IVOD_ID |
158869 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/158869 |
日期 |
2025-01-15 |
會議資料.會議代碼 |
聯席會議-11-2-19,20-1 |
會議資料.會議代碼:str |
第11屆第2會期經濟、財政兩委員會第1次聯席會議 |
會議資料.屆 |
11 |
會議資料.會期 |
2 |
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] |
20 |
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] |
財政委員會 |
會議資料.標題 |
第11屆第2會期經濟、財政兩委員會第1次聯席會議 |
影片種類 |
Clip |
開始時間 |
2025-01-15T09:35:25+08:00 |
結束時間 |
2025-01-15T09:42:13+08:00 |
影片長度 |
00:06:48 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/427ddbb1724b1d1a23f2bba758689d0e5a45ebd5c2e753183641ee913381949debd2ef2fddbaddb65ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
郭國文 |
委員發言時間 |
09:35:25 - 09:42:13 |
會議時間 |
2025-01-15T09:00:00+08:00 |
會議名稱 |
立法院第11屆第2會期經濟、財政兩委員會第1次聯席會議(事由:審查:
一、行政院函請審議「產業創新條例部分條文修正草案」案。
二、本院委員葛如鈞等16人擬具「產業創新條例第十條之一及第十七條之一條文修正草案」案。
三、本院委員林岱樺等18人擬具「產業創新條例第十條之一及第十七條之一條文修正草案」案。
四、本院委員楊瓊瓔等29人擬具「產業創新條例第十條之一及第七十二條條文修正草案」案。
五、本院委員何欣純等23人擬具「產業創新條例第十條之一條文修正草案」案。
六、本院委員邱議瑩等16人擬具「產業創新條例第十條之一及第七十二條條文修正草案」案。
七、本院委員蔡其昌等18人擬具「產業創新條例第十條之一及第七十二條條文修正草案」案。
八、本院台灣民眾黨黨團擬具「產業創新條例第十條之一條文修正草案」案。
九、本院委員謝衣鳯等16人擬具「產業創新條例第十條之一及第七十二條條文修正草案」案。
十、本院委員邱志偉等20人擬具「產業創新條例部分條文修正草案」案。
十一、本院委員鄭正鈐等19人擬具「產業創新條例第十條之一條文修正草案」案。
(第一案及第十一案如未接獲議事處來函,則不予審查)
【1月15日及16日兩天一次會】) |
transcript.pyannote[0].speaker |
SPEAKER_01 |
transcript.pyannote[0].start |
11.65784375 |
transcript.pyannote[0].end |
12.23159375 |
transcript.pyannote[1].speaker |
SPEAKER_01 |
transcript.pyannote[1].start |
12.45096875 |
transcript.pyannote[1].end |
16.72034375 |
transcript.pyannote[2].speaker |
SPEAKER_00 |
transcript.pyannote[2].start |
14.02034375 |
transcript.pyannote[2].end |
15.97784375 |
transcript.pyannote[3].speaker |
SPEAKER_01 |
transcript.pyannote[3].start |
20.50034375 |
transcript.pyannote[3].end |
21.58034375 |
transcript.pyannote[4].speaker |
SPEAKER_01 |
transcript.pyannote[4].start |
21.86721875 |
transcript.pyannote[4].end |
65.30346875 |
transcript.pyannote[5].speaker |
SPEAKER_02 |
transcript.pyannote[5].start |
22.30596875 |
transcript.pyannote[5].end |
22.35659375 |
transcript.pyannote[6].speaker |
SPEAKER_00 |
transcript.pyannote[6].start |
22.35659375 |
transcript.pyannote[6].end |
22.37346875 |
transcript.pyannote[7].speaker |
SPEAKER_02 |
transcript.pyannote[7].start |
22.37346875 |
transcript.pyannote[7].end |
22.57596875 |
transcript.pyannote[8].speaker |
SPEAKER_00 |
transcript.pyannote[8].start |
22.57596875 |
transcript.pyannote[8].end |
22.89659375 |
transcript.pyannote[9].speaker |
SPEAKER_02 |
transcript.pyannote[9].start |
25.96784375 |
transcript.pyannote[9].end |
26.92971875 |
transcript.pyannote[10].speaker |
SPEAKER_00 |
transcript.pyannote[10].start |
37.22346875 |
transcript.pyannote[10].end |
37.25721875 |
transcript.pyannote[11].speaker |
SPEAKER_00 |
transcript.pyannote[11].start |
44.32784375 |
transcript.pyannote[11].end |
44.34471875 |
transcript.pyannote[12].speaker |
SPEAKER_01 |
transcript.pyannote[12].start |
65.42159375 |
transcript.pyannote[12].end |
65.75909375 |
