iVOD / 167607

Field Value
IVOD_ID 167607
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/167607
日期 2026-03-18
會議資料.會議代碼 委員會-11-5-23-2
會議資料.會議代碼:str 第11屆第5會期交通委員會第2次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 2
會議資料.種類 委員會
會議資料.委員會代碼[0] 23
會議資料.委員會代碼:str[0] 交通委員會
會議資料.標題 第11屆第5會期交通委員會第2次全體委員會議
影片種類 Clip
開始時間 2026-03-18T11:06:05+08:00
結束時間 2026-03-18T11:18:07+08:00
影片長度 00:12:02
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/4e26a61b53ad6053c021877bbbeb8a2675f3d6415d2a29ea4d1c9dfa77de209814d5e53a528fd4095ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 許智傑
委員發言時間 11:06:05 - 11:18:07
會議時間 2026-03-18T09:00:00+08:00
會議名稱 立法院第11屆第5會期交通委員會第2次全體委員會議(事由:邀請數位發展部部長及國家科學及技術委員會主任委員就「落實臺灣AI治理與基礎建設,發展臺灣AI軟體產業」進行專題報告,並備質詢。【3月18日及19日二天一次會】)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 3.79409375
transcript.pyannote[0].end 5.61659375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 5.92034375
transcript.pyannote[1].end 6.66284375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 12.65346875
transcript.pyannote[2].end 13.19346875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 13.69971875
transcript.pyannote[3].end 14.45909375
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 14.67846875
transcript.pyannote[4].end 16.83846875
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 17.37846875
transcript.pyannote[5].end 23.06534375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 24.07784375
transcript.pyannote[6].end 26.03534375
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 26.69346875
transcript.pyannote[7].end 28.34721875
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 30.20346875
transcript.pyannote[8].end 31.82346875
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 32.24534375
transcript.pyannote[9].end 44.91846875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 45.79596875
transcript.pyannote[10].end 46.38659375
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 47.39909375
transcript.pyannote[11].end 52.36034375
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 52.68096875
transcript.pyannote[12].end 64.25721875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 64.86471875
transcript.pyannote[13].end 68.13846875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 68.66159375
transcript.pyannote[14].end 75.24284375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 75.37784375
transcript.pyannote[15].end 79.49534375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 79.86659375
transcript.pyannote[16].end 83.35971875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 84.08534375
transcript.pyannote[17].end 84.62534375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 84.77721875
transcript.pyannote[18].end 89.09721875
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 89.21534375
transcript.pyannote[19].end 92.47221875
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 93.73784375
transcript.pyannote[20].end 93.99096875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 94.49721875
transcript.pyannote[21].end 104.79096875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 105.34784375
transcript.pyannote[22].end 115.30409375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 110.17409375
transcript.pyannote[23].end 110.56221875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 115.54034375
transcript.pyannote[24].end 133.90034375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 118.12221875
transcript.pyannote[25].end 118.93221875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 129.58034375
transcript.pyannote[26].end 130.32284375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 132.31409375
transcript.pyannote[27].end 132.70221875
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 134.06909375
transcript.pyannote[28].end 139.97534375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 139.33409375
transcript.pyannote[29].end 141.25784375
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 141.20721875
