iVOD / 168837

Field Value
IVOD_ID 168837
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/168837
日期 2026-04-24
會議資料.會議代碼 院會-11-5-8
會議資料.會議代碼:str 第11屆第5會期第8次會議
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 院會
會議資料.標題 第11屆第5會期第8次會議
影片種類 Clip
開始時間 2026-04-24T14:30:25+08:00
結束時間 2026-04-24T14:46:13+08:00
影片長度 00:15:48
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6961fddac991000b91ce239d00924caab5a46e9be1b9bc706c6651c59f41735f9240d0f21f4d974d5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 廖偉翔
委員發言時間 14:30:25 - 14:46:13
會議時間 2026-04-24T09:00:00+08:00
會議名稱 第11屆第5會期第8次會議(事由:一、對行政院院長提出施政方針及施政報告繼續質詢。二、同意權之行使事項:本院司法及法制、內政兩委員會報告審查「總統咨,為最高檢察署檢察總長邢泰釗任期於115年5月7日屆滿,茲依法院組織法第66條第2項規定,提名徐錫祥為最高檢察署檢察總長,咨請同意案」案。(5月5日上午)三、審計長列席報告中華民國113年度中央政府總決算審核報告等案審核經過並備諮詢。(5月5日下午)四、4月24日上午9時至10時為國是論壇時間。)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 2.66346875
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 13.75034375
transcript.pyannote[1].end 16.97346875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 17.41221875
transcript.pyannote[2].end 18.82971875
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 29.32596875
transcript.pyannote[3].end 29.88284375
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 30.67596875
transcript.pyannote[4].end 31.30034375
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 31.73909375
transcript.pyannote[5].end 36.93659375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 37.35846875
transcript.pyannote[6].end 37.81409375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 37.89846875
transcript.pyannote[7].end 41.71221875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 42.84284375
transcript.pyannote[8].end 46.58909375
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 46.97721875
transcript.pyannote[9].end 50.47034375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 48.00659375
transcript.pyannote[10].end 48.95159375
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 50.52096875
transcript.pyannote[11].end 51.41534375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 51.82034375
transcript.pyannote[12].end 54.99284375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 55.21221875
transcript.pyannote[13].end 60.71346875
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 61.10159375
transcript.pyannote[14].end 64.69596875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 63.12659375
transcript.pyannote[15].end 63.48096875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 64.89846875
transcript.pyannote[16].end 73.13346875
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 73.13346875
transcript.pyannote[17].end 78.92159375
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 78.97221875
transcript.pyannote[18].end 79.02284375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 79.10721875
transcript.pyannote[19].end 84.00096875
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 84.30471875
transcript.pyannote[20].end 90.12659375
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 90.43034375
transcript.pyannote[21].end 105.73596875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 106.02284375
transcript.pyannote[22].end 110.00534375
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 110.29221875
transcript.pyannote[23].end 111.06846875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 111.38909375
transcript.pyannote[24].end 112.03034375
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 112.08096875
transcript.pyannote[25].end 122.59409375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 122.81346875
transcript.pyannote[26].end 125.73284375
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 126.45846875
transcript.pyannote[27].end 130.00221875
transcript.pyannote[28].speaker SPEAKER_03
transcript.pyannote[28].start 131.30159375
transcript.pyannote[28].end 133.27596875
transcript.pyannote[29].speaker SPEAKER_03
transcript.pyannote[29].start 133.44471875
transcript.pyannote[29].end 135.84096875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 133.47846875
transcript.pyannote[30].end 135.72284375
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 135.84096875
transcript.pyannote[31].end 140.09346875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 140.21159375
transcript.pyannote[32].end 145.40909375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 143.45159375
transcript.pyannote[33].end 143.58659375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 145.79721875
transcript.pyannote[34].end 150.23534375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 149.98221875
transcript.pyannote[35].end 156.10784375
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 155.11221875
transcript.pyannote[36].end 156.76596875
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 157.22159375
