| IVOD_ID |
168971 |
| IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/168971 |
| 日期 |
2026-04-29 |
| 會議資料.會議代碼 |
委員會-11-5-22-8 |
| 會議資料.會議代碼:str |
第11屆第5會期教育及文化委員會第8次全體委員會議 |
| 會議資料.屆 |
11 |
| 會議資料.會期 |
5 |
| 會議資料.會次 |
8 |
| 會議資料.種類 |
委員會 |
| 會議資料.委員會代碼[0] |
22 |
| 會議資料.委員會代碼:str[0] |
教育及文化委員會 |
| 會議資料.標題 |
第11屆第5會期教育及文化委員會第8次全體委員會議 |
| 影片種類 |
Clip |
| 開始時間 |
2026-04-29T12:39:22+08:00 |
| 結束時間 |
2026-04-29T12:52:54+08:00 |
| 影片長度 |
00:13:32 |
| 支援功能[0] |
ai-transcript |
| video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6301273cb2dfee84dea271401b74034dc607106bc22f509429ca0dd5c777562e9e84ac0ab64cdd6e5ea18f28b6918d91.mp4/playlist.m3u8 |
| 委員名稱 |
葉元之 |
| 委員發言時間 |
12:39:22 - 12:52:54 |
| 會議時間 |
2026-04-29T09:00:00+08:00 |
| 會議名稱 |
立法院第11屆第5會期教育及文化委員會第8次全體委員會議（事由：中央研究院、國家科學及技術委員會、數位發展部就「AI主權時代：學門建構與應用、研究應用倫理及數位透明度之配套措施」進行專題報告，並備質詢。【4月29日及30日二天一次會】） |
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| transcript.whisperx[0].start |
0.909 |
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主席好,麻煩請速發部國科會好,有請速發部國科會上備巡台 |
| transcript.whisperx[1].start |
23.976 |
| transcript.whisperx[1].end |
45.387 |
| transcript.whisperx[1].text |
我們現在講AI,其實大家都說台灣的AI算蠻厲害但是都是在講硬體,包括像我們現在股市都漲那麼多其實很多都AI的相關,但都是屬於硬體部分但我覺得在軟體這一塊,明明台灣有很好的條件可是台灣的軟體,我不知道現在政府對於軟體的投入有多少 |
| transcript.whisperx[2].start |
46.628 |
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62.523 |
| transcript.whisperx[2].text |
我們其實在上個世代像電子支付這些的台灣的軟體好像都有一些並沒有跟上社群媒體等等那現在AI軟體好不容易又有一個新的機會那到底我們對於AI軟體的輔導或者是給予的資源可能出現我們AI軟體的獨角獸 |
| transcript.whisperx[3].start |
68.408 |
| transcript.whisperx[3].end |
90.089 |
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我覺得政府也應該要去重視這一塊那現在業界比較重視的東西最主要跟兩位講最主要就是在算力因為大部分商業的軟體就是AI軟體他們要做機器人的話其實還是主要是跟國外的三大運在租算力可是這個費用是非常驚人的 |
| transcript.whisperx[4].start |
90.669 |
| transcript.whisperx[4].end |
110.377 |
| transcript.whisperx[4].text |
他要做一個對話機器人比如說好了要放在大賣場然後去跟那個機器人顧客去跟機器人對話比如說要找產品或者是詢問我要買什麼東西那請問東西在哪裡然後要問一些細節可能五分鐘他的算力就是非常可觀這個我不知道書畫部知道這事嗎應該知道嘛 |
| transcript.whisperx[5].start |
115.15 |
| transcript.whisperx[5].end |
137.46 |
| transcript.whisperx[5].text |
我們知道就是業界他們現在在後端會去對接各個不同的這個就是大圓模型但是在技術的發展中我們速發部現在也在推進就是台灣本土的小模型小圓模型的開發你不要答誰所問好不好 |
| transcript.whisperx[6].start |
138.18 |
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155.379 |
