| IVOD_ID |
162883 |
| IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/162883 |
| 日期 |
2025-06-18 |
| 會議資料.會議代碼 |
聯席會議-11-3-19,26,22-1 |
| 會議資料.會議代碼:str |
第11屆第3會期經濟、社會福利及衛生環境、教育及文化三委員會第1次聯席會議 |
| 會議資料.屆 |
11 |
| 會議資料.會期 |
3 |
| 會議資料.會次 |
1 |
| 會議資料.種類 |
聯席會議 |
| 會議資料.委員會代碼[0] |
19 |
| 會議資料.委員會代碼[1] |
26 |
| 會議資料.委員會代碼[2] |
22 |
| 會議資料.委員會代碼:str[0] |
經濟委員會 |
| 會議資料.委員會代碼:str[1] |
社會福利及衛生環境委員會 |
| 會議資料.委員會代碼:str[2] |
教育及文化委員會 |
| 會議資料.標題 |
第11屆第3會期經濟、社會福利及衛生環境、教育及文化三委員會第1次聯席會議 |
| 影片種類 |
Clip |
| 開始時間 |
2025-06-18T14:42:06+08:00 |
| 結束時間 |
2025-06-18T14:50:12+08:00 |
| 影片長度 |
00:08:06 |
| 支援功能[0] |
ai-transcript |
| video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/3c0085a4689617f52182a5ad36bd07c95c8a36db9e18c27bdb117453e643ccc9f93a7319753701da5ea18f28b6918d91.mp4/playlist.m3u8 |
| 委員名稱 |
謝衣鳯 |
| 委員發言時間 |
14:42:06 - 14:50:12 |
| 會議時間 |
2025-06-18T09:00:00+08:00 |
| 會議名稱 |
立法院第11屆第3會期經濟、社會福利及衛生環境、教育及文化三委員會第1次聯席會議（事由：審查：
一、行政院函請審議「外國專業人才延攬及僱用法修正草案」案。
二、本院委員何欣純等19人擬具「外國專業人才延攬及僱用法第十二條及第十四條條文修正草案」案。
三、本院委員陳亭妃等16人擬具「外國專業人才延攬及僱用法第四條、第六條及第十四條條文修正草案」案。
四、本院委員蔡易餘等17人擬具「外國專業人才延攬及僱用法修正草案」案。
五、本院委員羅美玲等16人擬具「外國專業人才延攬及僱用法修正草案」案。(詢答)
（第一案如未接獲議事處來函則不予審查。）） |
| transcript.pyannote[0].speaker |
SPEAKER_00 |
| transcript.pyannote[0].start |
0.03096875 |
| transcript.pyannote[0].end |
1.88721875 |
| transcript.pyannote[1].speaker |
SPEAKER_00 |
| transcript.pyannote[1].start |
4.36784375 |
| transcript.pyannote[1].end |
4.89096875 |
| transcript.pyannote[2].speaker |
SPEAKER_00 |
| transcript.pyannote[2].start |
4.90784375 |
| transcript.pyannote[2].end |
5.02596875 |
| transcript.pyannote[3].speaker |
SPEAKER_00 |
| transcript.pyannote[3].start |
11.20221875 |
| transcript.pyannote[3].end |
12.70409375 |
| transcript.pyannote[4].speaker |
SPEAKER_00 |
| transcript.pyannote[4].start |
13.09221875 |
| transcript.pyannote[4].end |
14.15534375 |
| transcript.pyannote[5].speaker |
SPEAKER_01 |
| transcript.pyannote[5].start |
14.69534375 |
| transcript.pyannote[5].end |
15.50534375 |
| transcript.pyannote[6].speaker |
SPEAKER_00 |
| transcript.pyannote[6].start |
22.71096875 |
| transcript.pyannote[6].end |
22.76159375 |
| transcript.pyannote[7].speaker |
SPEAKER_01 |
| transcript.pyannote[7].start |
22.76159375 |
| transcript.pyannote[7].end |
23.38596875 |
| transcript.pyannote[8].speaker |
SPEAKER_00 |
| transcript.pyannote[8].start |
23.77409375 |
| transcript.pyannote[8].end |
25.86659375 |
| transcript.pyannote[9].speaker |
SPEAKER_00 |
| transcript.pyannote[9].start |
26.15346875 |
| transcript.pyannote[9].end |
32.49846875 |
| transcript.pyannote[10].speaker |
SPEAKER_00 |
| transcript.pyannote[10].start |
32.95409375 |
| transcript.pyannote[10].end |
34.03409375 |
| transcript.pyannote[11].speaker |
SPEAKER_00 |
| transcript.pyannote[11].start |
34.42221875 |
| transcript.pyannote[11].end |
35.02971875 |
