1
00:00:00,040 --> 00:00:07,520
So I'm now running with this powerful model GPT, and hopefully you're either doing the same or you're
所以我现在正在使用这个强大的 GPT 模型，希望您也能这样做，或者您正在这样做

2
00:00:07,520 --> 00:00:13,520
using a smaller model like Phi 3 or 1 of the gamma variants, or perhaps something from llama, which
使用较小的模型，例如 Phi 3 或 1 的 gamma 变体，或者可能来自 llama 的模型，

3
00:00:13,560 --> 00:00:14,720
is made by meta.
是由元制作的。

4
00:00:14,960 --> 00:00:17,360
And I'm going to try and use this for a true purpose.
我将尝试将其用于真正的目的。

5
00:00:17,400 --> 00:00:19,600
I'm going to say, um, hi.
我要说，嗯，嗨。

6
00:00:20,200 --> 00:00:24,320
Uh, I'm trying to learn Spanish.
呃，我正在努力学习西班牙语。

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00:00:24,960 --> 00:00:27,600
I'm a total beginner.
我完全是个初学者。

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00:00:28,480 --> 00:00:31,280
Please have a conversation.
请进行对话。

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00:00:31,960 --> 00:00:38,720
A con with me as my Spanish tutor.
我作为我的西班牙语导师的骗局。

10
00:00:39,480 --> 00:00:39,880
All right.
好的。

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00:00:39,880 --> 00:00:40,960
Let's see how it does.
让我们看看它是如何实现的。

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00:00:41,200 --> 00:00:45,960
And this is the kind of thing that you might see in a commercial app like Duolingo.
这就是您可能会在 Duolingo 这样的商业应用程序中看到的情况。

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00:00:46,600 --> 00:00:51,800
First of all, notice that it starts by describing its thought process in this different color, in
首先，请注意，它首先用这种不同的颜色描述其思维过程，在

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00:00:51,800 --> 00:00:53,000
this gray color here.
这里的灰色。

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00:00:53,160 --> 00:00:56,080
And then we get the final answer.
然后我们就得到了最终的答案。

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It says, Hola, soy espanol.
上面写着，你好，西班牙大豆。

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00:00:59,200 --> 00:01:00,580
I forgive my horrible accent.
我原谅我可怕的口音。

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I assure you I am significantly better with Llms than I am with Spanish.
我向你保证，我的法学硕士比西班牙语好得多。

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00:01:06,820 --> 00:01:07,660
Uh, all right.
呃，好吧。

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00:01:07,660 --> 00:01:12,220
And you can see it says uh, yo or LA and it wants me to respond.
你可以看到它说“呃，哟”或“洛杉矶”，它希望我做出回应。

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00:01:12,260 --> 00:01:13,900
And so I could say, Hola.
所以我可以说，你好。

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00:01:14,700 --> 00:01:24,700
Um, may I add, uh, uh, and then, uh, you could see that it says data.
嗯，我可以补充一下，呃，呃，然后，呃，你可以看到它说的是数据。

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00:01:25,220 --> 00:01:30,860
So it will gradually take you through the process of having a beginner level conversation in Spanish.
因此，它将逐步引导您完成初级西班牙语对话的过程。

24
00:01:30,860 --> 00:01:35,740
And the great thing about this is that this is quite similar to the kind of functionality that you might
这样做的好处是，这与您可能会使用的功能非常相似

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find in an app.
在应用程序中查找。

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So I wanted to do this to show you that right off the bat, you can start getting actual value from
所以我想这样做是为了向您展示，您可以立即开始从中获得实际价值

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00:01:43,140 --> 00:01:48,260
running an open source AI large language model locally on your computer.
在您的计算机上本地运行开源 AI 大语言模型。

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Uh, even if you speak terrible Spanish like me.
呃，即使你像我一样说着糟糕的西班牙语。

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And hopefully I'll get better over time.
希望随着时间的推移我会变得更好。

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Next time I record this, I'm gonna have a great accent.
下次我录这个的时候，我的口音会很重。

