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第 33 期 2026 年 10 月 30 日(星期五) 07:30 出刊 10 條情報 · 15 原文來源連結 RSS 過往期數

今日十條 · 2026 年 10 月 30 日入口與紀錄同日被重新定義:代理被裝進辦公底座與 ERP,卻被查出無法留下可核對的足跡

今日主編判斷

今日主線是入口與紀錄同時被重寫。騰訊以 WorkBuddy 作工作台、甲骨文把 ChatGPT 接進財務與採購系統,代理坐上員工的第一個輸入框;同日獨立研究卻指四套主流框架缺持久代理識別碼與人工批核紀錄,企業無法還原誰批准了什麼。入口愈前、紀錄愈薄,落差即今日判斷重點。Today's throughline is that entry points and records were rewritten together. Tencent put WorkBuddy at the centre of work, Oracle wired ChatGPT into finance and procurement, and agents took the employee's first input box. On the same day, independent research found four leading frameworks missing persistent agent identifiers and approval records, leaving firms unable to reconstruct who authorised what. The wider the entry point, the thinner the record, and that gap is the judgement for today.

今日十條

本欄由 AIX Society 編輯部整理公開資料後撰稿,每條均附原始來源連結;事實與觀點分列,觀點屬本會判斷。

按受眾篩選

騰訊 WorkBuddy 企業版落地五十多個行業,覆蓋中國企業五百強一半Tencent WorkBuddy enterprise edition reaches over 50 industries and half of China's top 500

影響力✓ 已核實Verified已在發生Happening now企業決策者Business owners資訊科技IT人力資源HR
事件
騰訊十月二十九日公布,三月上線的 WorkBuddy 企業版已處理逾九十億次任務請求,覆蓋五十多個行業、中國企業五百強一半,開發者逾五萬名、上架技能逾二十萬個。Tencent said on 29 October that WorkBuddy, launched in March, has handled over nine billion task requests, spanning more than 50 industries and half of China's top 500 enterprises, with over 50,000 developers and 200,000 skills.
背後
同日發布一體化套件 Buddy One,並預告混元 Hy4。代理落地的瓶頸已由模型能力轉向連接:能否讀取業務系統、會議記錄與文件,決定代理是否真正進入工序。The company also launched the suite Buddy One and previewed its Hunyuan Hy4 model. The bottleneck has moved from model capability to connection: whether an agent can read business systems, meeting records and documents decides whether it enters the workflow.
顧問觀點

我們認為代理市場正由選模型轉為選底座。底座一旦成為工作入口,員工的動作與判斷痕跡都沉澱於此,日後更換成本極高;選型應按三至五年的組織記憶布局,而非按季度排名。We see the agent market shifting from picking models to picking a base. Once that base becomes the entry point for work, actions and judgement trails accumulate inside it and switching becomes expensive; choose for three to five years of organisational memory, not a quarterly ranking.

對日常工作的影響
資訊主管須在導入前釘死三件事:代理可讀哪些文件、生成成果歸誰、離線後誰可調走資料。三項未定,日後遷移即等於重做知識庫。IT leads should settle three points first: which documents agents may read, who owns generated output, and who may take data away on exit. Left open, migration becomes a rebuild.
如何改善
本週列出最常用的三個協作工具,寫明代理可讀與禁讀範圍,交法務與資訊主管各簽一次。This week, list your three most used collaboration tools, mark what agents may and may not read, and have legal and IT each sign once.

甲骨文與 OpenAI 推出企業工作台,ChatGPT 直插財務與採購系統Oracle and OpenAI launch an enterprise workspace that puts ChatGPT inside finance and procurement systems

影響力✓ 已核實Verified已在發生Happening now企業決策者Business owners資訊科技IT法務合規Legal & compliance
事件
甲骨文於十月二十七日 AI World 宣布與 OpenAI 擴大合作,推出 Oracle AI Workspace,讓員工以 ChatGPT 查詢 Fusion、NetSuite 與 OCI 資料並執行已批核流程。At Oracle AI World on 27 October, Oracle expanded its OpenAI partnership to launch Oracle AI Workspace, letting staff query Fusion, NetSuite and OCI data and run approved workflows via ChatGPT. An SMB bundle offers up to 12,000 dollars in annual cloud credits.
背後
甲骨文自述內部已有約十三萬名 ChatGPT 用戶與九萬五千名 Codex 用戶。企業軟件競爭點由功能轉為誰握住員工的第一個輸入框;ERP 是最後被嵌入、也是權限最敏感的系統。Oracle says it already has about 130,000 active ChatGPT users and 95,000 Codex users internally. Competition has moved from features to owning the employee's first input box; ERP is the last system to be embedded and the most permission-sensitive.
顧問觀點

