# Venture Capital Related Articles

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

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit06/20 06:06

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit06/20 06:06

Either Go Full-Stack or Get Out: The Calculations Behind xAI's $60 Billion Acquisition of Cursor

The article discusses xAI's $60 billion stock acquisition of Anysphere, the parent company of the AI coding tool Cursor, arguing that the core motivation is not market share but access to high-quality training data from its 7 million daily developers. It posits that to become a major AI player, a company must build a full-stack encompassing compute, model, and application layers. This thesis is illustrated by Anthropic's 540x revenue growth in 28 months, largely driven by its coding product, Claude Code, which captured 54% of the enterprise AI programming market. The author, a VC, contends that full-stack integration creates sustainable unit economics for model training and provides proprietary data for defensible competitive advantages, predicting a wave of model companies aggressively building or acquiring application-layer products. The central takeaway is that in an era where building products is 10x easier, ambition must be 10x greater to succeed.

marsbit06/18 09:41

Either Go Full-Stack or Get Out: The Calculations Behind xAI's $60 Billion Acquisition of Cursor

marsbit06/18 09:41

Buffett and VC, One Must Lose

The article examines the perceived investment conflict between Warren Buffett's value-oriented approach and the current aggressive, tech-focused venture capital (VC) landscape, particularly in AI. It notes that while direct public debate is limited, underlying tensions exist as Buffett's Berkshire Hathaway holds record cash, signaling caution, while VCs pour unprecedented capital into tech. The piece revisits two historical confrontations: the 2000 dot-com bubble, where Buffett warned against speculative tech investments despite market euphoria, and his 2007-2017 bet against hedge funds, which he won by advocating low-cost index funds. In both cases, Buffett opposed investing based on hype, excessive fees, or complexity rather than concrete business value. The core argument is that Buffett does not oppose innovation or VC itself but critiques investment decisions detached from fundamentals—such as ignoring profitability, over-relying on narratives like “this time is different,” or obscuring valuation with complex structures. For the current AI boom, he would likely question sustainable business models and cash flows amid high capital costs. The conclusion reiterates Buffett's “Mr. Market” parable: investors should use market volatility to their advantage, not be guided by it, emphasizing that disciplined valuation, not sentiment, should drive decisions.

marsbit06/18 03:10

marsbit06/18 03:10

Historical Bottom Signal Reappears? Messari Valued at $300 Million Sells for $10 Million

Messari, a major crypto data and research platform once valued at $300 million, was sold to rival Blockworks for just over $10 million in June 2026. This sale marks a broader, quiet contraction in the crypto industry. Data platforms like DappRadar and Parsec have shut down, media outlets like CoinDesk have been sold at steep discounts, and companies across the sector are laying off staff or pivoting to AI, which is disrupting traditional research and data business models. Venture capital investment in crypto has plummeted, with funding in Q1 2026 at its lowest since 2020, as capital and talent shift aggressively toward AI. Prominent crypto investors are leaving the space, and many funds are struggling. However, these extreme pessimism signals may historically indicate a market bottom. Bitcoin is down nearly 50% from its 2026 high, the Crypto Fear & Greed Index has been in "extreme fear" for months, and long-term Bitcoin holders control a near-record 80% of the supply. Similar combinations of deeply negative signals—including low VC activity and distressed asset sales—preceded major bull markets in 2018, 2020, and 2022. While Messari's downfall symbolizes a tough period, it also aligns with patterns seen at cycle lows.

marsbit06/17 01:07

Historical Bottom Signal Reappears? Messari Valued at $300 Million Sells for $10 Million

marsbit06/17 01:07

Hardcore First Look | Ocean Embodied Intelligence Company 'Shihang Intelligence' Secures Record-Breaking 1 Billion in Funding, Zhu Xiaohu, Temasek Place Bets

