# AI Related Articles

HTX News Center provides the latest articles and in-depth analysis on "AI", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

The True Value of DeepSeek V4 Lies Beyond Parameters

DeepSeek V4 represents a strategic breakthrough for China’s AI industry, not merely for its technical specifications—such as its 1.6 trillion parameters or 1 million token context length—but for its successful adaptation to domestic computing hardware like Huawei’s Ascend 950 and Cambricon chips. This move reduces reliance on NVIDIA’s CUDA ecosystem, which has long dominated AI training and inference. The model achieves this through several innovations: a hybrid attention mechanism (CSA + HCA) that optimizes long-context processing, MoE architecture that activates only a fraction of parameters per inference, and deep software-hardware co-design with domestic chipmakers. These improvements make it feasible to run a top-tier model efficiently on local hardware, significantly lowering inference costs and enhancing scalability. Priced competitively, DeepSeek V4 offers long-context capabilities at a fraction of the cost of comparable models, enabling practical enterprise applications—such as legal document analysis, financial research, and coding agents—that require processing large volumes of data in real-time. This demonstrates China’s growing ability to innovate within hardware constraints and marks a critical step toward AI supply chain independence.

marsbit04/25 08:08

The True Value of DeepSeek V4 Lies Beyond Parameters

marsbit04/25 08:08

a16z Founder: In the Agent Era, What Truly Matters Has Changed

Founder of a16z Marc Andreessen discusses the transformative shift into the Agent era in a recent podcast. He emphasizes that today’s AI is not an overnight breakthrough but the result of an 80-year evolution, now reaching practical utility. Key developments include the convergence of LLMs, reasoning models, coding capabilities, and agent-based recursive self-improvement. Andreessen describes agents as systems integrating LLMs with shells, file systems, markdown, and schedulers—combining new AI with established software components. This architecture enables introspection, state persistence, and cross-platform execution, moving beyond chatbots toward agent-first interaction. He predicts traditional UIs will fade as agents execute tasks on behalf of users or other bots. He compares the current AI investment cycle to the dot-com bubble but highlights stronger fundamentals, with major tech firms leading scalable, revenue-generating infrastructure expansion. Open source, edge inference, and local AI deployment are critical to global adoption and competition. Andreessen also addresses broader challenges: security risks, identity verification, financial infrastructure for agents, and organizational adoption. He cautions that societal and institutional barriers will shape the pace of AI integration, tempering both utopian and dystopian expectations.

marsbit04/25 02:05

a16z Founder: In the Agent Era, What Truly Matters Has Changed

marsbit04/25 02:05

DeepSeek No Longer Wants to Focus Only on Large Models

DeepSeek, a leading Chinese AI company, has released its new model series DeepSeek-V4, featuring two versions: the high-performance V4-Pro with 1.6 trillion parameters and the cost-efficient V4-Flash. Both support 1 million token context windows and use Mixture-of-Experts (MoE) architecture to improve efficiency. The company continues its strategy of offering competitive pricing, with input tokens priced as low as ¥0.2 per million tokens. A key revelation is DeepSeek’s explicit link between future price reductions and the mass availability of Huawei’s Ascend 950 AI chips in the second half of the year. This signals a strategic shift from relying solely on algorithmic and engineering optimizations to integrating domestic computing power into its core cost structure. DeepSeek has adapted its inference system to run efficiently on both NVIDIA GPUs and Huawei NPUs, potentially challenging NVIDIA's CUDA ecosystem dominance. Concurrently, DeepSeek is reportedly seeking significant external investment, with a pre-money valuation of around ¥300 billion. This move highlights growing pressures in scaling compute infrastructure, retaining top talent—amid recent departures of key researchers—and accelerating commercialization efforts. The company has also updated its consumer app with tiered model access, indicating a stronger product focus. The V4 release underscores that China's AI competition is evolving beyond pure model capability into a broader contest involving compute supply chains, engineering systems, financing, and talent strategy.