transcript.pyannote[37].end 164.22471875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 163.70159375
transcript.pyannote[38].end 164.47784375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 164.47784375
transcript.pyannote[39].end 165.13596875
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 165.13596875
transcript.pyannote[40].end 165.15284375
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 165.15284375
transcript.pyannote[41].end 165.30471875
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 165.30471875
transcript.pyannote[42].end 172.64534375
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 173.01659375
transcript.pyannote[43].end 174.77159375
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 174.82221875
transcript.pyannote[44].end 183.58034375
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 183.83346875
transcript.pyannote[45].end 187.88346875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 188.17034375
transcript.pyannote[46].end 192.60846875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 193.03034375
transcript.pyannote[47].end 195.08909375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 195.25784375
transcript.pyannote[48].end 208.42034375
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 208.94346875
transcript.pyannote[49].end 209.95596875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 210.25971875
transcript.pyannote[50].end 210.98534375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 211.28909375
transcript.pyannote[51].end 214.34346875
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 214.63034375
transcript.pyannote[52].end 216.80721875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 217.00971875
transcript.pyannote[53].end 217.46534375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 217.54971875
transcript.pyannote[54].end 219.96284375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 220.24971875
transcript.pyannote[55].end 237.54659375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 237.71534375
transcript.pyannote[56].end 238.86284375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 239.36909375
transcript.pyannote[57].end 243.80721875
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 244.00971875
transcript.pyannote[58].end 252.00846875
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 251.70471875
transcript.pyannote[59].end 258.60659375
transcript.pyannote[60].speaker SPEAKER_02
transcript.pyannote[60].start 258.87659375
transcript.pyannote[60].end 265.35659375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 263.97284375
transcript.pyannote[61].end 263.98971875
transcript.pyannote[62].speaker SPEAKER_03
transcript.pyannote[62].start 263.98971875
transcript.pyannote[62].end 264.42846875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 264.42846875
transcript.pyannote[63].end 265.79534375
transcript.pyannote[64].speaker SPEAKER_03
transcript.pyannote[64].start 265.35659375
transcript.pyannote[64].end 265.37346875
transcript.pyannote[65].speaker SPEAKER_03
transcript.pyannote[65].start 265.79534375
transcript.pyannote[65].end 274.94159375
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 265.87971875
transcript.pyannote[66].end 266.03159375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 266.03159375
transcript.pyannote[67].end 266.74034375
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 266.74034375
transcript.pyannote[68].end 266.75721875
transcript.pyannote[69].speaker SPEAKER_03
transcript.pyannote[69].start 275.04284375
transcript.pyannote[69].end 278.62034375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 277.32096875
transcript.pyannote[70].end 278.68784375
transcript.pyannote[71].speaker SPEAKER_03
transcript.pyannote[71].start 278.68784375
transcript.pyannote[71].end 278.80596875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 278.80596875
transcript.pyannote[72].end 280.89846875
transcript.pyannote[73].speaker SPEAKER_03
transcript.pyannote[73].start 280.03784375
transcript.pyannote[73].end 280.96596875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 280.96596875
transcript.pyannote[74].end 281.03346875
transcript.pyannote[75].speaker SPEAKER_03
transcript.pyannote[75].start 281.03346875
transcript.pyannote[75].end 281.57346875
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 281.57346875
transcript.pyannote[76].end 285.84284375
transcript.pyannote[77].speaker SPEAKER_03
transcript.pyannote[77].start 281.62409375
transcript.pyannote[77].end 288.27284375
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 287.22659375
transcript.pyannote[78].end 292.17096875
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 292.23846875
transcript.pyannote[79].end 295.83284375
transcript.pyannote[80].speaker SPEAKER_03