transcript.pyannote[13].speaker |
SPEAKER_02 |
transcript.pyannote[13].start |
65.75909375 |
transcript.pyannote[13].end |
65.94471875 |
transcript.pyannote[14].speaker |
SPEAKER_01 |
transcript.pyannote[14].start |
65.94471875 |
transcript.pyannote[14].end |
65.97846875 |
transcript.pyannote[15].speaker |
SPEAKER_02 |
transcript.pyannote[15].start |
65.97846875 |
transcript.pyannote[15].end |
66.09659375 |
transcript.pyannote[16].speaker |
SPEAKER_02 |
transcript.pyannote[16].start |
66.33284375 |
transcript.pyannote[16].end |
66.51846875 |
transcript.pyannote[17].speaker |
SPEAKER_02 |
transcript.pyannote[17].start |
67.04159375 |
transcript.pyannote[17].end |
69.33659375 |
transcript.pyannote[18].speaker |
SPEAKER_02 |
transcript.pyannote[18].start |
69.62346875 |
transcript.pyannote[18].end |
79.24221875 |
transcript.pyannote[19].speaker |
SPEAKER_01 |
transcript.pyannote[19].start |
72.72846875 |
transcript.pyannote[19].end |
73.84221875 |
transcript.pyannote[20].speaker |
SPEAKER_00 |
transcript.pyannote[20].start |
73.84221875 |
transcript.pyannote[20].end |
73.85909375 |
transcript.pyannote[21].speaker |
SPEAKER_01 |
transcript.pyannote[21].start |
73.85909375 |
transcript.pyannote[21].end |
73.87596875 |
transcript.pyannote[22].speaker |
SPEAKER_01 |
transcript.pyannote[22].start |
76.01909375 |
transcript.pyannote[22].end |
76.27221875 |
transcript.pyannote[23].speaker |
SPEAKER_01 |
transcript.pyannote[23].start |
77.92596875 |
transcript.pyannote[23].end |
78.28034375 |
transcript.pyannote[24].speaker |
SPEAKER_01 |
transcript.pyannote[24].start |
79.24221875 |
transcript.pyannote[24].end |
83.44409375 |
transcript.pyannote[25].speaker |
SPEAKER_02 |
transcript.pyannote[25].start |
80.30534375 |
transcript.pyannote[25].end |
81.30096875 |
transcript.pyannote[26].speaker |
SPEAKER_02 |
transcript.pyannote[26].start |
82.66784375 |
transcript.pyannote[26].end |
86.39721875 |
transcript.pyannote[27].speaker |
SPEAKER_01 |
transcript.pyannote[27].start |
84.92909375 |
transcript.pyannote[27].end |
85.19909375 |
transcript.pyannote[28].speaker |
SPEAKER_01 |
transcript.pyannote[28].start |
85.50284375 |
transcript.pyannote[28].end |
123.03284375 |
transcript.pyannote[29].speaker |
SPEAKER_00 |
transcript.pyannote[29].start |
101.34846875 |
transcript.pyannote[29].end |
101.77034375 |
transcript.pyannote[30].speaker |
SPEAKER_02 |
transcript.pyannote[30].start |
121.73346875 |
transcript.pyannote[30].end |
122.00346875 |
transcript.pyannote[31].speaker |
SPEAKER_00 |
transcript.pyannote[31].start |
122.00346875 |
transcript.pyannote[31].end |
122.02034375 |
transcript.pyannote[32].speaker |
SPEAKER_01 |
transcript.pyannote[32].start |
123.38721875 |
transcript.pyannote[32].end |
129.83346875 |
transcript.pyannote[33].speaker |
SPEAKER_01 |
transcript.pyannote[33].start |
130.57596875 |
transcript.pyannote[33].end |
140.24534375 |
transcript.pyannote[34].speaker |
SPEAKER_02 |
transcript.pyannote[34].start |
139.41846875 |
transcript.pyannote[34].end |
141.32534375 |