marsbit04/25 01:45

DeepSeek No Longer Wants to Focus Only on Large Models

marsbit04/25 01:45

AI Defeated Intel, and AI Saved Intel

Intel, once the dominant force in semiconductors with its CPUs powering the PC era, faced a severe crisis by 2024. Its stock plummeted 60% that year, culminating in its removal from the Dow Jones Industrial Average, replaced by NVIDIA—a shift symbolizing the transition from CPU to GPU dominance in the AI training era. Intel’s decline was driven by missed opportunities in mobile and AI, exacerbated by strategic missteps under multiple CEOs. In 2025, new CEO Lip-Bu Tan took over, implementing a turnaround strategy: drastic cost-cutting, refocusing on core areas like Xeon server CPUs and foundry services, and forging key partnerships. NVIDIA invested $5 billion in Intel, Google expanded orders for Xeon processors, and Elon Musk integrated Intel into his Terafab project. These moves, coupled with the AI industry’s shift from training to inference, revitalized demand for CPUs, which are critical for task orchestration in agent-based workloads. By Q1 2026, Intel’s revenue grew 7% year-over-year, with non-GAAP net income surging 156%. However, challenges remain, including ongoing losses and the need to scale advanced manufacturing processes. Intel’s recovery, while promising, hinges on sustaining this momentum in a rapidly evolving market.

marsbit04/25 01:32

marsbit04/25 01:32

Qubic Launches Dogecoin Mining Phase 3: What It Means For DOGE

Qubic has fully transitioned to its Dogecoin-focused mining architecture, marking the start of Phase 3 and removing Monero from its operations. The new system dedicates ASICs entirely to mining Dogecoin (DOGE) while CPUs and GPUs are used to train its AI framework, Aigarth—both running simultaneously at full capacity without alternating. The project claims this model offers higher profitability, reporting a 32% increase in daily earnings compared to traditional DOGE mining pools. Additionally, Qubic uses a circular capital mechanism where mined DOGE is sold to buy back its native token QU, which is then distributed to participants. While Qubic’s current hashrate share remains small (around 0.086%), the shift represents a tangible entry into Dogecoin mining. The focus now is on whether the project can scale its operations and impact DOGE mining landscape meaningfully. At the time of writing, DOGE was trading at $0.09791.

bitcoinist04/24 16:01

Qubic Launches Dogecoin Mining Phase 3: What It Means For DOGE

bitcoinist04/24 16:01

Long-Term Outlooks Suggest Ozak AI Could Sustain Multi-Dollar Price Levels Through Multiple Market Cycles

Long-term analyst outlooks suggest Ozak AI ($OZ) could sustain multi-dollar price levels across multiple market cycles, rather than retracing after an initial spike. Currently priced at $0.014 in presale with over $6.8M raised, the project is viewed as a long-term AI infrastructure asset rather than a short-term trade. Key factors supporting this view include its utility-driven demand, capital-efficient pricing structure, and ecosystem integrations with partners like Pyth Network and SINT. Analysts highlight that Ozak AI’s lower initial valuation requires smaller capital inflows to maintain higher price zones, increasing the likelihood of stability in the $3–$5 range as adoption grows. The platform’s AI Prediction Agents, data vaults, and EigenLayer AVS validation are expected to generate persistent token demand through various market conditions.

TheNewsCrypto04/24 13:32

Long-Term Outlooks Suggest Ozak AI Could Sustain Multi-Dollar Price Levels Through Multiple Market Cycles

TheNewsCrypto04/24 13:32

REAL Partners with RWA Inc. to Accelerate Tokenized Asset Infrastructure

REAL has entered into a strategic partnership with RWA Inc., a global platform specializing in real-world asset (RWA) tokenization, investor access, and Web3 growth infrastructure. The collaboration aims to build a more robust and scalable blockchain-based financing infrastructure. Together, they will explore how REAL’s RWA-focused Layer 1 blockchain can support tokenized asset issuances originated via RWA Inc., while improving investor onboarding, distribution, and post-issuance servicing. Key areas of cooperation include tokenized asset issuance, AI-powered automation, distribution channels, co-marketing initiatives, and the future use of AI in governance and financial workflows. The partnership seeks to create a more accessible, efficient, and scalable foundation for bringing real-world assets onto the blockchain.

