Industry News

Tracks company news, strategic changes, funding activities, and personnel adjustments across the blockchain and crypto industries, delivering a full-spectrum industry overview for our users.

From Suppliers to Shareholders: The Big Three Memory Chip Giants Jointly Invest in Anthropic, AI Supply Chain Power Structure Undergoing Reshuffle

For the first time, memory chip giants Micron, Samsung, and SK hynix have jointly invested in the same AI company, Anthropic, as part of its massive $65 billion Series H funding round. This strategic move, positioning the three rival HBM suppliers as "strategic infrastructure partners," highlights a fundamental shift in the AI industry's power dynamics. With HBM (High Bandwidth Memory) being a critically scarce resource essential for AI model training and inference, securing a stable supply has become a key competitive differentiator. By making these chipmakers shareholders, Anthropic aims to lock in this vital component for its rapid expansion, which includes securing major compute commitments from Amazon, Google, and others. For the memory trio, this investment represents a strategic bet on defining the future of AI hardware. Each company gains: SK hynix reinforces its dominant position in the NVIDIA supply chain; Samsung diversifies its client base beyond NVIDIA; and Micron leverages its geopolitical significance as the sole US-based HBM maker. Their collective move signals that competition in AI is evolving beyond model capability to encompass control over the entire compute supply chain—from chips and memory to power and networking. This vertical integration trend, where infrastructure providers become direct stakeholders in AI firms, marks the industry's maturation as AI transforms from a research project into essential global infrastructure, setting the stage for a new era of ecosystem competition.

marsbit05/30 04:40

From Suppliers to Shareholders: The Big Three Memory Chip Giants Jointly Invest in Anthropic, AI Supply Chain Power Structure Undergoing Reshuffle

marsbit05/30 04:40

Shanghai's Leading Large Model Company Initiates A-Share Listing

Shanghai-based AI large language model leader MiniMax has initiated the process for an A-share listing in China, having filed a pre-IPO tutoring report with the Shanghai Securities Regulatory Bureau on May 29. This move positions it to compete with Zhipu AI for the title of the first major domestic LLM company to list on the A-share market. Having already completed an IPO in Hong Kong in January 2026, MiniMax's stock price has surged approximately 409% since its debut, with its market capitalization reaching around HK$263.45 billion (approximately RMB 227.55 billion) as of May 29. The company's rapid growth is supported by strong business performance. Its Annual Recurring Revenue (ARR) has grown over 100% in the past two months and now exceeds $300 million. It serves over one million global enterprise and developer clients and has around 300 million users worldwide. For the full year 2025, MiniMax reported revenue of $79.038 million, with a gross margin of 25.4%. While it reported an adjusted net loss of $250 million, the loss rate has narrowed significantly year-over-year. On the product front, MiniMax has released several flagship models this year, including MiniMax-M2.5, M2.6, and M2.7, with the first and last being open-sourced. Its models gained significant traction earlier in the year, briefly becoming the top model provider by usage share on the OpenRouter platform in February. The company has also upgraded its AI agent product, now named Mavis, and is preparing to launch its next-generation MiniMax-M3 model. Technical previews indicate M3 will feature a novel "MiniMax Sparse Attention" mechanism, promising substantial improvements in inference speed. MiniMax's push for an A-share listing reflects a broader trend among China's leading AI firms, including Zhipu AI, Moonshot AI, StepFun, and 01.AI, to seek public listings. This strategy aims to secure broader financing channels to support the immense computational costs and ongoing commercialization efforts inherent in developing advanced large language models.

marsbit05/30 02:45

Shanghai's Leading Large Model Company Initiates A-Share Listing

marsbit05/30 02:45

Biology's Paradigm Shift: Zuckerberg's New Open-Source Model Completely Overturns Google's AlphaFold Throne

The AlphaFold era faces a major challenge. A new open-source AI model, ESMFold2, from Meta CEO Mark Zuckerberg's Biohub, has been released alongside a massive database of 11 billion predicted protein structures—surpassing the AlphaFold database by 8 billion entries. Published in Nature, the model is reported to outperform AlphaFold3 in key areas, particularly in predicting protein complexes. Crucially, it is fully open-source with no commercial restrictions. ESMFold2 takes a different technical approach, building on a protein language model trained on billions of sequences, including microbial data from diverse environments like soil and ocean—areas less covered by AlphaFold. The team validated its utility by designing and successfully synthesizing novel functional proteins in the lab. The decision to open-source everything is seen as a strategic move, similar to Meta's approach with its Llama models, aiming to build an ecosystem and accelerate global research. While scientists welcome the resource, some urge caution, noting the need for independent validation of predictions and questioning its performance on entirely novel protein folds. The development signals intensified competition in protein AI, rapidly evolving much like the large language model field, and represents a significant step forward in using AI to decode and engineer the machinery of life.

marsbit05/29 12:31

Biology's Paradigm Shift: Zuckerberg's New Open-Source Model Completely Overturns Google's AlphaFold Throne

marsbit05/29 12:31

Hurun Report Interview with Justin Sun: New Paradigms of Value Circulation under the Web3 Transformation Cycle

In a deep-dive interview with *Hurun Report*, Justin Sun, founder of TRON, outlines his vision for Web3's evolution from proof-of-concept to global adoption, emphasizing stablecoins as the cornerstone for building a new paradigm of value transfer. Sun defines the core mission as enabling low-cost, efficient global fund movement for anyone, anywhere, regardless of bank access. He argues that sustainable blockchain projects must be driven by genuine demand and usage, with stablecoin payments currently representing the most mature and scalable application. Citing TRON's position as a leading stablecoin network with over $86.3 billion in USDT circulation, he attributes this growth to real-world use in cross-border transfers, savings, and payments, viewing it as a "natural replacement" for traditional financial infrastructure's inefficiencies. On strategy, Sun advocates for a methodology combining data-driven iteration, rapid execution, and user-centricity. He highlights the pivotal decision to partner with Tether on TRC-20 USDT as a calculated move that capitalized on stablecoins' long-term trend and network effects. While Web3 is inherently global, Sun stresses the critical importance of local compliance and cultural adaptation for successful market entry. Looking ahead, Sun identifies the convergence of AI and blockchain as a key frontier. He sees AI as fundamentally reshaping thinking and decision-making, with blockchain providing decentralized infrastructure for AI, while AI enhances blockchain's intelligence and user experience. His advice to industry participants is to prioritize continuous learning, adaptability, and focused investment in building core, irreplaceable strengths within the broader Web3 landscape.

marsbit05/29 03:33

Hurun Report Interview with Justin Sun: New Paradigms of Value Circulation under the Web3 Transformation Cycle

marsbit05/29 03:33

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