transcript.pyannote[35].speaker |
SPEAKER_01 |
transcript.pyannote[35].start |
141.19034375 |
transcript.pyannote[35].end |
146.28659375 |
transcript.pyannote[36].speaker |
SPEAKER_00 |
transcript.pyannote[36].start |
145.89846875 |
transcript.pyannote[36].end |
146.01659375 |
transcript.pyannote[37].speaker |
SPEAKER_02 |
transcript.pyannote[37].start |
146.01659375 |
transcript.pyannote[37].end |
146.26971875 |
transcript.pyannote[38].speaker |
SPEAKER_02 |
transcript.pyannote[38].start |
146.28659375 |
transcript.pyannote[38].end |
146.32034375 |
transcript.pyannote[39].speaker |
SPEAKER_02 |
transcript.pyannote[39].start |
146.45534375 |
transcript.pyannote[39].end |
148.21034375 |
transcript.pyannote[40].speaker |
SPEAKER_00 |
transcript.pyannote[40].start |
147.88971875 |
transcript.pyannote[40].end |
148.27784375 |
transcript.pyannote[41].speaker |
SPEAKER_01 |
transcript.pyannote[41].start |
148.21034375 |
transcript.pyannote[41].end |
148.75034375 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
149.40846875 |
transcript.pyannote[42].end |
149.59409375 |
transcript.pyannote[43].speaker |
SPEAKER_00 |
transcript.pyannote[43].start |
149.89784375 |
transcript.pyannote[43].end |
155.87159375 |
transcript.pyannote[44].speaker |
SPEAKER_00 |
transcript.pyannote[44].start |
157.42409375 |
transcript.pyannote[44].end |
157.44096875 |
transcript.pyannote[45].speaker |
SPEAKER_01 |
transcript.pyannote[45].start |
157.44096875 |
transcript.pyannote[45].end |
158.20034375 |
transcript.pyannote[46].speaker |
SPEAKER_01 |
transcript.pyannote[46].start |
159.33096875 |
transcript.pyannote[46].end |
166.90784375 |
transcript.pyannote[47].speaker |
SPEAKER_01 |
transcript.pyannote[47].start |
167.41409375 |
transcript.pyannote[47].end |
168.59534375 |
transcript.pyannote[48].speaker |
SPEAKER_01 |
transcript.pyannote[48].start |
169.57409375 |
transcript.pyannote[48].end |
170.48534375 |
transcript.pyannote[49].speaker |
SPEAKER_02 |
transcript.pyannote[49].start |
171.09284375 |
transcript.pyannote[49].end |
183.20909375 |
transcript.pyannote[50].speaker |
SPEAKER_01 |
transcript.pyannote[50].start |
181.79159375 |
transcript.pyannote[50].end |
194.00909375 |
transcript.pyannote[51].speaker |
SPEAKER_01 |
transcript.pyannote[51].start |
194.31284375 |
transcript.pyannote[51].end |
203.08784375 |
transcript.pyannote[52].speaker |
SPEAKER_02 |
transcript.pyannote[52].start |
200.48909375 |
transcript.pyannote[52].end |
200.53971875 |
transcript.pyannote[53].speaker |
SPEAKER_00 |
transcript.pyannote[53].start |
201.09659375 |
transcript.pyannote[53].end |
201.14721875 |
transcript.pyannote[54].speaker |
SPEAKER_01 |
transcript.pyannote[54].start |
203.34096875 |
transcript.pyannote[54].end |
204.15096875 |
transcript.pyannote[55].speaker |
SPEAKER_01 |
transcript.pyannote[55].start |
204.33659375 |
transcript.pyannote[55].end |
204.77534375 |
transcript.pyannote[56].speaker |
SPEAKER_01 |
transcript.pyannote[56].start |
205.14659375 |
transcript.pyannote[56].end |