| transcript.pyannote[12].speaker |
SPEAKER_00 |
| transcript.pyannote[12].start |
35.82284375 |
| transcript.pyannote[12].end |
38.20221875 |
| transcript.pyannote[13].speaker |
SPEAKER_00 |
| transcript.pyannote[13].start |
38.64096875 |
| transcript.pyannote[13].end |
39.68721875 |
| transcript.pyannote[14].speaker |
SPEAKER_00 |
| transcript.pyannote[14].start |
39.85596875 |
| transcript.pyannote[14].end |
65.62409375 |
| transcript.pyannote[15].speaker |
SPEAKER_00 |
| transcript.pyannote[15].start |
65.96159375 |
| transcript.pyannote[15].end |
74.95596875 |
| transcript.pyannote[16].speaker |
SPEAKER_01 |
| transcript.pyannote[16].start |
75.44534375 |
| transcript.pyannote[16].end |
80.71034375 |
| transcript.pyannote[17].speaker |
SPEAKER_01 |
| transcript.pyannote[17].start |
81.04784375 |
| transcript.pyannote[17].end |
101.78721875 |
| transcript.pyannote[18].speaker |
SPEAKER_00 |
| transcript.pyannote[18].start |
89.18159375 |
| transcript.pyannote[18].end |
89.28284375 |
| transcript.pyannote[19].speaker |
SPEAKER_00 |
| transcript.pyannote[19].start |
89.51909375 |
| transcript.pyannote[19].end |
89.68784375 |
| transcript.pyannote[20].speaker |
SPEAKER_01 |
| transcript.pyannote[20].start |
102.58034375 |
| transcript.pyannote[20].end |
107.28846875 |
| transcript.pyannote[21].speaker |
SPEAKER_01 |
| transcript.pyannote[21].start |
107.44034375 |
| transcript.pyannote[21].end |
111.69284375 |
| transcript.pyannote[22].speaker |
SPEAKER_01 |
| transcript.pyannote[22].start |
111.82784375 |
| transcript.pyannote[22].end |
119.79284375 |
| transcript.pyannote[23].speaker |
SPEAKER_01 |
| transcript.pyannote[23].start |
119.86034375 |
| transcript.pyannote[23].end |
129.98534375 |
| transcript.pyannote[24].speaker |
SPEAKER_00 |
| transcript.pyannote[24].start |
120.29909375 |
| transcript.pyannote[24].end |
120.61971875 |
| transcript.pyannote[25].speaker |
SPEAKER_01 |
| transcript.pyannote[25].start |
130.23846875 |
| transcript.pyannote[25].end |
130.94721875 |
| transcript.pyannote[26].speaker |
SPEAKER_00 |
| transcript.pyannote[26].start |
130.27221875 |
| transcript.pyannote[26].end |
150.80909375 |
| transcript.pyannote[27].speaker |
SPEAKER_01 |
| transcript.pyannote[27].start |
131.87534375 |
| transcript.pyannote[27].end |
132.33096875 |
| transcript.pyannote[28].speaker |
SPEAKER_01 |
| transcript.pyannote[28].start |
151.02846875 |
| transcript.pyannote[28].end |
164.14034375 |
| transcript.pyannote[29].speaker |
SPEAKER_00 |
| transcript.pyannote[29].start |
155.29784375 |
| transcript.pyannote[29].end |
155.51721875 |
| transcript.pyannote[30].speaker |
SPEAKER_01 |
| transcript.pyannote[30].start |
164.27534375 |
| transcript.pyannote[30].end |
165.70971875 |
| transcript.pyannote[31].speaker |
SPEAKER_01 |
| transcript.pyannote[31].start |
166.08096875 |