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就是我現在只是在講說現在我們在從軟體業界軟體的需求去探討這件事情你不用去跟我扯到你有沒有去研發小語言那個是另外一回事啦我不要答非所問那所以如果說我們站在因為我們的無限的創意是在民間嘛 |
| transcript.whisperx[7].start |
155.859 |
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182.903 |
| transcript.whisperx[7].text |
如果今天政府能夠站在輔導知道他們缺什麼然後我們來協助他們的話我們可能就會出現非常多就是很厲害的AI軟體甚至可以走向國際跟世界所以你要去幫忙解決問題那大家現在最在意的就是算力嘛因為現在算力的費用非常可觀那我想請教一下我們政府一直在講說要建立那個算力中心嘛對吧那現在大概是要編列多少預算來做 |
| transcript.whisperx[8].start |
189.969 |
| transcript.whisperx[8].end |
201.78 |
| transcript.whisperx[8].text |
多少預算跟我也回報我們在AI信實大建設裡面有大概編列40幾億在40幾億做編列40幾億做算力你終極目標是要花多少錢啊終極目標啊 |
| transcript.whisperx[9].start |
214.678 |
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230.464 |
| transcript.whisperx[9].text |
那像我們在沙倫的這個AI Data Center的部分我們目前就是在就是主機的部分大概有123億4年到117年4年編了123億以沙倫的這個AI Data Center那除了這之外還有嗎 |
| transcript.whisperx[10].start |
236.53 |
| transcript.whisperx[10].end |
252.74 |
| transcript.whisperx[10].text |
剛剛講的是不包含就是土建的部分那另外還有其他目前還有已經包含在金創那邊有相關的資源投入所以總共多少嘛你們知道馬斯克他要建立那個算力中心你知道總共花多少錢嗎你們知道多少嗎 |
| transcript.whisperx[11].start |
256.397 |
| transcript.whisperx[11].end |
283.525 |
| transcript.whisperx[11].text |
馬斯克他建算力中心總共花了五十億美金五十億美金就是一千多億台幣啊那你現在是編一百多億嘛對所以我們國家的資源投入是一百多億啊那請問一下你覺得夠嗎各位委員幫我們會再做持續的你已經編到一百一十七年了四年你四年的計畫也才這樣而已啊而且這個算力只會越來越多 |
| transcript.whisperx[12].start |
285.854 |
| transcript.whisperx[12].end |
301.38 |
| transcript.whisperx[12].text |
所以我們現在是會採公司協議的方式跟民間多多合作來去跟民間合作是所以其實感覺上是有點不足啦但第二個問題就是那我們現在國家建制的算力中心如果軟體業者他要來使用的話 |
| transcript.whisperx[13].start |
302.02 |
| transcript.whisperx[13].end |
328.501 |
| transcript.whisperx[13].text |
那是用什麼方式?租?然後補助?還是用什麼方式?我們現在國網中心所擁有的算力中心我們現在有提供一個叫AI WRAP的平台那我們有大略規劃了三分之一的算力是提供給新創的業者或者中小企業他們可以來做申請那我們會有一些補助是補助?對 |
| transcript.whisperx[14].start |
329.541 |
| transcript.whisperx[14].end |
358.779 |
| transcript.whisperx[14].text |
那這是優惠啦會有些優惠那是怎麼樣的優惠他大概價格跟一般他如果去租三大雲的話會差到多少差到多少會差到多少一定比他們便宜啦只是說不會我們因為一定比較便宜我知道啊你難道比較貴人家會跟你租嗎對沒有因為基本上大概是便宜多少為什麼今天你們回答問題都我們都有定價啦那至於說是便宜多少嘛我覺得我沒有記得比例你已經花納稅人的錢建置了對不對是 |
| transcript.whisperx[15].start |
359.059 |
| transcript.whisperx[15].end |
376.468 |
| transcript.whisperx[15].text |
那為什麼要花納稅人的錢建制就是希望能夠透過一些方式去輔導我們產業的發展因為它可能是未來下一顆星星啊你們不是有強調自己AI內閣嗎所以你的租金當然比外國便宜啊不然誰要跟你租我現在問的是你租金大概便宜多少嘛 |
| transcript.whisperx[16].start |
378.32 |
| transcript.whisperx[16].end |
399.241 |
| transcript.whisperx[16].text |
這個我回去查他們的價格一直在變啦因為這個變化很快那我們的定價都出來了你們制定一個政策做一件事情制定了一個政策都沒有去思考說我價格大概定到多少我幫助得了產業喔都沒有去想這個問題喔我現在問理論上這個東西你應該對答如流了還要回去查喔 |
| transcript.whisperx[17].start |
400.686 |
| transcript.whisperx[17].end |
416.964 |
| transcript.whisperx[17].text |
跟委員報告,抒發部這邊有這個篆力的支持那那個部分是透過審查流程是免費的所以是新創來跟抒發部申請都免費是不是?是那審查要件是什麼?審查要件我請這個素產署的同仁跟您補充 |
| transcript.whisperx[18].start |
419.002 |
| transcript.whisperx[18].end |
431.637 |
| transcript.whisperx[18].text |
報告委員我們審查要件就是他的心理性還有他可以產品化這些等等這些對那個產業的發展AI產業發展比較多的這樣子的一些要件那請問一下他申請那個算力有上限嗎 |
| transcript.whisperx[19].start |
433.341 |
| transcript.whisperx[19].end |
453.02 |
| transcript.whisperx[19].text |
我們還是要看就是有上限嗎上限是多少我們大概是用點數來算大概一萬點兩萬點一萬點兩萬點是指什麼一個月一萬點兩萬點不是我們就是一個週期一個週期大概一個月那一萬點一個點數我們大概是算就是十萬Token這樣子十萬Token |
| transcript.whisperx[20].start |
453.96 |
| transcript.whisperx[20].end |
471.63 |
| transcript.whisperx[20].text |
類似這樣子就是有一個定量因為我們的算力不足所以我們就是用排隊的方式排隊所以就是很有限嘛就講得好像很厲害然後什麼AI那個講了一大堆然後業界真正需要的算力就是很有限嘛然後問個價格也講不太清楚 |
| transcript.whisperx[21].start |
472.31 |
| transcript.whisperx[21].end |
499.208 |
| transcript.whisperx[21].text |
好啦那我知道你們一直在講政府一直在講主權AI 主權AI啦但是說實在的政府當然有發展主權AI的需求啦可是其實業界對於主權AI期望不高啦大家都認為這個跟他們比較沒有關係其實算力才是最相關的你應該如果假設我們想要輔導我們的AI軟體的話真的算力這一塊應該要多投入一些資源比起主權AI啦 |
| transcript.whisperx[22].start |
500.109 |
| transcript.whisperx[22].end |
504.103 |
| transcript.whisperx[22].text |
那我想問一下你們講的主權AI是指大圓模型嗎? |
| transcript.whisperx[23].start |
506.005 |
| transcript.whisperx[23].end |
531.435 |
| transcript.whisperx[23].text |
跟委員報告主權AI其實不只是大語言模型有沒有包括會包括大語言模型但是更重要的是人才資料算力整合能夠訓練AI的一個能力當然啊當然都需要嘛因為這是一個整體嘛我想請教一下我們現在要建置自己的大語言模型那現在有趕上兩年前的OpenAI嗎 |
| transcript.whisperx[24].start |
536.158 |
| transcript.whisperx[24].end |
547.129 |
| transcript.whisperx[24].text |
誰可以回答書畫部書畫部不能回答嗎你們不是輔導軟體的嗎我們現在的主權AI大圓模型有沒有趕上兩年前的OpenAI |
| transcript.whisperx[25].start |
547.759 |
| transcript.whisperx[25].end |
569.041 |
| transcript.whisperx[25].text |
委員指的主權AI是指哪一個模型?就是大語言模型我們現在政府的要發展的大語言模型我們在策略上面速發部並不主著重於大語言模型的開發我們著重的是特用型的模型那並不是要去開發一個像OpenAI那樣子的Frontier模型所以我們的主權AI不是大語言模型是特用模型 |
| transcript.whisperx[26].start |
569.942 |
| transcript.whisperx[26].end |
591.341 |
| transcript.whisperx[26].text |
應該是說 如果委員說的主權AI的話我們速發部應該不是在專注在您所定義的這個模型這個上面而是在建構整個台灣主權AI能力包括您剛所提到的人才資料然後資金算力這些能力上面 |
| transcript.whisperx[27].start |
593.163 |
| transcript.whisperx[27].end |
600.189 |
| transcript.whisperx[27].text |
委員剛剛講的主權AI的大語言模型是不是專門指這個台德的部分可能要請鍾圓園來跟您說明那請鍾圓園 |
| transcript.whisperx[28].start |
605.918 |
| transcript.whisperx[28].end |
634.286 |
| transcript.whisperx[28].text |
向委員報告那您剛提到這個OpenAI的模型那我們確實有哪一個OpenAI的模型作為參考的基準它去年有一顆叫做OSS20B的模型那我們拿它來當作一個參考那我們的模型的在一些我們這個公務系統的一些應用上面的服務呢它的這個對於台灣的知識台灣的這個認知的這個能力呢是有超越原版的這個這個OpenAI的這個OSS的模型所以我們現在已經超過 |
| transcript.whisperx[29].start |
635.126 |
| transcript.whisperx[29].end |
647.508 |
| transcript.whisperx[29].text |
超過了OpenAIChap GPT已經超過它了它其中一顆比較小的模型我們有超過它有超過一顆比較小的模型那我講的大語言的模型 |
| transcript.whisperx[30].start |
649.382 |
| transcript.whisperx[30].end |
675.081 |
| transcript.whisperx[30].text |
他是比較小的大型語言模型那加油啦 加油我是那個中業資訊所有人我也是台德跟台德計畫裡面剛剛您講的那個東西我們大型語言模型我們台灣以我們的那個規模我們人口的規模這些東西我們沒有辦法跟Google或者是OpenAI這種大公司來pd這種general的LLM |
| transcript.whisperx[31].start |
675.521 |
| transcript.whisperx[31].end |
700.139 |
| transcript.whisperx[31].text |
是沒有辦法的我們能做的就是說把他的東西當做一個Foundation Model帶到中油經過Supervised Fine Tuning或Pre-training來帶到中油讓我們的百工百業在中油我們有比較大的軟體公司來做到中油或者是像中原或者是國科會這樣的政府機構來幫助我們的中小企業把上面那種大型營業模型想辦法 |
| transcript.whisperx[32].start |
701.824 |
| transcript.whisperx[32].end |
729.389 |
| transcript.whisperx[32].text |
帶到中油來然後讓中油再做一個平台來支持我們台灣的百工百業所以我們沒有能力因為我們就像剛剛講的 算力我問這個問題主要是這樣就是說我們大家講一個AI講得很大方向很大但是真正落實到大家真正的需求有沒有真的具體的照顧得到就是說就像主權AI喊得很大因為我們每個國家都要主權AI |
| transcript.whisperx[33].start |
730.549 |
| transcript.whisperx[33].end |
756.794 |
| transcript.whisperx[33].text |
但是實際上做出來的東西大家真的用不用得到還是說其實大部分的人還是會去用比如說Google啊或者是這就是大家關切的問題所以不要談太多口號我跟委員報告一下是有實際用到的比如說我們最近用了一個影像的部分我們就在上游的部分就用YOLOv7 YOLOv9這是我們台灣中研院自己發展出來的世界級的 |
| transcript.whisperx[34].start |
757.754 |
| transcript.whisperx[34].end |
778.738 |
| transcript.whisperx[34].text |
物件真正系統那翼龍電子新竹的上市公司翼龍電子他把它加工以後結合聯發科跟聯詠的12奈米的晶片還有NVIDIA的ORIN的晶片把它合在一起軟硬體結合以後訓練一個中油的平台放在CCTV上面 |
| transcript.whisperx[35].start |
779.198 |
| transcript.whisperx[35].end |
805.607 |
| transcript.whisperx[35].text |
因為以前我們的六都我們的CCDB在譬如說交通中心的話看到都只是看到video但是都沒有做任何的處理但是現在翼龍電的這個系統呢它是等於結合剛剛講的這個軟體跟硬體用台灣本土的帶到中油去它現在這個CCDB是用在高雄的捷運的車廂裡面那這車廂裡面它就可以去觀察車廂裡面的狀態OK 對那這是實際的用途好 謝謝 |
| transcript.whisperx[36].start |
811.947 |
| transcript.whisperx[36].end |
812.787 |
| transcript.whisperx[36].text |
好谢谢 |