# 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.

Fidelity Mid-Year Review: 6 Key Digital Asset Trends for 2026

Fidelity Digital Assets' mid-year review assesses progress against its 2026 outlook, highlighting six key trends. The integration of digital assets with traditional capital markets is accelerating, with growing institutional product adoption and clearer U.S. regulatory guidance. Token holder rights mechanisms are being tested but have yet to command a clear market premium. Competition from AI compute demand is potentially slowing Bitcoin mining hash rate growth, indicating a structural shift. Bitcoin's network faces low risk from increased data capacity but shows signs of potential minor consensus divergence with the rise of Knots nodes, while quantum security upgrades gain focus. Market dynamics have leaned bearish due to macro pressures, though Bitcoin's resilience in crises suggests underlying strength. Gold has performed strongly, supported by central bank buying and de-dollarization trends, though its anticipated positive correlation with Bitcoin hasn't yet materialized. Overall, beneath short-term volatility, foundational trends for long-term digital asset maturation are advancing.

链捕手06/01 15:18

Fidelity Mid-Year Review: 6 Key Digital Asset Trends for 2026

链捕手06/01 15:18

Five Cryptos That Could Outperform Bitcoin Over the Next Cycle Due To Higher Growth Velocity

Bitcoin's growth often sets market trends, but analysts believe the next cycle's highest percentage gains may come from assets with greater growth velocity. While Bitcoin provides stability, several cryptocurrencies are positioned for stronger relative upside. This article highlights five such assets, with a particular focus on Ozak AI as the potential high-growth standout of the cycle. Ethereum (ETH) is noted for its ongoing evolution and institutional adoption. Solana (SOL) is recognized for its high throughput and history of sharp rallies. Chainlink (LINK) is highlighted as essential infrastructure for DeFi and AI applications. Avalanche (AVAX) is mentioned for its subnet architecture and enterprise potential. Ozak AI ($OZ) is presented as a distinct early-stage opportunity, currently in presale at $0.014 with a target listing price of $1.00. The project is building a full AI-native blockchain ecosystem, including prediction agents, a data stream network, and structured data vaults. Analysts suggest its early valuation stage and focus on AI infrastructure could allow for exponential growth velocity compared to more mature assets like Bitcoin, which requires massive capital inflows for significant price movement. The final takeaway positions Ozak AI as a high-asymmetry bet for investors seeking exponential upside alongside more stable assets.

TheNewsCrypto06/01 12:27

Five Cryptos That Could Outperform Bitcoin Over the Next Cycle Due To Higher Growth Velocity

TheNewsCrypto06/01 12:27

What's New in Jensen Huang's 'Agent Factory'?

In a keynote at COMPUTEX 2026, NVIDIA CEO Jensen Huang shifted the company's focus from hardware "full-stack" solutions to the era of AI Agents. The centerpiece is the Vera Rubin platform, now in production, which is designed specifically for Agent workloads and offers 10x the efficiency of its predecessor. The platform features the new Vera CPU, built for AI, and incorporates Spectrum-X Ethernet Photonics with CPO technology for improved networking and energy efficiency. NVIDIA introduced DSX, an integrated toolkit for designing, simulating, and operating AI data centers, aiming to streamline "AI factory" deployment and management. For end-user deployment, the company unveiled DGX Station for Windows, a desktop AI supercomputer for running Agents locally, and the RTX Spark SoC for AI PCs. On the software front, NVIDIA launched the 550B-parameter Nemotron 3 Ultra model for enterprise Agents and the Cosmos 3 foundation model for physical AI, unifying visual reasoning and action prediction. In robotics, a partnership with Unitree yielded the H2 Plus, a reference humanoid robot built on the Isaac GR00T platform to lower development barriers. Security was emphasized with enhanced confidential computing for Vera Rubin and new data path security features for the BlueField-4 STX storage platform. The presentation highlighted a strategic pivot: NVIDIA is reorganizing its entire technology stack—from chips and data centers to models, software, and robots—around the emerging ecosystem of autonomous, practical AI Agents.

marsbit06/01 12:04

What's New in Jensen Huang's 'Agent Factory'?

marsbit06/01 12:04

From "Selling Cloud" to "Selling Token": Telecom Operators Fully Join the AI Battlefield

