2026-08-17 Segunda

Notícias de cripto - Página 812

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

NVIDIA's Market Share in China Drops Below 60%, Domestic AI Chips Seize Market with 1.65 Million Units Delivered Annually

Nvidia's market share in China's AI accelerator card market has declined significantly, dropping from approximately 95% to 55% in 2025, according to IDC data. During the same period, domestic Chinese manufacturers collectively captured 41% of the market, shipping 1.65 million units out of a total market of 4 million units. Huawei led the domestic suppliers with 812,000 units shipped, representing nearly half of the local market share. This shift is driven by both U.S. export controls and China’s aggressive domestic substitution policies. In November 2025, Beijing mandated that state-funded data centers must use domestic AI chips, accelerating the adoption of local alternatives. Huawei recently launched the Atlas 350 accelerator card, claiming 2.87 times the inference performance of Nvidia’s H20 in low-precision computing, though direct comparisons are complicated by architectural differences. While Chinese chips still lag behind in training large-scale AI models—estimated to be 5-10 years behind Nvidia—they have reached a "good enough" level for many commercial applications like inference tasks. The main challenge remains software ecosystem development, as Nvidia’s CUDA platform remains the industry standard. Chinese firms are responding with compatibility efforts and open-source initiatives. Several domestic AI chip companies are now pursuing IPOs, and Huawei continues heavy R&D spending to reduce foreign dependency. Even if U.S. export policies ease, the structural move toward domestic AI chips appears irreversible.

marsbit04/03 05:51

NVIDIA's Market Share in China Drops Below 60%, Domestic AI Chips Seize Market with 1.65 Million Units Delivered Annually

marsbit04/03 05:51

Nearly $300 Million Aimed at U.S. Midterm Elections, Tether Executive Takes Helm of Crypto Industry's Second-Largest Political Fund

A crypto super PAC named Fellowship, which claims to have raised over $100 million but has reported zero spending to the FEC, has appointed Jesse Spiro, Tether’s VP of Regulatory Affairs, as its chairman. This marks the first official public link between Tether and the PAC, despite earlier denials. Meanwhile, another major crypto PAC, Fairshake—backed by Coinbase, Ripple, and a16z—has amassed $193 million and has already spent over $8.6 million in Illinois primary races. Combined, the two PACs control nearly $300 million aimed at influencing the November midterm elections. The move comes as the crypto industry faces a critical legislative battle over the CLARITY Act, currently stalled in the Senate. A key point of contention is whether stablecoins can pay yields to users—a issue directly affecting Tether, the issuer of the world’s largest stablecoin, USDT. A recent Senate proposal would ban passive yield but allow transaction-based rewards, a compromise the industry finds too restrictive. With the White House’s top crypto advocate departing and the legislative window narrowing, Tether’s heightened political engagement signals a strategic push to shape regulation and protect its business interests through financial influence.

marsbit04/03 05:08

Nearly $300 Million Aimed at U.S. Midterm Elections, Tether Executive Takes Helm of Crypto Industry's Second-Largest Political Fund

marsbit04/03 05:08

Chinese and American AI Companies Rush to List, Crypto Waits in the Corner for Opportunities

Chinese AI companies are rushing to IPOs at reasonable valuations, driven by a "common prosperity" policy to distribute wealth more broadly, while US AI giants like OpenAI and Anthropic are expected to go public around late 2026 at valuations potentially 100x higher. This AI IPO wave is drawing significant investor attention and capital away from other sectors, including crypto, in the short term. As a result, crypto faces funding headwinds and price pressure. However, this downturn may create attractive early-stage investment opportunities in crypto by 2026, similar to the post-2018 cycle. Longer term, AI is expected to boost crypto adoption by improving user experience through AI frontends and enabling autonomous agent-to-agent commerce on blockchain networks.

