# Software Related Articles

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

Founder of Baixing.com: The Notion That Large Language Models Will Devour Everything, I Believe Half of It

Founder of Baixing.com: I Only Half-Believe the Saying “Large Language Models Will Devour Everything” Author: Wang Jianshuo, Founder of Baixing.com Many proclaim that large models are everything, but the author is skeptical. He argues that such sweeping claims often stem from a limited understanding of the future. Drawing parallels to past technologies like electricity and the internet—which were predicted to “devour everything” but didn’t—he suggests that large language models (LLMs) are better seen as a foundational base. Like electricity, this base is essential for modern development, but its real value emerges only when applied to specific scenarios through various “machines” or “tools” (e.g., Claude Code for programming, Claude Design for design). The author acknowledges that LLMs may indeed replace many existing software systems built on rigid rules, workflows, and forms (e.g., CRMs, SaaS tools), as these are precisely what LLMs excel at processing. However, he emphasizes that beyond software, elements like customer data, execution capabilities (e.g., booking a flight), trust, and physical-world interactions will not be “devoured.” Instead, he foresees that after streamlining existing software, LLMs will open up a larger space for innovative, next-generation applications. These new tools will likely feature fluid interfaces and rely less on fixed rules, unleashing greater creativity. The author cautions against short-sightedness, recalling how in 2004 many believed internet giants like Sina, Sohu, and NetEase would monopolize the market—only to be proven wrong by subsequent disruptions. In conclusion, while LLMs are a crucial foundation and a current focal point, the true mainstream of this wave lies in the diverse applications built atop them to solve concrete problems. The phrase “devour everything” is imprecise; the real opportunity lies in identifying and leveraging the areas where LLMs do bring transformative change.

marsbit07/07 13:54

Founder of Baixing.com: The Notion That Large Language Models Will Devour Everything, I Believe Half of It

marsbit07/07 13:54

Founder of Baixing.com: I Only Half Believe in the Notion that Large Language Models Devour Everything

The founder of Baixing Wang states that while large language models (LLMs) are an extremely important foundational technology—akin to electricity or the internet—he only "half believes" the notion that they will "consume everything." He argues that LLMs provide a base layer of intelligence, but real-world value and transformation come from integrating this intelligence into specific applications and devices designed for particular scenarios—like how electricity powers various appliances from washing machines to TVs. He agrees LLMs will likely consume or replace a significant portion of existing rule-based, workflow-driven software (e.g., many SaaS systems, CRMs), as these are precisely what LLMs excel at handling. However, numerous other elements—such as customer data, execution capabilities (e.g., booking a flight), trust, and physical-world interactions—will not be consumed. Wang emphasizes that after LLMs absorb certain software layers, they will open up a much larger space for innovation: new types of "streaming" software with less rigid interfaces, where fixed rules are managed by AI. This next wave of applications built on top of the stable LLM foundation is where the true mainstream opportunity lies. He cautions against the short-sightedness of declaring any technology as all-consuming, drawing parallels to past premature predictions about internet giants monopolizing the web. The key is to find opportunities within the areas LLMs do transform.

链捕手07/07 13:48

Founder of Baixing.com: I Only Half Believe in the Notion that Large Language Models Devour Everything

链捕手07/07 13:48

A Year Consumes a Solid-State Drive: Codex Log Bug Slammed as 'Slopware'

OpenAI's flagship AI coding tool, Codex, was found to have a critical bug causing its feedback logging system to silently and rapidly wear out users' SSDs. A developer reported that Codex was writing approximately 640 TB of data per year to a local SQLite database (`logs_2.sqlite`) through a constant cycle of inserting and immediately deleting log entries, primarily at the verbose TRACE level. While the database file itself remained around 1 GB, the underlying write-amplification from SQLite's WAL mechanism meant the physical SSD endured the full write load. This was enough to exceed the typical 600 TBW endurance rating of a consumer SSD within a year. The root cause was a hardcoded default logging level (`Level::TRACE`) in the configuration, which overrode any user attempts to reduce logging via environment variables. Analysis showed that over 96% of the logged data—including noisy WebSocket packet dumps and repeated system file events—was useless debug information. The issue, which had at least nine related bug reports in the Codex repository, remained latent because it didn't visibly consume disk space, only silently accumulated write cycles. After the report gained traction on Hacker News, OpenAI merged fixes estimated to reduce writes by about 85%. However, even post-fix, the tool would still write an estimated 96 TB annually. The incident sparked broader criticism of "slopware" in AI-assisted development tools, highlighting a lack of resource budgeting for disk, CPU, and memory in always-on agent software, and a reliance on modern hardware to mask inefficient code. Competing tools like Claude Code were noted to have similar issues.

marsbit07/02 08:50

A Year Consumes a Solid-State Drive: Codex Log Bug Slammed as 'Slopware'

marsbit07/02 08:50

David Schwartz Backs XRP Ledger 3.2.0 Upgrade With Major XRPL Hub Move

David Schwartz, co-creator of XRP Ledger and Ripple's CTO, has moved a major XRPL hub to version 3.2.0, a transition completed in under ten minutes. This upgrade follows the ledger's core software being renamed "xrpld" to distinguish it from Ripple. Key improvements include up to 40% better memory optimization and the fixCleanup3_2_0 amendment, enhancing security for features like vaults and decentralized exchanges. The update also introduces new tools for developers and invariant checks for ledger integrity. Concurrently, network governance updates include changes to the Unique Node List. The move underscores the commitment to maintaining the latest software across the XRPL ecosystem.

TheNewsCrypto06/17 13:45

David Schwartz Backs XRP Ledger 3.2.0 Upgrade With Major XRPL Hub Move

TheNewsCrypto06/17 13:45

Cursor's New 1.5T Model Abandons Kimi Foundation, $60 Billion Stock Swap for Cursor, Musk's First Move Targets Microsoft's GitHub

Cursor, a popular AI-powered coding tool, has been acquired by SpaceX in an all-stock deal valued at $60 billion. The announcement coincided with Cursor's unveiling of major new developments at the Compile conference: a new 1.5 trillion+ parameter AI model and a "GitHub for agents" platform called Origin. The upcoming model, trained from scratch on over 100,000 GPUs with 10-20x more computational power than before, marks a shift from Cursor's previous reliance on models like Kimi. Cursor's CEO, Michael Truell, emphasized the model will be a "generally intelligent" assistant, moving beyond just code generation to handle broader engineering tasks like planning, testing, and UI interaction. Simultaneously, Cursor introduced Origin, a "Git-native" code hosting platform designed for AI agents that perform thousands of operations daily, featuring automated conflict resolution for large-scale, AI-generated code changes. The acquisition by SpaceX provides Cursor with significant computational resources. Analysts suggest this combination—Cursor's expertise in reinforcement learning and SpaceX's computing power—could position them strongly in the AI race, potentially challenging established players like GitHub, Claude Code, and Codex.

marsbit06/17 10:28

Cursor's New 1.5T Model Abandons Kimi Foundation, $60 Billion Stock Swap for Cursor, Musk's First Move Targets Microsoft's GitHub

marsbit06/17 10:28

Helius CEO Says Crypto’s ‘Straw Houses’ Face Collapse As AI Raises The Stakes

Helius Labs CEO Mert Mumtaz warns that cryptocurrency is entering a critical security phase, demanding spaceflight-level rigor. He argues crypto's promise of irreversible execution can no longer tolerate the "sloppy" software standards of traditional web apps, where bugs can be patched. Instead, immutable financial code must be provably correct, akin to launching a spaceship. Mumtaz connects this to the historical "software crisis" and the need for formal verification. He criticizes the industry's "facade of decentralization"—reliance on admin keys and emergency interventions—which masks underlying fragility. AI is a dual catalyst: while it empowers attackers to find exploits faster, it also makes rigorous practices like formal verification, audits, and invariant checking more accessible at scale. This will trigger a "trial by fire" and "aggressive natural selection," separating robust "serious infrastructure teams" from fragile "straw house" protocols that may collapse. The ultimate goal is a crypto industry where demonstrable correctness and security are paramount, making it safer and more robust than centralized finance. Mumtaz's warning comes as AI models like Claude advance, compressing the time for both offensive and defensive security research in DeFi.

bitcoinist06/11 09:02

Helius CEO Says Crypto’s ‘Straw Houses’ Face Collapse As AI Raises The Stakes

bitcoinist06/11 09:02

Just Now, Claude Mythos 5 Released, Handles 50 Million Lines of Code in One Day

Anthropic has unveiled Claude Fable 5 and the more powerful Claude Mythos 5, its new flagship AI models. Fable 5, available to most users, features a safety mechanism that downgrades risky queries to the older Claude Opus 4.8. The unrestricted Mythos 5 is limited to trusted users for sensitive fields like cybersecurity and bio-research. Key capabilities include exceptional performance in software engineering, completing a 50-million-line code migration in one day, and advanced visual reasoning, demonstrated by autonomously beating a Pokemon game using only screenshots. The models excel at long-context tasks, complex analysis in finance/law, and frontier scientific research. Mythos 5 has independently designed protein compounds now in drug development pipelines. Pricing is set at $10 per million input tokens and $50 per million output tokens. The release signifies a shift in human-AI interaction, with early testers noting it feels less like directing a tool and more like delegating to an autonomous "studio" capable of executing multi-hour projects from high-level instructions.

marsbit06/10 00:23

Just Now, Claude Mythos 5 Released, Handles 50 Million Lines of Code in One Day

marsbit06/10 00:23

Presidential Q1 Holdings Disclosure: Trump's Money Accelerating Investment in AI Infrastructure?

President Trump's Q1 financial disclosure revealed a significant shift in his portfolio, with over $220 million in trading volume across 3,711 transactions. The key move was a reduction in "old platform" tech giants like Microsoft, Amazon, and Meta, as well as some defensive assets, with funds reallocated towards AI infrastructure. This reallocation systematically targets the AI supply chain: semiconductor leaders (Nvidia, Broadcom, Intel, AMD, Micron); AI hardware/server companies like Dell; enterprise software firms integrating AI (Oracle, ServiceNow, Adobe, Workday); and consumer electronics (Apple). Investments in broad market ETFs and bonds were maintained for balance. The disclosure, while not a direct trading guide due to lag and imprecise data, signals a notable trend: "smart money" is moving from mature internet platforms toward AI's physical and foundational layers—semiconductors, hardware, domestic manufacturing, and enterprise software adoption. This aligns with broader U.S. policy focuses on supply chain security and AI infrastructure, highlighting AI's evolution from models and applications to a full-scale build-out of its underlying ecosystem.

marsbit06/02 08:35

Presidential Q1 Holdings Disclosure: Trump's Money Accelerating Investment in AI Infrastructure?

marsbit06/02 08:35

The Death of the Three-Act Play: AI Ushers Enterprise Software Startups into the ‘Speedrun Era’

The Death of the Three-Act Play: How AI is Ushering in a 'Speedrun Era' for Enterprise Software Startups The traditional three-act play for building an enterprise software company—first, a niche wedge product; second, an expanded suite; third, a dominant platform—is becoming obsolete in the AI era. Previously, startups would spend 3-5 years perfecting a single-point solution to reach tens of millions in ARR (Act 1: The Wedge). Then, over another few years, they'd build adjacent products to form a suite and cross the $100M ARR threshold (Act 2: The Suite). Finally, with scale and user engagement, they could aim to become a foundational platform themselves (Act 3: The Platform). This model assumed a timeline measured in years. However, AI-driven tools have dramatically compressed software development costs and timelines. Companies like Cursor, Clay, and Harvey have scaled from near zero to approaching or surpassing $100M ARR in remarkably short periods, demonstrating a new competitive pace. The core argument is that in this rapidly changing market, relying on a small, "safe" wedge as a protective harbor may now be a conservative, even risky, strategy. The plummeting cost of building software means the time required for Acts 1 and 2 is approaching zero. Consequently, rational strategy now favors planning to build the entire vision from the outset. This shift changes the calculus for early-stage investment. The emphasis is moving from finding a defensible niche to backing founders with "unreasonable, relentless ambition" to reimagine entire workflows or replace incumbent platforms from day one. The age of gradual expansion is giving way to an era of immediate, full-scale ambition.

marsbit06/02 08:32

The Death of the Three-Act Play: AI Ushers Enterprise Software Startups into the ‘Speedrun Era’

marsbit06/02 08:32

Hedge Fund Q1 Interpretation: Everyone Is Selling Software, Buying Chips

Hedge Funds and Mutual Funds Aligned in Q1: Dumping Software, Buying Chips A clear consensus emerged among major U.S. hedge funds and mutual funds in Q1: they were simultaneously selling software stocks and pouring capital into the semiconductor sector. This aggressive rotation pushed semiconductor exposure in hedge fund long portfolios to a record high. Hedge funds delivered a 7% return year-to-date, while only 30% of large-cap active mutual funds outperformed their benchmarks. The average short interest for S&P 500 constituents rose to 3% of market cap, the highest since 2011. Within technology, the structural shift was stark. Hedge funds' semiconductor weighting hit an all-time high, while software fell to its lowest since 2019. Excluding Microsoft, mutual funds' relative overexposure to semis vs. software was the largest since 2012. Microsoft was among the most net-sold stocks by both groups. Hedge funds net purchased semiconductor names like LRCX and AMAT. Strategies diverged on leverage and cash. Hedge funds increased their net exposure to near a one-year high after an initial cut. Mutual funds raised their cash allocation, though it remains historically low at 1.4%. Sector alignment was high in Industrials (both overweight) but divergent in Tech: hedge funds increased their Tech net tilt by a record 853 basis points, while mutual funds reduced theirs. Clear splits also appeared in Financials and Consumer Discretionary. Four stocks appeared on both Goldman's hedge fund VIP and mutual fund overweight lists: BA, MA, MRVL, and V. This "shared favorites" basket has returned 10% YTD, outperforming the equal-weight S&P 500. Notably, all "Magnificent Seven" stocks are on the hedge fund VIP list but are uniformly underweighted by mutual funds.

marsbit05/27 08:04

Hedge Fund Q1 Interpretation: Everyone Is Selling Software, Buying Chips

marsbit05/27 08:04

活动图片

Regulatory Policyright-arrow

Ethereumright-arrow