transcript.pyannote[30].end 148.41284375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 147.33284375
transcript.pyannote[31].end 147.78846875
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 148.29471875
transcript.pyannote[32].end 154.70721875
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 155.95596875
transcript.pyannote[33].end 164.37659375
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 164.44409375
transcript.pyannote[34].end 176.40846875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 176.81346875
transcript.pyannote[35].end 178.19721875
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 178.55159375
transcript.pyannote[36].end 180.40784375
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 180.55971875
transcript.pyannote[37].end 193.68846875
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 193.84034375
transcript.pyannote[38].end 197.41784375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 196.62471875
transcript.pyannote[39].end 197.06346875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 197.83971875
transcript.pyannote[40].end 209.04471875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 209.58471875
transcript.pyannote[41].end 210.69846875
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 211.69409375
transcript.pyannote[42].end 212.35221875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 212.67284375
transcript.pyannote[43].end 215.62596875
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 216.11534375
transcript.pyannote[44].end 230.54346875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 228.73784375
transcript.pyannote[45].end 228.88971875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 228.90659375
transcript.pyannote[46].end 228.94034375
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 230.79659375
transcript.pyannote[47].end 244.85346875
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 245.42721875
transcript.pyannote[48].end 247.16534375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 247.40159375
transcript.pyannote[49].end 251.13096875
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 251.40096875
transcript.pyannote[50].end 252.95346875
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 253.67909375
transcript.pyannote[51].end 254.62409375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 254.94471875
transcript.pyannote[52].end 257.81346875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 258.89346875
transcript.pyannote[53].end 259.21409375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 259.45034375
transcript.pyannote[54].end 260.58096875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 260.51346875
transcript.pyannote[55].end 262.20096875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 261.54284375
transcript.pyannote[56].end 293.08221875
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 271.98846875
transcript.pyannote[57].end 272.34284375
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 293.08221875
transcript.pyannote[58].end 293.26784375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 293.26784375
transcript.pyannote[59].end 295.09034375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 294.17909375
transcript.pyannote[60].end 296.03534375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 295.90034375
transcript.pyannote[61].end 297.77346875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 296.74409375
transcript.pyannote[62].end 299.10659375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 299.10659375
transcript.pyannote[63].end 315.86346875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 314.07471875
transcript.pyannote[64].end 314.68221875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 314.93534375
transcript.pyannote[65].end 318.24284375
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 318.24284375
transcript.pyannote[66].end 334.02096875
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 319.96409375
transcript.pyannote[67].end 320.26784375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 325.73534375