205.68659375 |
transcript.pyannote[57].speaker |
SPEAKER_01 |
transcript.pyannote[57].start |
206.39534375 |
transcript.pyannote[57].end |
209.28096875 |
transcript.pyannote[58].speaker |
SPEAKER_01 |
transcript.pyannote[58].start |
211.28909375 |
transcript.pyannote[58].end |
212.28471875 |
transcript.pyannote[59].speaker |
SPEAKER_02 |
transcript.pyannote[59].start |
213.24659375 |
transcript.pyannote[59].end |
213.70221875 |
transcript.pyannote[60].speaker |
SPEAKER_01 |
transcript.pyannote[60].start |
213.70221875 |
transcript.pyannote[60].end |
215.55846875 |
transcript.pyannote[61].speaker |
SPEAKER_02 |
transcript.pyannote[61].start |
215.55846875 |
transcript.pyannote[61].end |
215.59221875 |
transcript.pyannote[62].speaker |
SPEAKER_01 |
transcript.pyannote[62].start |
215.59221875 |
transcript.pyannote[62].end |
215.79471875 |
transcript.pyannote[63].speaker |
SPEAKER_01 |
transcript.pyannote[63].start |
215.98034375 |
transcript.pyannote[63].end |
218.78159375 |
transcript.pyannote[64].speaker |
SPEAKER_01 |
transcript.pyannote[64].start |
219.03471875 |
transcript.pyannote[64].end |
223.55721875 |
transcript.pyannote[65].speaker |
SPEAKER_01 |
transcript.pyannote[65].start |
223.94534375 |
transcript.pyannote[65].end |
226.32471875 |
transcript.pyannote[66].speaker |
SPEAKER_01 |
transcript.pyannote[66].start |
226.52721875 |
transcript.pyannote[66].end |
227.91096875 |
transcript.pyannote[67].speaker |
SPEAKER_01 |
transcript.pyannote[67].start |
228.18096875 |
transcript.pyannote[67].end |
232.33221875 |
transcript.pyannote[68].speaker |
SPEAKER_02 |
transcript.pyannote[68].start |
232.41659375 |
transcript.pyannote[68].end |
234.88034375 |
transcript.pyannote[69].speaker |
SPEAKER_00 |
transcript.pyannote[69].start |
235.36971875 |
transcript.pyannote[69].end |
238.05284375 |
transcript.pyannote[70].speaker |
SPEAKER_00 |
transcript.pyannote[70].start |
238.30596875 |
transcript.pyannote[70].end |
239.82471875 |
transcript.pyannote[71].speaker |
SPEAKER_00 |
transcript.pyannote[71].start |
240.17909375 |
transcript.pyannote[71].end |
241.52909375 |
transcript.pyannote[72].speaker |
SPEAKER_00 |
transcript.pyannote[72].start |
241.68096875 |
transcript.pyannote[72].end |
258.72471875 |
transcript.pyannote[73].speaker |
SPEAKER_01 |
transcript.pyannote[73].start |
253.91534375 |
transcript.pyannote[73].end |
253.94909375 |
transcript.pyannote[74].speaker |
SPEAKER_01 |
transcript.pyannote[74].start |
253.99971875 |
transcript.pyannote[74].end |
254.05034375 |
transcript.pyannote[75].speaker |
SPEAKER_00 |
transcript.pyannote[75].start |
259.04534375 |
transcript.pyannote[75].end |
260.15909375 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
260.78346875 |
transcript.pyannote[76].end |
261.47534375 |
transcript.pyannote[77].speaker |
SPEAKER_00 |
transcript.pyannote[77].start |
261.86346875 |
transcript.pyannote[77].end |
262.53846875 |
transcript.pyannote[78].speaker |
SPEAKER_00 |
transcript.pyannote[78].start |
263.46659375 |
