# Funding Related Articles

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

Exploring Physical World AGI with "Visual Reasoning", ElorianAI Raises $55 Million

ElorianAI, co-founded by ex-Google AI expert Andrew Dai and former AI specialist Yinfei Yang, has raised $55 million in early funding to develop next-generation AI systems with advanced visual reasoning capabilities. While current large models excel in text-based tasks like programming and math, they perform poorly in visual reasoning—even top models like Gemini only match a 3-year-old’s ability in basic visual benchmarks. The key limitation lies in the architecture of current vision-language models (VLMs), which first convert visual inputs into text before reasoning, losing critical spatial and structural information. ElorianAI aims to build a native multimodal model that processes and reasons directly in visual space, enabling deeper understanding of physical relationships, constraints, and environments. The company plans to release a state-of-the-art visual reasoning model by 2026, with potential applications in robotics, disaster management, engineering, healthcare, and AI hardware. By using high-quality, diverse, and synthetically generated data, ElorianAI intends to create models that don’t just perceive but truly understand and reason about the physical world—bringing us closer to visual AGI.

marsbit04/23 10:10

Exploring Physical World AGI with "Visual Reasoning", ElorianAI Raises $55 Million

marsbit04/23 10:10

VCs Sticking to the Primary Market: How Much Money Do They Still Have?

The article discusses the current state of the cryptocurrency venture capital (VC) market, based on a debate among investors from firms like Pantera Capital, Crucible Capital, and others. Key insights reveal that while VC funds are not short on capital, there is a scarcity of high-quality investment opportunities. The discussion highlights a structural shift: early-stage funding is more dispersed and competitive, with many smaller funds active, but later-stage growth capital is highly concentrated among a few large players like Paradigm and Pantera. Data indicates that over 80% of funding in 2026 went to later rounds, but this includes "graduated" fintech projects that have entered traditional VC realms. The core issue is not the availability of money, but its distribution and accessibility—early-stage founders face intense competition for funding, while later-stage funding is gatekept by a handful of major firms. This reflects a broader trend where VCs are being more selective, prioritizing long-term, proven projects over narrative-driven investments, and founders must demonstrate substantial progress and resilience to secure capital.

Odaily星球日报04/22 07:42

VCs Sticking to the Primary Market: How Much Money Do They Still Have?

Odaily星球日报04/22 07:42

Spending $200 to Buy Stars, Scamming VCs Out of Tens of Millions: The Entire GitHub Fake Star Industry Exposed

A peer-reviewed study from Carnegie Mellon University (CMU) reveals that GitHub hosts approximately 6 million fake Stars, involving 18,600 repositories and 301,000 accounts, with AI/LLM projects being the largest non-malicious category for fake engagement. The fake Star market has exploded, with prices as low as $0.03 per Star. Research shows that venture capital firms, such as Redpoint Ventures, use GitHub Star counts as a key metric for evaluating startups, with median Stars at 2,850 for seed-stage funding. For less than $200, a project can artificially meet this threshold, distorting investment landscape. Over a dozen websites openly sell GitHub Stars, and fake Star activity saw explosive growth in 2024. AI-related repositories were among the most heavily affected. Despite GitHub’s policies against fake engagement, enforcement remains inconsistent: while 90% of flagged repositories were deleted, only 57% of involved accounts were suspended. The report highlights how purchased Stars can manipulate GitHub’s Trending algorithm and influence VC funding decisions, creating a cycle where artificial metrics attract real investment.

marsbit04/21 02:59

Spending $200 to Buy Stars, Scamming VCs Out of Tens of Millions: The Entire GitHub Fake Star Industry Exposed

marsbit04/21 02:59

Crypto Whale Wallets Accumulate Ozak AI Aggressively as Presale Funding Surpasses $6.8 Million

Crypto whales are aggressively accumulating Ozak AI tokens as the project's presale funding exceeds $6.8 million, signaling strong institutional interest. Analysts view this as strategic, long-term positioning rather than speculative trading, especially as large-cap assets like Bitcoin and Ethereum face growth compression. Ozak AI's presale has sold over 1.05 billion $OZ tokens at $0.014 each, attracting sustained demand from both whales and sophisticated retail investors. The project's AI-native utility, including Prediction Agents and EigenLayer integration, along with associations with Pyth Network and other firms, adds credibility. Market pullbacks are accelerating accumulation, with whales rotating into early-stage AI assets. A projected $1 listing target suggests significant upside potential post-listing.

TheNewsCrypto04/20 15:45

Crypto Whale Wallets Accumulate Ozak AI Aggressively as Presale Funding Surpasses $6.8 Million

TheNewsCrypto04/20 15:45

DeepSeek Funding: Liang Wenfeng's 'Realist' Pivot

DeepSeek, a leading Chinese AI company, has initiated its first external funding round, aiming to raise at least $300 million at a valuation of no less than $10 billion. This move marks a significant shift from its founder Liang Wenfeng’s previous idealistic stance of rejecting external capital to maintain independence. Despite strong financial backing from its parent company, quantitative trading firm幻方量化 (Huanfang Quant), which provided an estimated $700 million in revenue in 2025 alone, DeepSeek faces mounting challenges. Key issues include a 15-month gap in major model updates, delays in its flagship V4 release, and the loss of several core researchers to competitors offering significantly higher compensation. The company is also undergoing a strategic pivot by migrating its infrastructure from NVIDIA’s CUDA to Huawei’s Ascend platform, a move aligned with China’s push for technological self-reliance amid U.S. export controls. However, DeepSeek lags behind rivals like智谱AI and MiniMax—both now publicly listed—in areas such as product ecosystem, multimodal capabilities, and commercialization. The funding round, though relatively small in scale, is seen as a way to establish a market-validated valuation anchor, making employee stock options more competitive and facilitating talent retention. It also signals DeepSeek’s transition from a pure research-oriented organization to a commercially-driven player in the global AI ecosystem.

marsbit04/20 11:19

DeepSeek Funding: Liang Wenfeng's 'Realist' Pivot

marsbit04/20 11:19

Anthropic's One Trillion vs. DeepSeek's 10 Billion

In April 2026, Anthropic's implied valuation briefly surpassed $1 trillion in secondary markets, despite its last official valuation being $380 billion. Its annualized revenue surged to $30 billion, largely driven by enterprise adoption of Claude Code. However, OpenAI accused Anthropic of inflating revenue by $80 billion through gross accounting. Anthropic is not expected to be profitable until 2027. Meanwhile, DeepSeek, after three years of rejecting external funding, announced its first fundraising round targeting a valuation over $10 billion. Founder Liang Wenfeng had prioritized independence and research over capital, citing chip shortages as a bigger constraint than funding. The move aims to address talent retention challenges and potential shifts toward commercialization. Both companies represent different AI philosophies: Anthropic’s closed-source, enterprise-focused model contrasts with DeepSeek’s open-source, research-driven approach. Each faces core challenges—Anthropic must justify its valuation with eventual profits, while DeepSeek must balance growth with its founding vision amid new investors.

marsbit04/20 05:40

Anthropic's One Trillion vs. DeepSeek's 10 Billion

marsbit04/20 05:40

Hot Interaction Collection | SimpleChain Testnet Activity is Now Live; Giggles Waitlist Application (April 16)

Hot Interactive Projects Digest: SimpleChain Testnet, Giggles Waitlist, and Arc Network Points Program SimpleChain, an RWA-focused Layer 1 blockchain, has launched its testnet campaign. Users can register on the official website, connect their wallets, bind social accounts (X, Telegram, Discord), and complete both social and on-chain tasks. The project recently raised $15 million in seed funding. Giggles, a social app combining prediction markets with content trading, has opened its waitlist for early access (currently iOS only). It recently secured $1.2 million in pre-seed funding. Arc, a new stablecoin-optimized Layer 1 blockchain from Circle, has introduced a points program. Users can earn points by registering with a Google account, completing their profile, reading articles, watching videos, and registering for events. Circle's CEO has hinted at a potential future token for governance and incentives. Early participants are encouraged to reach at least 500 points to achieve the first "Architects" tier.

Odaily星球日报04/16 02:17

Hot Interaction Collection | SimpleChain Testnet Activity is Now Live; Giggles Waitlist Application (April 16)

Odaily星球日报04/16 02:17

Silicon Valley Startup Guru Steve Blank: In the AI Era, Companies Over Two Years Old Should Start Over

Silicon Valley entrepreneur Steve Blank argues that startups founded over two years ago are likely operating with outdated business plans due to rapid AI-driven changes. He emphasizes that AI is reshaping development speed, team structures, pricing models, and competitive moats. Startups must reassess their strategies, as AI tools enable faster MVP development, shift bottlenecks from engineering to judgment and distribution, and transform software from user interfaces to outcome-driven agents. Hardware startups are also affected, with AI accelerating design testing and integration. Blank warns against sunk cost mentalities and urges founders to pivot using current tools and market realities to survive. Key shifts include moving from product-market fit to AI agent-customer outcome fit and embracing parallel development over traditional agile methods.

marsbit04/16 02:02

Silicon Valley Startup Guru Steve Blank: In the AI Era, Companies Over Two Years Old Should Start Over

marsbit04/16 02:02

Ozak AI Continues Presale Growth Past $6.67 Million as Broader Crypto Market Sees Reduced Trading Volumes

Despite a broader cryptocurrency market experiencing volatility and declining trading volumes, Ozak AI’s to attract significant investor interest, surpassing $6.67 million in its presale funding. This indicates that capital is becoming more selective, focusing on projects with strong utility and long-term potential rather than short-term speculation. Ozak AI’s artificial intelligence and data-driven automation narrative resonates with current market trends, positioning it as a relevant player in the evolving DeFi and on-chain analytics space. The presale’s steady growth during a period of overall market consolidation suggests investor confidence in its asymmetric upside potential, as participants seek early positioning ahead of a anticipated market reacceleration.

TheNewsCrypto04/15 11:05

Ozak AI Continues Presale Growth Past $6.67 Million as Broader Crypto Market Sees Reduced Trading Volumes

TheNewsCrypto04/15 11:05

TAO is Elon Musk who invested in OpenAI, Subnet is Sam Altman

The article, titled "TAO is Elon Musk who invested in OpenAI, Subnet is Sam Altman," presents a critical analysis of the Bittensor (TAO) project. It argues that Bittensor functions as a decentralized AI marketplace where TAO tokens fund AI research via subnets. However, the author highlights a fundamental flaw: subnet operators have no obligation to return any value, such as AI models or profits, back to the TAO ecosystem or its token holders. This structure is likened to Elon Musk's early investment in the non-profit OpenAI, which later commercialized its technology without returning value to its initial benefactor. The bear case posits that Bittensor is essentially a wealth transfer from crypto speculators to AI researchers ("miners"). Subnets can use TAO incentives for development and then take their successful products elsewhere, leaving TAO holders with diluted tokens from inflation and no captured value. The lack of enforced equity or binding mechanisms means the project relies on a "hope" that subnet tokens maintain value. The optimistic perspective counters that two factors could create a successful, self-sustaining economy: 1) AI's perpetual and massive resource needs could incentivize subnets to stay for continued funding, and 2) crypto has a proven ability to aggregate resources through token incentives, as seen with Bitcoin and Ethereum. The conclusion states that investing in TAO is a bet on a博弈论 (game theory) miracle—that soft incentives alone will be enough to keep the best subnets within the ecosystem and create a flywheel effect. This outcome is possible but represents a highly skewed, low-probability success scenario amidst significant risks of failure.

marsbit04/13 14:01

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