Breaking News | Ocean Embodied Intelligence company "Shihang Intelligent" secures a record-breaking 1 billion RMB (approximately 10 billion yuan) in Series A financing, with investment from Zhu Xiaohu and Temasek. Author: Qiu Xiaofen | Editor: Yuan Silai Ocean Embodied Intelligence company "Shihang Intelligent" has completed its Series A funding round, raising over 1 billion RMB. This marks the largest single funding round in the global marine robotics field to date. Investors include upstream momentum funds from chip companies "Moore Thread" and "Kunlunxin," Singapore's state-owned investment platform Vertex Growth, and listed company Dyneo, among others. Existing investors like GSR Ventures (whose founder Zhu Xiaohu has invested for the fifth time), Vertex Ventures China, Hua Ying Capital, and Long Capital also significantly increased their investments. Founder and CEO Chen Xiaobo, a 1989-born alumnus of Harbin Engineering University, is a long-time expert in underwater robotics. He received the National Defense Science and Technology Progress Award at age 28 (the youngest recipient) and led the development of China's first commercial underwater cleaning robot. The funds will be used for core technology R&D, global market expansion, and building the industry chain ecosystem to scale the application of marine robots in complex underwater scenarios. The ocean is considered one of the most challenging environments for robotics due to low light, high turbidity, complex currents, limited communication, high pressure, and corrosion. "Shihang Intelligent" focuses on developing core underlying technologies for marine robots, covering six key systems: power, control, sensing, navigation, sealing, and deployment. Its robots are capable of operating at depths from 0 to 10,000 meters with full degrees of freedom, performing complex maneuvers, autonomous navigation, and multi-robot collaboration. Applications include ship cleaning, underwater security, offshore wind power, marine ranching, and seabed inspection. The company's order value for the first half of 2026 alone has exceeded 1 billion RMB. Its "Orca Robot" is used by major shipping companies and has performed maintenance on over a thousand large vessels. In April of this year, the company launched its ocean embodied large model "Cangqiong CEORION." Unlike traditional remote-controlled or pre-programmed robots, this model integrates environmental perception, task understanding, and action generation into a single end-to-end architecture. Trained on millions of hours of commercial operation data and simulation data, it covers 12 major underwater operation scenarios. In simulations, it achieved over 90% task success rate and over 70% zero-shot adaptation capability to unseen environments. A built-in physics reasoning module reduces collision risk by 80%, enabling autonomous operation even with weak or no communication. Recently, "Shihang Intelligent" was selected as a core technology partner for Singapore's Maritime and Port Authority national hull inspection and cleaning program. These advancements indicate marine robotics is moving from pilot projects to scaled applications, with real-world operations generating valuable data to continuously improve robot capabilities. CEO Chen Xiaobo stated the company will continue investing in core marine robotics technology, the embodied intelligence model, and global application scenarios to expand into more high-risk, high-difficulty, and high-value underwater operations.

marsbit06/15 01:58

Hardcore First Look | Ocean Embodied Intelligence Company 'Shihang Intelligence' Secures Record-Breaking 1 Billion in Funding, Zhu Xiaohu, Temasek Place Bets

marsbit06/15 01:58

Partner at Pantera Capital: How Tokenization Could Reshape the Private Equity and Early-Stage Investment Ecosystem?

The article discusses how tokenization could reshape private equity and early-stage investment. Historically, public markets allowed early access to high-growth companies, but today's leading tech firms (e.g., Stripe, SpaceX) remain private for over a decade, with private capital capturing their growth phase. Temporary fixes like SPVs and secondary markets have emerged but are not fundamental solutions. Tokenized venture assets present a potential solution, converging three trends: the explosive growth of SPVs, the rapid expansion of tokenized real-world assets (RWA), and the breakdown of the "token vs. equity" consensus, where project tokens have become subordinate to equity in value capture. This creates an opportunity for tokenized startups to offer public, liquid exposure to venture-scale returns. The landscape includes various models: equity-backed tokens via SPVs or funds (e.g., PreStocks, Robinhood Ventures) and synthetic perpetual futures offering only price exposure (e.g., TradeXYZ, Ventuals). Trading volume is heavily concentrated in late-stage, pre-IPO companies like SpaceX and Anthropic and shows a power-law distribution across platforms. Key challenges and opportunities include aligning with founder/team interests, which can be addressed through models like tokenized startup baskets, accelerator models, or community token distributions. Expanding into non-U.S. jurisdictions with less efficient capital markets offers another path. For perpetual futures models, the central challenge is accurate price discovery for private assets without reliable oracles; TradeXYZ's success with Cerebras Systems pre-IPO pricing demonstrates potential. Regulatory and legal structures for these tokenized instruments remain nascent and untested. In conclusion, tokenization represents an effort to restore the early, liquid access to high-growth companies that public markets once provided. It could also resolve the identity crisis of project tokens by granting them genuine claims on venture-scale upside, potentially fulfilling crypto's original promise with more mature infrastructure.

链捕手06/10 12:38

Partner at Pantera Capital: How Tokenization Could Reshape the Private Equity and Early-Stage Investment Ecosystem?

链捕手06/10 12:38

From 'The Big Short' to San Francisco: The Revelry and Dizziness Within the AI Bubble

From "The Big Short" to San Francisco: The Frenzy and Dizziness in the AI Bubble The article captures the intense, frenetic atmosphere in San Francisco, the epicenter of the current AI boom. Drawing a parallel to the "smell of money" from *The Big Short*, the author observes a city gripped by a singular status game centered entirely on AI and technology. This manifests in a palpable, caffeine-fueled anxiety ("people are shaking"), rampant comparison using vanity metrics like funding rounds, and pervasive "Big Bubble Behavior." The piece explores the city's stark contrasts: its dystopian streets versus beautiful vistas, and the disconnect between the doomsday concerns of some AI researchers and the optimistic, growth-focused "GTM" teams. It critiques the obsession with "math genius" founders as the new ticket to outsized returns, akin to scouting sports prodigies. Referencing economic historian Carlota Perez's "frenzy phase" and Karl Polanyi's "double movement," the author frames the boom as a period where financial speculation detaches from fundamentals, with society potentially becoming subordinate to a new economic force driven by "geniuses in data centers." Ultimately, while acknowledging the unprecedented wealth creation and party-like energy, the article concludes with cautionary advice: when the music is playing, you should dance, but don't get drunk. The core reminder is to stay grounded, avoid distorted judgment, and maintain perspective amidst the euphoria.

marsbit06/08 12:11

From 'The Big Short' to San Francisco: The Revelry and Dizziness Within the AI Bubble

marsbit06/08 12:11

Silicon Valley Moguls Gather for 'Werewolf' Reality Show, Billionaires Engage in Power Gameplay

Silicon Valley elites, including OpenAI's Sam Altman, Anduril's Palmer Luckey, and Signal's Moxie Marlinspike, gathered not for a tech discussion, but to film a reality show playing "Mafia" (the US version of Werewolf). The show, titled *MAFIA*, is produced by the legendary venture capital firm Founders Fund. Held at the historic Tosca Cafe in San Francisco, the game revealed participants' real-time decision-making and personalities under pressure. Altman applied analytical logic, Luckey's playful style made him an early target, and Marlinspike skillfully shifted the group's thinking. The session quickly devolved into a battle of intuition and accusation after Figma's Dylan Field was eliminated first. More than just entertainment, the show is seen as a public experiment and a rebellion against standard VC narratives. It demonstrates how Silicon Valley's new elite leverages "infotainment" to build influence. As traditional media wanes, figures like Founders Fund are taking control of content creation, understanding that narrative control and public performance are becoming crucial capital in the internet age. The strategic thinking, persuasive communication, and rapid decision-making displayed in the game mirror the very skills that drive their real-world success.

marsbit06/08 01:13

Silicon Valley Moguls Gather for 'Werewolf' Reality Show, Billionaires Engage in Power Gameplay

marsbit06/08 01:13

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit06/05 11:18

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit06/05 11:18

Which Companies Has NVIDIA's "Three-Track Investment Architecture" Invested In?

NVIDIA's investment strategy operates through a "three-track architecture," not just its NVentures venture arm. Corporate Development handles massive strategic bets (e.g., $30B in OpenAI, $10B in Anthropic, $20B in Synopsys). NVentures, a small team, focuses on early-stage, financial investments across sectors like quantum computing (Alice & Bob, PsiQuantum), AI infrastructure (OpenRouter, Tensormesh), and biotech. The NVIDIA Inception accelerator provides non-monetary support. This system allows NVIDIA to nurture startups and lock in strategic partners, creating a vast AI ecosystem. This aggressive capital deployment has drawn scrutiny. Critics like Michael Burry and EU regulators question potential "circular financing," where NVIDIA's equity investments in companies (e.g., CoreWeave, OpenAI) facilitate those companies' purchases of NVIDIA hardware, potentially inflating revenue. Supporters view it as a necessary "virtuous cycle" to secure supply and demand in a compute-scarce market. While NVentures' smaller deals appear like traditional VC, its role within the larger, controversial investment framework remains a point of debate.

marsbit06/04 06:42

Which Companies Has NVIDIA's "Three-Track Investment Architecture" Invested In?