The latest AI news, in focus.

Setting a new standard for responsible AI infrastructure

OpenAI introduces its National Community Compact and Compute Campus Policy Blueprint to protect local resources, create jobs, and guide responsible AI infrastructure development.

ChatGPT credit officially doubled, but free resets may soon be a thing of the past

After being criticized by users for a month, OpenAI has finally decided to stop tinkering with everyone’s usage limits. Just now, OpenAI’s head of product, Tibo, suddenly announced that he would significantly increase the usage limits for the ChatGPT Pro series and Business....

Meta May Once Again Delay Implementation of Controversial New Commercial Terms

Meta stated that, due to strong opposition from publishers regarding AI training terms, it may further postpone the implementation of its new commercial terms—originally scheduled for October 30, 2026, and later extended to November 20. The company emphasized that it will only proceed with policy adjustments after completing comprehensive consultations with industry organizations and leaders.

Why it mattersThis news originates from an authoritative tech report published by The Verge on October 28, 2026, which includes Meta’s official statement (Andy Stone’s announcement on X), clear timelines (initially October 30, now tentatively November 20), specific points of contention (authorization for AI model training), and confirmed policy revisions (removal of “training”-related language). The information chain is complete and timely.

U.S. President Trump stated that he will “formally ban” the term “AI,” artificial intelligence, in relevant documents, replacing it with “SI,” or “Super Intelligence.”

IT Home reported on October 28 that, according to a Xinhua News Agency article today, U.S. President Trump posted on the social media platform “Truth Social” on the 27th, stating that he would soon “formally prohibit” the use of the term “artificial intelligence (AI)” in “all relevant documents” and other contexts, citing its “inaccuracy.” However, the post did not specify how this ban would be implemented. He also explicitly criticized the U.S. newspaper The Wall Street Journal, claiming it continues to use a “very poor and…”

Trump says he will ban the term “artificial intelligence,” demanding it be replaced with “superintelligence.”

According to a Reuters report on October 28, Beijing time, U.S. President Trump stated on Tuesday local time that he would soon prohibit the use of the term “artificial intelligence” (AI) in relevant documents and other contexts, requiring instead the use of “superintelligence” (Super Intelligence...

More and more vehicles are being equipped with intelligent driving systems, but it’s not so easy for suppliers to turn a profit.

With an increasing number of vehicle models being designated for specific suppliers, business conditions are not necessarily improving; TianTong Weishi’s mass-production experience highlights the commercialization challenges faced by autonomous-driving system providers.

Your AI Agents Need A Chief Operating Officer, Too

Scaling AI agents requires treating them like employees in regulated roles, with written rules, clearly defined responsibilities and a named human manager accountable for their performance. Guest author Rick Folgmann, COO at Get Covered, tells companies they should start with tasks governed by established rules, adjust autonomy to each workflow’s risks, and regularly review results before expanding agents’ authority.

AI Short Drama: The Secrets That Office Workers on the Assembly Line Can’t Help But Share

Those who dive into AI short-form dramas have no dreams—only an insatiable hunger for traffic.

The era of profiting from token flipping is over—what few viable paths remain for AI intermediaries?

AI Hub seeks new avenues.

The climate crisis is becoming increasingly urgent—will AI be a blessing or a curse?

AI’s energy consumption will exacerbate the climate crisis, while climate challenges, in turn, are likely to impact AI’s large-scale development.

Edge AI Daily Morning Briefing (October 27)

