# 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.

The First Year of Computing Power Inflation: The Cheaper DeepSeek Gets, the Harder It Is to Stop This Round of Price Hikes

The year 2026 marks the beginning of "computing power inflation." While AI inference costs have dropped by over 80% in 18 months globally, China's three major cloud providers—Alibaba Cloud, Baidu AI Cloud, and Tencent Cloud—simultaneously announced price hikes of 20–30%. This reflects a deeper structural shift driven by Jevons Paradox: as unit costs fall (e.g., via models like DeepSeek-R1), demand explodes, especially with the rise of reasoning models and AI agents that consume 10–50x more tokens per task. Although DeepSeek open-sourced its model weights, it did not release its inference optimization stack, leaving a significant engineering efficiency gap between cloud providers and smaller players. The big three are leveraging this advantage to reposition: Alibaba focuses on high-margin premium clients, Baidu filters out low-value users, and Tencent capitalizes on ecosystem lock-in. Meanwhile, ByteDance’s Volcano Engine adopts a more moderate pricing strategy to capture displaced customers. Unexpectedly, the price surge is pushing large enterprises toward self-built computing solutions once their cloud bills exceed a certain threshold. While cloud providers aim to boost profitability, they risk driving away innovative startups and accelerating competition from GPU leasing and domestic hardware providers like Huawei. The涨价 trend is expected to persist for 2–3 years, fueled by rising token consumption from reasoning models, AI agent adoption, and NVIDIA export restrictions. The inflection point depends on whether domestic chips can match NVIDIA’s efficiency, likely around 2027–2028. Until then, cloud providers will maintain pricing power, and the key for AI companies is to optimize token usage—the real moat in this era.

marsbit52 мин. назад

The First Year of Computing Power Inflation: The Cheaper DeepSeek Gets, the Harder It Is to Stop This Round of Price Hikes

marsbit52 мин. назад

Robotics' "ChatGPT Moment": AI Moves into the Physical World, Blockchain Accelerates the Arrival of the Machine Economy

The integration of AI and robotics is accelerating the shift from digital intelligence to physical AI, enabling machines to perceive, reason, and act in real-world environments. Companies like Figure, Tesla, and Skild AI are driving advancements in humanoid and specialized robots, supported by significant investments—such as Skild’s $14B and Figure’s $10B+ funding rounds. Key enablers include declining hardware costs (actuators, sensors, batteries), edge computing (e.g., NVIDIA Jetson), and AI "world models" that learn physical intuition from video data rather than programmed instructions. Despite progress, challenges remain: collecting real-world robotic training data is slow and costly, and simulation-to-reality gaps persist. Blockchain and tokenization offer solutions by incentivizing decentralized data contribution and enabling robots to function as economic agents—earning, spending, and distributing profits autonomously. By 2030, physical AI could transform industries and households, with robots operating via standardized platforms and skill-based "app stores." The convergence of affordable hardware, advanced AI, decentralized coordination, and edge compute promises a future where intelligent robots become ubiquitous assistants in daily life and high-risk applications.

marsbit52 мин. назад

Robotics' "ChatGPT Moment": AI Moves into the Physical World, Blockchain Accelerates the Arrival of the Machine Economy

marsbit52 мин. назад

Qubic Starts Dogecoin Mining Phase 2, Shifting Rewards Away From XMR

Qubic has entered phase 2 of its Dogecoin mining rollout, shifting miner rewards from Monero (XMR) to DOGE-based incentives. Starting with epoch 209, computors can operate in either XMR or DOGE mode, with only the higher-yielding contribution counted per index—effectively phasing out XMR if DOGE is more profitable. All block rewards are used for QUBIC buybacks, which are then distributed proportionally based on Dogecoin shares submitted. This transition, part of a three-phase plan announced in March, aims to fully migrate from XMR to DOGE, allowing parallel operation of DOGE mining (via Scrypt ASICs) and AI training (on CPUs/GPUs). Phase 2 introduces weekly reward windows, aligning with Qubic’s goal of scaling toward full-capacity dual-workstream operations.

bitcoinist4 ч. назад

Qubic Starts Dogecoin Mining Phase 2, Shifting Rewards Away From XMR

bitcoinist4 ч. назад

Analysts Outline a Price Path for Ozak AI That Shows Gradual Expansion Toward the $6 Range

Ozak AI ($OZ), an AI cryptocurrency token combining AI technologies with decentralized physical infrastructure networks (DePIN), is gaining attention for its utility-driven growth approach. Currently in an advanced presale stage with over $6 million raised, the token is priced at $0.014. Analysts highlight its focus on automation, analytics, and scalability rather than hype, supported by strategic partnerships with entities like SINT, Hive Intel, and Pyth Network. These collaborations enhance functionality, data streaming, and liquidity. A gradual price expansion toward the $6 range is projected, driven by adoption, staking, and ecosystem development rather than short-term speculation.

