# Efficiency Related Articles

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

Cardano Foundation Drafts Dijkstra Upgrade For Smart Contract Execution

The Cardano Foundation has released a draft Cardano Improvement Proposal (CIP) called "Dijkstra," which proposes changes to enhance smart contract execution pathways and computational efficiency on the network. The proposal is currently in the discussion phase and is not active on the Cardano mainnet; it must progress through community review and refinement before potential implementation. Dijkstra addresses a core long-term challenge for Cardano: improving developer experience and smart contract performance without compromising its methodical, research-driven design philosophy. Enhanced execution efficiency could reduce computational friction, enabling developers to build more scalable and complex decentralized applications (dApps). This is seen as crucial for Cardano's competitiveness in a crowded smart contract market that includes rivals like Ethereum, Solana, and Avalanche. The publication of the CIP draft marks the start of a community evaluation process. Developers will assess its technical merits, potential trade-offs, and alignment with Cardano's broader roadmap. While the outcome is not guaranteed, the proposal signals ongoing work to strengthen Cardano's application layer for the future. The article emphasizes that the technical development story holds more significance than short-term market price movements.

bitcoinist08/21 06:44

Cardano Foundation Drafts Dijkstra Upgrade For Smart Contract Execution

bitcoinist08/21 06:44

Perspective: Value Investing in U.S. Stocks Is Not the Same as Fundamental Investing

The article challenges the notion that value investing in US stocks is equivalent to fundamental investing. It uses the astronomical analogy of Henrietta Leavitt separating a star's apparent brightness from its intrinsic luminosity to illustrate a key investment framework: an observed valuation multiple (like brightness) conflates two things—the actual quality of a business and the premium the market is willing to pay for its future (its "distance" or duration). The author argues that the popular narrative of "fundamentals are dead"—fueled by momentum and concentration in mega-cap tech—is flawed. While recognizing factors like winner-take-all dynamics and AI scale advantages, the piece warns against confusing broad thematic truths (e.g., "AI is big") with justified valuations for specific companies. It introduces a 2x2 matrix categorizing stocks based on whether they *looked* cheap/expensive at a point in time versus whether they *were* actually cheap/expensive in hindsight (e.g., expensive-looking Meta in 2022 was actually cheap). The core formula presented is: Forward Return ≈ Fundamental Growth × Change in Valuation Multiple. Over short periods, multiple changes drive returns, making markets seem narrative-driven. Over the long term, fundamental growth dominates. The article concludes that markets may be becoming *less* efficient due to complex, long-duration business models, narrative cycles, and private market dynamics, creating more opportunities for investors who can disentangle real quality from market sentiment.

marsbit08/21 05:26

Perspective: Value Investing in U.S. Stocks Is Not the Same as Fundamental Investing

marsbit08/21 05:26

After Two and a Half Years of Entrepreneurship and Full AI Adoption, the Company Has Actually Become More 'Traditional'

"After 2.5 years of running my company, achieving near 100% AI adoption with Agents in roles like finance, HR, and operations, we've paradoxically become more 'traditional.' We learned that establishing a thick AI middle layer creates bottlenecks. Instead, we advocate for a 'thin platform, thick frontline' model, empowering employees closest to problems to use AI tools themselves, fostering ownership and initiative. The true foundation isn't the AI models, but the unique data and context a company accumulates—our most vital, irreplaceable asset, requiring diligent governance. As AI handles repetitive, describable tasks, human roles revert to their core: building genuine relationships, trust, and brand reputation through authentic communication, which AI cannot accelerate. A critical question is where the time saved by AI goes. It must be returned—to clients, to creative work, to employees' own lives—rather than just fueling higher output demands. For managers, AI strips away execution-focused busywork, exposing the necessity to define clear goals, make tough judgments, and take ultimate responsibility. Onboarding newcomers presents a challenge: while AI can generate 80% solutions instantly, we must deliberately design paths for them to develop judgment, understand context, and safely learn from mistakes. Ultimately, AI's organizational value isn't about replacing people but removing unnecessary friction, allowing more meaningful human connection. The real test of an 'AI-era' company isn't its tech stack, but how it treats people: delegating creative power, returning saved time, fostering growth, and upholding accountability. The core luxury and purpose of our work remains authentic human relationships."

marsbit08/21 02:02

After Two and a Half Years of Entrepreneurship and Full AI Adoption, the Company Has Actually Become More 'Traditional'

marsbit08/21 02:02

Programmers Around the World Are Giving Money Away to Anthropic for Free, and the Company Finally Can't Stand It Anymore

Anthropic's recent blog post urges developers using Claude Code to stop wasting money on tokens. The core issue is inefficient usage that inflates costs, often unbeknownst to users. The article outlines six key optimization strategies: 1) Use `/clear` after completing a task to prevent irrelevant previous context from bloating future interactions. 2) Set the model and reasoning effort level at the start of a session; changing them mid-conversation invalidates the prompt cache, forcing a full-price recomputation of the entire history. 3) Attach files with `@` instead of typing paths manually to avoid unnecessary tool calls and exploratory file reads that add to the context. 4) Add quiet flags to noisy commands (e.g., in `CLAUDE.md`) to minimize lengthy output that fills the context window. 5) Use `/compact` before a break while the cache is still hot, as it costs only one-tenth of compressing after the cache expires. 6) Offload large-output tasks to sub-agents, which run in isolated contexts and only return conclusions, keeping the main conversation lean. The cost structure is explained: output tokens are 5x more expensive than input tokens due to serial "decoding." Pricing depends on the model (Opus, Sonnet, Haiku) and reasoning effort level. The most powerful cost-saving tool is the **prompt cache**, which allows reusing previously computed prefixes at 10% of the input cost. However, the cache is fragile and invalidated by switching models, changing effort levels, toggling Fast mode, using `/compact`, session timeout, or resuming old sessions. A critical problem is **context bloat (O(n²) growth)**, where each interaction accumulates files read and command outputs, making every subsequent round more expensive. Strategies to combat this include using `@` for files, quiet flags for commands, employing sub-agents, and using `/clear` or `/compact`. The `/rewind` command is also noted for trimming recent off-track turns without breaking the cache. The post frames efficient token management as a new essential skill for developers in the AI era, crucial for maximizing productivity within a budget.

marsbit08/17 03:46

Programmers Around the World Are Giving Money Away to Anthropic for Free, and the Company Finally Can't Stand It Anymore

marsbit08/17 03:46

BNB Chain’s BEP-675 Proposal Targets Faster Block Building

BNB Chain has proposed BEP-675, a draft upgrade aimed at increasing network throughput by optimizing the block production process. The core change introduces blind signing, allowing builders to submit pre-executed blocks directly to validators. This is designed to eliminate redundant execution work, potentially reducing a validator's critical path execution time from 125ms to 15ms. Initial testnet results indicate a possible doubling of throughput. Unlike scaling via larger blocks or shorter block times, this proposal focuses on workflow efficiency. It's important to note BEP-675 is currently a draft under the Pasteur hard fork timeline and is not active on the mainnet. If successfully implemented, it would provide BNB Chain with more performance headroom to support its high-activity ecosystem.

bitcoinist08/12 10:08

BNB Chain’s BEP-675 Proposal Targets Faster Block Building

bitcoinist08/12 10:08

When 'Odysseus' Encounters the Algorithm

Christopher Nolan's "Odyssey," a $250 million IMAX epic, premiered in July 2026, quickly grossing over $1 billion and setting box office and critical records. The film's production was defined by its physical scale: shooting across six countries with practical effects, custom-built IMAX cameras, and extensive use of film. Concurrently, the AI-generated film "Odysseus: The Fall," created by the independent studio Fountain0 for just $50,000, demonstrated the technical feasibility of AI in long-form filmmaking. This stark 5,000x cost difference highlights a broader industry conflict between traditional, experience-driven production and algorithmic efficiency. While the AI film achieved technical success, it revealed current limitations, such as unstable long shots, inconsistent characters, and a lack of nuanced emotional performance. More importantly, its infinite, low-cost nature lacks the scarcity and immersive "event" status that fuels the theatrical premium for films like Nolan's. The market strongly favored the traditional model's brand security, physical assets, and premium theatrical experience. The analysis suggests AI will not replace auteurs like Nolan but will significantly disrupt mid-tier productions and technical, labor-intensive roles (e.g., pre-visualization, VFX). This could erode the career pathways for future directors. Paradoxically, as AI content proliferates, the perceived value of "handcrafted," physically-shot cinema may rise, akin to artisanal goods. The core tension is framed as the irreconcilable conflict between algorithmic "efficiency logic" and cinematic "experience logic." Ultimately, the enduring human preference may be for the unique, difficult journey of traditional storytelling over the predictable, algorithmically smooth path.

marsbit08/10 03:53

When 'Odysseus' Encounters the Algorithm

marsbit08/10 03:53

Kenyan KNEC Places 15 Million Academic Records on Avalanche

The Kenyan National Examinations Council (KNEC) has digitized over 15 million academic records on the Avalanche ($AVAX) C-Chain blockchain. This new system allows for near-instant verification of certificates for job seekers and employers, replacing a paper-based process that previously took up to six months for large-scale checks. The initiative, developed with local tech firm LegitDoc, covers key exam records (KCPE, KCSE), professional diplomas, and teacher certificates. It aims to combat fraud by providing immutable, secure records easily verifiable through an official portal. While the network's ability to handle high volumes at low cost makes it attractive for such large-scale government projects, the price of AVAX has seen a significant decline. This project follows other major government uses of Avalanche, including land record management in India and document handling by California's DMV.