| transcript.pyannote[31].end |
187.27596875 |
| transcript.pyannote[32].speaker |
SPEAKER_00 |
| transcript.pyannote[32].start |
177.33659375 |
| transcript.pyannote[32].end |
177.45471875 |
| transcript.pyannote[33].speaker |
SPEAKER_01 |
| transcript.pyannote[33].start |
187.44471875 |
| transcript.pyannote[33].end |
210.42846875 |
| transcript.pyannote[34].speaker |
SPEAKER_00 |
| transcript.pyannote[34].start |
208.40346875 |
| transcript.pyannote[34].end |
209.48346875 |
| transcript.pyannote[35].speaker |
SPEAKER_00 |
| transcript.pyannote[35].start |
209.93909375 |
| transcript.pyannote[35].end |
211.98096875 |
| transcript.pyannote[36].speaker |
SPEAKER_00 |
| transcript.pyannote[36].start |
212.50409375 |
| transcript.pyannote[36].end |
213.51659375 |
| transcript.pyannote[37].speaker |
SPEAKER_00 |
| transcript.pyannote[37].start |
213.58409375 |
| transcript.pyannote[37].end |
232.12971875 |
| transcript.pyannote[38].speaker |
SPEAKER_01 |
| transcript.pyannote[38].start |
217.92096875 |
| transcript.pyannote[38].end |
218.34284375 |
| transcript.pyannote[39].speaker |
SPEAKER_01 |
| transcript.pyannote[39].start |
219.05159375 |
| transcript.pyannote[39].end |
219.08534375 |
| transcript.pyannote[40].speaker |
SPEAKER_01 |
| transcript.pyannote[40].start |
219.20346875 |
| transcript.pyannote[40].end |
219.25409375 |
| transcript.pyannote[41].speaker |
SPEAKER_01 |
| transcript.pyannote[41].start |
232.21409375 |
| transcript.pyannote[41].end |
238.25534375 |
| transcript.pyannote[42].speaker |
SPEAKER_01 |
| transcript.pyannote[42].start |
238.64346875 |
| transcript.pyannote[42].end |
240.22971875 |
| transcript.pyannote[43].speaker |
SPEAKER_01 |
| transcript.pyannote[43].start |
240.34784375 |
| transcript.pyannote[43].end |
243.48659375 |
| transcript.pyannote[44].speaker |
SPEAKER_00 |
| transcript.pyannote[44].start |
240.36471875 |
| transcript.pyannote[44].end |
240.82034375 |
| transcript.pyannote[45].speaker |
SPEAKER_00 |
| transcript.pyannote[45].start |
241.79909375 |
| transcript.pyannote[45].end |
244.21221875 |
| transcript.pyannote[46].speaker |
SPEAKER_01 |
| transcript.pyannote[46].start |
243.82409375 |
| transcript.pyannote[46].end |
247.77284375 |
| transcript.pyannote[47].speaker |
SPEAKER_00 |
| transcript.pyannote[47].start |
247.75596875 |
| transcript.pyannote[47].end |
253.37534375 |
| transcript.pyannote[48].speaker |
SPEAKER_01 |
| transcript.pyannote[48].start |
248.09346875 |
| transcript.pyannote[48].end |
248.49846875 |
| transcript.pyannote[49].speaker |
SPEAKER_01 |
| transcript.pyannote[49].start |
249.96659375 |
| transcript.pyannote[49].end |
250.47284375 |
| transcript.pyannote[50].speaker |
SPEAKER_01 |
| transcript.pyannote[50].start |
252.71721875 |
| transcript.pyannote[50].end |
252.97034375 |
| transcript.pyannote[51].speaker |
SPEAKER_00 |
| transcript.pyannote[51].start |
