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5 stories + 7 briefsModels got cheaper. Company ledgers still do not show a clear improvement
TechCrunch reported on October 25 that Apollo chief economist Torsten Slok questioned the financial payoff of AI spending outside the giant technology companies. In an original comment on October 24, he compared revenue per employee, margins, and related measures for large technology companies with the rest of the S&P 500, and argued that the latter had not shown the same improvement.
This is an economist's reading of aggregate data. It cannot be pushed into a claim that every company and every AI application has no benefit. It raises a question worth following: writing faster and calling a model more cheaply, when does that become higher revenue, a lower total cost, or more stable delivery? Business integration, human judgment, organizational coordination, and rework still sit in between. Measuring adoption cannot stop at counting model calls.
r/opensource tightens submissions of AI projects, and a community draws a line around maintenance
The Verge reported on October 25 that Reddit's r/opensource community published new submission rules. Projects that use AI, are made by AI, or are aimed at AI are not welcome, and the rules raise requirements for how long a project has existed, ongoing maintenance, and contributors. The report shows moderators' concern about low-quality submissions, and it also records user opposition and the response of starting another community.
The rules also involve language and moderation capacity. Moderators said it is hard to tell AI-generated text from AI translation, and the restriction would affect people who do not write in English. Assistive uses have exceptions and discretion, so the headline cannot be simplified into a ban on every AI feature.
This is one community's decision about submissions and governance. It is not a change in the definition of open source or in a software license. What is worth watching is who does the reading, the answering, the maintenance, and the filtering once projects become easier to produce.
AI search keeps the answer, and publishers have to compete again for the click
A Verge column on October 25 looks back at Google AI search and publishing. Once the answer appears on the search page, the link between a person getting the information and clicking through to the original site changes. The article discusses publishers' traffic pressure, Google's account of traffic to a wider set of sites, and disputes over how links are shown and how sites can opt out.
This is a review published that day. It is not Google launching a new search feature today. The existing path of AI Overviews and AI Mode is background. Year-by-year statistics are not rewritten as today's increase or decrease.
For people who produce content, the question is not only whether a model cites them. It is whether the citation supports a lasting relationship with readers. Models need reliable material, and the people who supply it need a reason to keep producing. After an answer on one page becomes convenient, how the rest of the chain is supported is still open.
Beyond the data-center build-out, grids and communities start to set the pace
WIRED published Molly Taft's October 25 interview with technology commentator Paris Marx, on what the US movement against data centers can learn from other places. Marx hosts Tech Won't Save Us and wrote Hyperscale: The Ambition and Excess of Big Tech's Data Empires.
The interview goes through disputes in Ireland, Chile, Singapore, and elsewhere over energy, water, approval, and local interests. It reminds the reader that buying chips and raising money is not the same as already having power, construction conditions, and community support. Limits in different places can also change where a facility is sited and what energy plan comes with it.
This is an original interview connecting older cases with the current discussion. The guest's view of the industry's prospects remains an opinion. What is worth reading today is that it pulls AI infrastructure back from a distant machine room to grid planning, public cost, and residents taking part.
杭州灵颜科技有限公司 makes robot facial interaction a product line of its own
Yingke's October 25 first interview with 杭州灵颜科技有限公司 shows another path in embodied AI: products built around a robot's facial expression, lip movement, and coordination with speech, rather than manufacturing a whole humanoid. The team calls the related hardware and software FaceSoul Agent.
In the report, the team describes mechanical designs such as cable drive, and a way to connect expression, gaze, and mouth shape with the dialogue output. It wants facial interaction to be a module that different robots can integrate. The capabilities and the experience come from the company's account. That is not yet evidence of delivery at scale across settings. Promotional comparisons in the original, including human-likeness ratios and industry-leading claims, are not conclusions of this issue.
The observation is that commercial embodied AI is not only what one machine demonstrates. It can also split into specialist suppliers of interaction parts, integration interfaces, and maintenance.
Yingke · 36Kr | October 25, 2026
In an original analysis on October 25, Max Woolf looks back at model price changes and especially how cache-read fees affect multi-turn agent tasks. A long conversation reuses context that is already there. Input, output, and cache cannot be mixed into one unit price. The article is a way of looking at cost structure. This issue does not treat its historical price table as a current purchase quote. For a real business, the more useful comparison is still the total cost, the wait, and the rework of finishing one task.
