads, revenue, and user time spent on mobile nearly doubled year-over-year in Q1. The market is highly dynamic, with new products like Codex quickly surpassing incumbents like Claude Code in daily installs. In the B2B space, enterprises are using multiple AI vendors, with less than 20% relying on a single supplier, indicating no winner-takes-all dynamic yet.

marsbit05/09 04:38

a16z Weekly Chart: Tech Giants Rely on 'Side Hustle' Investments for Income, Great AI Products Can Sell Out in a Day

marsbit05/09 04:38

$500 to Buy OpenAI Stock: Silicon Valley's Most Respectable Liquidity Invitation

Silicon Valley's largest venture capital platform, AngelList, has launched a new fund called USVC, allowing U.S. retail investors to buy into high-profile AI companies like OpenAI, Anthropic, and xAI with a minimum investment of $500—no accredited investor status required. Promoted by AngelList co-founder Naval Ravikant, the fund is framed as an opportunity for ordinary people to access high-growth private tech investments traditionally reserved for VCs. However, critics argue it functions more like an exit vehicle for early insiders. USVC acquires shares not through primary rounds but largely via secondary transactions—purchasing stakes from early investors, VC funds, and employees looking to cash out at peak valuations. With companies like xAI heavily weighted in the portfolio, the fund effectively channels retail money into providing liquidity for insiders who entered at much lower valuations. The fund’s structure raises concerns: shares are illiquid, with no secondary market, and buybacks are limited and discretionary. The actual annual fee reaches 3.61%, far above the advertised 1% management fee. This model parallels the "low float, high fully diluted valuation" strategy seen in crypto, where early investors profit by selling to latecomers at inflated prices. The timing—alongside similar moves by platforms like Robinhood—suggests that Silicon Valley’s sudden interest in retail inclusion may be less about democratizing access and more about securing exits for insiders.

marsbit04/23 05:31

$500 to Buy OpenAI Stock: Silicon Valley's Most Respectable Liquidity Invitation

marsbit04/23 05:31

Stanford 423-Page AI Report: US-China Gap Only 2.7%, Tsinghua DeepSeek Breaks into Global Top Ten

The 2026 AI Index Report from Stanford HAI reveals a rapidly closing gap between the U.S. and China in AI model performance, now at just 2.7%. Chinese models like DeepSeek and Tsinghua have entered the global top ten. Over 90% of cutting-edge AI models now come from industry, not academia. AI capabilities are advancing unprecedentedly—models now outperform humans in tasks like coding (SWE-bench), mathematics (IMO), and multimodal reasoning. However, "jagged frontiers" persist, with models excelling in complex tasks but struggling with basics like reading analog clocks (50.1% accuracy). Global corporate AI investment reached $581.7 billion in 2025, doubling year-over-year, with the U.S. leading. Yet, AI researcher immigration to the U.S. has plummeted 89% since 2017. AI adoption is high globally (58% workplace usage), especially in China (over 80%). Concerns include rising AI-related incidents (362 in 2025) and significant job displacement for young developers (20% decline in employment among 22-25-year-olds). The report highlights a disconnect between rapid AI progress and slower adaptation in regulation, education, and public trust.

marsbit04/15 03:10

Stanford 423-Page AI Report: US-China Gap Only 2.7%, Tsinghua DeepSeek Breaks into Global Top Ten

marsbit04/15 03:10

$700 Billion Poured into AI, Americans Taste the Bitter Fruit of Inflation First

A Federal Reserve analysis from the St. Louis Fed argues that AI optimism itself is a driver of inflation. The "news shock" of AI's revolutionary potential causes households and businesses to increase spending and investment in anticipation of future gains, pushing demand beyond current supply and creating inflationary pressure. This is supported by a Deutsche Bank experiment where AI models (dbLumina, Claude, ChatGPT-5.2) assessed a 20-40% probability that AI would raise inflation in the next year, citing surging demand for data centers, semiconductors, and electricity. They saw only a 5% chance of AI significantly reducing inflation. Massive capital expenditure underscores this demand. Amazon, Microsoft, Google, and Meta are projected to spend a combined ~$663B in 2026, a fourfold increase in four years. A significant portion funds power-hungry data centers. For example, OpenAI's "Stargate" project plans a 10-gigawatt capacity, equivalent to the entire electricity load of 16 Vermont states. U.S. data center electricity consumption is forecast to triple by 2030. While AI could eventually boost productivity and be disinflationary long-term, current data shows no such productivity jump. The U.S. economy now faces a cycle: massive AI investment fuels inflation, delays interest rate cuts, raises financing costs—yet the investment continues to accelerate. The outcome hinges on whether these AI models will ultimately make the economy more efficient, a question that remains unanswered.