From selling cloud services to tokens, operators fully join the AI battlefield. Major Chinese telecom operators—China Telecom, China Mobile, and China Unicom—are launching AI token packages for personal, family, and enterprise use. This marks a shift from selling traditional services like voice and data to offering tokens as a new standard unit for AI service consumption. Operators are transforming into AI service integrators, moving beyond their role as cloud providers. They are building an integrated structure that combines models, computing power, applications, unified billing, and security. By bundling various AI models, pooling heterogeneous computing resources, developing industry-specific agents, and leveraging their existing billing systems, they aim to lower entry barriers and simplify AI adoption for businesses. The token model is becoming a key packaging method for AI services, moving beyond developer markets to the mainstream. Operators are positioning themselves as the essential infrastructure for the AI era, aiming to make AI a billable, manageable, and reliable utility similar to electricity or network services. However, challenges remain in ensuring model quality, cost reduction, and achieving sustainable commercial success. The ultimate goal is to make AI a measurable and scalable production factor for industries.

marsbit06/01 10:13

From "Selling Cloud" to "Selling Token": Telecom Operators Fully Join the AI Battlefield

marsbit06/01 10:13

Unitree Passes the Hearing, Hangzhou Reaps the Rewards

Unitree Technology, a leading company in Hangzhou's tech scene known as one of the "Hangzhou Six Dragons," has officially passed the review for listing on the Shanghai Stock Exchange's STAR Market (科创板). It plans to raise 4.202 billion yuan for the research and development of intelligent robot models and robot hardware. This milestone will make Unitree the "first humanoid robotics stock." Founded in 2016 by Wang Xingxing, the company started humbly in a small office in Hangzhou's Binjiang district. Initially, the robotics sector was not viewed favorably by the market, with Unitree's products often labeled as "toys" and struggling to secure funding. At its most critical point, with only around 100,000 yuan left, Wang stopped his own salary to keep the company afloat. A crucial turning point came in 2018 when Hangzhou's state-owned capital system provided timely support. A financial platform under the city's state-owned assets completed due diligence in three days and granted a 20-million-yuan loan within a week. This "patient capital" infusion stabilized Unitree, enabling its transition from prototype development to mass production and commercial viability. Subsequently, Hangzhou Capital, through its two major 100-billion-yuan mother funds—the Hangzhou Science and Technology Innovation Fund and the Hangzhou Innovation Fund—participated in four of Unitree's financing rounds (B2, B3, C, and C+). This continuous backing helped the company grow, attract top-tier industrial investors like China Mobile, Tencent, Alibaba, and Geely, and solidify its position as a global leader in legged robotics. By 2025, Unitree achieved significant scale, with revenue reaching 16.99 billion yuan, net profit of 5.91 billion yuan, global leadership in humanoid robot shipments, and over 33,000 quadruped robots sold worldwide. Unitree's journey exemplifies Hangzhou's strategy of nurturing hard-tech startups from "seedlings" to industry leaders. Beyond Unitree, Hangzhou's capital ecosystem has supported other "Six Dragons" like Cloudwalk, BrainCo, and DeepSeek. The city has established a 500-billion-yuan "3+N" industrial fund cluster and specialized early-stage funds like the "Runmiao Fund" with a 20-year term to fill funding gaps for very early-stage projects. This robust "capital + talent" model, coupled with an influx of over 430,000 young professionals in 2025 alone, has fostered a vibrant innovation ecosystem. Hangzhou is now home to 48 unicorns and 413 potential unicorns, building comprehensive industrial chains in AI, robotics, brain-computer interfaces, and more. As Hangzhou experiences a wave of IPOs, it is solidifying its reputation as an ideal city for entrepreneurs.