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Uh, so anyways, have fun with it.
呃，无论如何，玩得开心吧。

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Use this.
用这个。

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00:01:58,380 --> 00:01:59,950
Try out different models.
尝试不同的模型。

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Try exploring how the larger size models are able to be more intelligent in how they interact with you.
尝试探索较大尺寸的模型如何能够更智能地与您互动。

35
00:02:06,430 --> 00:02:08,110
See these thinking type models?
看到这些思维型模型了吗？

36
00:02:08,110 --> 00:02:10,910
We'll be talking a lot more about them in the coming days.
未来几天我们将更多地讨论它们。

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00:02:11,070 --> 00:02:17,150
Get some exposure to this and enjoy the fact that you are harnessing the power of a large language model
对此进行一些接触并享受您正在利用大型语言模型的力量这一事实

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00:02:17,150 --> 00:02:18,870
locally on your computer.
在您的计算机本地。

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00:02:18,910 --> 00:02:24,070
Now, I'm hoping you've had a really enjoyable rabbit hole experience of trying out different models,
现在，我希望您在尝试不同的模型时获得了非常愉快的兔子洞体验，

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00:02:24,070 --> 00:02:27,750
experimenting, and being enamored by the power of these things.
尝试并被这些东西的力量所迷住。

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00:02:27,750 --> 00:02:29,030
But I have to pull you back.
但我必须把你拉回来。

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00:02:29,070 --> 00:02:34,630
It is time now for us to talk about everything that I've got in store for you for the next eight weeks,
现在是时候让我们谈谈我在接下来的八周内为你准备的一切了，

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00:02:34,790 --> 00:02:38,710
and this is a timeline that I'll be showing you frequently.
这是我会经常向您展示的时间表。

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00:02:38,710 --> 00:02:44,270
It's a timeline that shows you where you start over on the left, and the eight weeks that I have in
这是一个时间线，向您显示从左侧开始的位置，以及我的八周时间

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00:02:44,270 --> 00:02:45,030
store for you.
为您存储。

46
00:02:45,510 --> 00:02:49,590
Tomorrow I'm going to go through this in a lot more detail, but there's going to be this week, which
明天我将更详细地讨论这个问题，但这周将会有，

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00:02:49,590 --> 00:02:50,910
will be more foundational.
将会更加基础。

48
00:02:50,950 --> 00:02:53,110
Next week is about frontier models.
下周是关于前沿模型的。

49
00:02:53,110 --> 00:02:55,910
The week after is about open source models.
接下来的一周是关于开源模型的。

50
00:02:55,910 --> 00:02:59,570
Then it's about selecting the right model for the task at hand.
然后是为手头的任务选择正确的模型。

51
00:02:59,810 --> 00:03:01,170
Then it will be about rag.
然后就是关于抹布的。

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00:03:01,170 --> 00:03:04,330
We'll go deep on rag, one of the hottest topics in AI.
我们将深入探讨 rag，这是人工智能领域最热门的话题之一。

53
00:03:04,730 --> 00:03:09,730
Then we will fine tune a frontier model and then fine tune an open source model.
然后我们会微调一个前沿模型，然后微调一个开源模型。

54
00:03:09,730 --> 00:03:15,170
And finally, I will introduce a genetic AI in the final week of our eight week series.
最后，我将在八周系列的最后一周介绍基因人工智能。

55
00:03:15,170 --> 00:03:20,850
And at that point, you'll be able to wave a flag and say, I am now an LLM engineer.
到那时，你就可以挥舞旗帜说，我现在是一名法学硕士工程师。

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I have reached this milestone to mastery, and I've built a comprehensive curriculum for you throughout
我已经达到了精通的里程碑，并且我已经为您构建了全面的课程

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the next eight weeks.
接下来的八周。

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And one of the things I love about it is it really builds and builds and builds.
我喜欢它的原因之一是它确实可以构建、构建、构建。

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We start by covering a range of different models, different llms, open source and closed source.
我们首先介绍一系列不同的模型、不同的 llms、开源和闭源。

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Then we cover a lot of toolkits, libraries, frameworks that use those LMS things like hugging face
然后我们介绍了很多使用 LMS 的工具包、库、框架，比如拥抱脸

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00:03:44,690 --> 00:03:50,730
gradio for user interfaces, lang chain weights and biases, modal com, and then building on top of
用户界面的梯度、语言链权重和偏差、模态 com，然后构建在

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that, we apply different techniques to getting the most performance out of LMS techniques like Rag,
我们应用不同的技术来充分发挥 Rag 等 LMS 技术的性能，

63
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fine tuning and agents.
微调和代理。

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But by far the best thing about this course is the building.
但到目前为止，这门课程最好的地方是建筑。

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00:04:03,870 --> 00:04:07,230
I'm a big believer in learning by doing.
我坚信边做边学。

66
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I think the best way to learn is by building great commercial projects, and that we will do from multimodal
我认为最好的学习方式是建立伟大的商业项目，我们将从多式联运中做到这一点

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00:04:14,110 --> 00:04:20,510
projects to commercial consumer applications, to something that's more technical about porting code
项目到商业消费者应用程序，到一些关于移植代码更具技术性的东西

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00:04:20,510 --> 00:04:25,550
from one language to another, to stuff that involves vectors and training with lots of charts.
从一种语言到另一种语言，到涉及向量和大量图表训练的东西。

69
00:04:25,550 --> 00:04:29,630
And finally, a whopper of a commercial project at the end.
最后，最后是一个巨大的商业项目。

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So be prepared for lots of juicy building.
因此，请为大量有趣的建筑做好准备。

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And you may have noticed that I have other courses out there.
您可能已经注意到我还有其他课程。

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00:04:35,830 --> 00:04:37,310
I'm wondering how this fits in.
我想知道这是如何适应的。

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Or maybe you've taken some of those other courses, and the answer is that this course is complementary
或者也许您已经学习了其他一些课程，答案是这门课程是补充性的

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00:04:41,870 --> 00:04:44,070
to the others, and you can take them in any order.
给其他人，您可以按任何顺序接受它们。

75
00:04:44,070 --> 00:04:46,470
There is perhaps a natural order.
也许存在一种自然秩序。

76
00:04:46,630 --> 00:04:51,950
This course is quite foundational and lays the groundwork, so it might be better to take this first,
这门课程非常基础，奠定了基础，所以最好先学习这门课程，

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00:04:51,950 --> 00:04:53,510
at least the first couple of weeks of it.
至少是前几周。

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00:04:53,510 --> 00:04:55,630
But it doesn't matter if you've taken up on the other ones.
但如果你已经接受了其他的，那并不重要。

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A gigantic AI, a companion course which is all about applying this kind of LLM functionality to different
一个巨大的人工智能，一个配套课程，它是关于将这种 LLM 功能应用到不同的领域

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00:05:03,000 --> 00:05:05,120
Agentic use cases and frameworks.
代理用例和框架。

81
00:05:05,120 --> 00:05:09,440
And you can see I've put that there just slightly higher up, because it's it's sort of taking it to
你可以看到我把它放在稍微高一点的位置，因为它有点把它带到了

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00:05:09,480 --> 00:05:16,480
maybe the next step, but you could take identify first and then LLM engineering if you preferred AI
也许是下一步，但如果你更喜欢人工智能，你可以先进行识别，然后再进行法学硕士工程

83
00:05:16,520 --> 00:05:21,560
in production is a very different course that I've got that takes whatever you build and allows you
在生产中是一个非常不同的课程，我有它需要你构建的任何东西并允许你

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00:05:21,560 --> 00:05:27,880
to deploy it at scale in a production setting on a cloud platform like AWS.
在 AWS 等云平台上的生产环境中大规模部署它。

85
00:05:28,480 --> 00:05:34,600
And then I also have a briefing for founders and leaders, which is intended for a non-technical audience.
然后我还会向创始人和领导者介绍情况，这是针对非技术受众的。

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00:05:34,600 --> 00:05:40,360
It's commercial first and foremost, but I will say actually that I strongly recommend that even technical
它首先是商业性的，但实际上我会说，我强烈建议即使是技术性的