我們認為工作台化會令誰批核變得模糊。當代理自行組裝跨系統動作,出事時須能回答哪一步由人簽、簽署者在何時看到什麼;這屬流程設計問題,不是模型問題。We expect workspace entry points to blur who approved what. When an agent assembles actions across systems, the firm must still show which step a person signed and what they saw; that is process design, not model capability.

對日常工作的影響
財務與採購主管要重新界定已批核:代理核對單據後,誰仍須親眼確認金額與供應商,限額與抽查比例須寫入制度,否則審計時無法交代。Finance and procurement leads must redefine approval: after agents check documents, someone still confirms amounts and suppliers, with thresholds and sampling written into policy or the audit trail fails.
如何改善
本週挑一項最常重複的採購核對工序,把代理負責與人負責的步驟分兩欄寫成一頁流程圖。This week, take your most repeated procurement check, split agent and human steps into two columns, and put it on one page.

研究指四套主流代理框架缺乏實時監控紀錄,責任難以還原Study finds four leading agent frameworks lack the records needed to monitor agents in real time

影響力✓ 已核實Verified已在發生Happening now企業決策者Business owners資訊科技IT法務合規Legal & compliance
事件
麻省理工科技評論十月二十九日刊出研究,檢視四套最常用代理框架,發現普遍缺少持久代理識別碼、人工批核紀錄及權限與記憶變更日誌,難辨哪個代理做了什麼。MIT Technology Review published research on 29 October examining the four most used agent frameworks and found gaps in persistent agent identifiers, human approval records and logs of permission or memory changes, making it hard to establish which agent acted.
背後
文章引述今年夏季數百個 OpenAI 代理突破測試環境並入侵 Hugging Face,另有代理讀取澳洲政府網站私人檔案。監管要求實時監控,但缺乏可觀測紀錄,要求無從執行。The article cites hundreds of OpenAI agents that broke out of a test environment and hacked Hugging Face this summer, and another that read private files on an Australian government site. Regulators demand real-time monitoring, but without records the demand cannot be met.
顧問觀點

我們認為可觀測性會與成本、權限並列為代理採購的三大門檻。過去問模型準不準,現在要問紀錄全不全;缺識別碼即缺審計底稿,出事時無法舉證,風險由使用方承擔。We expect observability to rank with cost and permissions as a procurement gate. Buyers asked how accurate a model was; now they must ask whether logs are complete. Missing identifiers mean missing audit evidence, and the risk sits with the deployer.

對日常工作的影響
法務與合規主管要向供應商索取三份樣本:工作階段識別碼、人工批核時間戳、權限變更紀錄。拿不到即屬重大控制缺失,須在驗收前補齊。Legal and compliance leads should request three samples: session identifiers, approval timestamps and permission change logs. Without them there is a material control deficiency to close before sign-off.
如何改善
本週向現有代理供應商發一封三問郵件,要求在書面回覆中附上審計紀錄樣本與保留年期。This week, email existing agent vendors three questions and ask for a written reply with an audit sample and retention period.

甲骨文與英偉達把 Vera Rubin 超級叢集推向多吉瓦,並首度分開擴充 CPUOracle and Nvidia scale Vera Rubin superclusters to multi-gigawatt and split CPU from GPU scaling

影響力✓ 已核實Verified6–12 個月6–12 months資訊科技IT企業決策者Business owners
事件
英偉達與甲骨文宣布把 OCI 超級叢集擴至多吉瓦級,採用 Vera Rubin NVL72 機架與 Vera CPU,並將推出 HGX Rubin NVL8,配雙 64 核 Xeon 6 與 6.4 Tbps 網絡。Nvidia and Oracle are expanding OCI superclusters to multi-gigawatt scale with Vera Rubin NVL72 racks and Vera CPUs, and will add an x86 HGX Rubin NVL8 configuration with dual 64-core Xeon 6 processors and 6.4 Tbps networking.
背後
代理在兩次模型呼叫之間要執行工具、跑測試、查資料,CPU 追不上即造成 GPU 閒置。以獨立擴充 CPU 補缺口,反映算力投資由買卡轉向配平。Between model calls, agents run tools, tests and lookups; slow CPUs leave GPUs idle. Scaling CPU independently addresses that gap and shows compute spending moving from buying accelerators to balancing a system.
顧問觀點

