iVOD / 157497

Field Value
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/4b9db3dc7042177ad8ee2d16323d9c7a6e756e96dd8ac7a3e54b9bd157483afa903ae40ffbf143735ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 呂玉玲
委員發言時間 10:44:06 - 10:52:43
影片長度 517
會議時間 2024-11-27T09:00:00+08:00
會議名稱 立法院第11屆第2會期經濟委員會第17次全體委員會議(事由:審查114年度中央政府總預算案關於經濟部及所屬單位預算部分。(詢答))
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 4.04721875
transcript.pyannote[0].end 4.99221875
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 8.82284375
transcript.pyannote[1].end 9.98721875
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 12.09659375
transcript.pyannote[2].end 13.17659375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 15.97784375
transcript.pyannote[3].end 16.75409375
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 17.39534375
transcript.pyannote[4].end 20.06159375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 21.93471875
transcript.pyannote[5].end 22.23846875
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 23.28471875
transcript.pyannote[6].end 24.63471875
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 25.20846875
transcript.pyannote[7].end 45.35721875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 45.72846875
transcript.pyannote[8].end 62.14784375
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 62.40096875
transcript.pyannote[9].end 62.73846875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 62.73846875
transcript.pyannote[10].end 64.64534375
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 64.69596875
transcript.pyannote[11].end 86.66721875
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 86.66721875
transcript.pyannote[12].end 95.07096875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 95.81346875
transcript.pyannote[13].end 97.19721875
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 96.45471875
transcript.pyannote[14].end 98.76659375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 98.17596875
transcript.pyannote[15].end 107.47409375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 107.65971875
transcript.pyannote[16].end 139.46909375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 139.97534375
transcript.pyannote[17].end 140.73471875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 141.03846875
transcript.pyannote[18].end 141.05534375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 141.05534375
transcript.pyannote[19].end 161.81159375
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 141.07221875
transcript.pyannote[20].end 142.15221875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 162.11534375
transcript.pyannote[21].end 170.62034375
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 165.81096875
transcript.pyannote[22].end 166.06409375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 170.62034375
transcript.pyannote[23].end 170.63721875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 172.57784375
transcript.pyannote[24].end 191.03909375
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 180.49221875
transcript.pyannote[25].end 180.76221875
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 190.76909375
transcript.pyannote[26].end 191.00534375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 191.03909375
transcript.pyannote[27].end 191.25846875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 191.25846875
transcript.pyannote[28].end 191.30909375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 191.61284375
transcript.pyannote[29].end 191.68034375
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 191.68034375
transcript.pyannote[30].end 208.69034375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 194.29596875
transcript.pyannote[31].end 194.54909375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 208.69034375
transcript.pyannote[32].end 216.89159375
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 211.72784375
transcript.pyannote[33].end 211.74471875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 217.04346875
transcript.pyannote[34].end 217.06034375
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 217.06034375
transcript.pyannote[35].end 219.28784375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 217.16159375
transcript.pyannote[36].end 217.68471875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 219.76034375
transcript.pyannote[37].end 222.83159375
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 220.33409375
transcript.pyannote[38].end 222.81471875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 222.83159375
transcript.pyannote[39].end 228.68721875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 228.68721875
transcript.pyannote[40].end 228.77159375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 228.77159375
transcript.pyannote[41].end 229.00784375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 229.00784375
transcript.pyannote[42].end 229.15971875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 229.19346875
transcript.pyannote[43].end 275.98784375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 278.45159375
transcript.pyannote[44].end 278.78909375
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 279.70034375
transcript.pyannote[45].end 281.50596875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 281.50596875
transcript.pyannote[46].end 281.53971875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 281.53971875
transcript.pyannote[47].end 281.67471875
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 281.67471875
transcript.pyannote[48].end 281.70846875
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 281.70846875
transcript.pyannote[49].end 281.99534375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 284.17221875
transcript.pyannote[50].end 306.21096875
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 307.34159375
transcript.pyannote[51].end 309.72096875
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 308.79284375
transcript.pyannote[52].end 311.96534375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 311.27346875
transcript.pyannote[53].end 311.59409375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 312.30284375
transcript.pyannote[54].end 312.79221875
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 312.31971875
transcript.pyannote[55].end 313.34909375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 314.15909375
transcript.pyannote[56].end 315.96471875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 315.96471875
transcript.pyannote[57].end 316.80846875