transcript.pyannote[68].end 326.24159375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 331.97909375
transcript.pyannote[69].end 342.49221875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 343.06596875
transcript.pyannote[70].end 343.70721875
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 344.17971875
transcript.pyannote[71].end 344.85471875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 345.46221875
transcript.pyannote[72].end 346.79534375
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 347.08221875
transcript.pyannote[73].end 347.67284375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 347.82471875
transcript.pyannote[74].end 348.17909375
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 348.17909375
transcript.pyannote[75].end 348.61784375
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 349.03971875
transcript.pyannote[76].end 351.77346875
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 352.36409375
transcript.pyannote[77].end 352.71846875
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 352.41471875
transcript.pyannote[78].end 352.65096875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 353.29221875
transcript.pyannote[79].end 354.96284375
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 355.51971875
transcript.pyannote[80].end 359.67096875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 359.90721875
transcript.pyannote[81].end 364.19346875
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 364.58159375
transcript.pyannote[82].end 368.78346875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 368.85096875
transcript.pyannote[83].end 383.29596875
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 383.46471875
transcript.pyannote[84].end 387.09284375
transcript.pyannote[85].speaker SPEAKER_00
transcript.pyannote[85].start 387.48096875
transcript.pyannote[85].end 392.08784375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 392.29034375
transcript.pyannote[86].end 395.76659375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 396.12096875
transcript.pyannote[87].end 396.98159375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 396.27284375
transcript.pyannote[88].end 396.35721875
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 397.48784375
transcript.pyannote[89].end 402.02721875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 402.19596875
transcript.pyannote[90].end 402.21284375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 402.21284375
transcript.pyannote[91].end 402.24659375
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 402.24659375
transcript.pyannote[92].end 409.16534375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 409.65471875
transcript.pyannote[93].end 411.69659375
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 412.57409375
transcript.pyannote[94].end 415.27409375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 415.71284375
transcript.pyannote[95].end 426.09096875
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 426.46221875
transcript.pyannote[96].end 429.31409375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 429.41534375
transcript.pyannote[97].end 434.49471875
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 434.78159375
transcript.pyannote[98].end 435.96284375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 436.55346875
transcript.pyannote[99].end 437.32971875
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 438.51096875
transcript.pyannote[100].end 442.35846875
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 441.10971875
transcript.pyannote[101].end 441.63284375
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 442.47659375
transcript.pyannote[102].end 444.21471875
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 445.04159375
transcript.pyannote[103].end 451.42034375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 451.55534375
transcript.pyannote[104].end 457.52909375
transcript.pyannote[105].speaker SPEAKER_00
transcript.pyannote[105].start 458.25471875