253.62846875 |
| transcript.pyannote[51].end |
289.30221875 |
| transcript.pyannote[52].speaker |
SPEAKER_01 |
| transcript.pyannote[52].start |
287.66534375 |
| transcript.pyannote[52].end |
295.88346875 |
| transcript.pyannote[53].speaker |
SPEAKER_01 |
| transcript.pyannote[53].start |
296.01846875 |
| transcript.pyannote[53].end |
298.09409375 |
| transcript.pyannote[54].speaker |
SPEAKER_00 |
| transcript.pyannote[54].start |
298.31346875 |
| transcript.pyannote[54].end |
298.71846875 |
| transcript.pyannote[55].speaker |
SPEAKER_01 |
| transcript.pyannote[55].start |
298.60034375 |
| transcript.pyannote[55].end |
301.35096875 |
| transcript.pyannote[56].speaker |
SPEAKER_00 |
| transcript.pyannote[56].start |
300.38909375 |
| transcript.pyannote[56].end |
302.81909375 |
| transcript.pyannote[57].speaker |
SPEAKER_01 |
| transcript.pyannote[57].start |
302.81909375 |
| transcript.pyannote[57].end |
308.69159375 |
| transcript.pyannote[58].speaker |
SPEAKER_00 |
| transcript.pyannote[58].start |
307.40909375 |
| transcript.pyannote[58].end |
307.81409375 |
| transcript.pyannote[59].speaker |
SPEAKER_01 |
| transcript.pyannote[59].start |
309.18096875 |
| transcript.pyannote[59].end |
312.65721875 |
| transcript.pyannote[60].speaker |
SPEAKER_00 |
| transcript.pyannote[60].start |
312.67409375 |
| transcript.pyannote[60].end |
322.56284375 |
| transcript.pyannote[61].speaker |
SPEAKER_01 |
| transcript.pyannote[61].start |
318.32721875 |
| transcript.pyannote[61].end |
321.12846875 |
| transcript.pyannote[62].speaker |
SPEAKER_01 |
| transcript.pyannote[62].start |
322.02284375 |
| transcript.pyannote[62].end |
326.25846875 |
| transcript.pyannote[63].speaker |
SPEAKER_01 |
| transcript.pyannote[63].start |
326.61284375 |
| transcript.pyannote[63].end |
327.57471875 |
| transcript.pyannote[64].speaker |
SPEAKER_00 |
| transcript.pyannote[64].start |
327.57471875 |
| transcript.pyannote[64].end |
328.11471875 |
| transcript.pyannote[65].speaker |
SPEAKER_01 |
| transcript.pyannote[65].start |
327.62534375 |
| transcript.pyannote[65].end |
327.64221875 |
| transcript.pyannote[66].speaker |
SPEAKER_01 |
| transcript.pyannote[66].start |
327.87846875 |
| transcript.pyannote[66].end |
338.89784375 |
| transcript.pyannote[67].speaker |
SPEAKER_00 |
| transcript.pyannote[67].start |
331.48971875 |
| transcript.pyannote[67].end |
331.79346875 |
| transcript.pyannote[68].speaker |
SPEAKER_00 |
| transcript.pyannote[68].start |
336.80534375 |
| transcript.pyannote[68].end |
336.88971875 |
| transcript.pyannote[69].speaker |
SPEAKER_01 |
| transcript.pyannote[69].start |
338.96534375 |
| transcript.pyannote[69].end |
344.97284375 |
| transcript.pyannote[70].speaker |
SPEAKER_01 |
| transcript.pyannote[70].start |
345.12471875 |
| transcript.pyannote[70].end |
350.54159375 |
| transcript.pyannote[71].speaker |