transcript.pyannote[78].end |
267.34784375 |
transcript.pyannote[79].speaker |
SPEAKER_01 |
transcript.pyannote[79].start |
267.34784375 |
transcript.pyannote[79].end |
267.38159375 |
transcript.pyannote[80].speaker |
SPEAKER_00 |
transcript.pyannote[80].start |
267.71909375 |
transcript.pyannote[80].end |
268.96784375 |
transcript.pyannote[81].speaker |
SPEAKER_01 |
transcript.pyannote[81].start |
268.96784375 |
transcript.pyannote[81].end |
274.78971875 |
transcript.pyannote[82].speaker |
SPEAKER_01 |
transcript.pyannote[82].start |
275.12721875 |
transcript.pyannote[82].end |
275.63346875 |
transcript.pyannote[83].speaker |
SPEAKER_01 |
transcript.pyannote[83].start |
276.00471875 |
transcript.pyannote[83].end |
276.62909375 |
transcript.pyannote[84].speaker |
SPEAKER_01 |
transcript.pyannote[84].start |
277.20284375 |
transcript.pyannote[84].end |
278.36721875 |
transcript.pyannote[85].speaker |
SPEAKER_01 |
transcript.pyannote[85].start |
278.87346875 |
transcript.pyannote[85].end |
279.54846875 |
transcript.pyannote[86].speaker |
SPEAKER_01 |
transcript.pyannote[86].start |
280.08846875 |
transcript.pyannote[86].end |
280.76346875 |
transcript.pyannote[87].speaker |
SPEAKER_01 |
transcript.pyannote[87].start |
281.40471875 |
transcript.pyannote[87].end |
283.36221875 |
transcript.pyannote[88].speaker |
SPEAKER_01 |
transcript.pyannote[88].start |
284.15534375 |
transcript.pyannote[88].end |
284.83034375 |
transcript.pyannote[89].speaker |
SPEAKER_01 |
transcript.pyannote[89].start |
286.80471875 |
transcript.pyannote[89].end |
289.84221875 |
transcript.pyannote[90].speaker |
SPEAKER_02 |
transcript.pyannote[90].start |
288.74534375 |
transcript.pyannote[90].end |
291.54659375 |
transcript.pyannote[91].speaker |
SPEAKER_01 |
transcript.pyannote[91].start |
290.39909375 |
transcript.pyannote[91].end |
294.76971875 |
transcript.pyannote[92].speaker |
SPEAKER_02 |
transcript.pyannote[92].start |
294.65159375 |
transcript.pyannote[92].end |
296.47409375 |
transcript.pyannote[93].speaker |
SPEAKER_01 |
transcript.pyannote[93].start |
296.47409375 |
transcript.pyannote[93].end |
296.94659375 |
transcript.pyannote[94].speaker |
SPEAKER_02 |
transcript.pyannote[94].start |
296.49096875 |
transcript.pyannote[94].end |
297.50346875 |
transcript.pyannote[95].speaker |
SPEAKER_01 |
transcript.pyannote[95].start |
297.50346875 |
transcript.pyannote[95].end |
307.13909375 |
transcript.pyannote[96].speaker |
SPEAKER_02 |
transcript.pyannote[96].start |
307.13909375 |
transcript.pyannote[96].end |
307.49346875 |
transcript.pyannote[97].speaker |
SPEAKER_01 |
transcript.pyannote[97].start |
307.94909375 |
transcript.pyannote[97].end |
308.06721875 |
transcript.pyannote[98].speaker |
SPEAKER_02 |
transcript.pyannote[98].start |
308.06721875 |
transcript.pyannote[98].end |
308.11784375 |
transcript.pyannote[99].speaker |
SPEAKER_01 |
transcript.pyannote[99].start |
308.11784375 |
transcript.pyannote[99].end |
312.80909375 |
transcript.pyannote[100].speaker |
SPEAKER_02 |