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00:05:40,360 --> 00:05:45,400
people do consider taking this briefing, because I think it's a super power for tech.
人们确实考虑参加这次简报，因为我认为这是科技的超级力量。

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00:05:45,400 --> 00:05:51,200
People like us to also have a good sense of the commercial applications of Llms.
像我们这样的人也对法学硕士的商业应用有很好的了解。

89
00:05:51,320 --> 00:05:55,640
And so again, the course is complement each other, take them in whatever order you like.
再说一次，这些课程是相辅相成的，可以按照你喜欢的顺序学习。

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00:05:55,680 --> 00:06:00,420
Maybe it's most natural to start with LM engineering, but it doesn't matter if you've already done
也许从 LM 工程开始是最自然的，但如果您已经完成了也没关系

91
00:06:00,420 --> 00:06:01,940
the others and you're coming to it now.
其他人，你现在就来吧。

92
00:06:02,140 --> 00:06:08,460
And most importantly, I've designed this curriculum and this course so that it will appeal to everyone.
最重要的是，我设计了这个课程和课程，以便它能够吸引每个人。

93
00:06:08,460 --> 00:06:13,820
If you are a complete beginner and you're coming to AI for the first time, prepare to be astonished.
如果您是一个完全的初学者，并且是第一次接触人工智能，请准备好感到惊讶。

94
00:06:13,820 --> 00:06:16,420
But this will be a nice smooth on ramp for you.
但这对你来说将是一个很好的平滑坡道。

95
00:06:16,420 --> 00:06:20,820
But also, if you're a pro, then sure, some of the stuff in weeks one and two are going to be things
而且，如果你是一名职业选手，那么当然，第一周和第二周的一些内容将会是

96
00:06:20,820 --> 00:06:21,460
you already know.
你已经知道了。

97
00:06:21,500 --> 00:06:22,340
Absolutely.
绝对地。

98
00:06:22,340 --> 00:06:27,460
But I'm hoping to to still tease you with some interesting new content to there'll be something that
但我仍然希望能用一些有趣的新内容来逗弄你，因为会有一些东西

99
00:06:27,460 --> 00:06:28,860
might surprise you.
可能会让你感到惊讶。

100
00:06:28,900 --> 00:06:30,300
Something for everyone.
适合每个人的东西。

101
00:06:30,460 --> 00:06:31,460
That's the plan.
这就是计划。

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00:06:31,740 --> 00:06:35,500
All right, just before we get into it, let me now quickly introduce myself.
好吧，在我们开始之前，让我快速介绍一下自己。

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00:06:35,540 --> 00:06:35,780
Yes.
是的。

104
00:06:35,780 --> 00:06:38,980
So to convince you that I'm actually qualified to talk to you about this.
所以为了让你相信我实际上有资格和你谈论这个。

105
00:06:39,260 --> 00:06:40,380
My name is Ed Donner.
我叫埃德·唐纳。

106
00:06:40,420 --> 00:06:44,700
I am the co-founder and CTO of an AI startup called Nebula.
我是一家名为 Nebula 的人工智能初创公司的联合创始人兼首席技术官。

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00:06:44,900 --> 00:06:46,300
You can check us out at Nebula.
您可以在星云查看我们。

108
00:06:47,580 --> 00:06:52,020
And I spent most of my career at JP Morgan, where I started out in London, which is where I'm from
我职业生涯的大部分时间是在摩根大通度过的，我的起点是伦敦，我来自伦敦

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00:06:52,020 --> 00:06:58,390
originally, and then spent some time in Tokyo and then moved to NYC, which is where I am at right
最初是在东京呆了一段时间，然后搬到了纽约，这就是我右边的地方

110
00:06:58,390 --> 00:06:58,790
now.
现在。

111
00:06:59,150 --> 00:07:04,870
And most recently at JP Morgan, I was a managing director, running a technology team of about 300
最近在摩根大通担任董事总经理，负责管理一支约 300 人的技术团队

