# 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.

Memory Card Prices Double in Four Months: How Long Will the Surge Last?

NAND flash memory prices have entered a rapid upward cycle, with consumer-grade storage products like microSD cards seeing significant retail price increases. For example, a SanDisk Extreme 128GB microSD card rose from $17 in October 2025 to nearly $40 by February 2026—a 130% surge in under four months. This price surge is driven by structural shifts in the NAND market, primarily due to soaring demand from AI data centers. These large-scale buyers are securing the majority of NAND wafer supply through long-term contracts, leaving limited inventory for the consumer market. According to TrendForce, NAND contract prices rose 55–60% in Q1 2026, with enterprise SSD prices climbing 53–58%. Retail prices rose even more sharply due to constrained supply in the distribution channel. Unlike the 2016–2017 price cycle caused by production transitions, the current spike is demand-led. AI data centers are consuming NAND capacity at an unprecedented rate, with 2026 demand growth estimated at 20–22% against supply growth of only 15–17%. Manufacturers are prioritizing high-margin enterprise products over consumer-grade storage, further tightening retail availability. New production capacity from major suppliers like Samsung, Micron, and Kioxia is not expected until late 2027 or 2028. Until then, consumer storage prices are likely to remain high, with no significant price relief anticipated in the near term.

marsbit14 ч. назад

Memory Card Prices Double in Four Months: How Long Will the Surge Last?

marsbit14 ч. назад

The Allbirds, the Internet-Famous Shoes That Took Silicon Valley by Storm, Are Now All in on AI

Allbirds, the once-popular sustainable shoe brand favored by Silicon Valley elites and celebrities, has announced a drastic pivot from footwear manufacturing to AI infrastructure. On April 15, 2026, the company revealed plans to abandon its shoe business entirely, rebrand as "NewBird AI," and focus on GPU-as-a-service and AI cloud solutions. The move caused its stock to surge over 800% in a single day. The brand, known for its wool-based eco-friendly shoes, had struggled financially in recent years. Revenue fell from a peak of $298 million in 2022 to $152 million in 2025, with cumulative losses of $419 million over five years. In March 2026, Allbirds sold its intellectual property and footwear assets for just $39 million—a fraction of its former $4.1 billion valuation. The company secured up to $50 million in convertible notes to fund the acquisition of GPU hardware for AI compute leasing. However, the announcement lacked details about technical capacity, clients, or infrastructure plans. Critics highlight the high execution risks in the competitive AI infrastructure market, dominated by major cloud providers. The shift reflects a broader trend of companies rebranding around AI to attract investor interest, despite uncertain fundamentals. Allbirds also removed its "public benefit" corporate mission, signaling a departure from its original sustainability ethos. The move underscores the power of AI narrative in today’s capital markets, where storytelling often precedes substance.

marsbit15 ч. назад

The Allbirds, the Internet-Famous Shoes That Took Silicon Valley by Storm, Are Now All in on AI

marsbit15 ч. назад

The Complete Landscape of Encrypted AI Protocols: Starting from Ethereum's Main Battlefield, How to Build a New Operating System for AI Agents?

The year 2026 is emerging as a pivotal moment for the convergence of Crypto and AI, marked by AI's evolution from a tool to an autonomous economic agent. These AI agents require identity, payment channels, and verifiable execution environments—needs that blockchain is uniquely positioned to address. Ethereum is positioning itself as the trust layer for AI. Vitalik Buterin's updated framework outlines a vision where Ethereum provides verifiable, auditable infrastructure for AI, rather than accelerating its development unchecked. This is being realized through key protocol developments: - **Identity & Reputation (ERC-8004):** A standard for creating NFT-based identities for AI agents, complete with a reputation system built on verifiable on-chain interactions. - **Payments (x402):** Now under the Linux Foundation, this protocol embeds machine-to-machine payments directly into HTTP requests, enabling agents to pay for API access seamlessly with stablecoins or traditional methods. - **Execution (ERC-8211):** Allows AI agents to execute complex, multi-step DeFi transactions atomically in a single signature, overcoming a major operational bottleneck. Beyond Ethereum, other ecosystems are finding their roles. Solana is becoming a hub for high-frequency, low-cost agent payments and interactions due to its speed and low fees. Decentralized physical infrastructure networks (DePIN) provide the necessary compute power. In summary, a complementary crypto-AI stack is forming: Ethereum sets the standards for trust and identity, Solana excels at high-frequency execution, and DePIN supplies decentralized computation. The goal is not to accelerate AI uncontrollably, but to build a verifiable, decentralized foundation for the incoming AI agent economy.

marsbit15 ч. назад

The Complete Landscape of Encrypted AI Protocols: Starting from Ethereum's Main Battlefield, How to Build a New Operating System for AI Agents?

marsbit15 ч. назад

The DeepSeek You've Been Waiting For Has Long Changed

The article discusses the delayed release of DeepSeek V4, a highly anticipated AI model in China, and explores the reasons behind its slowed development. Initially a leader in the global AI race, DeepSeek has fallen behind competitors like OpenAI, Anthropic, and Google, which release major updates every few months. A key factor is DeepSeek's shift in focus due to national strategic priorities. In early 2025, the Chinese government encouraged the company to use Huawei’s Ascend processors instead of NVIDIA’s GPUs, aligning with broader efforts to achieve technological self-reliance. DeepSeek attempted to train its models on Huawei’s Ascend 910C chips but faced technical challenges, including instability and communication issues during distributed training. As a result, the company continued using NVIDIA hardware for training while only using Ascend chips for inference. In 2026, DeepSeek prioritized adapting V4 to Huawei’s new Ascend 950PR and Cambricon chips, aiming for a full migration from NVIDIA’s CUDA to Huawei’s CANN framework. This adaptation process, particularly ensuring precision alignment across hardware, consumed significant time and resources, slowing down model iteration. The delay also reflects DeepSeek’s evolving role from a purely market-driven entity to a "national mission-oriented" company. This shift has come at a cost: the model now lags behind competitors in areas like code generation and multimodal capabilities, and the company has faced talent drain, with key researchers leaving for better-paying opportunities at larger tech firms. Despite these challenges, V4’s release is seen as a potential milestone for China’s AI industry, demonstrating that advanced models can run on domestic hardware ecosystems. While it may not be a groundbreaking model in terms of performance, its success could validate China’s broader strategy for AI independence.

marsbitВчера 10:32

The DeepSeek You've Been Waiting For Has Long Changed

marsbitВчера 10:32

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