Source: Max Woolf · October 25, 2026 · Original cost-structure analysis; historical prices are not treated as a current quote
On October 25, Qbitai interviewed securities lawyers and capital-market people about technology, commercialization, and governance as robot companies prepare for a listing. This issue uses observations from those independent interviews. Research and customer purchasing have their own cycles, which may not match an investor's exit. Better technical capability does not automatically mean the company keeps a profit. Financing, filing, and listing dates in the article that the companies have not publicly confirmed are not treated as facts that have already happened.
Qbitai · 36Kr | October 25, 2026
Source: Qbitai · 36Kr · October 25, 2026 · Independent interviews; unconfirmed financing, filing, and listing dates are not treated as facts
TechCrunch's October 25 roundup of AI necklaces, bands, rings, and portable devices shows different uses, including meeting notes, reminders, and companionship. This is a same-day arrangement of existing products, not a simultaneous launch. For a user, how much sound is captured is only the start. When it can be muted, where the record is stored, whether it can be deleted, and whether the reminder is useful decide whether the device becomes a lasting service rather than a novelty.
Source: TechCrunch · October 25, 2026 · Same-day roundup of existing products, not a simultaneous launch
On October 25, Julien Simon published an outside look at Apple's on-device model Core Advanced. He says he used public system tools and commands, recorded file reads, memory, and energy on a particular Mac, and compared performance on math tasks. He did not obtain the model weights. Some architectural explanations are the author's inference. What can be watched today is the tradeoff for an on-device model: resource use, energy, task performance, and controllability have to be read together. A single machine and a limited set of questions cannot establish a general ranking.
The AI Realist | October 25, 2026
Source: The AI Realist · October 25, 2026 · External observation on one Mac with public tools; weights not obtained and some architecture notes are the author's inference
On October 25, Wiz disclosed the Gheist activity it has been tracking. Attackers abused leaked GitHub credentials and wrote workflows into repositories to steal secrets. The researchers say one control on public repositories blocked a large number of attempts, but later activity was still observed in private and enterprise environments. The investigation also involves AI-service credentials. This is not a vulnerability in an AI model. The link to agent engineering is that once code generation, automatic execution, and production credentials are connected, write permission and execute permission have to be managed separately, and workflow changes have to be checked.
Wiz Research | October 25, 2026
Source: Wiz Research · October 25, 2026 · Research disclosure of credential abuse; not an AI-model vulnerability
The Verge on October 24 relayed an interview with a producer of Blue Planet III. The series keeps some underwater debris, boats, or less-than-ideal shooting conditions that might once have been cut, in order to show a real ocean. This item is about half an hour earlier than the 24-hour news start, and it is included as 48-hour catch-up. Keeping a flaw is a creative choice. It cannot by itself be a technical standard for identifying AI images. What it reflects is how viewers and makers rebuild trust in a picture.
Source: The Verge · October 24, 2026 · Relay of a producer interview; 48-hour catch-up, not a technical test for identifying AI images
TechCrunch on October 25 reviews the first episode of an Odyssey made by Grok Imagine with Wonder Studios and director Dev Walker, and discusses the difference between how realistic a single shot looks and how compelling the whole story is. The clip's release note is dated October 23. What this issue includes is a new original review, not a first release packaged as today's launch. The author's artistic judgment is an opinion. The product question is specific: after several minutes of pictures can be generated in a row, character, pacing, and narrative still have to hold.
Source: TechCrunch · October 25, 2026 · New original review of a clip whose release note is dated October 23; artistic judgment is an opinion
Industry Insights
Conversation SpotlightOpenAI chief financial officer Sarah Friar, in an October 14 Business Post Podcast interview, discusses the funding needs of a frontier-model company and enterprise adoption. Her role concentrates the view on commercialization, capital arrangements, and customer workflows. The episode is about safety concerns, enterprise transformation, and financing. It is not a product-performance review.
A specific public page on q.cxspace.com, in the excerpt at 00:07:42, presents her examples: talking with an airline about scheduling, and with a bank about customer service, turning model capability into a concrete business problem. At 00:23:33 the excerpt discusses compute being purchased before the matching cash flow, and supply that may not arrive as expected. This is a paraphrase of the published excerpt. An automatic extract on the site is not treated as a word-for-word human check.
The link to today's news is that Apollo's macro question, the model-price analysis, and the data-center disputes land on payoff, operating cost, and whether resources actually arrive. Friar's older interview is one explanation from inside a company. It is not her response to these new reports, and it is not evidence that a particular listing plan has been decided.
Concourse · Business Post Podcast | October 14, 2026
Source: Concourse · Business Post Podcast · October 14, 2026 · Visible excerpts on the published page; automatic extract is not treated as a word-for-word human check
Research Briefs
1 paperWhy read it today: discussions of company payoff and AI cost both ask how a tool's capability becomes real capability. This September 17 preprint in the Paper-Radar library, Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants, puts the same question in a learning interface. Getting an answer and learning it yourself are not the same result. This is a historical related look-back. It is not a new paper from today, and it is not counted in the 36-hour source-catalog total.
The authors had 704 participants practice fraction arithmetic and then take a test without AI help. While the ability to ask for help remained, they compared metacognitive feedback, an effort reward, and the corresponding controls. The feedback reminded participants how they had just used AI and which practice had been replaced by a complete answer. The authors report that this feedback reduced requests for a complete answer and improved the later independent test. The effort reward did not show the same effect.
The important limit is that the study did not find that merely providing AI access significantly lowered independent-test performance. The experiment is short and uses a specific arithmetic task. It cannot be pushed into a claim that all AI makes people worse, or that one prompt improves long-term job performance. What it offers is a design direction that can be tested: let the user decide how much thinking to delegate, rather than only chase a faster answer.
Open Source Spotlight
1 projectOn October 24, Terence Tao's blog published a guest announcement by Abhinav Nellore, Johannes Schmitt, Soledad Villar, and Rachel Ward, inviting the community to join oai-math-revised and improve hard-to-follow wording and incomplete citations in OpenAI math writing. This is 48-hour catch-up. Terence Tao is not written as the sole author of the project announcement.
The project treats explanation, citation, and the ability to review as the object of collaboration, not only more answers. For AI-assisted research, this is a concrete next step: after peers read the output, can the argument be traced and revised. The project license and contribution rules follow the repository's current statement. This issue did not audit the mathematics.
Coverage notes · Incomplete · 26/51 checks recorded
Coverage is incomplete. At 05:00 Beijing time, 42 of 51 upstream sources were complete. This machine checked the final hour and accepted the results separately. The final count is 26 complete, 25 partial, and 0 failed. Partial does not mean there was no new material, and a successful visit to an entry point does not mean every page or venue was checked. The final source catalog has 28 items. Hitting a catalog count is not the same as coverage.
The full candidate pool keeps records of what was kept, dropped, merged, or still awaiting review. A Hacker News discussion time is not treated as the original publication time. Items with an unknown time or blocked access are not mixed into the strict 36-hour count. The OpenReview venue check is still incomplete. The visible arXiv announcement date is October 23. The Hugging Face interface for the specified date was empty. None of that proves there are no new papers anywhere. The related-paper look-back does not cancel the collection gap.
The conversation section uses visible excerpts from a specific page that is already online, and it keeps the automatic-extract mark and the historical date. News facts, a guest's opinion, an author's analysis, and a vendor's own account are stated separately. Product promotion or a limited measurement is not expanded into a general conclusion.
Coverage gaps reflect incomplete checks; they do not establish that a source had no updates.
- Claude Blog — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Google DeepMind — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Microsoft AI — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Qwen — Partially checked. A static fetch of the single-page app was empty. The old blog is stale and cannot show that there were no updates. The final-hour check did not establish that every configured entry point was fully covered.
- Tongyi Lab — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- DeepSeek — Partially checked. Additional URLs were not fully rendered. The final-hour check did not establish that every configured entry point was fully covered.
- Moonshot AI — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Z.ai — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- StepFun — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Mistral — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- European Commission Digital Strategy — Partially checked. The origin returned CloudFront HTTP 403. Only a fetched list was read. The final-hour check did not establish that every configured entry point was fully covered.
- UNESCO AI — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- OECD.AI — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- arXiv cs.AI / cs.LG / cs.CL — Partially checked. Submissions after the latest announced slice were not yet visible. The final-hour check did not establish that every configured entry point was fully covered.
- OpenReview — Partially checked. Not every venue was scanned. The final-hour check did not establish that every configured entry point was fully covered.
- 36Kr AI (article-level checks for original and syndicated reporting) — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Cyberspace Administration of China · News (AI-related) — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- ByteDance Seed · Blog and papers — Partially checked. Not every blog category was rendered. The final-hour check did not establish that every configured entry point was fully covered.
- MiniMax·News & Updates — Partially checked. Without a browser, the page showed no news cards. The final-hour check did not establish that every configured entry point was fully covered.
- TechCrunch — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Ars Technica — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- MIT Technology Review — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- 404 Media — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Hacker News — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
- Databricks Research — Partially checked. The final-hour check did not establish that every configured entry point was fully covered.