112
00:07:04,870 --> 00:07:06,670
software engineers and scientists.
软件工程师和科学家。

113
00:07:06,670 --> 00:07:12,030
And before Nebula, I was the founder and CEO of an AI startup called untapped.
在星云之前，我是一家名为 Untapped 的人工智能初创公司的创始人兼首席执行官。

114
00:07:12,350 --> 00:07:15,190
And this picture is this is a magical moment for me.
这张照片对我来说是一个神奇的时刻。

115
00:07:15,190 --> 00:07:20,950
This is a picture from a Times Square billboard on the day that the acquisition of my AI startup was
这是我的人工智能初创公司被收购当天时代广场广告牌上的一张照片

116
00:07:20,950 --> 00:07:23,590
announced a couple of years ago, which was really great.
几年前宣布的，这真的很棒。

117
00:07:23,670 --> 00:07:26,670
Uh, and in case you don't believe me, I can prove it.
呃，如果你不相信我，我可以证明这一点。

118
00:07:26,710 --> 00:07:29,430
If you squint and you look super carefully.
如果你眯着眼睛看得非常仔细。

119
00:07:29,430 --> 00:07:34,990
Near the bottom right of that picture is, in fact, a picture of me in there, just to prove that it
事实上，在那张照片的右下角附近有一张我在那里的照片，只是为了证明它

120
00:07:34,990 --> 00:07:36,910
was, in fact, me, uh, with this startup.
事实上，是我，呃，和这家初创公司一起。

121
00:07:36,910 --> 00:07:39,430
But that was my my moment in Times Square.
但这是我在时代广场的时刻。

122
00:07:39,550 --> 00:07:43,230
And I think it's obligatory with these things to have some kind of personal life picture.
我认为对这些事情有必要有某种个人生活的描述。

123
00:07:43,230 --> 00:07:45,830
So here's me in front of a plane that I just flew.
这是我站在我刚刚驾驶的飞机前。

124
00:07:45,990 --> 00:07:51,230
And you might think I'm showing this because I'm very skilled at flying planes, but but quite on the
你可能认为我展示这个是因为我非常擅长驾驶飞机，但实际上

125
00:07:51,230 --> 00:07:58,570
contrary, uh, my my great talent when it comes to all things LM is only surpassed by my complete inability
相反，呃，我在LM的所有事情上的伟大天赋只能被我完全的无能所超越

126
00:07:58,570 --> 00:08:02,050
to do anything that requires hand-eye coordination.
做任何需要手眼协调的事情。

127
00:08:02,210 --> 00:08:08,370
So if you're walking onto a plane and you glance into the cockpit and you see that it's me there holding
所以，如果你走上飞机，朝驾驶舱一看，你会发现是我抱着

128
00:08:08,370 --> 00:08:12,570
the yoke, then you want to be looking for a parachute really quickly.
轭，那么你想尽快找到降落伞。

129
00:08:12,770 --> 00:08:19,090
Uh, but but if you've come to some online course and it's on LMS and you see that it's this guy giving
呃，但是如果你参加过 LMS 上的一些在线课程，你会发现是这个人在提供

130
00:08:19,090 --> 00:08:21,810
the talk on LMS, then congratulations.
关于 LMS 的演讲，那么恭喜你。

131
00:08:22,010 --> 00:08:23,570
That is my sweet spot.
那是我的甜蜜点。

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You've come to the right place.
您来对地方了。

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Let's get on with it.
让我们继续吧。

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I will just mention also that that one cool thing about that bottom right hand picture is that I actually
我还要提一下，右下角那张照片的一件很酷的事情是，我实际上

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live right there as well.
也住在那里。

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It's strangely not many people live in Times Square, but I live like a block from Times Square, right
奇怪的是，住在时代广场的人并不多，但我住的地方离时代广场只有一个街区，对吧

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behind where that hard Rock cafe guitar is.
在硬摇滚咖啡馆吉他所在的地方后面。

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I'm kind of behind there, and I'm looking out at that right now.
我有点落后了，现在我正在看着它。