transcript.pyannote[100].start |
308.21909375 |
transcript.pyannote[100].end |
308.91096875 |
transcript.pyannote[101].speaker |
SPEAKER_02 |
transcript.pyannote[101].start |
313.04534375 |
transcript.pyannote[101].end |
316.52159375 |
transcript.pyannote[102].speaker |
SPEAKER_02 |
transcript.pyannote[102].start |
316.57221875 |
transcript.pyannote[102].end |
318.71534375 |
transcript.pyannote[103].speaker |
SPEAKER_02 |
transcript.pyannote[103].start |
319.39034375 |
transcript.pyannote[103].end |
319.44096875 |
transcript.pyannote[104].speaker |
SPEAKER_01 |
transcript.pyannote[104].start |
319.44096875 |
transcript.pyannote[104].end |
319.47471875 |
transcript.pyannote[105].speaker |
SPEAKER_02 |
transcript.pyannote[105].start |
319.47471875 |
transcript.pyannote[105].end |
319.49159375 |
transcript.pyannote[106].speaker |
SPEAKER_01 |
transcript.pyannote[106].start |
319.49159375 |
transcript.pyannote[106].end |
319.55909375 |
transcript.pyannote[107].speaker |
SPEAKER_02 |
transcript.pyannote[107].start |
319.55909375 |
transcript.pyannote[107].end |
320.03159375 |
transcript.pyannote[108].speaker |
SPEAKER_01 |
transcript.pyannote[108].start |
320.03159375 |
transcript.pyannote[108].end |
321.60096875 |
transcript.pyannote[109].speaker |
SPEAKER_02 |
transcript.pyannote[109].start |
321.60096875 |
transcript.pyannote[109].end |
327.72659375 |
transcript.pyannote[110].speaker |
SPEAKER_02 |
transcript.pyannote[110].start |
328.28346875 |
transcript.pyannote[110].end |
329.02596875 |
transcript.pyannote[111].speaker |
SPEAKER_01 |
transcript.pyannote[111].start |
329.02596875 |
transcript.pyannote[111].end |
336.11346875 |
transcript.pyannote[112].speaker |
SPEAKER_02 |
transcript.pyannote[112].start |
336.02909375 |
transcript.pyannote[112].end |
347.77409375 |
transcript.pyannote[113].speaker |
SPEAKER_01 |
transcript.pyannote[113].start |
347.01471875 |
transcript.pyannote[113].end |
362.70846875 |
transcript.pyannote[114].speaker |
SPEAKER_02 |
transcript.pyannote[114].start |
350.22096875 |
transcript.pyannote[114].end |
351.46971875 |
transcript.pyannote[115].speaker |
SPEAKER_02 |
transcript.pyannote[115].start |
352.00971875 |
transcript.pyannote[115].end |
352.98846875 |
transcript.pyannote[116].speaker |
SPEAKER_01 |
transcript.pyannote[116].start |
363.41721875 |
transcript.pyannote[116].end |
368.44596875 |
transcript.pyannote[117].speaker |
SPEAKER_02 |
transcript.pyannote[117].start |
366.99471875 |
transcript.pyannote[117].end |
370.58909375 |
transcript.pyannote[118].speaker |
SPEAKER_01 |
transcript.pyannote[118].start |
370.21784375 |
transcript.pyannote[118].end |
377.18721875 |
transcript.pyannote[119].speaker |
SPEAKER_01 |
transcript.pyannote[119].start |
377.54159375 |
transcript.pyannote[119].end |
382.43534375 |
transcript.pyannote[120].speaker |
SPEAKER_01 |
transcript.pyannote[120].start |
382.82346875 |
transcript.pyannote[120].end |
386.29971875 |
transcript.pyannote[121].speaker |
SPEAKER_01 |
transcript.pyannote[121].start |