TheNewsCrypto04/24 12:49

REAL Partners with RWA Inc. to Accelerate Tokenized Asset Infrastructure

TheNewsCrypto04/24 12:49

Not Just DeepSeek, Big Tech Companies Want to 'Abandon' NVIDIA

The article discusses how major tech companies are attempting to reduce their reliance on Nvidia, despite its dominant position in the AI chip market, where it enjoys a 75.2% GAAP gross margin. Companies like DeepSeek are adapting their models to run on domestic alternatives such as Huawei’s Ascend chips, while in the U.S., Google and Meta are developing their own AI chips (TPU and MTIA series) to complement external partnerships. Nvidia’s CEO, Jensen Huang, acknowledges that Moore’s Law is fading and that export restrictions may slow China’s AI development but could ultimately spur a self-sufficient ecosystem. Notably, Chinese firms are leading in open-source models, which could eventually challenge Nvidia’s monopoly. OpenAI is actively diversifying away from Nvidia, signing a $20 billion deal with Cerebras, a startup using wafer-scale chips to reduce latency and cost. Cerebras, founded by Andrew Feldman, aims to challenge Nvidia with its unique architecture but faces financial and competitive risks, including heavy dependence on OpenAI and geopolitical tensions. While competition is intensifying with players like AMD and Groq (which partnered with Nvidia), the overall demand for compute continues to grow. The market is shifting toward a diversified supplier model, though Nvidia remains a formidable force.

marsbit04/24 12:29

Not Just DeepSeek, Big Tech Companies Want to 'Abandon' NVIDIA

marsbit04/24 12:29

Ozak AI’s Forecast Range Expands to $8–$11 as AI Adoption Accelerates Across DeFi, Data, and Automation Markets

Ozak AI ($OZ) is emerging as a leading AI-backed crypto investment, positioned at the intersection of AI, DePIN (Decentralized Physical Infrastructure Network), and tokenized economic growth. With AI adoption accelerating in DeFi, data analytics, and automation, the project's forecasted value has expanded to a range of $8–$11. Currently in advanced presale stages, Ozak AI has raised over $6 million, with tokens priced at $0.014, indicating strong pre-listing commitment. Its DePIN architecture supports scalable, decentralized AI processing, distinguishing it from other AI tokens. The $OZ token offers utility through staking, voting, and network expansion, driving demand. The $8–$11 valuation is based on successful presale activity, exchange listings, and growing adoption in decentralized markets, positioning Ozak AI for significant potential growth.

TheNewsCrypto04/24 12:19

Ozak AI’s Forecast Range Expands to $8–$11 as AI Adoption Accelerates Across DeFi, Data, and Automation Markets

TheNewsCrypto04/24 12:19

Illustrating the Capital Market After DeepSeek V4's Launch: Zhipu and MiniMax Plunge, NVIDIA Panics

DeepSeek V4, a 1T parameter MoE model with a 285B Flash version, has been fully open-sourced under Apache 2.0, triggering significant reactions across capital markets. Chinese AI chipmakers like Cambricon and Hygon saw major stock gains, with Cambricon rising 60% monthly. In contrast, Hong Kong-listed AI firms Zhipu and MiniMax dropped over 7%, facing heavy short-selling. NVIDIA’s shares dipped, with analysts noting a "decoupling" of Chinese and North American AI inference demand. The launch intensified competition in the AI model space, following 11 major releases in 30 days, including GPT-5.5 and Llama 4. Unlike others, V4’s permissive licensing and full open-source release challenged closed-source models on performance, cost, and accessibility. Critically, V4 announced Day-0 support for domestic chips like Huawei’s Ascend 950PR and Cambricon’s Siyuan 590, offering better cost-performance than NVIDIA counterparts. This shift reduces reliance on CUDA, aligning with NVIDIA CEO’s earlier concerns about Chinese AI chips threatening its dominance. The move signals a tangible step in China’s AI supply chain independence, redirecting compute demand to local manufacturers like Hua Hong Semiconductor.

marsbit04/24 11:37

Illustrating the Capital Market After DeepSeek V4's Launch: Zhipu and MiniMax Plunge, NVIDIA Panics