transcript.pyannote[80].start 296.89596875
transcript.pyannote[80].end 298.29659375
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 298.29659375
transcript.pyannote[81].end 301.21596875
transcript.pyannote[82].speaker SPEAKER_03
transcript.pyannote[82].start 298.71846875
transcript.pyannote[82].end 299.15721875
transcript.pyannote[83].speaker SPEAKER_03
transcript.pyannote[83].start 299.86596875
transcript.pyannote[83].end 306.53159375
transcript.pyannote[84].speaker SPEAKER_03
transcript.pyannote[84].start 306.88596875
transcript.pyannote[84].end 318.25971875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 318.20909375
transcript.pyannote[85].end 322.90034375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 323.60909375
transcript.pyannote[86].end 331.60784375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 331.74284375
transcript.pyannote[87].end 332.35034375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 332.82284375
transcript.pyannote[88].end 351.41909375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 333.02534375
transcript.pyannote[89].end 333.46409375
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 334.03784375
transcript.pyannote[90].end 335.01659375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 352.09409375
transcript.pyannote[91].end 366.31971875
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 366.64034375
transcript.pyannote[92].end 389.80971875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 390.61971875
transcript.pyannote[93].end 391.46346875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 392.13846875
transcript.pyannote[94].end 395.49659375
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 395.88471875
transcript.pyannote[95].end 397.80846875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 397.97721875
transcript.pyannote[96].end 400.22159375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 400.86284375
transcript.pyannote[97].end 408.20346875
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 408.59159375
transcript.pyannote[98].end 412.15221875
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 411.35909375
transcript.pyannote[99].end 430.22534375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 429.93846875
transcript.pyannote[100].end 439.28721875
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 439.48971875
transcript.pyannote[101].end 452.39909375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 452.85471875
transcript.pyannote[102].end 455.68971875
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 455.94284375
transcript.pyannote[103].end 456.75284375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 457.36034375
transcript.pyannote[104].end 466.69221875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 464.71784375
transcript.pyannote[105].end 465.49409375
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 466.10159375
transcript.pyannote[106].end 473.96534375
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 469.02096875
transcript.pyannote[107].end 469.81409375
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 473.29034375
transcript.pyannote[108].end 477.72846875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 474.50534375
transcript.pyannote[109].end 487.56659375
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 485.65971875
transcript.pyannote[110].end 486.35159375
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 486.40221875
transcript.pyannote[111].end 487.36409375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 487.36409375
transcript.pyannote[112].end 487.43159375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 487.93784375
transcript.pyannote[113].end 489.99659375
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 493.20284375
transcript.pyannote[114].end 496.91534375
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 497.97846875
transcript.pyannote[115].end 503.20971875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 503.66534375
transcript.pyannote[116].end 507.81659375
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 508.22159375
transcript.pyannote[117].end 516.25409375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 516.38909375
transcript.pyannote[118].end 519.39284375
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 519.73034375
transcript.pyannote[119].end 522.71721875
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 522.80159375
transcript.pyannote[120].end 526.27784375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 526.64909375
transcript.pyannote[121].end 532.03221875
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 532.30221875
transcript.pyannote[122].end 541.34721875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 541.73534375
