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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.

marsbitAyer 10:32

The DeepSeek You've Been Waiting For Has Long Changed

marsbitAyer 10:32

NVIDIA Starts Selling the Method of Making Shovels

NVIDIA is accelerating its own GPU design process with AI tools, reducing tasks that took 8 engineers 1010 months to a single GPU running overnight, while achieving better results. However, it is not using AI to fully design GPUs yet. Instead, it is embedding its technology across the chip industry. A key move is its $2020 billion investment in Synopsys, a leading EDA (Electronic Design Automation) tool provider, and partnerships with Cadence and Siemens. This integrates NVIDIA’s hardware acceleration into essential chip design software, making its GPUs the fastest platform for EDA tools. Competitors like AMD and Intel now face a dilemma: use slower tools or rely on NVIDIA’s hardware to design competing chips. Chinese GPU firms, despite high market valuations, struggle with massive losses and dependence on restricted foreign EDA tools. NVIDIA’s strategy extends from AI-enhanced design to manufacturing, creating a self-reinforcing cycle where its hardware becomes essential for developing faster chips—even for those aiming to compete with it.

marsbitAyer 10:04

NVIDIA Starts Selling the Method of Making Shovels

marsbitAyer 10:04

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

The $59 Billion Illusion: How the Female Version of Buffett Fell from Grace?

"Cathie Wood, once hailed as the 'next Warren Buffett' and a star among millennial investors, saw her flagship ARKK ETF soar to a peak of $59 billion in assets under management (AUM) by February 2021. Her strategy of betting on disruptive technologies like Tesla, genomics, and AI—while publicly sharing her research and daily trades—initially delivered staggering returns, with ARKK surging 152% in 2020 as she doubled down during the COVID crash. However, rising interest rates exposed the fragility of her high-growth, unprofitable tech holdings. ARKK plummeted nearly 75% from its peak, erasing over $50 billion in AUM by 2026. Critics labeled her approach—essentially applying venture capital (VC) logic to public markets—as fundamentally flawed. Unlike VC, where losses are absorbed by private gains, public markets impose real-time pricing and liquidity pressures, accelerating losses during downturns. Ironically, while Wood correctly predicted the AI revolution, she sold NVIDIA early—missing out on over $1.2 billion in gains—to maintain her "anti-consensus" brand and focus on smaller, speculative names. Her daily transparency and massive scale turned her into a target, as markets anticipated her moves. Despite recent pivots back into gene editing and AI infrastructure, her assets remain a fraction of their peak, underscoring the gap between predicting trends and profiting from them."

marsbit04/02 04:13

The $59 Billion Illusion: How the Female Version of Buffett Fell from Grace?

marsbit04/02 04:13

Nvidia Loses 40% of Chinese Market in Three Years | Rewire Morning News

Nvidia's market share in China's AI GPU market has dropped from 95% to 55% over three years, with Huawei capturing 20% of the market. The U.S. Federal Reserve warns that AI hype itself may be driving inflation by boosting consumer spending and corporate investment. Intel repurchased a factory in Ireland for $14.2 billion, signaling a strategic shift toward manufacturing sovereignty. Wall Street firms like JPMorgan and Paradigm are entering the prediction markets, indicating growing institutional interest. In DeFi, Drift Protocol on Solana suffered a $285 million hack due to a private key leak. Other notable news includes Block’s plan to replace middle management with AI, Anthropic’s DMCA takedown mishap, and a record $16.1 billion in Chinese VC funding for Q1 focused on AI and semiconductors.

