# Сопутствующие статьи по теме AI

Новостной центр HTX предлагает последние статьи и углубленный анализ по "AI", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Funding Weekly Report | 14 Public Funding Events, Kalshi Completes $10B New Funding Round at $220B Valuation Led by Coatue Management

Weekly Funding Roundup: 14 Deals and $10.49B+ in Total Funding, Led by Kalshi's $1B Round Last week (5.4-5.10) saw 14 notable funding events in the global blockchain ecosystem, raising over $10.49 billion in total. Key highlights include Kalshi, a prediction market platform, securing a $1 billion round led by Coatue Management, reaching a $22 billion valuation. The platform now boasts ~2 million MAUs and $178B in annualized trading volume. In DeFi, regulated on-chain reinsurer OnRe raised $5 million in Series A funding, and Bitcoin-backed credit protocol Saturn Credit completed a $2 million seed round. For Infrastructure & Tools, OpenTrade raised $17 million to expand its stablecoin yield infrastructure, and RWA platform Balcony secured $12.7 million to deploy its property settlement service in the US. Centralized Finance saw one deal: AI-driven trading platform Stockcoin.ai completed a seed round led by Amber Group. In the prediction market sector alongside Kalshi, AI-powered platform Elastics raised $2 million. Other notable deals include SC Ventures' strategic investment in crypto market maker GSR and Centrifuge securing a "seven-figure" investment from Coinbase to become a core RWA partner for Base. On the investor side, Haun Ventures raised a new $1 billion fund targeting crypto and AI, and Multi Investment raised ~$616 million to focus on blockchain and Web3 investments.

marsbit05/11 03:15

Funding Weekly Report | 14 Public Funding Events, Kalshi Completes $10B New Funding Round at $220B Valuation Led by Coatue Management

marsbit05/11 03:15

"The Big Short" Burry and Legendary Investor Jones Warn in Unison: AI Frenzy Reminiscent of Pre-Crash 2000

Michael Burry, famous for predicting the U.S. housing market crash, warns that the current stock market obsession with artificial intelligence resembles the final stages of the dot-com bubble. In a recent post, Burry noted that financial media is dominated by AI talk, and markets no longer react logically to economic data like jobs reports or consumer sentiment. Instead, stocks are rising simply because they have been rising, driven by a widely accepted two-letter narrative—AI—akin to late 1999 and early 2000. He compared the Philadelphia Semiconductor Index's sharp rally to the period just before the March 2000 tech crash. Similarly, legendary macro trader Paul Tudor Jones compared the AI-driven rally to the pre-dot-com bubble era of 1999, suggesting the bull market might have another year or two to run. However, he cautioned that if valuations continue to expand—potentially pushing the stock market capitalization to GDP ratio to 300-350%—a severe and dramatic correction would eventually follow. Both investors highlight the exuberant, speculative fervor around AI stocks, drawing parallels to past market manias preceding significant downturns.

marsbit05/11 02:54

"The Big Short" Burry and Legendary Investor Jones Warn in Unison: AI Frenzy Reminiscent of Pre-Crash 2000

marsbit05/11 02:54

Crypto ETF Weekly Report | Last Week, U.S. Bitcoin Spot ETFs Saw Net Inflows of $631 Million; U.S. Ethereum Spot ETFs Saw Net Inflows of $70.3 Million

Crypto ETF Weekly Report: US Bitcoin spot ETFs saw a net inflow of $631 million last week, bringing total net assets to $106.66 billion. BlackRock's IBIT led inflows with $596 million. US Ethereum spot ETFs recorded a net inflow of $70.3 million, with total net assets reaching $13.73 billion, primarily driven by BlackRock's ETHA ($100 million). In Hong Kong, Bitcoin spot ETFs had a net inflow of 15.57 BTC (assets: $320 million), while Ethereum spot ETFs saw no inflows. On the options front, Bitcoin spot ETF options saw a total notional trading volume of $976 million and a put/call ratio of 2.90, indicating heightened short-term trading activity and a bullish sentiment. Additionally, a market report noted Coinbase and Kraken dominate 22% of AI citations in the US crypto sector, with BlackRock's IBIT leading responses to "Bitcoin ETF" queries. Meanwhile, the SEC has delayed its review of the first batch of prediction market ETFs linked to real-world events like election outcomes.