SPEAKER_00 |
| transcript.pyannote[71].start |
349.24221875 |
| transcript.pyannote[71].end |
349.74846875 |
| transcript.pyannote[72].speaker |
SPEAKER_00 |
| transcript.pyannote[72].start |
350.54159375 |
| transcript.pyannote[72].end |
372.05721875 |
| transcript.pyannote[73].speaker |
SPEAKER_01 |
| transcript.pyannote[73].start |
355.26659375 |
| transcript.pyannote[73].end |
358.82721875 |
| transcript.pyannote[74].speaker |
SPEAKER_00 |
| transcript.pyannote[74].start |
372.29346875 |
| transcript.pyannote[74].end |
374.21721875 |
| transcript.pyannote[75].speaker |
SPEAKER_00 |
| transcript.pyannote[75].start |
374.48721875 |
| transcript.pyannote[75].end |
421.14659375 |
| transcript.pyannote[76].speaker |
SPEAKER_01 |
| transcript.pyannote[76].start |
396.22221875 |
| transcript.pyannote[76].end |
396.66096875 |
| transcript.pyannote[77].speaker |
SPEAKER_00 |
| transcript.pyannote[77].start |
422.04096875 |
| transcript.pyannote[77].end |
430.56284375 |
| transcript.pyannote[78].speaker |
SPEAKER_00 |
| transcript.pyannote[78].start |
431.32221875 |
| transcript.pyannote[78].end |
433.12784375 |
| transcript.pyannote[79].speaker |
SPEAKER_01 |
| transcript.pyannote[79].start |
433.41471875 |
| transcript.pyannote[79].end |
433.56659375 |
| transcript.pyannote[80].speaker |
SPEAKER_00 |
| transcript.pyannote[80].start |
433.95471875 |
| transcript.pyannote[80].end |
435.79409375 |
| transcript.pyannote[81].speaker |
SPEAKER_01 |
| transcript.pyannote[81].start |
435.96284375 |
| transcript.pyannote[81].end |
439.72596875 |
| transcript.pyannote[82].speaker |
SPEAKER_01 |
| transcript.pyannote[82].start |
440.09721875 |
| transcript.pyannote[82].end |
441.26159375 |
| transcript.pyannote[83].speaker |
SPEAKER_01 |
| transcript.pyannote[83].start |
441.46409375 |
| transcript.pyannote[83].end |
460.56659375 |
| transcript.pyannote[84].speaker |
SPEAKER_00 |
| transcript.pyannote[84].start |
451.63971875 |
| transcript.pyannote[84].end |
452.16284375 |
| transcript.pyannote[85].speaker |
SPEAKER_00 |
| transcript.pyannote[85].start |
460.34721875 |
| transcript.pyannote[85].end |
461.84909375 |
| transcript.pyannote[86].speaker |
SPEAKER_01 |
| transcript.pyannote[86].start |
460.85346875 |
| transcript.pyannote[86].end |
461.07284375 |
| transcript.pyannote[87].speaker |
SPEAKER_01 |
| transcript.pyannote[87].start |
461.49471875 |
| transcript.pyannote[87].end |
464.61659375 |
| transcript.pyannote[88].speaker |
SPEAKER_01 |
| transcript.pyannote[88].start |
465.02159375 |
| transcript.pyannote[88].end |
469.88159375 |
| transcript.pyannote[89].speaker |
SPEAKER_00 |
| transcript.pyannote[89].start |
468.76784375 |
| transcript.pyannote[89].end |
474.08346875 |
| transcript.pyannote[90].speaker |
SPEAKER_01 |
| transcript.pyannote[90].start |
470.87721875 |
| transcript.pyannote[90].end |