transcript.pyannote[123].end 552.85596875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 552.97409375
transcript.pyannote[124].end 556.02846875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 556.21409375
transcript.pyannote[125].end 557.27721875
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 557.66534375
transcript.pyannote[126].end 559.25159375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 559.72409375
transcript.pyannote[127].end 578.05034375
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 578.05034375
transcript.pyannote[128].end 579.31596875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 579.46784375
transcript.pyannote[129].end 585.28971875
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 585.66096875
transcript.pyannote[130].end 590.31846875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 589.25534375
transcript.pyannote[131].end 589.79534375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 590.63909375
transcript.pyannote[132].end 590.67284375
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 590.67284375
transcript.pyannote[133].end 590.94284375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 590.94284375
transcript.pyannote[134].end 593.59221875
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 590.97659375
transcript.pyannote[135].end 591.33096875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 593.62596875
transcript.pyannote[136].end 602.28284375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 598.60409375
transcript.pyannote[137].end 599.19471875
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 602.28284375
transcript.pyannote[138].end 612.55971875
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 602.36721875
transcript.pyannote[139].end 602.87346875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 612.98159375
transcript.pyannote[140].end 616.12034375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 616.52534375
transcript.pyannote[141].end 630.46409375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 630.36284375
transcript.pyannote[142].end 632.69159375
transcript.pyannote[143].speaker SPEAKER_00
transcript.pyannote[143].start 630.48096875
transcript.pyannote[143].end 630.97034375
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 633.48471875
transcript.pyannote[144].end 640.42034375
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 636.60659375
transcript.pyannote[145].end 637.23096875
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 639.69471875
transcript.pyannote[146].end 646.41096875
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 646.78221875
transcript.pyannote[147].end 647.99721875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 648.50346875
transcript.pyannote[148].end 651.76034375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 651.96284375
transcript.pyannote[149].end 655.25346875
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 655.45596875
transcript.pyannote[150].end 656.02971875
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 656.18159375
transcript.pyannote[151].end 658.35846875
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 658.67909375
transcript.pyannote[152].end 660.67034375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 661.26096875
transcript.pyannote[153].end 666.64409375
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 666.67784375
transcript.pyannote[154].end 671.50409375
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 671.72346875
transcript.pyannote[155].end 675.03096875
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 675.58784375
transcript.pyannote[156].end 677.15721875
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 677.32596875
transcript.pyannote[157].end 677.84909375
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 678.28784375
transcript.pyannote[158].end 682.77659375
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 683.06346875
transcript.pyannote[159].end 685.74659375
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 686.21909375
transcript.pyannote[160].end 691.02846875
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 691.24784375
transcript.pyannote[161].end 695.71971875
transcript.pyannote[162].speaker SPEAKER_01
transcript.pyannote[162].start 696.02346875
transcript.pyannote[162].end 699.53346875
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 699.61784375
transcript.pyannote[163].end 700.39409375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 700.57971875
transcript.pyannote[164].end 702.03096875
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 702.18284375
transcript.pyannote[165].end 708.62909375
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 709.10159375
transcript.pyannote[166].end 710.85659375
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 711.61596875