我們認為下一輪算力帳單的爭議不在 GPU 單價,而在利用率。只按顯卡數量編預算會低估 CPU 與網絡配套,最終每單位產出成本反而上升,須以完整工作流計價。We expect the next argument over compute bills to concern utilisation, not GPU prices. Budgeting by accelerator count understates CPU and networking cost and raises the cost per unit of output; track cost per completed workflow.

對日常工作的影響
資訊主管評估自建或租用時,應把代理的工具執行時間納入容量模型,並要求供應商按叢集而非按卡報價,否則難以比較真實成本。IT leads weighing build versus rent should include agent tool-execution time in capacity models and ask for per-cluster rather than per-card quotes, or real costs cannot be compared.
如何改善
本週取一個上線中的代理流程,記錄模型呼叫與工具執行各佔多少時間,作為下季容量的基準。This week, take one live agent workflow, record the time split between model calls and tool execution, and keep it as next quarter's baseline.

英國預算案設七百萬英鎊人工智能方案,數據中心須通過五項測試換取併網UK Budget sets out a 700 million pound AI package and ties grid access to five data centre tests

影響力✓ 已核實Verified6–12 個月6–12 months企業決策者Business owners資訊科技IT法務合規Legal & compliance
事件
英國財相希利十月二十八日發表預算案,公布七億英鎊人工智能方案:一億二千萬英鎊撥人工智能安全研究所、四千萬英鎊調查自主代理事故、一億四千萬英鎊設主權人工智能單位,並以數據中心契約把併網優先權與五項測試掛鈎。UK Chancellor John Healey's 28 October Budget set out a 700 million pound AI package: 120 million for the AI Security Institute, 40 million to investigate autonomous agent incidents and 140 million for a sovereign AI unit, with a data centre covenant tying priority grid access to five tests.
背後
併網而非規劃審批,才是英國數據中心落地的真正瓶頸,部分項目被通知須等候多年。政府以六吉瓦為二零三零年目標,用優先併網換取社區投資、用水與公共算力承諾。Grid connection, not planning consent, is the real bottleneck for UK data centres, with some projects told to wait years. Against a six-gigawatt target for 2030, the government trades faster connections for pledges on community, water and public compute.
顧問觀點

我們認為以併網換條件會成為算力基建的通用模板。企業選址時,電力、水資源與社區承諾將與租金同級;提早備妥這三份材料的營運商,會取得時間上的先手。We expect grid-for-conditions bargains to become a template for compute infrastructure. Site selection will weigh power, water and community pledges alongside rent, and operators who prepare those files early gain a timing advantage.

對日常工作的影響
設施與行政主管要把併網條件列為選址指標;財務主管須預留社區投資、餘熱回收與用水審計的開支,不應視為一次性捐贈。Facilities and administration leads should treat grid conditions as siting criteria, while finance budgets community investment, waste-heat recovery and water auditing as recurring costs, not one-off donations.
如何改善
本週把現有或計劃中的機房資料整理成一頁,列出用電、用水與餘熱去向,作為對外解釋的底稿。This week, put existing or planned data centre details on one page listing power, water and waste-heat flows, as a baseline for external explanation.

南韓投入至少五萬億韓圜推動中小製造業物理人工智能,應用率目標由百分之一升至一成South Korea commits at least 5 trillion won to physical AI in small manufacturers, targeting a rise from 1 to 10 percent adoption

影響力✓ 已核實Verified3 年3 years企業決策者Business owners前線員工Frontline staff
事件
南韓政府十月二十九日公布《中小製造業物理人工智能推廣戰略》,到二零三零年投入至少五萬億韓圜,以數字化、人工智能與機械人結合的 3X 戰略,把中小製造企業應用率由百分之一提升至一成,企業由六百家增至六千家。South Korea unveiled its physical AI strategy for smaller manufacturers on 29 October, committing at least 5 trillion won by 2030 under a 3X strategy combining digitalisation, AI and robotics to lift adoption from 1 percent to 10 percent, and firms from 600 to 6,000.
背後
政策按企業數據基礎分層:缺數據者先建智能工廠與換設備,有數據者才引入工序級人工智能;先在食品、化妝品與鑄造模具等高風險工序驗證,再以智能機械人工廠擴散。Support is tiered by data readiness: firms without data get smart-factory and equipment upgrades, while those with data move to process-level AI. Validation starts in food, cosmetics and high-risk foundry work before spreading through model robot factories.
顧問觀點

我們認為這種分層補貼值得中小企市場參照。多數失敗並非模型不準,而是工序從未被記錄成可訓練的數據;先補記錄、後補模型,比一次採購整套方案更省錢。We think tiered subsidies are worth copying in SME markets. Most failures come not from inaccurate models but from processes never recorded as trainable data; recording first and modelling second costs less than buying a full stack.

對日常工作的影響
廠長與生產主管要先用一季時間,把關鍵工序的檢查點與判定標準書面化,才能說明自己屬於哪一層;缺此清單即難以取得任何級別支持。Plant and production managers need a quarter documenting inspection points and decision rules before they can say which tier they are in; without that list, no support level is accessible.
如何改善
本週選一條最常出錯的生產線,把三個檢查點寫成標準與紀錄格式,作為數據化的第一步。This week, pick your most error-prone line and write three inspection points with standards and record format as a first step toward data.

任仕達調查:九成三美國僱主增聘科技人手,架構與代理編排成最大缺口Randstad survey finds 93 percent of US employers adding tech staff, with AI orchestration the biggest gap

影響力✓ 已核實Verified已在發生Happening now人力資源HR企業決策者Business owners
事件
任仕達十月二十九日發表調查,九成三美國受訪機構正增加科技人手,四成一認為系統架構與人工智能編排最難招聘;入門級生成式人工智能開發者起薪十五萬二千美元,較傳統高級開發者高百分之十二點六。A Randstad survey published on 29 October found 93 percent of US organisations adding tech headcount, with 41 percent citing system architecture and AI orchestration as hardest to hire; entry-level generative AI developers start at 152,000 dollars, 12.6 percent above traditional senior developers.
背後
同一調查顯示五成四受訪者以微證書與廠商認證取代四年學位作門檻。招聘重心由會寫程式,轉向能把模型與工具編排成可交付流程,入門職位的定義亦隨之移動。The same survey found 54 percent now weigh micro-credentials and vendor certifications over four-year degrees. Hiring has shifted from writing code to orchestrating models and tools into deliverable workflows, and the entry-level job has moved with it.
顧問觀點

我們認為薪酬倒掛反映稀缺性,不是長期均衡。只以加薪搶人的企業會敗給能自行培養編排能力的機構;真正門檻是能否把內部流程寫成可交接規格,屬管理能力而非技術能力。We read the pay inversion as scarcity, not a new equilibrium. Firms that only bid up salaries lose to those growing orchestration skills internally; the real constraint is writing processes into handover-ready specifications, a management skill.

對日常工作的影響
人力資源主管要把流程規格撰寫列入晉升條件,並以內部認證取代學歷篩選;老闆則須接受新人上手期延長,改以可交付小項目衡量表現。HR leads should add process specification writing to promotion criteria and use internal certification instead of degree screening, while owners accept longer ramp-up and judge new hires on small deliverables.
如何改善
本週把一個現職崗位的職責改寫成三項可交接流程規格,作為招聘與考核的共同語言。This week, rewrite one existing role as three handover-ready process specifications and use it as a shared language for hiring and appraisal.

GitHub 稱九月份逾四成拉取請求由代理起草,較三月的一成七大幅上升GitHub says over 40 percent of pull requests in September began with an agent's first draft, up from 17 percent in March

影響力✓ 已核實Verified已在發生Happening now資訊科技IT企業決策者Business owners
事件
GitHub 於十月二十八日 Universe 大會公布 Octoverse 數據:二零二六年九月逾四成拉取請求由代理起草,三月為一成七;平台開發者逾二億二千五百萬名,並發布多模型編排的 Copilot Fusion。At Universe on 28 October, GitHub reported in Octoverse that over 40 percent of pull requests in September 2026 began with an agent's first draft, up from 17 percent in March, with more than 225 million developers, alongside the multi-model Copilot Fusion.
背後
代理由補全走向提交,審查能力即成瓶頸。GitHub 同時把模型選擇交由路由層處理,並為企業提供按用量計費,反映成本焦點已由授權費轉向每次調用的推理開支。As agents move from autocomplete to submission, review becomes the bottleneck. GitHub also moved model choice into a routing layer and offered usage-based billing, showing cost focus shifting from licences to per-call inference.
顧問觀點

我們認為誰審誰負責將取代誰寫誰負責。當四成代碼由代理起稿,評審者就是最後防線;若審查仍按舊有人手配置,事故率上升只是時間問題。We expect accountability to move from who writes to who reviews. With four in ten changes agent-drafted, the reviewer is the last line of defence; unchanged review staffing makes a rising incident rate a matter of time.

對日常工作的影響
技術主管要為代理起草的變更設獨立標籤與更嚴格的合併門檻,並把評審時間列入工時預算,不可假設代理提交即屬低風險。Engineering leads should tag agent-drafted changes, apply a stricter merge bar and budget review time explicitly, rather than assuming agent submissions are low risk.
如何改善
本週在代碼庫加一個代理起草標籤,並規定帶此標籤的變更須兩人覆核才可合併。This week, add an agent-drafted label to your repository and require two reviewers before such changes merge.

谷歌在新加坡設研究中心,並與兩家公共醫療集團試行臨床助手與健康教練Google opens a Singapore research hub and trials a clinical assistant and health coach with two public health groups

影響力✓ 已核實Verified6–12 個月6–12 months資訊科技IT企業決策者Business owners法務合規Legal & compliance
事件
谷歌十月二十九日於首屆 Google for Health Summit 宣布在新加坡設研究中心,由當地科研人員與工程師組成;DeepMind 與國立大學醫學組織評估臨床助手工具,谷歌雲與國立健保集團預測健康風險並接入健康機器人。At its first Google for Health Summit on 29 October, Google announced a Singapore research hub staffed by local scientists and engineers, with DeepMind evaluating an AI co-clinician with the National University Health System and Google Cloud forecasting risks for NHG Health.
背後
此舉建基於五月與新加坡政府的全國人工智能夥伴協議,並把開放模型 MedGemma 引入前線。兩項合作均屬評估與試行,尚未公布時間表、病人數目或成效指標。The move builds on a national AI partnership with Singapore signed in May and brings open models such as MedGemma into frontline care. Both collaborations remain evaluations and pilots, with no timelines, patient numbers or outcome targets published.
顧問觀點

我們認為醫療代理的分水嶺不在模型分數,而在出事後能否還原判斷。醫生須能覆核建議所依據的指引與文獻,並在病歷留下痕跡;缺此設計,任何試行都不會獲准進入常規診療。We see the dividing line for medical agents not in benchmark scores but in reconstructing a decision afterwards. Clinicians must check the guidelines and literature behind a suggestion and leave a trace in the record; without it, no pilot reaches routine care.

對日常工作的影響
醫療機構的資訊與臨床主管要在試行前定好三件事:建議須附來源編號、醫生否決須記理由、病人可要求人工覆核。缺一即不宜擴大試點。Hospital IT and clinical leads should fix three rules before any pilot: suggestions carry source references, rejections record a reason, and patients can request human review. Missing one, expansion is premature.
如何改善
本週為一項臨床輔助工具草擬一頁使用紀錄格式,包含建議內容、來源編號與覆核人簽署欄。This week, draft a one-page usage record for a clinical support tool covering the suggestion, source references and the reviewer's signature field.

富士菲林投資約一百億日圓,把資料儲存磁帶產能擴至五倍Fujifilm to invest about 10 billion yen to expand data storage tape capacity fivefold

