Pump.fun新竞品，MakeNow.Meme好玩在哪？

长文源：区块律动Publicado em 2001-08-24Última atualização em 2024-08-02

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After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

The stock price of Marvell Technology surged 32.5% on June 2nd, driven by NVIDIA CEO Jensen Huang highlighting its custom ASICs and optical interconnects as core to AI data center architecture. This event brought attention to the Chinese semiconductor family behind Marvell: the Dai siblings. The story centers on three siblings, all UC Berkeley graduates, whose three-decade entrepreneurial journey aligns with major semiconductor industry shifts. In 1995, youngest sister Dai Wei Li co-founded Marvell with her husband Sehat Sutardja and his brother, focusing on storage controllers. Eldest brother Dai Wei Min founded EDA company Ultima, later sold to Cadence, and later founded VeriSilicon (芯原) in China, becoming a leading semiconductor IP provider. Second brother Dai Wei Jin co-founded EDA firm Silicon Perspective (sold to Cadence) and GPU IP company Vivante, later acquired by VeriSilicon. The combined "Dai-Sutardja" family network extends beyond Marvell. Their ventures and investments form a comprehensive ecosystem for the post-Moore's Law, chiplet era. Key holdings include: Dream Big Semiconductor (AI SuperNICs, acquired by Arm), Alphawave (high-speed SerDes IP, acquired by Qualcomm), and Silicon Box (a chiplet advanced packaging foundry). VeriSilicon itself thrives on the AI ASIC and IP boom in China. Collectively, the family's AI infrastructure-related portfolio is estimated at over $22 billion. Their strategy represents a distinct path: building critical components for open standards and key manufacturing capacity in the chiplet era, rather than pursuing standalone AI chip dominance. While this path may not create the next NVIDIA, it has enabled repeated successful exits and sustained influence within the global semiconductor industry.

marsbitHá 15m

After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

marsbitHá 15m

Microsoft is Afraid of Being Marginalized by AI Giants

Microsoft, once the defining force of the PC era, now faces a familiar challenge in the AI age: the risk of being relegated to a profitable but invisible infrastructure provider. This anxiety was laid bare at Build 2026, where CEO Satya Nadella unveiled a major strategic pivot. The catalyst was a quiet April agreement that dissolved Microsoft's exclusive licensing and cloud-hosting deal with OpenAI, its once-vital partner. This erased Microsoft's key AI moat. With OpenAI and Anthropic defining AI applications and gaining enterprise traction—even within Microsoft's own ranks—Nadella had to answer: without exclusivity, what is Microsoft's role? The answer was a suite of seven in-house AI models, a developer-focused AI workstation (Surface RTX Spark Dev Box), and, most crucially, the Agent 365 platform for enterprise AI governance. The models, notably targeting Anthropic's strengths in coding and enterprise, signal a defensive move. However, the broader strategy is to make the models themselves less decisive. Financially, Microsoft's AI revenue is strong, driven largely by Azure running others' models. Yet its user-facing products like Copilot show weak penetration and engagement. Microsoft earns infrastructure money but lacks direct user mindshare. Nadella's core fear is being "hollowed out." As OpenAI and Anthropic prepare for IPOs and gain financial independence, they may build their own infrastructure, threatening Azure's lucrative AI revenue stream. Microsoft's window is to entrench itself deeper: not as the model creator, but as the indispensable platform for securely deploying, managing, and governing all AI models within the enterprise through Agent 365. Build 2026 revealed Microsoft's bet: in the AI era, the ultimate power lies not in any single model, but in the enterprise "operating system" that controls them. Nadella is determined to ensure Microsoft is the driver of this new era, not just a passenger.

marsbitHá 28m

Microsoft is Afraid of Being Marginalized by AI Giants

marsbitHá 28m

US Stocks Surge 16% in Two Months: Only 4 Occurrences in History, the Most Recent Was Just Before the 1987 Crash