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 317.07846875
transcript.pyannote[58].end 318.59721875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 318.59721875
transcript.pyannote[59].end 318.91784375
transcript.pyannote[60].speaker SPEAKER_02
transcript.pyannote[60].start 318.93471875
transcript.pyannote[60].end 320.99346875
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 321.73596875
transcript.pyannote[61].end 322.88346875
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 323.17034375
transcript.pyannote[62].end 340.36596875
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 340.45034375
transcript.pyannote[63].end 341.17596875
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 340.87221875
transcript.pyannote[64].end 345.86721875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 346.28909375
transcript.pyannote[65].end 347.89221875
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 348.34784375
transcript.pyannote[66].end 357.22409375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 357.59534375
transcript.pyannote[67].end 358.81034375
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 359.08034375
transcript.pyannote[68].end 361.03784375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 362.21909375
transcript.pyannote[69].end 363.53534375
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 363.53534375
transcript.pyannote[70].end 363.55221875
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 363.55221875
transcript.pyannote[71].end 364.48034375
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 364.48034375
transcript.pyannote[72].end 364.53096875
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 365.62784375
transcript.pyannote[73].end 401.08221875
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 368.36159375
transcript.pyannote[74].end 368.63159375
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 383.46471875
transcript.pyannote[75].end 383.53221875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 383.61659375
transcript.pyannote[76].end 383.81909375
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 401.16659375
transcript.pyannote[77].end 421.60221875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 405.40221875
transcript.pyannote[78].end 405.67221875
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 415.94909375
transcript.pyannote[79].end 416.59034375
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 421.88909375
transcript.pyannote[80].end 431.96346875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 423.37409375
transcript.pyannote[81].end 424.11659375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 425.38221875
transcript.pyannote[82].end 425.75346875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 425.82096875
transcript.pyannote[83].end 426.04034375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 431.96346875
transcript.pyannote[84].end 433.06034375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 433.80284375
transcript.pyannote[85].end 455.03159375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 443.89409375
transcript.pyannote[86].end 444.36659375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 455.03159375
transcript.pyannote[87].end 456.11159375
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 456.11159375
transcript.pyannote[88].end 457.63034375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 456.63471875
transcript.pyannote[89].end 459.84096875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 460.00971875
transcript.pyannote[90].end 466.74284375
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 467.80596875
transcript.pyannote[91].end 472.59846875
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 472.91909375
transcript.pyannote[92].end 494.70471875
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 475.43346875
transcript.pyannote[93].end 476.27721875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 494.70471875
transcript.pyannote[94].end 494.80596875
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 494.80596875
transcript.pyannote[95].end 495.04221875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 495.04221875
transcript.pyannote[96].end 512.96346875
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 512.96346875
transcript.pyannote[97].end 513.28409375
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 514.75221875
transcript.pyannote[98].end 515.59596875
transcript.whisperx[0].start 4.036
transcript.whisperx[0].end 22.91
transcript.whisperx[0].text 響鐘
transcript.whisperx[1].start 25.649
transcript.whisperx[1].end 44.636
transcript.whisperx[1].text 臺灣的中小企業的彈性跟創新的能量是維繫我國經濟發展跟社會安定非常重要的那尤其很多的中小企業也引領著產業的隱形冠軍所以我們在2023年的中小企業的白皮書裡面都有來提到尤其是全體企業
transcript.whisperx[2].start 46.056
transcript.whisperx[2].end 60.641
transcript.whisperx[2].text 中小企業部分占了98%。如果我們的政府還是把眼光放在來扶植核心的產業,長期忽視了中小企業的發展,這對整個就業市場會造成很不健康的影響。部長你認同嗎?
transcript.whisperx[3].start 63.084
transcript.whisperx[3].end 77.062
transcript.whisperx[3].text 我認同委員這樣的推詢是 那尤其現在很多企業在數位的轉型上 有碰到這個六大的瓶頸的困難的問題那部長你在這邊 你了解這個六大問題之後 你要怎麼樣去解決這些問題呢
transcript.whisperx[4].start 78.063
transcript.whisperx[4].end 78.524
transcript.whisperx[4].text 我們大概會透過兩個方法 第一個就是說幫助這些產業先數位化
transcript.whisperx[5].start 95.828
transcript.whisperx[5].end 97.489
transcript.whisperx[5].text 蘇維化與資料儲存、資訊導入AI化、智慧化
transcript.whisperx[6].start 111.218
transcript.whisperx[6].end 137.587
transcript.whisperx[6].text 那麼他可以提供比較好的資訊這個提供比較好的資訊會讓業者他比較容易做對的決策那我們幫助這些中小企業第一個就是讓他高質化選做對的事情然後第二個我們幫他降低成本然後讓他把事情做對這個大概是我們現在中小企業署創新署在努力的這個部分
transcript.whisperx[7].start 140.028
transcript.whisperx[7].end 159.546
transcript.whisperx[7].text 太多了所以我就針對製造業來跟部長來提醒尤其在製造業來講的話目前有57%的業者他們是第一階段只有數位化那第二階段是數位優化有5.2%那第三階段的話是數位的轉型有30.8%
transcript.whisperx[8].start 162.228
transcript.whisperx[8].end 190.546
transcript.whisperx[8].text 有一部分7%的完全沒有數位化那你知道這個原因在哪裡嗎像成本問題不願意投資還是看不到它的成效原因就是非常的多啦每一個產業因為這個產業有的規模太小有的它資金太少有的它不願意跟產業鏈配合我想我們會針對這一些盤點出來的問題然後下去把它集中以後下去解決這個問題
transcript.whisperx[9].start 192.047
transcript.whisperx[9].end 216.204
transcript.whisperx[9].text 經濟部已經把抓出這個六大問題了那尤其是製造業是很重要的中小企業我們希望部長在這邊瞭解問題去對他們各別的不同的各產業他們的不同跟他們的落差你知道相應應的一個對策要做出來是我們會從供應鏈的這樣的一個垂直的關係然後來輔導這一些比較弱的這些廠商
transcript.whisperx[10].start 217.09
transcript.whisperx[10].end 244.718
transcript.whisperx[10].text 臺灣﹚
transcript.whisperx[11].start 244.718
transcript.whisperx[11].end 245.599
transcript.whisperx[11].text 請問那我們現在也有做出一個目標在2028年的話我們在IC設計的這個能量方面
transcript.whisperx[12].start 274.743
transcript.whisperx[12].end 275.826
transcript.whisperx[12].text 我們能成長多少?