marsbit04/02 02:25

Nvidia Loses 40% of Chinese Market in Three Years | Rewire Morning News

marsbit04/02 02:25

When Bitcoin Miners Take to Space

SpaceX is reportedly preparing for a historic IPO with a target of $1.75 trillion, while simultaneously advancing plans to deploy AI data centers in orbit, leveraging space’s vacuum for cooling and solar energy for power. This has sparked interest in whether Bitcoin mining—also energy-intensive and dependent on computing hardware—could also move to space. The core idea involves placing mining ASICs on the back of solar panels in orbit, using abundant solar energy to power mining operations. Heat dissipation in vacuum, a key challenge, is manageable through thermal radiation, and communication with mining pools is feasible with low latency via low Earth orbit satellites. However, the economics remain prohibitive. Launch costs, currently around $2,720 per kilogram via Falcon 9, make mining payloads financially unviable. Estimates suggest that with current technology, the payback period would exceed 100 years. SpaceX’s Starship may eventually reduce launch costs below $200/kg, making space mining more feasible. Companies like Starcloud—backed by NVIDIA and top VCs—are already testing orbit-based computing, including AI and planned Bitcoin mining experiments. Others, like SpaceChain and Cryptosat, focus on secure blockchain nodes and cryptographic services in space rather than mining. While orbital mining is not yet economically competitive with terrestrial operations, it represents a long-term vision for radically reducing energy costs and expanding the infrastructure of decentralized networks beyond Earth.

marsbit04/01 03:49

When Bitcoin Miners Take to Space

marsbit04/01 03:49

NVIDIA Case Reopened: Accused of Concealing $1 Billion in 'Mining' Revenue, a Hidden Chapter in the AI Giant's History

Nvidia Faces Renewed Investor Lawsuit Over Alleged $1 Billion Undisclosed Crypto Mining Revenue A US judge has approved a class-action lawsuit against Nvidia and its CEO Jensen Huang. Investors allege that between 2017 and 2018, Nvidia concealed the extent to which its gaming graphics card revenue depended on cryptocurrency mining demand, misleading shareholders about associated risks. The suit claims over $1 billion in crypto-related revenue was largely reported under the "Gaming" segment, downplaying the business's exposure to volatile crypto market cycles. Following a corrective disclosure in November 2018, Nvidia’s stock fell approximately 28.5% over two days. Internal evidence, including an executive email, suggested that previous statements had positively influenced the company's stock price. This case revives a lawsuit initially filed in 2018, which had previously been dismissed. During the 2017 crypto boom and the 2020 bull market, Nvidia’s GPUs were in high demand from miners, causing shortages for gamers. The company later launched dedicated CMP mining cards. In 2022, the SEC charged Nvidia with insufficient disclosure of mining’s impact on gaming revenue, resulting in a $5.5 million settlement. The class action covers investors who bought Nvidia stock between August 2017 and November 2018. A case management conference is scheduled for April 21.

marsbit03/27 10:29

NVIDIA Case Reopened: Accused of Concealing $1 Billion in 'Mining' Revenue, a Hidden Chapter in the AI Giant's History

marsbit03/27 10:29

Bitcoin Now Less Volatile Than Tesla, Nvidia — Schwab Data

Morgan Stanley is nearing the launch of the first spot Bitcoin ETF from a major U.S. bank, reflecting Bitcoin's growing integration into mainstream finance. According to Charles Schwab data, Bitcoin's volatility has significantly decreased, dropping to 42% in 2025—below that of Tesla (63%) and Nvidia (50%). Over a three-year period, Bitcoin's maximum drawdown was 50%, compared to 54% for Tesla and 37% for Nvidia. While still volatile, Bitcoin now exhibits price swings closer to major equities rather than the highly speculative asset it once was. Despite this maturation, it remains riskier than traditional safe-havens like gold and more stable than Ethereum within crypto markets.

bitcoinist03/27 02:01

Bitcoin Now Less Volatile Than Tesla, Nvidia — Schwab Data

bitcoinist03/27 02:01

Nvidia Lands In Court Over Crypto Secret — Here Is What Investors Missed

Nvidia faces a certified class action lawsuit over allegations it under-disclosed crypto mining revenue linked to its gaming GPU sales during the 2017–2018 period. Investors claim the company misled them by attributing significant revenue growth to gaming rather than cryptocurrency mining, creating a "revenue gap" between internal knowledge and public statements. After Nvidia’s CFO later acknowledged a revenue shortfall due to crypto-related inventory issues, the stock fell nearly 30%. The lawsuit, now moving forward, cites internal emails suggesting management was aware the stock price was artificially sustained by misleading disclosures. The case introduces legal and financial risks for Nvidia amid its current prominence in AI.

bitcoinist03/26 13:01

Nvidia Lands In Court Over Crypto Secret — Here Is What Investors Missed

bitcoinist03/26 13:01

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