471.14721875 |
| transcript.pyannote[91].speaker |
SPEAKER_01 |
| transcript.pyannote[91].start |
471.85596875 |
| transcript.pyannote[91].end |
472.44659375 |
| transcript.pyannote[92].speaker |
SPEAKER_01 |
| transcript.pyannote[92].start |
473.29034375 |
| transcript.pyannote[92].end |
476.44596875 |
| transcript.pyannote[93].speaker |
SPEAKER_00 |
| transcript.pyannote[93].start |
476.15909375 |
| transcript.pyannote[93].end |
476.93534375 |
| transcript.pyannote[94].speaker |
SPEAKER_01 |
| transcript.pyannote[94].start |
476.86784375 |
| transcript.pyannote[94].end |
480.29346875 |
| transcript.pyannote[95].speaker |
SPEAKER_01 |
| transcript.pyannote[95].start |
480.34409375 |
| transcript.pyannote[95].end |
480.41159375 |
| transcript.pyannote[96].speaker |
SPEAKER_00 |
| transcript.pyannote[96].start |
480.41159375 |
| transcript.pyannote[96].end |
480.69846875 |
| transcript.pyannote[97].speaker |
SPEAKER_01 |
| transcript.pyannote[97].start |
480.69846875 |
| transcript.pyannote[97].end |
481.15409375 |
| transcript.pyannote[98].speaker |
SPEAKER_01 |
| transcript.pyannote[98].start |
481.39034375 |
| transcript.pyannote[98].end |
482.03159375 |
| transcript.whisperx[0].start |
0.029 |
| transcript.whisperx[0].end |
0.809 |
| transcript.whisperx[0].text |
謝謝主席 我想要請我們的劉主委請主委謝謝委員 |
| transcript.whisperx[1].start |
23.82 |
| transcript.whisperx[1].end |
34.726 |
| transcript.whisperx[1].text |
主委好我想請問就是國發會未來你每年要投入多少錢去培養AI的人才以及 |
| transcript.whisperx[2].start |
35.885 |
| transcript.whisperx[2].end |
65.225 |
| transcript.whisperx[2].text |
我們現在雖然說是AI的人才可是在很多的方面例如我們那天在審查的這個個資保護那很多的企業甚至是公部門都需要相關的人才未來國發會要怎麼樣子去規劃現在大家都面臨到這個相關的資訊人才也好在 |
| transcript.whisperx[3].start |
66.045 |
| transcript.whisperx[3].end |
74.544 |
| transcript.whisperx[3].text |
某部分可能偏鄉或者是中小企業都面臨到無法取材的這樣子的窘境怎麼樣解決 |
| transcript.whisperx[4].start |
75.769 |
| transcript.whisperx[4].end |
101.819 |
| transcript.whisperx[4].text |
就AI人才我们在之前有做过统计那我们相关的数位科技人才从学校来讲S10的部分可以有六万七千人左右的毕业生那另外我们会加上速发部经济部跟国科会的在那个转职上面的社会教育的部分那那个时候我们统计下来有将近十万人一年 |
| transcript.whisperx[5].start |
102.639 |
| transcript.whisperx[5].end |
129.473 |
| transcript.whisperx[5].text |
那現在那是在既有預算下那最近經濟部又提出來他們有一個20萬人的AI人才培育計畫那他們希望是在環球科大這有一個計畫所以我們現在積極的在這個部分去佈建更多的人才那我們在新的AI實像計畫裡面我們在人才上面我們也重新定調在未來到40年之前我們會增加50萬以上的人才出來 |
| transcript.whisperx[6].start |
130.473 |
| transcript.whisperx[6].end |
148.002 |
| transcript.whisperx[6].text |
你確定有50萬嗎那為什麼到現在為止最基礎的資訊人才甚至在企業裡面要防各資要保護各資的相關的人才以及在政府部門我們都還有匱乏的這樣子的情況那怎麼樣達成這個目標 |
| transcript.whisperx[7].start |
151.644 |
| transcript.whisperx[7].end |
176.572 |
| transcript.whisperx[7].text |
因為這幾乎大概是我過去十幾年的生涯當數位產業在蓬勃發展的時候跟需求大量增加的時候其實人才的培育一定會跟不上企業需求的變化我們過去就只能做的事情就是盡量第一個我們盡量培育內部的人才第二個我們吸引外部的人才進來協助所以這幾條路線都在進行中 |
| transcript.whisperx[8].start |
177.492 |
| transcript.whisperx[8].end |
193.921 |
| transcript.whisperx[8].text |