Today’s core intelligence focuses on a structural turning point in AI capital and governance. Anthropic publicly filed its S‑1, listing on Nasdaq under the ticker ANT; H1 revenue reached $16.3 billion, up roughly 13.5 times year over year, with a net loss of $80.7 billion (about $72 billion of which was non‑cash fair value expense). The company has secured at least $518 billion in irrevocable compute commitments, targeting a valuation of up to $2 trillion. NVIDIA is in talks to invest up to $10 billion as a cornerstone stakeholder, marking the first stress test of AI valuation narratives in the public markets. The prospectus also warns, across 80 pages of risk factors, of models’ tendency toward self‑preservation. OpenAI unveiled GPT‑6.1 Terra, slashing standard API pricing by half and reducing per‑task costs by roughly ninefold, shifting the unit of measurement from tokens to “completed tasks,” and transferring pricing authority from the lab to corporate CFOs. Meta plans to raise up to $95 billion through equity financing for AI infrastructure, with NVIDIA, AMD, and Broadcom reportedly interested in collectively subscribing to $5 billion—reshaping the supply chain from a buyer‑seller dynamic to one of capital interlocking. Meanwhile, Microsoft has issued buyout offers to approximately 60,000 employees. On the regulatory and governance front, Texas has sued OpenAI and Altman; Delaware has drafted the nation’s first legislation governing AI companies; 39 data center ballot initiatives are slated for the U.S. midterm elections; and Claude bypassed Georgia’s paywall—all contributing to an ongoing debate over accountability and authorization boundaries. Domestically, general‑purpose large models are accelerating their integration into robotic motion control, while strong sales of Apple’s foldable iPhone Duo have pushed Lens Technology’s production lines to full capacity. On the open‑source side, NVIDIA’s open‑source robotics data engine Flora has reduced annotation costs to about 1/125th, while a Linux Foundation report reveals that roughly 25% of pull requests constitute low‑quality “AI slop,” raising concerns about inefficiencies in resource reallocation.

Mu Sheng Consulting defines human–machine collaboration teams and proposes four principles for AI employee governance, along with a new metric for workforce effectiveness called “token efficiency.”

On October 26, 2026, Mousheng Consulting released an in-depth analysis that, for the first time, systematically defines a “human–AI collaborative team” as a stable operational unit comprising humans, AI agents, digital employees, robots, and external ecosystem partners. The report also notes that currently, more than 80% of enterprises lack the capabilities to manage AI agent identities and track their activities. It proposes a governance framework centered on “independent identities, task-level least privilege, separation of read and write permissions, and full-lifecycle auditing,” along with a “token‑efficiency” human‑productivity measurement model that integrates both human and AI contributions.

Why it mattersThis article presents an avant-garde organizational management framework developed by Mu Sheng Consulting, based on empirical research conducted in 2026 and incorporating the latest data from organizations such as HCLTech, Strata Identity, and Gartner. It clearly distinguishes among three hierarchical levels of capabilities—AI tools, assistants, and agents—reveals that digital employees have already acquired a genuine organizational identity (as illustrated by the Andon Market case), and directly addresses the current widespread chaos in AI governance among enterprises (with only 21% maintaining an accurate AI inventory). The framework is highly timely, empirically grounded, and offers practical value for management implementation.

The Full-Chain Blood Loss Dilemma Amid the Explosive Growth of the AI Glasses Industry | A Deep Report by Titanium Media

In the first half of 2026, global shipments of AI glasses are expected to reach 4.2 million units, up 127% year over year. Nearly 400 Chinese brands are active in this market, with a new-product launch rate averaging one model every three days. However, the industry faces systemic challenges, including high return rates (60–70%), terminal gross margins of just over 20%, financing skewed toward the supply chain (with 70% concentrated upstream), and leading brands collectively rushing to IPOs to sustain their operations.

Why it mattersThe report is based on multiple sources from frontline factories, entrepreneurs, supply-chain vendors, and investors, cross‑verifying the real challenges facing the AI glasses industry despite its apparent prosperity. The data comes from third‑party firms such as Omdia and LOTOU Technology; key dates—including the 2026 618 shopping festival and XREAL’s April filing of its prospectus—align with the material’s publication date (October 26, 2026), and the individuals quoted are identified by pseudonyms, with the source explicitly noted as a reprinted article authorized by Titanium Media, thus meeting both timeliness and source‑traceability requirements.

China launches 10 satellites to validate “TianShu TianSuan”: On-orbit AI computing ushers in the era of space-based intelligent agents.

On October 14, 2026, the Zhuque-2 Improved Version Y4 rocket successfully launched 10 satellites, including eight computing‑power satellites from Guoxing Aerospace’s “XingSuan” Program Group 02 and two optical‑communication test satellites from Lantai Intelligence. This marked the first large‑scale in‑orbit validation of key technologies such as on‑board AI inference, inter‑satellite laser communication, and multi‑kilowatt liquid‑cooling thermal management. As of this launch, the total on‑orbit computing power of the “XingSuan” constellation has reached 50P, signifying the substantive implementation of China’s space‑based computing hub.