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So.
所以。

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So you're sort of picture me looking out where those two lines meet right now, and the other place
所以你有点像我看着这两条线现在交汇的地方，以及另一个地方

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where I am is on LinkedIn.
我在 LinkedIn 上。

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And I gotta warn you, I'm gonna go on about this, like, a hundred times.
我必须警告你，我会继续谈论这个，大概一百遍。

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I love connecting with people on LinkedIn.
我喜欢在 LinkedIn 上与人交流。

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Some people are coy about connecting on LinkedIn.
有些人对于在 LinkedIn 上联系感到羞涩。

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They're like, you can tell me where we met and I might connect with you.
他们就像，你可以告诉我我们在哪里见面，我可能会和你联系。

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I'm not like that at all.
我根本不是那样的人。

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If if you want to connect with me, then I'm thrilled.
如果您想与我联系，我会很高兴。

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Uh, send me an invite and I'll connect.
呃，向我发送邀请，我会联系。

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You can say hi and I'll say hi back.
你可以打个招呼，我也会打个招呼。

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It's not an agent.
这不是代理。

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It'll really be me.
真的会是我。

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Uh, you could also just, uh, just just send the connect and I'll accept it.
呃，你也可以，呃，只是发送连接，我会接受它。

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Um, uh, whilst it's not an agent, I do reserve the right occasionally to copy and paste some of my
嗯，呃，虽然不是代理，但我确实保留偶尔复制和粘贴我的一些内容的权利

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answers, because I do get through quite a lot of them.
答案，因为我确实解决了很多问题。

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But I will always for sure interact with you and I love it.
但我肯定会永远与你互动，我喜欢它。

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And also, if you post information about the course, if you post your progress through the course or
此外，如果您发布有关课程的信息，如果您发布课程进度或

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projects that you build, and you tag me on your LinkedIn post, that I will come in and weigh in and
你构建的项目，你在 LinkedIn 帖子上标记我，我会参与进来并权衡

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add to it.
添加到它。

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And I find it such a fabulous way to amplify your achievement, and also to get other people in the
我发现这是一种绝佳的方式来扩大你的成就，也可以让其他人加入进来

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community, other data scientists, seeing it and responding as well.
社区、其他数据科学家也看到了这一点并做出了回应。

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So please do, do do that liberally.
所以请一定要慷慨地这样做。

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It sometimes takes me a few days, but I will get there.
有时我需要几天时间，但我会到达那里。

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Tag me and let me weigh in.
标记我并让我权衡一下。

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And so, in summary, I'm a software engineer, a data scientist, an entrepreneur, and a leader in
因此，总而言之，我是一名软件工程师、数据科学家、企业家和领导者

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the field of AI.
人工智能领域。

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But there's something else I do as well.
但我还做其他事情。

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In 2024, a friend of mine persuaded me to make a Udemy course teaching other people about AI.
2024 年，我的一位朋友说服我制作一门 Udemy 课程，向其他人教授人工智能知识。

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And it was, of course, the first version of this course, LM engineering, and I made a few others
当然，这是这门课程的第一个版本，LM 工程，我还制作了其他一些版本

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since, and I've been so lucky that they've been quite successful.
从那时起，我很幸运，他们非常成功。

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And there's now more than a quarter of a million people taking my Udemy courses.
现在有超过 25 万人参加我的 Udemy 课程。

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And it's been a total joy, and I love interacting with people on it.
这是一种完全的快乐，我喜欢与人互动。

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It's also such a great opportunity for everyone on it because as I say, you can post on LinkedIn,
这对每个人来说也是一个很好的机会，因为正如我所说，你可以在 LinkedIn 上发帖，

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I can weigh in and it has such a multiplier effect in the community to get everyone involved in your
我可以参与其中，这在社区中具有倍增效应，可以让每个人都参与到您的活动中

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journey.
旅行。

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And that's why I urge you to post about it and enjoy the journey, enjoy the experience, and share
这就是为什么我敦促您发布有关它的信息并享受这段旅程，享受这段经历并分享

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it with all of us.
与我们所有人一起。