transcript.pyannote[167].end 728.01846875
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 714.28221875
transcript.pyannote[168].end 715.21034375
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 728.27159375
transcript.pyannote[169].end 730.51596875
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 730.98846875
transcript.pyannote[170].end 732.55784375
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 732.81096875
transcript.pyannote[171].end 735.02159375
transcript.pyannote[172].speaker SPEAKER_01
transcript.pyannote[172].start 735.49409375
transcript.pyannote[172].end 751.12034375
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 748.01534375
transcript.pyannote[173].end 749.56784375
transcript.pyannote[174].speaker SPEAKER_01
transcript.pyannote[174].start 751.37346875
transcript.pyannote[174].end 752.53784375
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 751.40721875
transcript.pyannote[175].end 757.53284375
transcript.pyannote[176].speaker SPEAKER_01
transcript.pyannote[176].start 757.53284375
transcript.pyannote[176].end 760.87409375
transcript.pyannote[177].speaker SPEAKER_03
transcript.pyannote[177].start 760.09784375
transcript.pyannote[177].end 760.62096875
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 760.89096875
transcript.pyannote[178].end 761.31284375
transcript.pyannote[179].speaker SPEAKER_01
transcript.pyannote[179].start 761.44784375
transcript.pyannote[179].end 764.02971875
transcript.pyannote[180].speaker SPEAKER_01
transcript.pyannote[180].start 764.18159375
transcript.pyannote[180].end 767.05034375
transcript.pyannote[181].speaker SPEAKER_01
transcript.pyannote[181].start 767.37096875
transcript.pyannote[181].end 770.44221875
transcript.pyannote[182].speaker SPEAKER_01
transcript.pyannote[182].start 770.62784375
transcript.pyannote[182].end 775.43721875
transcript.pyannote[183].speaker SPEAKER_01
transcript.pyannote[183].start 775.84221875
transcript.pyannote[183].end 782.03534375
transcript.pyannote[184].speaker SPEAKER_01
transcript.pyannote[184].start 782.52471875
transcript.pyannote[184].end 785.34284375
transcript.pyannote[185].speaker SPEAKER_01
transcript.pyannote[185].start 785.66346875
transcript.pyannote[185].end 792.81846875
transcript.pyannote[186].speaker SPEAKER_01
transcript.pyannote[186].start 793.08846875
transcript.pyannote[186].end 795.72096875
transcript.pyannote[187].speaker SPEAKER_01
transcript.pyannote[187].start 795.85596875
transcript.pyannote[187].end 799.34909375
transcript.pyannote[188].speaker SPEAKER_01
transcript.pyannote[188].start 799.73721875
transcript.pyannote[188].end 800.09159375
transcript.pyannote[189].speaker SPEAKER_01
transcript.pyannote[189].start 800.26034375
transcript.pyannote[189].end 804.12471875
transcript.pyannote[190].speaker SPEAKER_01
transcript.pyannote[190].start 804.34409375
transcript.pyannote[190].end 806.99346875
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 807.63471875
transcript.pyannote[191].end 809.32221875
transcript.pyannote[192].speaker SPEAKER_01
transcript.pyannote[192].start 809.44034375
transcript.pyannote[192].end 811.24596875
transcript.pyannote[193].speaker SPEAKER_01
transcript.pyannote[193].start 811.46534375
transcript.pyannote[193].end 812.56221875
transcript.pyannote[194].speaker SPEAKER_01
transcript.pyannote[194].start 812.66346875
transcript.pyannote[194].end 813.86159375
transcript.pyannote[195].speaker SPEAKER_01
transcript.pyannote[195].start 813.92909375
transcript.pyannote[195].end 816.46034375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 816.98346875
transcript.pyannote[196].end 820.05471875
transcript.pyannote[197].speaker SPEAKER_01
transcript.pyannote[197].start 820.37534375
transcript.pyannote[197].end 820.71284375
transcript.pyannote[198].speaker SPEAKER_01
transcript.pyannote[198].start 821.43846875
transcript.pyannote[198].end 824.89784375
transcript.pyannote[199].speaker SPEAKER_02
transcript.pyannote[199].start 825.85971875
transcript.pyannote[199].end 834.14534375
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 829.58909375
transcript.pyannote[200].end 836.69346875
transcript.pyannote[201].speaker SPEAKER_03
transcript.pyannote[201].start 834.14534375
transcript.pyannote[201].end 834.19596875
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 836.81159375
transcript.pyannote[202].end 843.88221875
transcript.pyannote[203].speaker SPEAKER_01
transcript.pyannote[203].start 844.25346875
transcript.pyannote[203].end 851.15534375
transcript.pyannote[204].speaker SPEAKER_01
transcript.pyannote[204].start 851.57721875
transcript.pyannote[204].end 859.22159375
transcript.pyannote[205].speaker SPEAKER_01
transcript.pyannote[205].start 859.60971875
transcript.pyannote[205].end 872.08034375