所以包括現在有一些外資進來的時候經濟部也會要求他們也能夠帶進一半的人才那有的就先答應了20%那答應的人才之後呢也是要從各國找進來因為不容易像我們最近協助一家企業他從七個國家找進人來 |
| transcript.whisperx[9].start |
196.522 |
| transcript.whisperx[9].end |
211.692 |
| transcript.whisperx[9].text |
那我們就協助他們辦到他們的薪資如果能達到金卡的16萬的標準那我們也會協助他用金卡來做所以我們最近都在做那但是如果這次的修法能夠更開放的話會更容易讓大家知道這是高階的那 |
| transcript.whisperx[10].start |
212.992 |
| transcript.whisperx[10].end |
231.419 |
| transcript.whisperx[10].text |
問題是在某一些中小企業的部分還是沒有辦法對這些人才不管是AI的也好甚至是比較資訊的或者是在資訊設備上面的這樣子的人才都有缺乏的情況 |
| transcript.whisperx[11].start |
232.699 |
| transcript.whisperx[11].end |
247.653 |
| transcript.whisperx[11].text |
對 現在我們在我們其實有很多這個數位教育就是協助非數位科系的可以轉那目前也蠻多那有多少人這數量我們可能跟各部位收集之後跟委員報告了 |
| transcript.whisperx[12].start |
248.273 |
| transcript.whisperx[12].end |
272.886 |
| transcript.whisperx[12].text |
是不是能夠盡快因為要讓所有部會了解而且即便是有這樣子的人才我們有沒有辦法能夠就是幫他們媒合到適合的企業因為現在中小企業甚至比較偏鄉的企業都沒有辦法來獲取他們所需要的資訊人員我現在只是說資訊人員更何況未來如果是高階的AI人員 |
| transcript.whisperx[13].start |
277.628 |
| transcript.whisperx[13].end |
297.855 |
| transcript.whisperx[13].text |
那你的AI人才,我看到你的AI新十大建设的草案里面,你说一年要花1500亿去培训人才吗?这个是结合到我们在创新创业投资,在总统的这个政见里面,他希望能够带动国内投资量人。 |
| transcript.whisperx[14].start |
298.835 |
| transcript.whisperx[14].end |
325.937 |
| transcript.whisperx[14].text |
達到一年1500億所以不是單指人才的培訓不是人才的培訓我們我們有另外一個計劃我們是在額外增加50萬人的AI人才的計劃所以1500億這個部分是指創業創新而不是培養人才因為我要知道說如果1500億是培養人才到底能多少出來譬如說舉例我們現在有100億放進在這個AI的 |
| transcript.whisperx[15].start |
326.717 |
| transcript.whisperx[15].end |
345.607 |
| transcript.whisperx[15].text |
新創上面那我們在100億在創新在綠領這個綠色創新的部分那我們最近也會有100億放進到機器人創新部分大概屬於像這樣的一個計畫那包括我們最近會有創新創業這個創業競賽那這些都是在希望能夠帶動跟協助這個產業的發展還有新創的發展 |
| transcript.whisperx[16].start |
350.669 |
| transcript.whisperx[16].end |
371.635 |
| transcript.whisperx[16].text |
未來我有看到你們要推動智慧交通智慧城市等等我們希望大家可以在全民智慧城市裡面發展你們到底規劃的如何因為我們知道說未來一定是高齡化的一個現象像美國已經有Wemo有Robotex等等的這樣子的情況對於中南部的 |
| transcript.whisperx[17].start |
372.395 |
| transcript.whisperx[17].end |
389.807 |
| transcript.whisperx[17].text |
一個民眾來說他的就是說他的交通系統沒有辦法像六都有這樣子比較便捷的這樣公共運輸那你到了中南部當現在有產生了高齡化的駕駛的問題的時候你說請他們去做公共運輸 |
| transcript.whisperx[18].start |
393.47 |
| transcript.whisperx[18].end |
420.538 |
| transcript.whisperx[18].text |
可是你往中南部走嘛是不是你知道說中南部怎麼會有辦法有便捷的大眾運輸那未來如何解決這個問題當你在說智慧交通的時候我想要請問我們的現在的路況有沒有辦法符合智慧交通的情況以及未來我們怎麼樣子解決這樣子一個 |
| transcript.whisperx[19].start |
422.099 |
| transcript.whisperx[19].end |
432.973 |
| transcript.whisperx[19].text |
大家如果不要大家沒有辦法開車高齡的長者沒有辦法開車你怎麼樣給予他們便捷的大眾運輸系統在中南部 |
| transcript.whisperx[20].start |
434.045 |
| transcript.whisperx[20].end |
455.942 |
| transcript.whisperx[20].text |
这样的情况这怎么改善我想委员提的是一个非常好的议题的确在农村大家会有交通不便性的问题我们会把这个问题反映到负责整个智慧生活圈的国科会然后它会搭在我们数位国家2.0的方案里面 |
| transcript.whisperx[21].start |
456.562 |
| transcript.whisperx[21].end |
481.033 |
| transcript.whisperx[21].text |
去实施这个智慧交通的部分所以那是国会会负责对但是我会把这个讯息跟国会会分享一下因为这个的确在如果我们待过乡下都知道这真的是在中南部非常困难非常困难也带需要解决的问题因为很多的村庄连大众交通工具都没有根本都没有没有连公车都没有所以我们得重视这样的问题好谢谢好谢谢 |