transcript.pyannote[105].end 463.16534375
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 463.63784375
transcript.pyannote[106].end 478.72409375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 478.72409375
transcript.pyannote[107].end 479.33159375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 479.33159375
transcript.pyannote[108].end 484.71471875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 485.08596875
transcript.pyannote[109].end 505.25159375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 503.49659375
transcript.pyannote[110].end 503.93534375
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 506.02784375
transcript.pyannote[111].end 527.02034375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 526.10909375
transcript.pyannote[112].end 527.45909375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 527.45909375
transcript.pyannote[113].end 533.43284375
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 533.07846875
transcript.pyannote[114].end 535.13721875
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 535.93034375
transcript.pyannote[115].end 539.52471875
transcript.pyannote[116].speaker SPEAKER_00
transcript.pyannote[116].start 539.74409375
transcript.pyannote[116].end 540.13221875
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 540.73971875
transcript.pyannote[117].end 547.67534375
transcript.pyannote[118].speaker SPEAKER_00
transcript.pyannote[118].start 547.92846875
transcript.pyannote[118].end 555.20159375
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 554.10471875
transcript.pyannote[119].end 555.62346875
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 555.91034375
transcript.pyannote[120].end 573.30846875
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 573.61221875
transcript.pyannote[121].end 575.16471875
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 575.24909375
transcript.pyannote[122].end 575.26596875
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 575.31659375
transcript.pyannote[123].end 579.82221875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 579.40034375
transcript.pyannote[124].end 580.73346875
transcript.pyannote[125].speaker SPEAKER_00
transcript.pyannote[125].start 580.73346875
transcript.pyannote[125].end 589.08659375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 586.89284375
transcript.pyannote[126].end 587.11221875
transcript.pyannote[127].speaker SPEAKER_00
transcript.pyannote[127].start 589.25534375
transcript.pyannote[127].end 591.11159375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 589.30596875
transcript.pyannote[128].end 589.59284375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 591.11159375
transcript.pyannote[129].end 592.24221875
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 591.85409375
transcript.pyannote[130].end 614.98971875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 615.22596875
transcript.pyannote[131].end 642.15846875
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 620.79471875
transcript.pyannote[132].end 620.92971875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 623.96721875
transcript.pyannote[133].end 624.79409375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 625.46909375
transcript.pyannote[134].end 626.02596875
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 639.34034375
transcript.pyannote[135].end 639.74534375
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 642.39471875
transcript.pyannote[136].end 657.12659375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 656.40096875
transcript.pyannote[137].end 657.95346875
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 657.95346875
transcript.pyannote[138].end 663.89346875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 658.17284375
transcript.pyannote[139].end 658.64534375
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 662.57721875
transcript.pyannote[140].end 662.96534375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 664.39971875