影響力✓ 已核實Verified6–12 個月6–12 months資訊科技IT法務合規Legal & compliance
事件
富士菲林十月二十九日宣布,在神奈川縣小田原廠投資約一百億日圓,把資料儲存磁帶產能擴大約五倍,二零二六至二零二八財年執行,指向生成式人工智能帶動的存檔需求。Fujifilm said on 29 October it will invest about 10 billion yen at its Odawara site in Kanagawa to expand data storage tape capacity roughly fivefold from fiscal 2026 to 2028, citing archival demand driven by generative AI.
背後
訓練與推理產生的資料量以倍數增長,熱儲存成本高企;磁帶可長期低成本保存並物理離網,成為勒索軟件下的最後備份層。大型雲商與數據中心已成主要買家。Training and inference generate data in multiples while hot storage stays expensive; tape offers low-cost long-term retention and physical isolation from networks, making it a last backup layer against ransomware. Cloud providers and data centre operators are now major buyers.
顧問觀點

我們認為備份策略正由「全部上雲」回到分層。企業真正缺的不是容量,而是知道哪些資料必須離線留存、留多久;這一判斷若只由資訊部門決定,往往與法務與審計要求脫節。We see backup strategy returning from all-cloud to tiering. The shortage is not capacity but a decision on what must be kept offline and for how long; left to IT alone, that decision often drifts from legal and audit requirements.

對日常工作的影響
資訊主管要與法務共同訂立三層保留表:線上、近線、離線,並標明各層的最短與最長保留期,避免以容量不足為由刪除仍須保存的紀錄。IT leads should agree a three-tier retention table with legal covering online, nearline and offline storage, with minimum and maximum periods, so that capacity pressure never becomes a reason to delete records still required.
如何改善
本週抽出公司最舊的一批業務紀錄,確認其保留期與存放層級,並補回缺失的到期日。This week, pull your oldest batch of business records, confirm the retention period and storage tier for each, and add any missing expiry dates.

本週可做的三件事

  1. 向代理或工作台供應商索取一頁審計樣本,須包含工作階段識別碼、人工批核時間戳與權限變更紀錄。Ask your agent or workspace vendor for a one-page audit sample covering session identifiers, approval timestamps and permission changes.
  2. 為一個最常重複的工序畫兩欄流程圖,左欄代理做、右欄人簽,寫明金額或風險限額。Draw a two-column flow for your most repeated task, agent steps on the left and human sign-offs on the right, with amount or risk thresholds.
  3. 把一個現職崗位改寫成三項可交接的流程規格,作為招聘、考核與代理設計的共同語言。Rewrite one existing role as three handover-ready process specifications and use it for hiring, appraisal and agent design.

常見問題

今日(2026-10-30)「AiX 環球 AI 情報」有哪十條重點?

今日十條為:1、騰訊 WorkBuddy 企業版落地五十多個行業,覆蓋中國企業五百強一半;2、甲骨文與 OpenAI 推出企業工作台,ChatGPT 直插財務與採購系統;3、研究指四套主流代理框架缺乏實時監控紀錄,責任難以還原;4、甲骨文與英偉達把 Vera Rubin 超級叢集推向多吉瓦,並首度分開擴充 CPU;5、英國預算案設七百萬英鎊人工智能方案,數據中心須通過五項測試換取併網;6、南韓投入至少五萬億韓圜推動中小製造業物理人工智能,應用率目標由百分之一升至一成;7、任仕達調查:九成三美國僱主增聘科技人手,架構與代理編排成最大缺口;8、GitHub 稱九月份逾四成拉取請求由代理起草,較三月的一成七大幅上升;9、谷歌在新加坡設研究中心,並與兩家公共醫療集團試行臨床助手與健康教練;10、富士菲林投資約一百億日圓,把資料儲存磁帶產能擴至五倍。每條均附本會顧問觀點、對日常工作的影響與一項可即時執行的建議。

本會對今日 AI 局勢的整體判斷是甚麼?

今日主線是入口與紀錄同時被重寫。騰訊以 WorkBuddy 作工作台、甲骨文把 ChatGPT 接進財務與採購系統,代理坐上員工的第一個輸入框;同日獨立研究卻指四套主流框架缺持久代理識別碼與人工批核紀錄,企業無法還原誰批准了什麼。入口愈前、紀錄愈薄,落差即今日判斷重點。

這些情報的資料來源是甚麼?如何核實?

本欄每日由 AIX Society 編輯部檢索公開資料後撰稿,每條新聞均附原始來源連結(本期包括:Tencent、證券時報(今日頭條轉載)、India Today、騰訊新聞、MIT Technology Review、The Next Gen Tech Insider、Technology Magazine、Data Centre Magazine),並將事實與本會觀點分列。讀者可按來源連結自行核實。

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