cryptonews.ru08/03 23:23

Kenyan KNEC Places 15 Million Academic Records on Avalanche

cryptonews.ru08/03 23:23

How Token-Hungry is Claude Code? A Comparative Experiment Shows Up to 30x Difference Across Three Frameworks

Claude Code's Token Consumption Exposed: Comparison Experiment Shows Up to 30x Difference Between Frameworks A recent experiment by the Composio team tested the same model (Kimi K3) across three different agent frameworks (Claude Code, Hermes, and Kimi Code) on 28 identical tasks. While task completion rates were similar, token consumption varied dramatically. The median token usage was approximately 61k for Kimi Code, 67k for Hermes, and a staggering 340k for Claude Code – about 6 times more than Kimi Code. For individual tasks, the maximum difference reached 30x. In terms of cost, using Claude Code averaged $2 per task compared to $0.22 for Kimi Code and $0.28 for Hermes (based on Kimi K3 pricing). Speed also differed, with Hermes being the fastest. Analysis suggests Claude Code's high token usage stems from its harness repeatedly feeding extensive context (previous messages, tool calls, command outputs, file contents) back into the model across multiple interaction rounds, significantly inflating input tokens rather than generating longer outputs. This highlights a crucial trend: the agent framework (harness) is becoming as important as the model itself for cost and efficiency. A separate study from Writer showed that simply switching the orchestration layer to their optimized harness reduced average task cost by 41% and latency by 44% across various models without sacrificing quality. The conclusion is clear: for cost-effective AI agents, optimizing the harness may yield greater savings than changing the model. The future of agent competition may hinge not just on capability ("can it do it?") but on efficiency ("who does it for less?").

marsbit07/31 12:26

How Token-Hungry is Claude Code? A Comparative Experiment Shows Up to 30x Difference Across Three Frameworks

marsbit07/31 12:26

The Blockchain Industry Enters a Phase of Mass Adoption and Efficiency

In Q2 2026, the blockchain industry demonstrated a divergence between market sentiment and fundamental network growth. While on-chain activity surged, network fee revenues declined due to protocol designs making block space cheaper and more abundant. Ethereum saw institutional staking reach an all-time high of 40.2 million ETH. Despite processing nearly double the transactions per second, its network revenue fell 51% YoY to $64 million, with staker yields driven primarily by consensus rewards. Solana processed nearly 10 billion transactions, but its economic value also dropped to $51 million due to reduced congestion. Notably, its real-world asset (RWA) sector boomed, with tokenized stock trading volume growing 2,479x YoY to $3.32 billion in June 2026. Hyperliquid emerged as an outlier, generating $175 million in revenue with 32% of its $652 billion trading volume from non-crypto markets like commodities. Avalanche saw transaction growth but a sharp drop in fee revenue, while focusing on sovereign L1s for enterprise use. The NEAR Protocol ecosystem shifted from gas-intensive apps to Intents-based trading and introduced a novel feature allowing users to pay for AI services via staked tokens. The Tempo network, backed by Stripe and Paradigm, processed $386 million in stablecoin transfers, including $30 million for contractor payouts by Deel. The report concludes that the industry is transitioning from high-fee speculation to a phase of mass adoption and infrastructure efficiency, where cheap block space fuels transaction growth and institutional entry.

cryptonews.ru07/31 11:46

The Blockchain Industry Enters a Phase of Mass Adoption and Efficiency

cryptonews.ru07/31 11:46

Aave Gradually Phasing Out 75 Low-Utilization Reserve Assets! Here Are the Details

The leading decentralized finance (DeFi) lending protocol, Aave, has announced a major restructuring to improve platform efficiency. Founder Stani Kulechov stated the protocol will gradually phase out underutilized assets and scale back operations on certain blockchains. Specifically, Aave plans to cease support for 50 underused reserve assets on its native network and an additional 25 reserve assets across the Sonic, Scroll, zkSync, Metis, Soneium, and Aptos networks, totaling 75 assets. Management explained this move aims to allocate resources more efficiently and focus on assets with higher user demand. The restructuring will affect approximately $98.1 million in reserve assets and $15.6 million in loan positions. Aave stated the phase-out will be gradual, with transition plans to minimize user disruption. Experts note that periodically removing low-liquidity or underused assets is common in DeFi to reduce maintenance costs and enhance security and operational efficiency. As one of the world's largest DeFi protocols by Total Value Locked (TVL), Aave's decision may cause short-term liquidity shifts in affected assets but is viewed as a step toward building a more efficient and sustainable ecosystem in the long term.

cryptonews.ru07/30 09:21

Aave Gradually Phasing Out 75 Low-Utilization Reserve Assets! Here Are the Details

cryptonews.ru07/30 09:21

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