U.S. stocks have surged 16% over April and May, a gain seen only four times since WWII, according to Deutsche Bank strategist Henry Allen. Three prior instances followed recessions, but the sole non-recession precedent was in early 1987, months before the "Black Monday" crash. The current rally is underpinned by AI enthusiasm and strong data, but its speed without an economic recovery is historically unprecedented. Meanwhile, credit spreads remain near record lows despite growing consumer strain—the U.S. savings rate hit just 2.6% in April, a level last seen before the Global Financial Crisis, and consumer sentiment is at its lowest since 1952. Market risks are concentrated. While stocks and credit markets appear immune to geopolitical tensions, sovereign bonds tell a different story. Treasury yields have tracked oil prices and recently hit multi-year highs, creating a widening divergence with equities. Surprisingly stable oil prices, despite the prolonged closure of the Strait of Hormuz, have been a key pillar for risk assets. However, if the blockage persists, this support could fade, raising the risk of a stagflation shock not currently priced in.

marsbitHá 29m

US Stocks Surge 16% in Two Months: Only 4 Occurrences in History, the Most Recent Was Just Before the 1987 Crash

marsbitHá 29m

CPU, Quietly Returning to the Center of the AI Computing Power Stage

Over the past three years, AI computing power narratives have been dominated by GPUs. However, starting in 2026, this story began to shift. While training large models remains GPU-intensive, the rapid growth of inference and AI agent workloads, which require high levels of task orchestration, concurrency, and data flow management, has highlighted a renewed critical role for CPUs. These are tasks GPUs are not designed to handle. Intel's recent launch of the Xeon 6+ processor, built on its Intel 18A process and featuring up to 288 efficiency cores (E-cores), exemplifies this strategic pivot. It is positioned not as a mere companion to GPUs but as the essential "control plane" for AI infrastructure, optimized for high-density, energy-efficient, and high-throughput workloads characteristic of AI agents and inference. This "CPU resurgence" is not about CPUs outperforming GPUs in raw computation. It reflects a systemic bottleneck: as AI scales from training single models to deploying countless intelligent agents, the demand for coordination and data handling surges. Major cloud providers are also developing their own high-density ARM-based server CPUs for similar workloads. However, Intel's success with this strategy faces significant challenges. Competition includes NVIDIA's integrated CPU-GPU solutions, the expanding adoption of cloud vendors' in-house ARM CPUs, and the crucial market test of Intel's 18A manufacturing process against rivals like TSMC's N2. In conclusion, CPUs are indeed reclaiming a central, though redefined, role in AI compute—managing the complex orchestration that enables massive-scale AI deployment. While the trend is clear, which company will ultimately lead this CPU resurgence remains an open question to be decided in the data centers of 2027 and beyond.

marsbitHá 49m

CPU, Quietly Returning to the Center of the AI Computing Power Stage

marsbitHá 49m

TON Rebrands Native Token As Gram, Reviving Original White Paper Name

The native token of the Toncoin (TON) network is being rebranded to 'Gram,' reviving its original name from the project's first white paper. This change, announced by Telegram co-founder and CEO Pavel Durov, is the fourth step in his "Make TON Great Again" (MTONGA) initiative. The transition period is expected to take about three weeks, and a new logo has been previewed. The rebrand follows Telegram's official return to the ecosystem in May as its largest validator, after a six-year absence that began with a 2020 legal dispute with the SEC. Durov stated that the move "returns to our roots" and paves the way for future developments, with three more steps remaining in the MTONGA roadmap. At the time of the announcement, Gram was trading around $2.02.

bitcoinistHá 1h

TON Rebrands Native Token As Gram, Reviving Original White Paper Name

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Como comprar PUMP

Bem-vindo à HTX.com!Tornámos a compra de Pump.fun (PUMP) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar Pump.fun (PUMP) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu Pump.fun (PUMP)Depois de comprar o teu Pump.fun (PUMP), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona Pump.fun (PUMP)Transaciona facilmente Pump.fun (PUMP) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

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