marsbit04/02 11:03

$700 Billion Poured into AI, Americans Taste the Bitter Fruit of Inflation First

marsbit04/02 11:03

Meta Continues to Lay Off 20%: An "Efficiency Revolution" in the AI Era or Cost Anxiety?

Meta plans to lay off 20% of its workforce (approximately 16,000 employees), its largest reduction since late 2022, to offset high AI infrastructure costs and enhance AI-driven efficiency. According to Bernstein analyst Mark Shmulik, this move may signal Meta's successful transformation into an "AI-first" company, potentially widening its competitive advantage. The company is investing heavily in AI data centers and talent, and internal performance metrics now emphasize "AI-driven impact." While some suspect "AI greenwashing" to mask financial motives, Shmulik suggests the layoffs could reflect genuine efficiency gains from AI integration. Meta's rising revenue per employee and significant capital expenditure support this shift. If successful, Meta’s restructuring could set a template for AI-powered organizations, prompting industry-wide imitation and reactive overhauls.

marsbit03/17 13:28

Meta Continues to Lay Off 20%: An "Efficiency Revolution" in the AI Era or Cost Anxiety?

marsbit03/17 13:28

Wall Street's Hottest Trades Are All Retreating

A broad-based risk-off sentiment has swept across Wall Street, with previously popular trades from tech stocks to gold and cryptocurrencies experiencing a sharp pullback. Unlike previous sell-offs triggered by specific events, this retreat stems from accumulating concerns over stretched valuations and growing anxiety about the sustainability of the AI-driven rally. Key developments include: the S&P 500 falling for three consecutive sessions, the Nasdaq 100 posting its worst decline since last April, silver plunging 17% after hitting record highs, and Bitcoin crashing 10%—erasing gains made since the previous presidential election. Meanwhile, U.S. Treasuries rebounded as a traditional safe haven. Despite strong earnings, tech giants like Alphabet and Amazon faced selling pressure due to concerns over their aggressive spending plans, particularly in AI. The market is reevaluating whether massive AI investments will yield returns and which companies might be left behind. Additional uncertainties include potential changes in Federal Reserve leadership and overall monetary policy direction. The sell-off reflects a broader shift toward defensive positioning, as investors question whether the momentum-driven rally in tech and crypto has been overextended and due for a correction.

marsbit02/06 02:14

Wall Street's Hottest Trades Are All Retreating

marsbit02/06 02:14

Dialogue with Wang Qiao: Currently, Crypto Tokens Don't Attract Me Much, Heavily Invested in Google in 2026

In a podcast interview, Qiao Wang discusses his investment strategy and views on AI in 2026. He expresses caution about the current optimistic market sentiment, holding 40% of his portfolio in cash. His remaining investments are split 50/50 between stocks and Bitcoin, with minimal exposure to other crypto tokens. His largest stock holdings are Google and Tencent, citing their strong fundamentals and undervaluation. He also sees potential in AI-driven biotech. Wang highlights the breakthrough capabilities of Claude Opus 4.5, noting its ability to execute complex coding tasks from simple natural language prompts, blurring the line between chatbots and coding assistants. He believes AI is dramatically boosting startup productivity, potentially leading to one or two-person unicorn companies. While software moats are weakening, he argues that giants like Google and Adobe retain strong enterprise-level defenses. He advises everyone to learn to "code" using AI automation tools to optimize personal workflows, as these technologies will significantly amplify the productivity of efficient individuals. For health, he emphasizes the irreplaceable basics: diet, sleep, and exercise, avoiding extreme optimization due to the negative effects of stress.

marsbit01/20 08:40

Dialogue with Wang Qiao: Currently, Crypto Tokens Don't Attract Me Much, Heavily Invested in Google in 2026