marsbit06/01 10:11

Unitree Passes the Hearing, Hangzhou Reaps the Rewards

marsbit06/01 10:11

Nvidia Rack Disassembly Reveals New Growth Opportunity, MLCC Value Surges 182%

Supply bottlenecks in AI infrastructure have expanded to fundamental hardware components like multilayer ceramic capacitors (MLCCs), crucial for stabilizing power and filtering noise in AI servers. Both Goldman Sachs and Morgan Stanley highlight MLCCs as entering a historic "volume-price dual increase" supercycle driven by AI. Goldman forecasts the AI server MLCC market to surge over fourfold from ~$1.4B in FY2025 to ~$5.8B in FY2030, a 34% CAGR. The core driver is a structural supply-demand imbalance. While AI server demand is projected to grow ~4.3x by 2030, industry capacity expands at only ~10% annually, constrained by internal production of equipment and materials. This is compounded by strong demand from electric vehicles. The shortage is evident, with lead times for high-end MLCCs exceeding 20 weeks. The price cycle has officially begun. Japanese leaders Murata and Taiyo Yuden have raised prices by 15-35% for AI server and automotive MLCCs since April, citing material costs. Japan's April export data confirms the trend, with MLCC export value up 28% year-over-year. Profit leverage is significant: Goldman estimates a mere 5% price increase could boost Murata's FY2027 operating profit by ~13% and Taiyo Yuden's by up to 37%. Morgan Stanley's teardown of Nvidia's upcoming Vera Rubin AI rack reveals another catalyst: the MLCC value per rack has skyrocketed 182% from the previous generation to ~$4,320, highlighting the component's growing importance. With demand set to massively outstrip constrained supply, and price increases just starting, analysts position MLCCs at the beginning of a major, prolonged upcycle.

marsbit06/01 09:06

Nvidia Rack Disassembly Reveals New Growth Opportunity, MLCC Value Surges 182%

marsbit06/01 09:06

Interview with 7 Ordinary Professionals: After AI Arrived, How Are You Doing?

This article interviews seven professionals from diverse fields like Web3, bulk chemical trading, digital agriculture, and traditional wholesale to examine the impact of AI on their work. Key themes emerge from the discussions. AI has become integral to their workflows, primarily for increasing efficiency in tasks such as coding, content creation, research, and data analysis. Individuals across roles, from developers to managers, report that AI tools like ChatGPT and Claude have significantly reduced workloads and accelerated learning, creating opportunities for "super individuals" or one-person teams. However, this efficiency comes with a double-edged sword. It intensifies competition, pushing professionals to constantly learn new tools and adapt, leading to widespread anxiety about job security and a heightened pressure to keep pace. Interviewees anticipate significant job reductions in roles like administrative support, finance, HR, customer service, and some creative fields. A recurring view is that AI acts as a "great equalizer," amplifying the capabilities of those who use it effectively while leaving others behind, potentially deepening polarization. Despite AI's capabilities, interviewees identify enduring human strengths. AI struggles with tasks requiring deep contextual understanding, complex judgment in areas like risk assessment and system stability (especially in finance/Web3), nuanced human communication, and handling exceptions in logistics and manufacturing. These areas remain firmly in the human domain. Consequently, many professionals are refocusing their career strategies. They plan to evolve from task executors into "complex system owners," "super coordinators" managing AI agents, or specialists in high-level areas like business context, risk control, product design, and personal branding. In summary, the article portrays AI not as an optional tool but as a transformative force reshaping job demands. While it automates routine work, it also creates new forms of pressure and competition. The future, as seen by these professionals, belongs to those who can strategically integrate AI to augment uniquely human skills like judgment, responsibility, and strategic oversight.

marsbit06/01 08:17

Interview with 7 Ordinary Professionals: After AI Arrived, How Are You Doing?

marsbit06/01 08:17

Wang Chuan: When the Neighbor Old Wang Made 30x on Memory Stocks, How to Avoid Anxiety (Part Six) - The Trap of Commoditized Goods