Reviewing a source does not constitute independent testing. Paper-reading scope is stated with each item; experiments were not reproduced.
Sources & discoveries 28 links
Titles are retained from the Chinese edition; source names are shown in English. This discovery list includes material not read in full.
News · 26 links
- AI用得更便宜，企业账本为什么还没明显改善AI delivers ‘zero financial payoff’ to most companies, Apollo economist saysTechCrunch
- r/opensource收紧AI项目投稿，社区开始为维护成本划边界r/opensource just banned AI, non-English speakers, and moreThe Verge
- AI搜索留住了答案，出版者要重新争取读者的点击Google’s AI search changes upended online publishingThe Verge
- 数据中心扩建之外，电网与社区开始决定AI的落地节奏What the US Movement Against Data Centers Can Learn From Everywhere ElseWIRED
- 灵颜科技把机器人面部交互做成独立产品方向吉大刘春宝孵化，00后团队创业仿生灵巧脸，拿下数千万融资丨36氪首发Yingke · 36Kr
- 模型降价之后，智能体成本还要看缓存与整段任务OpenAI and Anthropic cut their LLM prices by up to 80% within a few months. Why?Max Woolf
- 机器人上市讨论转向商业交付与融资时间表IPO遇冷？机器人老板们烧香、磕头、翻旧账Qbitai · 36Kr
- AI穿戴设备盘点：常开麦克风之外，还要有可控的服务The hottest AI wearables and gadgets you should know aboutTechCrunch
- 一项苹果端侧模型观察，把注意力转向内存与能耗Exploring Apple's On-Device Model: Twenty Billion Parameters in FlashThe AI Realist
- Wiz披露Gheist活动：自动化工作流本身也是凭据边界Gheist: Attempted Scaled Abuse of Stolen GitHub Tokens StumblesWiz Research
- 《蓝色星球III》保留拍摄的不完美，回应生成影像时代的真实感Blue Planet III is keeping the rough edges in the age of AIThe Verge
- Grok《奥德赛》短片的新评论，把问题从逼真带回叙事Grok releases the first seven minutes of its AI-generated ‘Odyssey’TechCrunch
- 观点：为何看好计算机却质疑AI基础设施扩建Why I’m Short the AI Buildout Even Though I’m Long Computersunverifiablerewards.substack.com
- 观点：AI能复制Photoshop之后，谁还会创造下一个FigmaIf AI Can Copy Photoshop, Why Would Anyone Build the Next Figma?vincentschmalbach.com
- 观点：AI生产率提升会怎样影响经济Can AI Make Us So Productive That It Destroys the Economy?vincentschmalbach.com
- 机器能成为战争罪责任主体吗：一场法律讨论Can machines be war criminals?vox.com
- 研究者称三星电视存在AI音频及截图广告追踪行为Cybersecurity bounty hunter says Samsung TVs use AI to record audio and screenshots for ads — 'Finally found a company that truly listens to its customers,' says hackertomshardware.com
- 丈母娘也开始抢AI人了36Kr AI
- 比尔·盖茨谈AI时代的就业冲击与税收Bill Gates warns the ‘evolutionary’ age of AI will be brutal for workersobserver.co.uk
- 硅谷的天才们怎么天天研究让 AI 在《我的世界》里砍树？36Kr AI
- 观点：AI实验室取代工程师的商业逻辑，何以反噬自身客户OpenAI and Anthropic Wanted to Replace Engineers. Instead, They Shot Their Own Customers.techbronerd.substack.com
- 上下文工程现状：何时使用确定性与概率性方法The State of Context Engineeringdbreunig.com
- 基于大模型的渗透测试执行框架怎样工作How LLM-Based Penetration Testing Harnesses Workutkusen.substack.com
- Billboard报道Elvis音乐权利方起诉AnthropicAnthropic Sued For Stealing Elvis Presley Music to Train AI: ‘Deeply Protective of These Iconic Songs’billboard.com
- 观点：人类服务会变成奢侈品吗Will humans become a luxury?artfish.ai
- 让自己的博客更容易被AI智能体阅读Making My Blog Readable By AI Agentsdeallocatedobjects.com
Concourse · 1 links
- Interconnects播客：Kimi K3.1 Pro、网络安全与MusePodcast: Kimi K3.1 Pro, the new cyber reality, and Muse musingsInterconnects
Open source and releases · 1 links
- 数学社区建立修订库，改进OpenAI数学写作的解释与引用oai-math-revised: a community hub for revising OpenAI’s math write-upsTerence Tao's blog · guest announcement