transcript.pyannote[206].speaker SPEAKER_03
transcript.pyannote[206].start 866.64659375
transcript.pyannote[206].end 868.18221875
transcript.pyannote[207].speaker SPEAKER_01
transcript.pyannote[207].start 872.50221875
transcript.pyannote[207].end 875.99534375
transcript.pyannote[208].speaker SPEAKER_03
transcript.pyannote[208].start 874.02096875
transcript.pyannote[208].end 874.03784375
transcript.pyannote[209].speaker SPEAKER_00
transcript.pyannote[209].start 874.03784375
transcript.pyannote[209].end 874.44284375
transcript.pyannote[210].speaker SPEAKER_03
transcript.pyannote[210].start 874.44284375
transcript.pyannote[210].end 874.71284375
transcript.pyannote[211].speaker SPEAKER_00
transcript.pyannote[211].start 874.71284375
transcript.pyannote[211].end 874.93221875
transcript.pyannote[212].speaker SPEAKER_03
transcript.pyannote[212].start 874.93221875
transcript.pyannote[212].end 874.96596875
transcript.pyannote[213].speaker SPEAKER_00
transcript.pyannote[213].start 874.96596875
transcript.pyannote[213].end 875.03346875
transcript.pyannote[214].speaker SPEAKER_03
transcript.pyannote[214].start 875.03346875
transcript.pyannote[214].end 875.18534375
transcript.pyannote[215].speaker SPEAKER_03
transcript.pyannote[215].start 876.53534375
transcript.pyannote[215].end 876.97409375
transcript.pyannote[216].speaker SPEAKER_01
transcript.pyannote[216].start 876.97409375
transcript.pyannote[216].end 876.99096875
transcript.pyannote[217].speaker SPEAKER_00
transcript.pyannote[217].start 876.99096875
transcript.pyannote[217].end 877.12596875
transcript.pyannote[218].speaker SPEAKER_03
transcript.pyannote[218].start 876.99096875
transcript.pyannote[218].end 877.19346875
transcript.pyannote[219].speaker SPEAKER_01
transcript.pyannote[219].start 877.12596875
transcript.pyannote[219].end 877.14284375
transcript.pyannote[220].speaker SPEAKER_01
transcript.pyannote[220].start 877.19346875
transcript.pyannote[220].end 877.24409375
transcript.pyannote[221].speaker SPEAKER_03
transcript.pyannote[221].start 877.24409375
transcript.pyannote[221].end 877.44659375
transcript.pyannote[222].speaker SPEAKER_03
transcript.pyannote[222].start 878.03721875
transcript.pyannote[222].end 878.17221875
transcript.pyannote[223].speaker SPEAKER_00
transcript.pyannote[223].start 878.17221875
transcript.pyannote[223].end 889.00596875
transcript.pyannote[224].speaker SPEAKER_03
transcript.pyannote[224].start 878.20596875
transcript.pyannote[224].end 878.76284375
transcript.pyannote[225].speaker SPEAKER_02
transcript.pyannote[225].start 879.91034375
transcript.pyannote[225].end 880.97346875
transcript.pyannote[226].speaker SPEAKER_03
transcript.pyannote[226].start 880.97346875
transcript.pyannote[226].end 881.02409375
transcript.pyannote[227].speaker SPEAKER_01
transcript.pyannote[227].start 881.02409375
transcript.pyannote[227].end 881.64846875
transcript.pyannote[228].speaker SPEAKER_01
transcript.pyannote[228].start 889.00596875
transcript.pyannote[228].end 894.18659375
transcript.pyannote[229].speaker SPEAKER_00
transcript.pyannote[229].start 891.57096875
transcript.pyannote[229].end 894.30471875
transcript.pyannote[230].speaker SPEAKER_00
transcript.pyannote[230].start 894.65909375
transcript.pyannote[230].end 899.78909375
transcript.pyannote[231].speaker SPEAKER_01
transcript.pyannote[231].start 899.36721875
transcript.pyannote[231].end 900.17721875
transcript.pyannote[232].speaker SPEAKER_00
transcript.pyannote[232].start 900.17721875
transcript.pyannote[232].end 900.90284375
transcript.pyannote[233].speaker SPEAKER_01
transcript.pyannote[233].start 900.19409375
transcript.pyannote[233].end 901.84784375
transcript.pyannote[234].speaker SPEAKER_00
transcript.pyannote[234].start 901.84784375
transcript.pyannote[234].end 903.11346875
transcript.pyannote[235].speaker SPEAKER_01
transcript.pyannote[235].start 901.88159375
transcript.pyannote[235].end 902.74221875
transcript.pyannote[236].speaker SPEAKER_01
transcript.pyannote[236].start 902.79284375
transcript.pyannote[236].end 902.86034375
transcript.pyannote[237].speaker SPEAKER_01
transcript.pyannote[237].start 903.28221875
transcript.pyannote[237].end 907.01159375
transcript.pyannote[238].speaker SPEAKER_01
transcript.pyannote[238].start 907.26471875
transcript.pyannote[238].end 910.55534375
transcript.pyannote[239].speaker SPEAKER_01
transcript.pyannote[239].start 910.84221875
transcript.pyannote[239].end 914.48721875
transcript.pyannote[240].speaker SPEAKER_01
transcript.pyannote[240].start 914.65596875
transcript.pyannote[240].end 915.26346875
transcript.pyannote[241].speaker SPEAKER_01
transcript.pyannote[241].start 915.51659375
transcript.pyannote[241].end 924.13971875
transcript.pyannote[242].speaker SPEAKER_01
transcript.pyannote[242].start 924.83159375
transcript.pyannote[242].end 933.13409375