TheNewsCrypto13 ч. назад

Analysts Outline a Price Path for Ozak AI That Shows Gradual Expansion Toward the $6 Range

TheNewsCrypto13 ч. назад

Behind the MiniMax 'Pseudo-Open Source' Controversy: Has Yan Junjie's Ideal Succumbed to Capital Anxiety?

The article discusses the controversy surrounding MiniMax's "pseudo-open-source" release of its flagship M2.7 model. Initially presented as open-source, the model was later released under a "Modified-MIT" license that restricts commercial use without written permission, sparking backlash from the developer community. This move is seen as a departure from true open-source principles and reflects the tension between technological idealism and commercial pressures. MiniMax, which recently went public, faces significant financial challenges, with substantial losses despite growing revenues. The company’s decision to limit commercial use is interpreted as an effort to protect its revenue streams and control how its models are deployed, especially after instances of third-party misuse affected its reputation. The incident highlights a broader industry trend where "open-weight" models are increasingly distinguished from fully open-source ones, raising concerns about trust and legal certainty for developers and enterprises. The author concludes that MiniMax’s shift represents a pragmatic, if controversial, business strategy aimed at ensuring profitability, even at the cost of community trust.

marsbit15 ч. назад

Behind the MiniMax 'Pseudo-Open Source' Controversy: Has Yan Junjie's Ideal Succumbed to Capital Anxiety?

marsbit15 ч. назад

Apple Sends Siri Staff to AI 'Cram School', Jensen Huang's Bold Prediction Begins to Materialize

Apple is reportedly sending nearly 200 engineers from its Siri team to a multi-week AI programming "boot camp" to retrain them in AI-assisted coding, just two months before its major WWDC event. This unusual move reflects Apple's urgent effort to modernize Siri’s development process amid industry-wide shifts toward AI-powered tools like Claude Code and OpenAI’s Codex. The restructured Siri team now consists of only about 60 core developers, with another 60 assigned to test Siri’s performance and safety. The reshuffle follows internal delays in launching a new AI-powered Siri, originally planned for early 2025. Under new leadership—software chief Craig Federighi and hardware veteran Mike Rockwell—Apple is pushing to integrate Google’s Gemini model to power a more conversational, multi-step capable Siri. The situation underscores a broader trend: engineers who don’t adapt to AI tools risk being sidelined, as companies like Meta and NVIDIA emphasize AI-augmented productivity. While Apple’s retraining approach is relatively supportive compared to outright layoffs, it highlights how rapidly AI is reshaping tech roles—making traditional skills less relevant and accelerating a new industrial standard for software development.

marsbit15 ч. назад

Apple Sends Siri Staff to AI 'Cram School', Jensen Huang's Bold Prediction Begins to Materialize

marsbit15 ч. назад

No More Selling Shoes, Now Selling Computing Power: Will AI Computing Power Follow the Same Path as DAT?

Former footwear brand Allbirds announced a pivot to AI computing infrastructure under the name NewBird AI, raising $50 million and causing its stock to surge 582% in a single day. This shift echoes last year’s trend of companies rebranding as Digital Asset Treasuries (DATs), though the AI compute model differs significantly. The move highlights a structural shortage in AI computing power. Gartner projects global AI spending to reach $2.52 trillion by 2026, with over half dedicated to infrastructure. Major tech firms like Microsoft, Google, and Amazon are ramping up capital expenditures, yet supply remains constrained due to long GPU lead times and soaring demand from both training and inference workloads. Nvidia CEO Jensen Huang predicts a $1 trillion AI chip and infrastructure market by 2027. Unlike DAT companies—which held volatile crypto assets—AI compute firms rely on physical infrastructure, operational expertise, and long-term contracts that generate recurring revenue. However, analysts caution that Allbirds’ modest funding and lack of experience may signal “AI-washing,” akin to earlier blockchain hype. While the strategy offers a potential lifeline for struggling public companies, sustainable success requires genuine operational capability and significant investment.

