# Attention Related Articles

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

YouTube Crypto Channel Views Drop 70% by 2026, Retail Attention Crisis Reshaping Next Cycle

Major cryptocurrency YouTube channels are experiencing a severe decline in viewership, signaling a potential crisis in retail investor attention for the next market cycle. Analysis of six top channels shows monthly view counts have plummeted 27% to 79% compared to January 2025, with four channels down approximately 75%. While subscriber counts remain high (e.g., Coin Bureau with 2.72M, Altcoin Daily with 1.65M), current engagement tells a different story. Recent 30-day view counts are significantly lower: Coin Bureau at 1.24M views, Crypto Banter at 1.06M, with Altcoin Daily and Benjamin Cowen performing relatively better at 1.79M and 1.8M respectively. The core issue is that subscriber numbers are cumulative and reflect past interest, while views measure current demand. The dramatic drop indicates a fragmented and more selective retail audience. This contrasts sharply with the 2021 bull market, where channels reportedly garnered 3-4 million daily views. Now, daily views for major channels range from roughly 35,000 to 60,000. This divergence suggests a new type of market cycle. Bitcoin's price can be sustained by ETFs and institutional activity, but without strong retail engagement via content channels, the dynamics of the next bull run will be fundamentally different. The real signal for a retail resurgence will be a sustained increase in daily and monthly view counts, not subscriber growth. If viewership fails to recover, long-form YouTube content may become a lagging indicator, with retail attention shifting to other, faster formats.

marsbit07/01 04:32

YouTube Crypto Channel Views Drop 70% by 2026, Retail Attention Crisis Reshaping Next Cycle

marsbit07/01 04:32

Why More AI Agents Does Not Equal Higher Productivity?

Editor's Note: As AI Agents become cheaper and easier to use, a new constraint emerges: the cost isn't in launching more Agents, but in the human attention required to manage, judge, and integrate their outputs. This hidden cost is called the "orchestration tax." The article argues that a developer's cognitive bandwidth is the key bottleneck—a serial, non-parallelizable resource akin to a Global Interpreter Lock (GIL). While many Agents can run concurrently, their results ultimately require human judgment for review, conflict resolution, and final integration. Therefore, more Agents don't automatically mean higher productivity; they can simply create longer queues, lead to cognitive fatigue, and create the illusion of busyness without real output. The core solution is to design workflows around this scarce human attention. Key strategies include: scaling the number of Agents to match review capacity (not UI capacity), categorizing tasks (delegating independent ones, keeping complex judgment-heavy ones serial), batch reviewing results to minimize context-switching costs, automating verifiable checks to reserve human judgment for critical decisions, and protecting focused, uninterrupted thinking time. Ultimately, the critical skill is not launching many Agents, but architecting systems that respect the fundamental limit of human attention. Unpaid "orchestration tax" accumulates as both technical and cognitive debt, undermining system understanding and quality. True productivity comes from thoughtfully managing the single-threaded resource—your focus.

marsbit05/31 22:44

Why More AI Agents Does Not Equal Higher Productivity?

marsbit05/31 22:44

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

The price of Xiaomi's MiMo-V2.5 series API has been permanently reduced by up to 99%, specifically for the "Input (Cache Hit)" cost, which covers users re-reading historical context in long conversations. MiMo's head, Luo Fuli, published a detailed technical blog to clarify that this drastic price cut stems from genuine engineering breakthroughs, not a marketing stunt or a simple price war. The core of the achievement lies in six key engineering optimizations. First, the model architecture adopts a Hybrid Sliding Window Attention (SWA), reducing the memory footprint (KVCache) to 1/7th of a traditional model. Second, a dual-pool memory management system actually utilizes these savings, allowing a single GPU to handle over 5 times more concurrent users. Third, an upgraded prefix caching mechanism achieves a cache hit rate of 93-95% for repeated reads, meaning most such requests bypass GPU computation entirely. Fourth, a self-developed distributed cache (GCache) utilizes idle SSD space on existing GPU servers, eliminating additional storage costs. Fifth, an intelligent scheduling system (LLM-Router) efficiently routes requests to maximize cache reuse and performance. Sixth, Multi-Token Prediction (MTP) accelerates the model's text generation ("output") side. Together, these systemic optimizations dramatically lower the real computational cost per request, enabling the 99% price reduction for cached inputs while reportedly maintaining positive gross margins. Luo Fuli's disclosure aims to shift the narrative from "price war" to a demonstration of substantive AI engineering progress.

marsbit05/31 10:37

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

marsbit05/31 10:37

The Fall of Crypto Actually Has Little to Do with Scamming Retail Investors

The decline of Crypto is not primarily due to "scamming retail investors," but stems from deeper structural issues, according to a seasoned Crypto OG. Key problems include: 1. **Misunderstanding of Bitcoin’s Whitepaper**: The core concept is not "decentralization" (a term absent in the whitepaper) but "distributed trust architecture" — eliminating the need for trusted third parties. Many projects fail to achieve even basic distributed systems while overusing decentralized rhetoric. 2. **Loss of Incremental Users**: Grand narratives (Web3, Metaverse, GameFi, etc.) have oversold the technology’s capabilities, leading to repeated user disappointment and eroded trust. The market now suffers from a lack of new participants. 3. **Erosion of Community Belief**: Many communities engage in "narrative engineering" — using complex jargon to attract new users while insiders anticipate selling at peaks. This creates a cycle of hype, pump, and dump, damaging overall market credibility. 4. **Premature Financialization**: Crypto prioritized token launches and financialization before establishing robust infrastructure or mature applications. This led to overvaluation and repeated failures when technology couldn’t support inflated prices. 5. **Shift in Attention**: Human attention is moving from social and community interactions (like Telegram and Discord) toward AI-driven engagement. As an attention-dependent market, Crypto is naturally declining as interest wanes. The OG concludes that while Crypto isn’t dead, its current narrative has ended. The real tragedy is exhausting two decades of storytelling in just three years, before the underlying technology was ready. Scams are inevitable in markets, but the absence of new believers is fatal.

比推03/12 18:31

The Fall of Crypto Actually Has Little to Do with Scamming Retail Investors

比推03/12 18:31

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