transcript.pyannote[141].end 670.66034375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 667.87596875
transcript.pyannote[142].end 668.14596875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 670.66034375
transcript.pyannote[143].end 671.67284375
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 670.84596875
transcript.pyannote[144].end 685.34159375
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 676.71846875
transcript.pyannote[145].end 677.46096875
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 678.96284375
transcript.pyannote[146].end 679.38471875
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 686.38784375
transcript.pyannote[147].end 691.39971875
transcript.pyannote[148].speaker SPEAKER_00
transcript.pyannote[148].start 692.63159375
transcript.pyannote[148].end 708.44346875
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 704.61284375
transcript.pyannote[149].end 705.43971875
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 708.59534375
transcript.pyannote[150].end 716.72909375
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 708.62909375
transcript.pyannote[151].end 709.03409375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 710.46846875
transcript.pyannote[152].end 710.78909375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 711.51471875
transcript.pyannote[153].end 714.60284375
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 716.13846875
transcript.pyannote[154].end 716.30721875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 716.72909375
transcript.pyannote[155].end 716.96534375
transcript.pyannote[156].speaker SPEAKER_00
transcript.pyannote[156].start 716.96534375
transcript.pyannote[156].end 719.86784375
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 717.75846875
transcript.pyannote[157].end 718.51784375
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 720.89721875
transcript.pyannote[158].end 722.97284375
transcript.whisperx[0].start 4.103
transcript.whisperx[0].end 28.048
transcript.whisperx[0].text 謝謝主席 我們請部長請林部長部長早安部長好是我看部長壓力一定很大那個剛辛純講說那個台中要不可取代的城市是那我們主席是台南那我是高雄
transcript.whisperx[1].start 30.428
transcript.whisperx[1].end 44.503
transcript.whisperx[1].text 所以這個全部都要把台灣變成世界啦不可取代的國家就是除了硬體之外我想軟體也是我們必須要非常努力的部分那
transcript.whisperx[2].start 47.435
transcript.whisperx[2].end 67.783
transcript.whisperx[2].text 我們大概3月底樹化部會有一個產業座談這是我從去年就一直要求也參與過多次就是我們高雄地區海嵐的建設所以在去年的3月然後去年的6月跟12月我自己也在
transcript.whisperx[3].start 68.923
transcript.whisperx[3].end 92.217
transcript.whisperx[3].text 高雄辦的AI行農還有AI漁業還有AI商圈的這些座談會那我們也希望說這些AI的應用可以落實在我們的生活當中那針對這個數位港的部分先請教一下部長我們大致上什麼時候可以完成
transcript.whisperx[4].start 94.906
transcript.whisperx[4].end 117.675
transcript.whisperx[4].text 蘇維港是我想這個是我們一直持續在推動的一件事情所以比較難說是確定說哪時候完成我們應該是想說這個是我們現在就是很重要一件事情是那個算力中心那我們知道說現在有一些台灣的民間的大廠他這個算力中心的選址都會在南部謝謝
transcript.whisperx[5].start 118.875
transcript.whisperx[5].end 131.812
transcript.whisperx[5].text 南部的那個電力比較充足然後南部的那個就是也是我們現在政府一直希望說把高科技產業不需要通通集中在北部那以前傳統上一些硬體產業像說那個
transcript.whisperx[6].start 134.996
transcript.whisperx[6].end 152.152
transcript.whisperx[6].text 我們那個台積電等等以前都是在新竹到台北之間所以現在都全台灣佈局了對 全台灣都佈局了那已經北部這個地方已經過度擁擠了那我們是希望往中南部的就是分散所以我現在希望說要要求跟拜託部長就是說我們從
transcript.whisperx[7].start 155.984
transcript.whisperx[7].end 176.015
transcript.whisperx[7].text 台灣是台積電護國神山是世界的翹楚這個在硬體上面其實是沒有問題的那硬體布局台灣其實也各地都有這個我們也謝謝台積電跟我們中央的努力還有地方的爭取那現在就是說我們相關的配套
transcript.whisperx[8].start 177.046
transcript.whisperx[8].end 196.132
transcript.whisperx[8].text 譬如說我們數位港 海南站我們應該盡快完成至少這個是資訊流那在全台灣總是我們要有一個自己的安全的穩定的資訊港口可以進出的所在所以這個
transcript.whisperx[9].start 198.033
transcript.whisperx[9].end 210.312
transcript.whisperx[9].text 為什麼我一直在要求希望能夠盡快完成也希望說部長能夠把這個時間盡量縮短來完成這個數位港海嵐站的這個目標那另外就是
transcript.whisperx[10].start 211.921
transcript.whisperx[10].end 229.227
transcript.whisperx[10].text 鴻海在台灣在高雄現在他在我們高雄打算蓋兩棟大樓那這些將來可能也是一個重要的算力中心沒錯他上一次我看新聞揮打也合作所以將來會有
transcript.whisperx[11].start 230.928
transcript.whisperx[11].end 257.569
transcript.whisperx[11].text 光是新聞寫的是4千多顆啦那當然就是說這些未來會變成一個超級算力中心在高雄那我們在想到就是剛剛新淳也有提到就是應用的部分那超級算力中心在高雄之後呢我想包括交換中心在高雄有沒有打算設交換中心
transcript.whisperx[12].start 259.543