transcript.pyannote[243].speaker SPEAKER_01
transcript.pyannote[243].start 933.47159375
transcript.pyannote[243].end 934.04534375
transcript.pyannote[244].speaker SPEAKER_01
transcript.pyannote[244].start 934.26471875
transcript.pyannote[244].end 935.31096875
transcript.pyannote[245].speaker SPEAKER_01
transcript.pyannote[245].start 942.19596875
transcript.pyannote[245].end 946.97159375
transcript.pyannote[246].speaker SPEAKER_00
transcript.pyannote[246].start 946.58346875
transcript.pyannote[246].end 946.80284375
transcript.pyannote[247].speaker SPEAKER_00
transcript.pyannote[247].start 946.97159375
transcript.pyannote[247].end 948.96284375
transcript.pyannote[248].speaker SPEAKER_03
transcript.pyannote[248].start 950.11034375
transcript.pyannote[248].end 950.58284375
transcript.whisperx[0].start 0.169
transcript.whisperx[0].end 1.31
transcript.whisperx[0].text 謝謝主席 謝謝韓院長有請卓榮泰院長麻煩請卓院長備詢
transcript.whisperx[1].start 29.366
transcript.whisperx[1].end 40.518
transcript.whisperx[1].text 廖文豪院長好院長我想你是跨部會的指揮官相信接下來問題你大概都可以能夠親自回答那院長請問一下今年10月電價漲不漲
transcript.whisperx[2].start 43.221
transcript.whisperx[2].end 64.198
transcript.whisperx[2].text 委員應該清楚電價都是一直是電價審議委員會最終的決定我們只能評估現在的狀況但是這個審議委員會其實也是你們行政院組的嘛那委員也是你們大概也是你們提名的那我想院長你總有一個方向吧因為過去其實你們說一聲漲或不漲大概方向也是這樣子
transcript.whisperx[3].start 64.958
transcript.whisperx[3].end 80.412
transcript.whisperx[3].text 各有其責各失其職我們當然希望民生穩定工業也能夠穩定這是整個社會對我們的期待謝謝 院長因為你剛有提到要穩定物價所以現況就是這樣中油4月份對電業的用戶氣價調漲41.58%每立方公尺從13.2元也漲到18.7元也是電業史上最大的漲幅
transcript.whisperx[4].start 90.501
transcript.whisperx[4].end 105.47
transcript.whisperx[4].text 那首當其衝當然是台電那央行的3月的禮監事會也已經把2026年的CPI上修至1.8那3月份的核心CPI是1.94%畢竟2%的警戒線所以央行自己也試算
transcript.whisperx[5].start 106.891
transcript.whisperx[5].end 129.506
transcript.whisperx[5].text 電價每漲10%推升CPI0.36個百分點所以油電價跟CPI是連提因式的雙升曲線所以我就是想要問因為你今天院方你們也宣布說這個統裝瓦斯不漲價那我就想請問一下說那10月份的電價不知道院長你究竟是支持漲價還是不支持漲價
transcript.whisperx[6].start 131.511
transcript.whisperx[6].end 155.517
transcript.whisperx[6].text 確定的是9月之前不漲價沒有人會在沒有條件之下去支持或不支持一件事情總之控制在CPI2%這個是我們的一個目標目前雖然他往上調但是你也知道這兩三個月來的狀況是特別特別的緊張好 院長因為你現在沒有辦法明確的表達沒有錯你的意思就是說你不能確定因為報告員我們是
transcript.whisperx[7].start 157.481
transcript.whisperx[7].end 182.033
transcript.whisperx[7].text 充分的資料給審議委員會委員了解說實際的狀況,最後決定還是他們好部長,沒關係院長因為其實你們經濟部次長之前也親口說如果戰爭三個月內結束,十月的電價調漲壓力比較小可是今天已經四月二十四號其實四週已經過去,離三個月的時間也只剩下不到九個禮拜布蘭特原油也衝上一百塊以上
transcript.whisperx[8].start 183.934
transcript.whisperx[8].end 208.062
transcript.whisperx[8].text 所以停火停不住那油價到現在也還在漲那剩下九週要怎麼結束所以我覺得這三個月的這個所謂的平行宇宙的時間表真的是讓我們很擔憂啊那連川普自己都說到11月油價會維持在高檔那就算明天的戰事結束所謂的LNG的長約跟聯動的油價也有遞延的效果所以從
transcript.whisperx[9].start 209.162
transcript.whisperx[9].end 229.257
transcript.whisperx[9].text 這個二五戰爭的前例歐洲的這個天然氣也花了整整兩年才回到一定的水平而且不是三個月所以我想這個問題是一個很結構性的問題那我也想問一下關心一下說那現在這個相關的原油有什麼樣的進展一個具體的事情請教就是這個台塑的
transcript.whisperx[10].start 229.937
transcript.whisperx[10].end 251.692
transcript.whisperx[10].text 軍扇輪這個兩百萬桶的原油說大概五月六號到達台灣那你們當初大動作有新聞宣傳說這個可能有兩週的時間那我想要請問一下行政院有沒有掌握這批原油呢他是確定在內銷還有沒有說不能外銷這個部分想要請問一下因為畢竟他是私人公司
transcript.whisperx[11].start 251.732
transcript.whisperx[11].end 270.544
transcript.whisperx[11].text 我請部長來說明原則性說我們對油的掌握目前安全存量比較高是沒有大問題的比較緊張是天然氣但是我們到六月之前也都沒有問題細部的規劃我想請問一下這兩百萬桶原油你們有沒有掌握因為我們現在戰爭已經一個多月了那我們原來
transcript.whisperx[12].start 271.28
transcript.whisperx[12].end 295.358
transcript.whisperx[12].text 油品的部分我們的儲備量都有140天那也都沒有減少所以這200萬桶原油我想要請教不好意思我們有跟台塑有跟他聯絡嗎是不是以國內供應為主原則上以國內為主好那我想要另外再請教一個問題因為當初也有說過這個河母之海峽要收過路費那你們有沒有掌握這艘船它有付過路費嗎
transcript.whisperx[13].start 297.166
transcript.whisperx[13].end 321.144
transcript.whisperx[13].text 這個我們就沒有你們不曉得你們沒有掌握我們確定就是說它進來的量可以優先使用在國內然後呢四月份五月份該進來的部分至少四月份的四條的這個原油的進來船已經都到港了所以也沒有問題那五月份也陸續會到港按照這個時程對因為我們現在看到的事情是這個原油價格
transcript.whisperx[14].start 321.704
transcript.whisperx[14].end 332.018
transcript.whisperx[14].text 一定一路高檔次再到年底啊所以我們很擔心民眾的生活所以你們今天也提出說要計程車要補貼六千元對不對
transcript.whisperx[15].start 332.947
transcript.whisperx[15].end 348.317
transcript.whisperx[15].text 你們今天有提出嘛可是本席想要說的事情是我們不反對但是現在的這個所有的不管是油價、瓦斯器、民生全部都在漲那我想要請問一下那一樣的用油的外送員物流業、小貨車業一樣繳電費的攤商、夜市家庭
transcript.whisperx[16].start 352.139
transcript.whisperx[16].end 372.253
transcript.whisperx[16].text 我覺得這個是全面性的衝擊啊所以本席想要建議行政院的應變應該是一個全方位的包含這些中產甚至弱勢邊緣戶受衝擊的產業跟家庭都要接得住不是單就部分的職業我們應該是全方位的一個這個預算去支持他們
transcript.whisperx[17].start 372.853
transcript.whisperx[17].end 391.286
transcript.whisperx[17].text 所以我想要問一下因為今天早上我也看到新聞行政院也有發言人也有說中央政府要推出民生物價的平穩措施整體的裁員上在盤整將事實對外說明想要請問一下什麼時候然後你們盤整大概是什麼方向請院長回答
transcript.whisperx[18].start 392.299
transcript.whisperx[18].end 408.117
transcript.whisperx[18].text 就是針對各部會目前所受到的產業的衝擊正在做更細部的規劃那麼昨天提出的是我們對一些大宗運輸的事業首先來做一些補貼因為它的價錢是不能浮動的
transcript.whisperx[19].start 408.698
transcript.whisperx[19].end 437.401
transcript.whisperx[19].text 所以他的支出負擔重了就是產業所以有沒有時程表不好意思院長你們大概有沒有什麼時程表你說各個部會去盤點那盤點到什麼時候主計處主計這個主計長也有說這個這次的能源衝擊大約說衝擊需要1300億那想要請問一下這個盤點這算是盤點完的價格嗎金額嗎還是不是那是各部會送出來的一個出估那我們還要看各部會之間的一個橫向的一個協調有些可能可以互相的支援