Odaily星球日报15 ч. назад

No More Selling Shoes, Now Selling Computing Power: Will AI Computing Power Follow the Same Path as DAT?

Odaily星球日报15 ч. назад

Dialogue with a16z Co-founder: The Physical Laws of the Old World Are Dead, Crypto Becomes Key Infrastructure for AI

At a16z Fintech Connect, Ben Horowitz discusses how AI revolution is fundamentally rewriting the rules of software competition. He argues that traditional moats like data lock-in and UI familiarity are vanishing, as AI can easily replicate code, transfer data, and interact flexibly with software. CEOs of legacy companies must recognize these shifts and pivot towards delivering unique value beyond outdated advantages. Horowitz highlights that while some businesses face obsolescence, others with complex, entrenched operational networks (like travel platforms) may retain relevance. The conversation also covers critical infrastructure bottlenecks in the AI boom—from GPU shortages and power constraints to supply chain issues—emphasizing the need for massive investment in physical and digital infrastructure. Horowitz strongly links AI and blockchain, arguing that crypto is essential for solving AI-generated problems: identity verification, content authenticity, fraud prevention, universal basic income distribution, and enabling AI economic agency. Looking ahead, he speculates on VC’s evolving role—whether it scales up alongside mega-companies or adapts to a decentralized compute landscape—and strikes an optimistic note on AI’s long-term impact, foreseeing unprecedented improvements in global living standards despite transitional disruption.

marsbit17 ч. назад

Dialogue with a16z Co-founder: The Physical Laws of the Old World Are Dead, Crypto Becomes Key Infrastructure for AI

marsbit17 ч. назад

The Other Side of the Stock Market Rally: Energy Restructuring, Bitcoin Squeeze, and Market Mismatch

The article examines the complex and seemingly contradictory signals in global markets, where rising equities, falling oil prices, and cooling inflation expectations coexist with unresolved structural tensions. In digital assets, a major corporate strategy added nearly $1 billion in Bitcoin, increasing its holdings significantly, while Bitcoin's price action is seen as less important than the persistent negative funding rates, indicating a crowded short position that could lead to a sharp upward repricing. The global oil trade is rapidly rewiring, with the U.S. Gulf Coast becoming a key supplier to Europe and Asia amid Middle East disruptions. However, the article warns that such supply shocks can lead to permanent demand destruction as consumers and governments adapt. U.S. equities rose on optimism over potential geopolitical de-escalation and softer PPI data, led by tech stocks like NVIDIA. Meanwhile, the U.S. Federal Reserve maintains a wait-and-see stance on rates. Geopolitically, U.S.-Iran negotiations are ongoing alongside a maritime blockade, which has disrupted energy infrastructure and supply chains. Finally, the push for supply chain reshoring, particularly in critical minerals and defense, is accelerating but faces significant execution challenges related to permitting, financing, and labor, moving the issue from cost to one of strategic necessity.

marsbit18 ч. назад

The Other Side of the Stock Market Rally: Energy Restructuring, Bitcoin Squeeze, and Market Mismatch

marsbit18 ч. назад

Dragonfly Survey on Current State of Crypto Recruitment: Compliance Roles +340%, Data Science +74%, Crypto Enters the Era of On-Demand Hiring

Dragonfly's 2026 crypto talent report reveals a fundamental shift in hiring: companies now recruit based on actual need rather than market hype. In 2025, the industry saw a net reduction of 472 roles, but compliance positions surged by 340% and data science roles grew by 74%. The second half of 2025 brought discipline and recovery, with hiring stabilizing. Candidates are now more cautious, prioritizing company durability, clear role definition, and tangible impact over broad narratives. Engineering, AI/ML, and security roles remain highly competitive. Founders are advised to hire based on milestones—not cycles—and provide clear value propositions to attract talent. Remote work remains common, but key hubs like New York and the Bay Area dominate. AI's influence is significant, but its unclear impact in crypto may slow hiring. The outlook for 2026 is flat to moderate growth, driven by execution-focused teams with credible stories.

marsbit19 ч. назад

Dragonfly Survey on Current State of Crypto Recruitment: Compliance Roles +340%, Data Science +74%, Crypto Enters the Era of On-Demand Hiring

marsbit19 ч. назад

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