transcript.whisperx[12].end 275.937
transcript.whisperx[12].text 交換中心就是資料交換中心我們現在是希望就是說回答就是希望我們這個算力中心如果設在那邊以後當然裡面會有除了資料以外就是最重要是有AI的model那我們這個地方我們都會努力去做那我們現在先
transcript.whisperx[13].start 276.557
transcript.whisperx[13].end 296.483
transcript.whisperx[13].text 想法就是說因為我們政府部門也要使用AI政府部門的AI就非常的敏感政府部門的公務員都知道如果直接用美國的AI系統伺服器可能在美國在日本在新加坡所以在台灣要有自己的對以後都是關鍵基礎設施
transcript.whisperx[14].start 299.584
transcript.whisperx[14].end 317.937
transcript.whisperx[14].text 對 因為那些我們輸入的資料第一個可能資料機密或外洩我們政府的資料不希望流到台灣之外那另外就是說我們在司法上有沒有管轄權如果我們用的是那個在海外的這些資料中心其實我們報案以前大詐等等所以我就說我們打算做自己的
transcript.whisperx[15].start 318.597
transcript.whisperx[15].end 333.529
transcript.whisperx[15].text 所以我們一定要有自己的資料中心那第一步要使用的可能就是我們這些政府單位都必須用到那個國內的這些資料中心所以我們是從這個方向我們跟民間的企業像那個像鴻海等所以其實AI它有
transcript.whisperx[16].start 334.369
transcript.whisperx[16].end 354.655
transcript.whisperx[16].text 因為電力的問題 算力需要大的電力所以我們高雄現在 當然鴻海來高雄我們也非常的感謝就是電力 算力 再來就是純力 運力那你的資料中心至少純力 是不是應該也要佈局
transcript.whisperx[17].start 355.62
transcript.whisperx[17].end 382.572
transcript.whisperx[17].text 是 當然那包括就是交換中心算力跟存力的連結這個都必須要有資料中心跟交換中心去做連結是那這樣子整個佈局才會比較穩定那都是我們自己佈局的也才比較不會有治安 國安的問題是 沒錯所以這個部分我是希望說書畫部能夠
transcript.whisperx[18].start 384.052
transcript.whisperx[18].end 411.328
transcript.whisperx[18].text 設計一些比較具體的讓國人知道那包括就是像高雄現在的亞洲資產中心比如說台北金融中心的實體在台北最豐富嘛那金融中心的數位化它的data的數位化事實上亞洲資產中心這裡就是一個很好的地方所以也就是說你把
transcript.whisperx[19].start 412.805
transcript.whisperx[19].end 435.456
transcript.whisperx[19].text RWA這些把它數位化數位化之後那其實亞洲資產中心這個地方應該就是可以規劃我們的所有的金融業務的純利數位化在亞洲資產中心這個地方我也希望說數化部可以做一下規劃那另外就是說剛剛
transcript.whisperx[20].start 439.368
transcript.whisperx[20].end 456.983
transcript.whisperx[20].text 齊邁市長現在在亞利桑那嘛對不對就是說這個戰略三角事實上我們除了硬體之外軟體像矽谷或者是舊金山灣區那部長也提過現在有很多移到德州那就是說這一些AI應用
transcript.whisperx[21].start 458.308
transcript.whisperx[21].end 484.503
transcript.whisperx[21].text 我們將來希望AI for 百工百業但是for 百工百業呢它必須要有一個比較強的輔導的AI應用的團隊來輔導百工百業進入AI的領域那民間現在各公司當然都會各顯神通去努力啦那國家在塑化部的角度有沒有類似這樣一個AI應用的大引擎
transcript.whisperx[22].start 485.131
transcript.whisperx[22].end 504.811
transcript.whisperx[22].text OK我們現在速發部我們的政策是這樣子我們有五大政策工具分別是算力資料人才行銷以及資金那因為我們認為說像這種AI這種軟體技術進步太快如果凡事都要由政府來主導的話政府的運作速度會比較慢那我們是希望
transcript.whisperx[23].start 506.127
transcript.whisperx[23].end 534.725
transcript.whisperx[23].text 我們政府的職責是創造一個生態系以後讓這個民間的公司可以健康的發展事實上台灣是有相當不錯的軟體產業像我們知道的那個趨勢訓練完美移動這個都在都是國際型的公司都是用AI的公司而且他們都是有龐大獲利的公司那我們希望說除了這可以招商到台灣對多幾家像這樣子可以走入國際的AI公司我們希望能培養出來所以我之前有跟
transcript.whisperx[24].start 535.97
transcript.whisperx[24].end 556.164
transcript.whisperx[24].text 文化部建議過一件事情我覺得我們書畫部可以參考是之前我們所有的電影的投資是以前文化部是用補助不是用投資是而用補助就是說我可能一百元兩百元我準備要補助處理對搞不好就是一開始這樣後來不知道是所以後來
transcript.whisperx[25].start 557.265
transcript.whisperx[25].end 579.375
transcript.whisperx[25].text 我就跟他們建議說你應該用投資的角度所以現在文化部有一個文策院文策院就是說我不是純粹用補助的角度我是用投資的角度這樣用補助的角度會讓有些人故意要找查的或故意要唱衰的他會說你這個都是圖利這個就很討厭也很麻煩
transcript.whisperx[26].start 580.816
transcript.whisperx[26].end 610.006
transcript.whisperx[26].text 那你用投資的角度就是說你現在有100億兩天變200億你現在有1000億兩天變2000億這種角度對國家也好對產業的發展也好是沒錯那包括我們的國發基金對我是建議就是說數化部應該去思考一下說如何我剛剛提到了這個AI應用的大引擎是那包括我們自己內部的培養是包括整合各大學變成AI人才培育基地是
transcript.whisperx[27].start 610.686
transcript.whisperx[27].end 638.825
transcript.whisperx[27].text 或者是說吸納國外的這些已經有具體的而且有經驗的而且有能力的大公司有可能到台灣來投資這就是互相的嘛一方面是招商存錢 招商一方面是用國家的角度去投資把這些AI應用的大引擎扣到台灣來那像現在舊金灣食育他們那邊有很多的AI獨角獸他們是否不同的項目嘛
transcript.whisperx[28].start 639.845
transcript.whisperx[28].end 658.274
transcript.whisperx[28].text 我們如果國家不管是我們一起投資或是招商來至少國家有這樣子一個佈局未來所有的AI應用的大的引擎或者是大的公司在台灣可以更多這就是我們的目標對這個部分目標不錯啦事務部本來就有設定這樣子的目標那大概
transcript.whisperx[29].start 664.797
transcript.whisperx[29].end 690.993
transcript.whisperx[29].text 那個進度齁 我希望說如果有機會的話 那個蘇華部可以幫忙整理一些進度那我們一方面也可以來了解這個目標實現的機會有多大啦或者是速度有多快時間差不多啦 好那重點就是說我們最後一個簡單的結論啦這個大家都會講到黃仁勳 他說莫定力已到了盡頭啦所以這個加倍已經
transcript.whisperx[30].start 692.674
transcript.whisperx[30].end 717.998
transcript.whisperx[30].text 已經算是小case了將來是加數十倍數百倍都不一定所以我是希望說這個部分希望說我們蘇化部可以做這樣的規劃也希望說那個部長整理一下資料實際下也讓我對這一部分有更多的了解那就拜託那個部長請蘇化部整理一下資料了解一下這些大引擎動作進度到哪裡好 謝謝委員的提醒與支持好 謝謝我們謝謝
transcript.whisperx[31].start 721.041
transcript.whisperx[31].end 722.301
transcript.whisperx[31].text 許智傑委員的發言