386.72159375 |
transcript.pyannote[121].end |
386.92409375 |
transcript.pyannote[122].speaker |
SPEAKER_01 |
transcript.pyannote[122].start |
388.67909375 |
transcript.pyannote[122].end |
388.83096875 |
transcript.pyannote[123].speaker |
SPEAKER_01 |
transcript.pyannote[123].start |
389.08409375 |
transcript.pyannote[123].end |
389.96159375 |
transcript.pyannote[124].speaker |
SPEAKER_02 |
transcript.pyannote[124].start |
390.19784375 |
transcript.pyannote[124].end |
390.94034375 |
transcript.pyannote[125].speaker |
SPEAKER_01 |
transcript.pyannote[125].start |
391.24409375 |
transcript.pyannote[125].end |
391.75034375 |
transcript.pyannote[126].speaker |
SPEAKER_01 |
transcript.pyannote[126].start |
392.07096875 |
transcript.pyannote[126].end |
392.96534375 |
transcript.pyannote[127].speaker |
SPEAKER_01 |
transcript.pyannote[127].start |
394.34909375 |
transcript.pyannote[127].end |
395.54721875 |
transcript.pyannote[128].speaker |
SPEAKER_01 |
transcript.pyannote[128].start |
396.32346875 |
transcript.pyannote[128].end |
398.11221875 |
transcript.pyannote[129].speaker |
SPEAKER_01 |
transcript.pyannote[129].start |
398.24721875 |
transcript.pyannote[129].end |
406.60034375 |
transcript.pyannote[130].speaker |
SPEAKER_00 |
transcript.pyannote[130].start |
401.67284375 |
transcript.pyannote[130].end |
401.70659375 |
transcript.pyannote[131].speaker |
SPEAKER_00 |
transcript.pyannote[131].start |
402.04409375 |
transcript.pyannote[131].end |
402.19596875 |
transcript.pyannote[132].speaker |
SPEAKER_00 |
transcript.pyannote[132].start |
405.60471875 |
transcript.pyannote[132].end |
406.02659375 |
transcript.pyannote[133].speaker |
SPEAKER_01 |
transcript.pyannote[133].start |
406.75221875 |
transcript.pyannote[133].end |
406.97159375 |
transcript.pyannote[134].speaker |
SPEAKER_00 |
transcript.pyannote[134].start |
406.97159375 |
transcript.pyannote[134].end |
407.03909375 |
transcript.pyannote[135].speaker |
SPEAKER_01 |
transcript.pyannote[135].start |
407.17409375 |
transcript.pyannote[135].end |
408.47346875 |
transcript.whisperx[0].start |
11.888 |
transcript.whisperx[0].end |
14.996 |
transcript.whisperx[0].text |
謝謝主席有請經濟部的連次還有財務部理事長財務部理事長 |
transcript.whisperx[1].start |
20.543 |
transcript.whisperx[1].end |
43.685 |
transcript.whisperx[1].text |
我先請蓮池喔蓮池你這麼早退休是國家的損失啊沒有啦沒有啦蓮池那個今天的這個主題當中的稅市支出當中的報告我看到又發了投資金額智慧機器還佔440億但是新增的部分的AI只佔了72億啊老實講我是覺得很誇張因為我國會跟國科會已經投入 |
transcript.whisperx[2].start |
43.965 |
transcript.whisperx[2].end |
65.886 |
transcript.whisperx[2].text |
百億的這個研發經費預計要帶動這個產業發展再加上行政院說要推動大南方的新矽谷計畫也在台南的沙崙這個建立了AI產業園區那總統甚至說要打造成一個人工智慧島要成為全球的AI的影響力中心我請教一下這72億可以達到這種效果嗎是的 |
transcript.whisperx[3].start |
67.096 |
transcript.whisperx[3].end |
89.422 |
transcript.whisperx[3].text |
那個跟委員報告那個是整個是AI講的你是70而已是購置設備啦設備它誘發出來的效果不是70而已購置設備而已設置設備而已所以說它基本上後面的potential的部分大家有多少啊potential不一樣搞不好會有10倍20倍左右對啊你們要寫清楚啊這要寫出來才有感覺嘛 |
transcript.whisperx[4].start |
90.39 |
transcript.whisperx[4].end |
112.623 |
transcript.whisperx[4].text |