Wang Chuan: When the Neighbor Lao Wang Made 30x on Storage Stocks, How to Stay Anxiety-Free (Part 6) - The Trap of Commoditized Goods. This essay uses historical and current examples to analyze the cyclical and high-risk nature of the data storage industry. It begins with the 1990s rise and dramatic fall of Iomega, whose stock soared over 160x in 18 months before collapsing 97% from its peak, illustrating the fleeting success of storage "meme stocks." The core problem is that storage products, like DRAM and flash memory, are highly commoditized. This leads to extreme volatility: prices have plummeted over 80% multiple times, and company stocks often crash 95% or go bankrupt. The industry's dynamic is defined by "elastic demand facing heavy-asset, long-cycle, rigid supply." When demand spikes and supply is fixed, prices skyrocket, as seen recently with AI-driven demand for High Bandwidth Memory (HBM). Companies like Sandisk and Micron have reported massive revenue and gross margin jumps (e.g., Sandisk's gross margin rising from 22.5% to 78.3%) despite minimal increases in production volume. However, these high margins are self-defeating. They incentivize massive new capacity investments (hundreds of billions planned from 2026), with supply expected to surge by late 2027. Once new supply meets demand, prices and profits will crash, potentially leading to a scenario where "selling more results in earning less." The article debunks the safety of long-term supply agreements, comparing them to fragile non-aggression pacts easily broken when market conditions shift. It warns that when an industry is highly profitable but trades at low P/E ratios, the risk is greatest, as plummeting prices quickly erase those earnings. Multiple asymmetric risks loom, including economic recession, reduced AI spending, faster-than-expected capacity expansion (especially from Chinese firms), and technological innovations that reduce memory requirements. In conclusion, the storage sector is a cyclical trap where periods of euphoric profits are often precursors to devastating downturns, luring unprepared investors into a "wealth incinerator."

marsbit06/01 07:13

Wang Chuan: When the Neighbor Old Wang Made 30x on Memory Stocks, How to Avoid Anxiety (Part Six) - The Trap of Commoditized Goods

marsbit06/01 07:13

Interview with Macro Master Raoul Pal: The Economic Singularity is Approaching, Don’t Get Off the Ride in the Next Four Years

Interview with macro expert Raoul Pal discusses the approaching "economic singularity," where AI-driven growth outpaces traditional economic systems. He explains the unprecedented scale of the AI race between the US and China, arguing capital will continue flooding this sector as neither side can afford to stop. Pal sees this as a catalyst for cryptocurrency, as AI agents will operate on-chain, creating an "infinite TAM" for crypto networks. He views the recent crypto downturn as a normal bull market correction, advocating for a long-term "buy and hold" strategy over trying to time the market. Key investments include Layer 1 smart contract platforms like Ethereum, Solana, and Sui, which he believes will capture most value due to their foundational role. He also sees potential in privacy coins like Zcash and a future resurgence for high-end NFTs as digital trophy assets. Pal emphasizes that while AI stocks are hot, crypto offers superior asymmetric returns. He outlines a bullish case for 2026-2027 based on institutional adoption, pro-regulation, increased global liquidity, and crypto's current undervaluation relative to assets like the Nasdaq. His core advice: accumulate crypto assets during dips and hold for the long term, as the shift towards a digital, AI-agent-driven economy is inevitable.

链捕手06/01 06:10

Interview with Macro Master Raoul Pal: The Economic Singularity is Approaching, Don’t Get Off the Ride in the Next Four Years

链捕手06/01 06:10

NVIDIA Launches DSX Platform, Expanding into AI Factory Infrastructure

NVIDIA has unveiled the DSX platform at its GTC Taipei event, marking a strategic expansion from GPU sales into comprehensive AI factory infrastructure solutions. The platform addresses challenges like power supply, cooling, and resource orchestration as AI models scale, shifting the industry focus from single-chip performance to overall infrastructure efficiency. DSX integrates NVIDIA's chips, systems, software, and partner technologies to cover the entire AI factory lifecycle—from design and simulation to deployment and operations. It aims to accelerate deployment, improve reliability and operational efficiency, and reduce the cost per generated token in AI inference. The software suite includes DSX MaxLPS, which uses 45°C liquid cooling and rack-level optimization to allow up to 40% more GPUs per megawatt, and DSX OS, an open-source platform for AI factory operations. The platform also encompasses reference designs, digital twin simulation (DSX Sim), dynamic workload adjustment based on grid conditions (DSX Flex), and data exchange between systems. Early adopters include cloud providers like CoreWeave and Lambda. Major hardware partners, including Dell, HPE, Lenovo, and Supermicro, are developing DSX-ready systems. Pilot projects for DSX Flex are underway with energy providers. Strategically, DSX represents NVIDIA's ongoing transition from an AI chip supplier to a full-stack AI infrastructure platform provider, aiming to set industry standards and solidify its market leadership.

marsbit06/01 04:27

NVIDIA Launches DSX Platform, Expanding into AI Factory Infrastructure