transcript.whisperx[13].start 284.349
transcript.whisperx[13].end 303.86
transcript.whisperx[13].text 報告委員 我們有推動金創計畫那我們要來推動國內IC設計去導入先進或國際高度信任的優勢特殊晶片我們預估IC設計產業採用先進製程的晶片的比率會從112年的39%提升到113年的43%113年43% 現在不是20年2028年能夠提升到多少
transcript.whisperx[14].start 314.375
transcript.whisperx[14].end 340.191
transcript.whisperx[14].text 我們期待能夠到50%提升到50%因為我們跟美國的差距是多少你知道嗎我們現在是20%美國將近有60%差了3倍你現在提高了50%我也樂觀其成那就加油啦好不好那因為現在人才在這資訊方面的人才是有斷層的人才不足而且在整個產業上也有缺工的情形部長都知道吧
transcript.whisperx[15].start 341.031
transcript.whisperx[15].end 353.924
transcript.whisperx[15].text 但是現在我們看到很多的資訊在資訊通訊科技學門裡面畢業沒有投入在這個就業的方面非常的多在2019年裡面19.63%到現在2023年到36.58%部長知道什麼原因嗎為什麼畢業沒有投入這個職場也許不願意到工廠去工作
transcript.whisperx[16].start 365.723
transcript.whisperx[16].end 387.23
transcript.whisperx[16].text 所以這個就是很多的因素啦也許可能就是有當兵的問題各方面但是我們希望說能夠在缺工那個人才我們怎麼樣去培訓人才怎麼樣去徵才這是很重要的這部長在這方面的因應也要找出一個對策好不好那尤其是在國外的留學生裡面將近有2萬人在台灣也是讀這個資訊通訊這個科系的但是留到台灣的話也不到一半
transcript.whisperx[17].start 394.232
transcript.whisperx[17].end 400.753
transcript.whisperx[17].text 這部分我們之前在院會裡面有討論過那我們會希望過去這個兩萬多人的這個僑外生將來可以有百分之七十八十留在台灣透過一些這個方法我們現在勞動部就是有在設計這樣子讓他們留下來的這個方案
transcript.whisperx[18].start 424.687
transcript.whisperx[18].end 432.638
transcript.whisperx[18].text 國發會、國發會跟勞動部他們在討論你們的目標呢?我們的目標,我們自己這個他們現在不留下來的原因有知道嗎?
transcript.whisperx[19].start 433.831
transcript.whisperx[19].end 433.931
transcript.whisperx[19].text 經濟部自己本身
transcript.whisperx[20].start 460.192
transcript.whisperx[20].end 465.465
transcript.whisperx[20].text 正跟教育部在協商我們經濟部會每一年訓練兩萬五千位
transcript.whisperx[21].start 468.087
transcript.whisperx[21].end 493.939
transcript.whisperx[21].text 橋外生跟本土的這個學生專業的就是比較科技業的你們訓練好能夠就業嗎?就業2萬5千的就業二加4計畫就在執行這件事情也就是說兩年他來讀書由國家提供這個學費跟雜費那經濟部提供生活費所以他們畢業就一定要投入一定要在這個工作在工作不然的話他就要罰這個就是要還那個錢
transcript.whisperx[22].start 494.779
transcript.whisperx[22].end 494.799
transcript.whisperx[22].text 謝謝委員
IVOD_ID 157497
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/157497
日期 2024-11-27
會議資料.會議代碼 委員會-11-2-19-17
會議資料.屆 11
會議資料.會期 2
會議資料.會次 17
會議資料.種類 委員會
會議資料.委員會代碼[0] 19
會議資料.標題 第11屆第2會期經濟委員會第17次全體委員會議
影片種類 Clip
開始時間 2024-11-27T10:44:06+08:00
結束時間 2024-11-27T10:52:43+08:00
支援功能[0] ai-transcript