
wutantang
创作者
一边哼唱练 AI 专业英语,一边熟记机器人研发底层理论,备考术语、自研陪伴智能体两不误,用听歌的轻松方式搞定造 AI 必备英文与专业常识。
方言歌词
[ti:Lyric Version (版本2)] [ar:妙音AI] [00:00.47]Deep [00:00.77]learning [00:01.25]lets [00:01.53]computational [00:03.03]models [00:03.52]stand, [00:04.40]Stacked [00:05.01]processing [00:05.82]layers [00:06.32]form [00:06.78]their [00:07.20]own [00:07.68]band, [00:08.08]Learn [00:08.39]data’ [00:08.79]s [00:08.81]shapes, [00:09.46]abstraction [00:10.85]tier [00:11.21]by [00:11.56]tier, [00:12.16]Decode [00:12.84]hidden [00:13.32]features [00:13.90]year [00:14.33]after [00:14.62]year. [00:16.19]It [00:16.32]lifts [00:16.59]the [00:16.80]benchmark [00:17.43]of [00:17.63]the [00:17.87]cutting-edge [00:18.85]way, [00:19.76]Speech [00:20.20]recognition [00:21.36]finds [00:21.78]a [00:21.95]brighter [00:22.68]day, [00:23.71]Spot [00:23.97]objects’ [00:24.76]form, [00:25.21]detect [00:25.66]where [00:25.95]targets [00:26.91]lay, [00:27.79]Drug [00:28.20]research, [00:29.00]genomes [00:29.48]walk [00:29.76]a [00:29.94]new [00:30.25]highway. [00:31.79]Big [00:32.01]datasets [00:32.97]hide [00:33.49]complex [00:33.97]structured [00:34.57]design, [00:34.77]Backprop [00:35.12]guides [00:37.58]params [00:38.09]to [00:38.35]redefine, [00:39.43]From [00:39.67]last [00:40.05]layer’ [00:40.45]s [00:40.87]data [00:41.61]build [00:41.86]the [00:42.04]next [00:42.39]outline, [00:43.60]Tweak [00:44.13]inner [00:44.86]values [00:45.61]till [00:45.87]the [00:46.11]model [00:46.85]align. [00:47.71]ConvNet [00:48.67]breaks [00:49.14]limits [00:49.62]for [00:49.89]pic [00:50.45]and [00:50.92]video [00:51.87]sight, [00:52.47]Speech [00:52.92]and [00:53.29]audio [00:53.95]gain [00:54.49]brand-new [00:55.47]insight, [00:56.45]Recurrent [00:57.20]nets [00:57.92]unlock [00:58.44]sequential [00:59.93]rhyme, [01:00.73]Text [01:00.95]and [01:01.21]spoken [01:01.77]words [01:03.05]find [01:03.76]their [01:04.24]perfect [01:04.95]time.
原版歌词
[ti:Lyric Version (版本2)] [ar:妙音AI] [00:00.47]Deep [00:00.77]learning [00:01.25]lets [00:01.53]computational [00:03.03]models [00:03.52]stand, [00:04.40]Stacked [00:05.01]processing [00:05.82]layers [00:06.32]form [00:06.78]their [00:07.20]own [00:07.68]band, [00:08.08]Learn [00:08.39]data’ [00:08.79]s [00:08.81]shapes, [00:09.46]abstraction [00:10.85]tier [00:11.21]by [00:11.56]tier, [00:12.16]Decode [00:12.84]hidden [00:13.32]features [00:13.90]year [00:14.33]after [00:14.62]year. [00:16.19]It [00:16.32]lifts [00:16.59]the [00:16.80]benchmark [00:17.43]of [00:17.63]the [00:17.87]cutting-edge [00:18.85]way, [00:19.76]Speech [00:20.20]recognition [00:21.36]finds [00:21.78]a [00:21.95]brighter [00:22.68]day, [00:23.71]Spot [00:23.97]objects’ [00:24.76]form, [00:25.21]detect [00:25.66]where [00:25.95]targets [00:26.91]lay, [00:27.79]Drug [00:28.20]research, [00:29.00]genomes [00:29.48]walk [00:29.76]a [00:29.94]new [00:30.25]highway. [00:31.79]Big [00:32.01]datasets [00:32.97]hide [00:33.49]complex [00:33.97]structured [00:34.57]design, [00:34.77]Backprop [00:35.12]guides [00:37.58]params [00:38.09]to [00:38.35]redefine, [00:39.43]From [00:39.67]last [00:40.05]layer’ [00:40.45]s [00:40.87]data [00:41.61]build [00:41.86]the [00:42.04]next [00:42.39]outline, [00:43.60]Tweak [00:44.13]inner [00:44.86]values [00:45.61]till [00:45.87]the [00:46.11]model [00:46.85]align. [00:47.71]ConvNet [00:48.67]breaks [00:49.14]limits [00:49.62]for [00:49.89]pic [00:50.45]and [00:50.92]video [00:51.87]sight, [00:52.47]Speech [00:52.92]and [00:53.29]audio [00:53.95]gain [00:54.49]brand-new [00:55.47]insight, [00:56.45]Recurrent [00:57.20]nets [00:57.92]unlock [00:58.44]sequential [00:59.93]rhyme, [01:00.73]Text [01:00.95]and [01:01.21]spoken [01:01.77]words [01:03.05]find [01:03.76]their [01:04.24]perfect [01:04.95]time.
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