transcript.whisperx[20].start 437.921
transcript.whisperx[20].end 456.572
transcript.whisperx[20].text 那什麼時間呢我認為最好的時間就是我們評估完之後能不能用現在的公務預算或是現在先行之前的那個特別預算來用如果我們必須再追加預算的話那必須就是在大院審查預算結束之後
transcript.whisperx[21].start 457.432
transcript.whisperx[21].end 473.614
transcript.whisperx[21].text 再提出是合理如果還沒有審查完我們提出大院也能夠接受那我們也可以把事實的計算之後來提出最佳因素這本席就是要告訴你說這個時間要快一般的民眾現在真的是等不起現在就在漲民眾是等不起那我也請
transcript.whisperx[22].start 474.375
transcript.whisperx[22].end 496.753
transcript.whisperx[22].text 大約那個審查預算的速度快一點因為你剛剛有說到還有其他特別預算那你還要盤點嘛所以你們盤點的速度然後以及到時候提出的方案也請盡速提出來好不好我們都來加快那另外我想要進一步來問一下我們國家的這個新十大的AI建設我想要
transcript.whisperx[23].start 498.164
transcript.whisperx[23].end 525.506
transcript.whisperx[23].text 我拜讀過你們的新十大建設的核定本那四年1900億裡面有所謂的智慧交通、智慧防災、智慧觀光、智慧醫療也都在裡面那昨天呢4月23號速發部的資安署認定說這個高德地圖是危害國家資通安全的產品所以公務機關跟國軍都已經禁用那民用層級的部分你們是呼籲說民眾不要下載你們說5月才可以公布完整的資安評測
transcript.whisperx[24].start 526.727
transcript.whisperx[24].end 541.078
transcript.whisperx[24].text 那在這個不管是圖資或者是國安的考量上我們是尊重行政院的立場但是站在民眾的立場上面你們呼籲民眾不要用我想是沒有用的因為關鍵是你有沒有辦法有一個更好用的APP
transcript.whisperx[25].start 541.818
transcript.whisperx[25].end 544.2
transcript.whisperx[25].text 我現在我就用Google Map
transcript.whisperx[26].start 559.758
transcript.whisperx[26].end 577.923
transcript.whisperx[26].text 阿不是我是說那現在Google Map就是沒有辦法滿足這些相關的需求嘛所以我剛剛就問說你們呼籲人家不要用但是民間的反應就是說覺得他很好用所以重點是我們有沒有你的這新時代AI建設裡面有沒有可以有辦法扶植出一個這樣子的好用的民用的APP
transcript.whisperx[27].start 578.283
transcript.whisperx[27].end 593.242
transcript.whisperx[27].text 新十大AI新十大建設我們有十項的項目在裡面其中最頂端那一項就是加強我們的軟體登峰我們必須把我們的軟體做得更好目前在處理會做出來比他更好用的民用APP嗎
transcript.whisperx[28].start 593.883
transcript.whisperx[28].end 615.991
transcript.whisperx[28].text 我不能夠馬上說一定會做出一個類似這樣的APP但是地圖的APP我們現在就有其他可以安全使用的院長因為我有看到你們在這個裡面的十大建設裡面有所謂智慧交通緊急車輛救援還有智慧景區精準天候預測然後哪一項是在哪一項裡面你們會在哪一項裡面去做這件事情
transcript.whisperx[29].start 617.347
transcript.whisperx[29].end 632.495
transcript.whisperx[29].text 這個部分的話跟委員報告就是說這個部分會屬於AI軟體產業登峰這一塊那這一塊其實是跟我們的全民社會生活全是連結在一起的所以速發部會全力的來開發很多的APP軟體所以你們有沒有信心做得比他更好
transcript.whisperx[30].start 634.393
transcript.whisperx[30].end 660.443
transcript.whisperx[30].text 這個我們會有信心那我也會你會有信心我會跟那個抒發部一起來協調好 院長真的要做到因為既然政府認定高德是境外敵對勢力的產品那我們就不能讓中國大陸的APP做得比我們國家自己的APP更好用我想這是民間的競爭力也是國家的尊嚴好 所以我想要講到你所謂的AI的部分要做這樣的APP要有
transcript.whisperx[31].start 661.684
transcript.whisperx[31].end 682.387
transcript.whisperx[31].text 運轉的AI要有算力要有電那台灣政府的算力到底準備有多少呢我想要直接告訴你這個還要另外再問一件事情也是關於時事的部分等一下會一併來討論這個AI今天還有一件事情川普公開點名台灣說美國要取得全球50%的晶片市場
transcript.whisperx[32].start 683.147
transcript.whisperx[32].end 710.676
transcript.whisperx[32].text 而台灣是最大宗的來源那他已經讓台積電承諾1650億美元要赴美那美光承諾2000億那總共要1兆美元投資到美國那一年半以後對於這個不到美國設廠的晶片公司課予極高的關稅所以想要問一下院長針對這個新聞川普講這個東西行政院怎麼看打算怎麼因應第一由此可見台灣的重要性
transcript.whisperx[33].start 711.653
transcript.whisperx[33].end 730.145
transcript.whisperx[33].text 我們在這種晶片製造上的重要性再來台灣會繼續站在最領先的地位不論是它的值或是量台灣永遠站在最領先的地位第三我們跟美方現在進行三利益的調查很多的過程我們在當中我們必須清楚的說明台灣最有利於雙邊的一些立場
transcript.whisperx[34].start 731.058
transcript.whisperx[34].end 749.558
transcript.whisperx[34].text 院長你可以看到這張圖喔其實我想我們是非常擔憂的啊這黃仁勛也說過五層蛋糕啊好第一層最下面是能源再來是晶片再來雲端再來模型再來應用結果我們現在製造的第二層蛋糕正在被挖走當中並沒有被菜團邀我們去那邊設好
transcript.whisperx[35].start 752.541
transcript.whisperx[35].end 759.665
transcript.whisperx[35].text 台積公司在台灣設廠的速度跟量我想未來委員會更清楚這五層蛋糕剛剛中間這層晶片現在已經被要求大量的去美國設廠
transcript.whisperx[36].start 767.429
transcript.whisperx[36].end 781.622
transcript.whisperx[36].text 但是我們的算力呢我們算力有沒有辦法跟上呢想要問一下一個很殘酷的事實台灣最會賺錢的公司就是我們剛說台積電正在賣算力給全世界但是我們有準備好嗎台灣的政府有沒有算力可以買
transcript.whisperx[37].start 782.583
transcript.whisperx[37].end 796.998
transcript.whisperx[37].text 台積電在資本支出它一年在2026年它是大概560億美元左右在新台幣1.6兆到1.7兆左右它一間的資本支出是台灣政府AI新十大建設4年1900億的8到9倍
transcript.whisperx[38].start 799.813
transcript.whisperx[38].end 824.597
transcript.whisperx[38].text 那現在大家都很關心所謂的AI的Token算力喔那所以包含輝達的工程師他說黃仁勳說如果年薪50萬美金他要用至少用到25萬美金的Token才可以算是有賺錢而且越用越多每一次運算就是會賺錢然後每一次運算也都需要電所以院長你知道各國政府現在在AI算力上面做了些什麼事嗎
transcript.whisperx[39].start 826.005
transcript.whisperx[39].end 850.947
transcript.whisperx[39].text 我們也有自己算力的建設在AI新時代建設裡面有嗎?有啊我想要告訴你看起來比較起來是遠遠不夠因為英國4月才剛啟動說5億的這個約合新台幣大概200億的主權AI基金新加坡也紮了約新台幣將近40億、30億來補助中小企業買雲端算力
transcript.whisperx[40].start 851.627
transcript.whisperx[40].end 875.594
transcript.whisperx[40].text 那韓國呢2月也首批的這個有4300多片的GPU到貨那2030年他打算要26萬片共同的一個點就是這幾個政府都希望政府先把企業接上算力把政府把企業接上算力好那我們台灣呢現在看起來我們只有算力只有140片GPU那這個量級到底夠不夠呢
transcript.whisperx[41].start 876.955
transcript.whisperx[41].end 883.861
transcript.whisperx[41].text 我們在2028年的時候公部門加市部門的話我們大概會有算力會有131,912.6的PF那針對這個公部門的部分我們是不是應該建樹先提供給企業
transcript.whisperx[42].start 894.75
transcript.whisperx[42].end 923.729
transcript.whisperx[42].text 公部門加私部門那私部門的話大概就是紅海這個部分的話大概2028年會大概9萬左右院長和各位行政官員我想要說的事情就是其實剛剛說到最底層算力來自於電力之前我想院長也很清楚電力跟算力跟國力所以現在各個國家政府都領先的在衝刺去買雲端的算力我們是不是應該先去預購這些雲端算力回來
transcript.whisperx[43].start 924.85
transcript.whisperx[43].end 935.136
transcript.whisperx[43].text 我們是不是應該先準備起來所以短期的部分是不是應該雲端先再加大的預購然後企業現在就能用或學術單位就能用那當然中長期我們要