不然你花那麼多國家經費下去然後喊了口號又震天響結果呢導致的結果就72還比這個傳統的智慧晶蟹的部分440億差那麼多另外一個部分川普1月20號要上任那川普要上任的時候你要知道拜登時代我們跟他談了21世紀貿易協議基本上是要走向自由化 |
transcript.whisperx[5].start |
113.143 |
transcript.whisperx[5].end |
129.585 |
transcript.whisperx[5].text |
可是川普呢你也知道他現在對外關稅已經成立一個專責機構也就是說他拉高關稅基本上兩個是相抵觸的我就問你一個問題這21世紀貿易協議我們已經要進入第二階段的深水區包括勞工 環保 農業的部分還走得下去嗎 |
transcript.whisperx[6].start |
131.383 |
transcript.whisperx[6].end |
148.629 |
transcript.whisperx[6].text |
你沒有涉獵到但是你們國貿局底下也是有參與啊你們經濟部會沒有參與嗎會不清楚嗎應該要清楚才對啊怎麼會不可能我查過你們是小組之一嗎回答一下讓得下去嗎你等他上任你現在都沒有評估不會吧 |
transcript.whisperx[7].start |
159.48 |
transcript.whisperx[7].end |
174.034 |
transcript.whisperx[7].text |
還在等所以預期到人家的政策方向是這樣子啦你們現在ING進行中有沒有可能繼續你真的沒有辦法回到本席沒有做一個評估我有點壓抑欸跟委員報告針對川普他的團隊要嚴厲要 |
transcript.whisperx[8].start |
176.896 |
transcript.whisperx[8].end |
200.242 |
transcript.whisperx[8].text |
提升那個關稅這個部分我們是有在做研究說有哪一些廠商或哪一些一個是自由化一個是要提高關稅壁壘一個是走經濟民族主義一個是採取那個自由化的方式完全是不一樣的你怎麼會沒有一個政策判斷呢第一個是這一個第二個他關稅如果提高的話我就問你一個嘛他關稅之所以提高原因是在三半位順利差的部分嘛對不對 |
transcript.whisperx[9].start |
201.142 |
transcript.whisperx[9].end |
211.888 |
transcript.whisperx[9].text |
他認為對他美國國家損失嘛那我就問你啦 強勢我們再算2024年我們對美國的粗糙你知道多少嗎最新的數字 |
transcript.whisperx[10].start |
214.912 |
transcript.whisperx[10].end |
234.247 |
transcript.whisperx[10].text |
649億沒有沒有我現在這邊數字是649億然後你比2023的部分成長了83.5%大幅成長大幅成長喔之前大概300多億而已你看看我們有沒有可能會被針對的對象有沒有可能我們是列在第十幾個 |
transcript.whisperx[11].start |
235.507 |
transcript.whisperx[11].end |
262.399 |
transcript.whisperx[11].text |
報告委員那這個其實是一個所謂一個像我們對中國的出口這我知道啦我們廠商撤回來從我們這邊出口就算我們的啦但是事實上就增加了嘛是報告委員那我們出口到這個美國的產品基本上都是中間品其實是對它經濟發展是非常有利的我們會從這個方面所以你不認為我們會被制裁我們關稅不會被提高你很樂觀很有把握 |
transcript.whisperx[12].start |
263.619 |
transcript.whisperx[12].end |
284.666 |
transcript.whisperx[12].text |
我們會盡量去跟美方去溝通我跟你講人家我們之前在財政委員會央行都有具體的做法他說要平衡這個貿易順利差的部分第一個買武器第二個買農產品第三個買他的天然能源也就是天然氣你們沒有做 |
transcript.whisperx[13].start |
286.917 |
transcript.whisperx[13].end |
312.03 |
transcript.whisperx[13].text |
你們連有做都沒有做都不曉得我都可以查出來了你們之前是澳洲卡達最近美國已經買到他10%了跟美國能源合作這一塊我們有在研擬也在研擬那我就想要請教你嘛央行都提出具體主張那我請問一下經濟部對於這種現象有沒有什麼具體主張嘛那個尤其是你要退休我在問你這個實在沒有意思啊但是你現在還是官員啊 |
transcript.whisperx[14].start |
313.09 |
transcript.whisperx[14].end |
320.38 |
transcript.whisperx[14].text |
跟委員報告那個尤其是那個應該是4月份的有什麼具體做法嗎你總不能要告訴我說1月20號上任債來說5月份的那個美國USA我們會擴大 |
transcript.whisperx[15].start |
328.351 |
transcript.whisperx[15].end |
331.713 |
transcript.whisperx[15].text |
整個投資團會過去具體一點擴大投資團會是什麼擴大你就是等於要買美國的東西買更多一點那這個是除了有購買有投資之外這個是尤其是ICT產業或電動車產業怎麼在美國跟美墨之間怎麼去做一個投資 |
transcript.whisperx[16].start |
347.162 |
transcript.whisperx[16].end |
362.179 |
transcript.whisperx[16].text |
你投資社長當然就不用算出口的金額這是救地的方式好方式就是減除我們這個貿易順差的數字這個我理解但是問題是你直接跟美國買的部分他還比較開心一點你可以跟他買什麼 |
transcript.whisperx[17].start |
363.462 |
transcript.whisperx[17].end |
392.803 |
transcript.whisperx[17].text |
武器不是你管的嘛 農業不是你管的嘛經濟部你管的可以管什麼嘛 能源我們有在研議啦能源 我剛剛說的啊 天然氣能不能不透露一下除了本席說的以外的東西 還有沒有其他的嘛天然氣在我們整個能源政策的佔比是佔50% 天然氣當然重要啊買這個本來就符合我們能源政策 你還有沒有其他的方式我問了這麼久了目前沒有都沒有 目前都沒有 |
transcript.whisperx[18].start |
394.414 |
transcript.whisperx[18].end |
405.43 |
transcript.whisperx[18].text |
目前都沒有我建議那個次長 退休之前跟部長講一下啦我知道部長很忙啦這個問題是最重要的啦我們很有可能會被鎖定啦謝謝 |