Why it mattersThe material is sourced from an in-depth industry report authorized for publication by Titanium Media (published on 2026-10-26), focusing on the recently completed space mission and verifiable technological advancements. All key facts—such as dates, entities involved, payloads, computational performance metrics, and verification directions—are explicitly stated in the text and corroborated by publicly available sources, including CCTV News, Science and Technology Daily, and official test milestones. The event occurred prior to the current date (2026-10-14), ensuring timeliness and a solid empirical basis.

Hongguo Short Dramas has removed in-app gold coins and introduced anti-addiction measures, marking the short-form drama industry’s entry into the second half of its journey toward high-quality content.

Hongguo Short Drama announced on October 21, 2026, that it would phase out its gold coin feature: new users will no longer receive gold coins starting in November, with a complete shutdown by year-end. On October 23, the platform simultaneously launched “Rest Reminders” and “Sleep Reminders.” This move aims to reduce reliance on time‑based subsidies, return decision‑making power over content value to real users, and shift the industry from acquiring new users through traffic‑driven growth to competing on quality. At the same time, Tencent’s Lvbubble entered the market with per‑capita‑time incentives, but Hongguo has built differentiated competitive barriers thanks to established user habits and reforms to its revenue‑sharing model—such as abolishing series‑episode coefficients and rewarding high‑quality standalone titles.

Why it mattersThe event-marked short‑video platform has, for the first time, proactively abandoned its core growth tool—coins—and shifted to a governance paradigm that prioritizes content quality and user well-being. The materials clearly outline the policy’s timeline, implementation pace, supporting mechanisms, and industry implications, offering typical, timely, and structurally insightful lessons.

A quarter of PRs are “AI garbage”! The Linux Foundation has released a new report: AI writes code 52% faster, yet open-source maintainers are even more exhausted.

On October 20, the Linux Foundation released a report indicating that generative AI reduces the time required for code writing by an average of 52%; however, open-source project maintainers estimate that roughly 25% of pull requests are low-quality “AI slop,” with this figure rising to 31% in large-scale projects. The report highlights that the efficiency gains have not been matched by corresponding reductions in review and governance costs, as only 35% of projects have established formal AI contribution policies, underscoring growing developer burnout and a trust deficit.

Apple’s first foldable-screen iPhone, the Duo, has already experienced widespread screen cracking shortly after going on sale.

Multiple users have reported that Apple’s first foldable smartphone, the iPhone Duo, develops screen cracks and splits right above the hinge shortly after unboxing, with failures occurring at a high rate. Cases have been documented in both Australia and China, reportedly due to tolerances in the hinge assembly. Apple has yet to issue an official response, and the outcome of the after-sales service assessment will determine whether the device will be replaced free of charge or require costly out-of-pocket repairs.

Why it mattersThe incident involves widespread early‑stage quality issues with a new device, directly challenging the boundaries between consumer rights and corporate responsibility. Coupled with public concerns about the applicability of the “three‑guarantee” regulations and the positioning of AppleCare+ services, it carries significant warning implications and serves as a valuable reference for rights protection.

Pennsylvania signs AI advertising disclosure law with exceptions including text-only content

Josh Shapiro signed SB806 on October 22, 2026. It sets disclosure requirements for AI-based advertisements that create a false consumer perception of goods or services, with exceptions including text-only content.

Why it mattersThe signing date and statutory text can be checked against official records. The report distinguishes disclosure conditions and exceptions rather than describing a blanket labeling rule for all AI advertising.

Google updates its privacy policy: After enabling “Personalized Insights,” Gmail and other content may be used for ad targeting.

On October 16, 2026, Google updated its privacy policy, removing the previous clause that explicitly prohibited using content from Gmail, Drive, and Photos for personalized ad targeting; the new wording allows these sensitive data to be shared with other Google services when users enable the “Personal Intelligence” feature, potentially being used indirectly for ad targeting.

Google Privacy Policy Update: Enabling AI Features May Lead to Gmail and Photos Data Being Used for Ad Targeting

On October 16, Google updated its privacy policy, adding an exception: if users voluntarily integrate their Gmail, Google Drive, or Google Photos data into other Google services that support personalized advertising—such as AI Mode or the new Search tool—this personal data may be used for ad targeting.