marsbit04/03 05:00

Chinese and American AI Companies Rush to List, Crypto Waits in the Corner for Opportunities

marsbit04/03 05:00

$300 Billion in One Quarter, AI Absorbs 80% of Global Venture Capital Funding

In Q1 2026, global venture capital funding reached a record $300 billion, with AI capturing 80% ($242 billion) of the total. Four mega-deals dominated: OpenAI ($122B), Anthropic ($30B), xAI ($20B), and Waymo ($16B), accounting for two-thirds of the quarter’s funding. The market showed extreme concentration, with fewer deals and larger average rounds, indicating a fragile breadth beneath the headline numbers. Crypto funding saw a modest recovery, reaching approximately $8.6 billion, though two-thirds of this occurred in March. Capital flowed mainly into regulated infrastructure like stablecoin payments, custody, and compliance, rather than speculative projects. Broader trends included growth in robotics, defense tech, and cybersecurity—often adjacent to AI. Geographically, the U.S. dominated with 83% of total funding, followed by China and the U.K. The venture market is increasingly fragmented: U.S.-led AI platforms attract massive late-stage capital, China’s on state-driven funding, and Europe faces a growth capital gap. Looking ahead, VC totals may remain high but concentrated. Valuation discipline is returning in secondary markets, exit windows remain volatile, and crypto must compete with AI for investor attention. The market is defined by selectivity and divergence, not broad recovery.

marsbit04/03 04:40

$300 Billion in One Quarter, AI Absorbs 80% of Global Venture Capital Funding

marsbit04/03 04:40

The Life-and-Death Game of Large Models: From the 'Six Dragons' to the Dual Giants Going Public — The Bubble, Breakthrough, and Endgame of AI Entrepreneurship

The Chinese AI large model startup landscape has undergone a drastic reshuffle in just two years. The initial "AI Six Dragons" quickly narrowed to the "Four Strong," and by early 2026, only Zhipu AI and MiniMax had successfully listed on the Hong Kong Stock Exchange, becoming the first independent large model companies to go public. The industry has shifted from a technology and capital-driven frenzy to a focus on commercial viability and sustainable business models. Zhipu AI and MiniMax, though now publicly traded, face immense pressure with significant losses, high valuations, and challenges in achieving profitability. Zhipu relies heavily on enterprise customization projects, while MiniMax depends on overseas consumer products with limited monetization. In contrast, non-listed companies like DeepSeek and Kimi have thrived by focusing on technical excellence and niche markets. DeepSeek targets global users with cost-efficient operations, and Kimi dominates long-text processing for professional use cases. Meanwhile, former contenders like Baichuan AI and 01.AI have shifted to vertical sectors, struggling against tech giants and thinner margins. The industry is governed by three key realities: only a few players can compete in the general-purpose large model space; public listings bring heightened scrutiny and inevitable valuation corrections; and vertical markets are highly competitive, not a safe retreat. The sector is expected to consolidate within one to two years, with a stable structure emerging—led by major tech firms, a few top independent companies, and specialized vertical players. Listing is not an exit but a rite of passage, separating those that can achieve profitability from those that cannot. The era of speculation is over; survival depends on technology, product strength, and sustainable business models.

marsbit04/03 04:31

The Life-and-Death Game of Large Models: From the 'Six Dragons' to the Dual Giants Going Public — The Bubble, Breakthrough, and Endgame of AI Entrepreneurship

marsbit04/03 04:31

Adding Another Oracle, Polymarket's Ambition Exposed

Polymarket, a leading prediction market platform, has announced the integration of Pyth Network as its oracle provider for settling prediction markets related to traditional assets. This new batch of markets will cover commodities like gold, silver, WTI crude oil, and natural gas, as well as U.S. stocks including NVIDIA, Apple, Tesla, and ETFs. Pyth will supply real-time pricing data via WebSocket, enabling second-by-second sampling and live charts for traders. This move is part of Polymarket’s ongoing expansion of its oracle infrastructure. Initially reliant on UMA’s optimistic oracle for subjective events like elections, the platform later integrated Chainlink for automated crypto price settlements (e.g., BTC and ETH). With Pyth—known for its institutional data sources like Jump Trading and Jane Street—Polymarket now extends into traditional finance, forming a multi-layered oracle system: UMA for social and political events, Chainlink for crypto, and Pyth for traditional assets. By expanding its data sources, Polymarket is broadening the scope of tradable futures—effectively turning real-world uncertainties into betable markets. The end goal appears to be a unified super-platform where any verifiable event—macro data, earnings, sports, weather, or AI releases—can be priced and traded.