链捕手05/11 02:02

Crypto ETF Weekly Report | Last Week, U.S. Bitcoin Spot ETFs Saw Net Inflows of $631 Million; U.S. Ethereum Spot ETFs Saw Net Inflows of $70.3 Million

链捕手05/11 02:02

Your Claude Will Dream Tonight, Don't Disturb It

This article explores the recent phenomenon of AI companies increasingly using anthropomorphic language—like "thinking," "memory," "hallucination," and now "dreaming"—to describe machine learning processes. Focusing on Anthropic's newly announced "Dreaming" feature for its Claude Agent platform, the piece explains that this function is essentially an automated, offline batch processing of an agent's operational logs. It analyzes past task sessions to identify patterns, optimize future actions, and consolidate learnings into a persistent memory system, akin to a form of reinforcement learning and self-correction. The article draws parallels to similar features in other AI agent systems like Hermes Agent and OpenClaw, which also implement mechanisms for reviewing historical data, extracting reusable "skills," and strengthening long-term memory. It notes a key difference from human dreaming: these AI "dreams" still consume computational resources and user tokens. Further context is provided by discussing the technical challenges of managing AI "memory" or context, highlighting the computational expense of large context windows and innovations like Subquadratic's new model claiming drastically longer contexts. The core critique argues that this strategic use of human-centric vocabulary does more than market products; it subtly reshapes user perception. By framing algorithms with terms associated with consciousness, companies blur the line between tool and autonomous entity. This linguistic shift can influence user expectations, tolerance for errors, and even perceptions of responsibility when systems fail, potentially diverting scrutiny from the companies and engineers behind the technology. The article concludes by speculating that terms like "daydreaming" for predictive task simulation might be next, continuing this trend of embedding the idea of an "inner life" into computational processes.

marsbit05/11 00:15

Your Claude Will Dream Tonight, Don't Disturb It

marsbit05/11 00:15

Duan Yongping's Bottom-Fishing in CoreWeave Is Turning into a Battleground for Bulls and Bears

CoreWeave's Q1 2026 earnings report has intensified the ongoing bull-bear battle over the AI infrastructure stock. While revenue doubled year-over-year to $2.08B and the firm's remaining performance obligation (RPO) surged to nearly $100B, its net loss more than doubled to $740M. The critical point of contention is profitability: while adjusted EBITDA margin was a robust 56%, the adjusted operating margin collapsed to just 1% due to soaring infrastructure and sales costs. A weaker-than-expected Q2 revenue guidance further triggered an 11.4% single-day stock drop. The bull thesis hinges on CoreWeave's massive order backlog, deep strategic ties with NVIDIA (as a customer, investor, and key supplier), and a diversified client base now including Anthropic and Meta. The bear case focuses on the "scale at all costs" model, where expanding revenue leads to wider losses, ballooning debt ($25B), and massive capital expenditures ($6.8B in Q1). Insider selling by executives contrasts with a notable new investor: Chinese investor Duan Yongping initiated a small position (0.12% of his portfolio) in Q4 2025 near the stock's lows. The coming Q2 report is seen as a key test for management's promise of a profit margin recovery.

marsbit05/11 00:09

Duan Yongping's Bottom-Fishing in CoreWeave Is Turning into a Battleground for Bulls and Bears

marsbit05/11 00:09

China's Version of 'Tech Burning Man' Debuts in Shanghai, muShanghai Creates a Global Geek 'Pop-up City'

From May 10 to June 6, 2026, the inaugural muShanghai "Pop-up City" experiment, dubbed China's version of a "tech Burning Man," launched in Shanghai. Co-organized by the international open-source community The Mu and the Hongqiao Alibaba Center, this 28-day event aimed to build a global "parallel city" for geeks, attracting over 800 participants from more than 50 countries, including former OpenAI engineers and startup founders. The program featured four themed weeks: AI Week, Biotech Week, Robotics Week, and Culture Week, hosting nearly 100 sessions like ClawCon 2026. Activities ranged from discussions on AI safety and consumer apps to robot battles and cyberpunk culture, culminating in large outdoor "Innovator Marketplaces." A core principle was "Build in Public," encouraging open sharing of projects and progress. Hongqiao Alibaba Center served as the co-host and primary venue, positioning itself as a first-stop hub for international talent in China. The event marks a significant step for The Mu community, which has previously organized similar pop-up cities in Argentina and San Francisco, in bringing its model of immersive, collaborative innovation to China. It aims to be a key window for global科创 (scientific and technological innovation) exchange.

marsbit05/11 00:09

China's Version of 'Tech Burning Man' Debuts in Shanghai, muShanghai Creates a Global Geek 'Pop-up City'

marsbit05/11 00:09

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

Finance CEO Raoul Pal prefers Solana over Bitcoin, citing its high throughput and low transaction costs as better suited for the future crypto-AI era. He believes Solana is ideal for machine-to-machine microtransactions and AI-driven DeFi activity, predicting AI agents will soon dominate DeFi users. While Bitcoin serves as a store of value, Pal sees higher growth in networks built for mass, automated transactions. This view was highlighted at Consensus 2026, where AI integration and crypto infrastructure were key themes.

bitcoinist05/10 10:31

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

bitcoinist05/10 10:31

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit05/10 09:38

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit05/10 09:38

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit05/10 08:09

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit05/10 08:09

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit05/10 07:37

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit05/10 07:37

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