Odaily星球日报04/03 04:10

Adding Another Oracle, Polymarket's Ambition Exposed

Odaily星球日报04/03 04:10

Manhattan Private Credit Launches Network to Connect Investors With Private Credit Markets as Bank Lending Continues to Contract

Manhattan Private Credit has launched a private capital network to connect investors with the growing private credit market, which has expanded into a multi-trillion-dollar sector as traditional bank lending contracts. The platform serves as an infrastructure layer, facilitating deal origination and capital matching across private credit, litigation funding, structured lending, asset-backed finance, and special situations. It connects investors, borrowers, developers, and legal firms who previously relied on fragmented, relationship-driven networks. The company emphasizes that its model resembles a platform business, matching supply and demand without originating deals itself. The growth of private credit is driven by banks retreating from areas like property development lending and bridge finance due to post-GFC regulations. Manhattan targets time-sensitive, event-driven opportunities where traditional banks are slow or disinterested. Access is provided through a membership structure, offering platform and network access rather than an investment product. The launch bets on the sustained structural gap between private lending demand and traditional bank supply.

TheNewsCrypto04/03 04:05

Manhattan Private Credit Launches Network to Connect Investors With Private Credit Markets as Bank Lending Continues to Contract

TheNewsCrypto04/03 04:05

Bitcoin fees hit a 6-year low: Why it matters for BTC’s next move

Bitcoin is trading near $66,000 amid a pullback driven by macroeconomic and geopolitical pressures. On-chain data suggests a potential bottom may be forming, with the Bitcoin Fund Flow Ratio at a historically significant level of 0.065—a pivot point that has previously preceded bullish reversals. Declining transaction fees, now at a six-year low, indicate reduced speculative activity and cooling on-chain demand, similar to conditions before the 2022 rebound. However, spot market activity remains weak, with limited capital inflows and persistent selling pressure. While these signals hint at stabilization, a sustained recovery will depend on renewed investor interest and stronger capital entering the market.

ambcrypto04/03 04:02

Bitcoin fees hit a 6-year low: Why it matters for BTC’s next move

ambcrypto04/03 04:02

Crypto Expert Says Dogecoin Is A Weak Altcoin You Do Not Want To Be Holding, Here’s Why

A crypto analyst, ColinTCrypto, has issued a bearish warning for Dogecoin (DOGE), labeling it a "weak altcoin" that investors should avoid holding. DOGE is already down over 46% this year, trading around $0.09 at a critical support level. The analyst's chart analysis indicates a prolonged downward trend from its 2021 peak, with the formation of a white triangle suggesting a potential breakdown. He predicts a further 20% drop to $0.073 if this support fails, attributing the weakness to a broader risk-off environment driven by geopolitical tensions and rising energy costs. Other analysts echo this sentiment, noting that Dogecoin and other altcoins show strong bearish signals and are on the verge of further declines amid weak market sentiment.

bitcoinist04/03 04:01

Crypto Expert Says Dogecoin Is A Weak Altcoin You Do Not Want To Be Holding, Here’s Why

bitcoinist04/03 04:01

The Art of Saving in the AI Era: How to Spend Every Token Wisely

In the AI era, tokens are the new currency, and efficiency is paramount. This article outlines strategies to minimize token usage while maximizing value. Key principles include prioritizing high signal-to-noise ratio inputs by removing unnecessary content like greetings, repetitive context, or verbose instructions before processing. Converting files (e.g., PDFs to clean Markdown) and compressing images drastically reduce token consumption. Avoid conversational, multi-turn interactions; instead, provide clear, concise, and complete instructions upfront to prevent costly back-and-forth. Output costs are higher than input, so eliminate AI pleasantries and enforce structured responses (e.g., JSON) over verbose explanations. Use system prompts to mandate direct answers and disable unnecessary features like "extended thinking" for simple tasks. Manage context efficiently: start new conversations for new tasks, compress long histories, and leverage prompt caching to reuse fixed instructions at lower costs. Employ model tiering—assigning complex tasks to premium models (e.g., Claude Opus) and simpler subtasks to cheaper ones (e.g., Claude Haiku)—to optimize cost and performance. Ultimately, the most effective saving is questioning whether a task requires AI at all. Human judgment remains a critical filter to avoid unnecessary token expenditure, ensuring that AI complements rather than replaces human efficiency.

marsbit04/03 03:22

The Art of Saving in the AI Era: How to Spend Every Token Wisely

marsbit04/03 03:22

活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow