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(中英附文稿)AI不只帮你写文案:吴恩达谈从重复劳动到主动解

字幕摘录

时间英文中文
0:00There's been a lot of misinformation about AI.对AI的误导很多.
0:03This is Andrew.这是安德鲁。
0:04他共同创办了Google Brain和Coursera.
0:07His machine learning course has reached millions of learners,他的机器学习课程 已经达到了数百万的学习者,
0:09and he is one of the most influential voices in AI today.他是今天AI最有影响力的声音之一。
0:13So a handful of leading AI companies所以,少数主要的AI公司
0:14have been very loud voices of fear-mongering around AI在AI周围发出恐惧的声音
0:18to try to get regulations passed.试图让 条例通过。
0:20This drumbeat of fear-based messaging恐怖讯息的鼓声
0:22has skewed societal's perception扭曲了社会观念
展开字幕全文(939 条)
序号英文中文
1There's been a lot of misinformation about AI.对AI的误导很多.
2This is Andrew.这是安德鲁。
3他共同创办了Google Brain和Coursera.
4His machine learning course has reached millions of learners,他的机器学习课程 已经达到了数百万的学习者,
5and he is one of the most influential voices in AI today.他是今天AI最有影响力的声音之一。
6So a handful of leading AI companies所以,少数主要的AI公司
7have been very loud voices of fear-mongering around AI在AI周围发出恐惧的声音
8to try to get regulations passed.试图让 条例通过。
9This drumbeat of fear-based messaging恐怖讯息的鼓声
10has skewed societal's perception扭曲了社会观念
11to be really negative on AI.对AI非常负面。
12People talk to me about data centers and job loss.人们和我谈论数据中心和失业问题。
13Maybe AI could do 30, 40 percent of many jobs.也许AI能做30%,40%的工作。
14And what that means is, well, that 60 percent that a human does这意味着 人类60%的工作
15has become even more valuable.已经变得更加宝贵。
16What about loss of human control over AI?对AI失去人的控制怎么办?
17I think about something else that we can't control.我想到别的东西,我们不能控制。
18I think you're one of the voices in AI我觉得你是AI里的声音之一
19who comes with a huge background有着巨大背景的人
20and machine learning and teaching AI,以及机器学习和教学
21and also you're a positive voice,而且你是一个积极的声音,
22because this is something that I've been seeing,因为这是我见过的
23especially this summer, how poor lives the society has become,特别是今年夏天 社会的贫穷生活
24especially on social media, when I'm posting about AI尤其是在社交媒体上 当我发布AI时
25and people talk to me about data centers and job loss.人们和我谈论数据中心和失业
26Why do you think this wave started recently?你觉得这波为什么是最近才开始的?
27What do you think the causes are?你觉得原因是什么?
28There's been a lot of misinformation about AI,关于AI有很多错误信息,
29and the root cause of a lot of this is an unfortunate attempt原因很多都是不幸的尝试
30that started two, three years ago两三年前开始的
31of, I think, PR and registry capture.公关和登记记录
32It turns out that one of the most valuable things原来最有价值的东西之一
33in AI right now is the giant AI models,在AI现在 是巨大的AI模型,
34giant large-language models that some companies have trained.一些公司训练的大型大语言模型。
35But if you spend billions of dollars training a model,但如果你花几十亿美元训练一个模特儿
36it's really inconvenient if someone else trains a model如果别人训练一个模特儿 实在太不方便了
37and wants to give it to anyone in the world to use for free.并想把它给世界上的任何人免费使用.
38So a handful of leading AI companies, I think, as you know,所以,一些主要的AI公司,我认为,你知道,
39have been very loud voices, fear-mongering around AI在AI周围发出非常响亮的声音 恐惧的恐惧
40to try to get regulations passed,试图通过条例,
41to create an unfair playing field that favors incumbents创造一个有利于现任者的不公平竞争环境
42so that we all have to pay a high toll for use of AI,因此,我们都必须付出高昂的代价来使用AI,
43while stymieing the other teams,一方面阻击其他队伍,
44be it researchers or other companies,无论是研究者还是其他公司,
45that want to just give away open way to open source models想要给开源模型开辟道路
46that anyone could use much cheaper.任何人都可以使用便宜得多。
47Unfortunately, fear-mongering works.不幸的是,恐惧的侵扰是有效的。
48When you go and say AI is like nuclear weapons,当你去说AI就像核武器,
49which is an analogy that has no basis in fact,这是没有根据的比喻,
50what do they have to even do with each other?他们之间有什么关系?
51Or when you go around and cherry pick cases of AI,或者当你绕圈子去 和樱桃挑AI的案件,
52you know, making a misstep做错事
53and make it much bigger than it is.让它比它大得多。
54Or even spread misinformation about how AI uses data centers,甚至散布关于AI如何使用数据中心的错误信息,
55uses a lot more water than the actual reality.用的水比现实多得多
56This drumbeat of fear-based messaging恐怖讯息的鼓声
57has skewed societal's perception扭曲了社会观念
58to be really negative on AI, which is unfortunate对AI非常负面,这是不幸的
59because this is slowing down American adoption in AI.因为这减缓了美国在AI的收养速度.
60This is making America less competitive.这使得美国的竞争力降低.
61And unless we get the truth about AI out there,除非我们知道AI的真相
62which is that it's fantastic benefit with some problems,这对解决一些问题有好处
63but not nearly the degree to which they're blown up to be,但不是被炸得那么严重
64it will hurt individuals.它会伤害个人。
65I'm gonna read out some of the problems我要宣读一些问题
66that people are highlighting, job loss and inequality.人们正在强调,失业和不平等。
67What do you think?你觉得呢?
68The job apocalypse, the job pocalypse,工作启示录, 工作浮夸,
69this idea that AI will take over 50% of jobs,这个想法,AI将占据50%的工作,
70people will be out of work, rioting in the streets,人们将失业,在街头暴动,
71that's just not gonna happen.那只是不会发生。
72With every wave of technology, including AI,随着每一波技术,包括AI,
73the skills we need to do great work shifts,我们所需要的技术 做伟大的工作转变,
74and so AI is changing job professions.所以AI正在改变职业
75But boy, I wish AI just doesn't work well enough.但是,孩子,我希望AI 只是工作不够好。
76I know that handful of businesses want to hype up AI我知道有几家企业想哄骗AI
77to say, we have super intelligence,说,我们有超级智能,
78or we'll have artificial intelligence or whatever,或者我们有人工智能之类的
79and can do all the stuff that humans do.并且可以做人类做的一切
80I wish AI work better, which is not good enough我希望人工智能工作做得更好 这还不够好
81to make AI do everything a human does.让人工智能做人的一切
82And if you look at the analysis of jobs,如果你看看工作的分析,
83economists, like my friend Eric Brinovson at Stanford,经济学家,像我的朋友埃里克·布里诺夫森 在斯坦福,
84Andy McAfee at MIT,麻省理工学院的安迪·麦卡菲
85economists have analyzed many people's jobs经济学家分析了很多人的工作
86and by breaking it down into individual tasks,并把它分成个人任务,
87and maybe AI could do 30, 40% of many jobs.也许AI能做30%,40%的工作。
88And what that means is, well, that 60% that a human does也就是说,人类60%的工作
89has become even more valuable越来越珍贵
90because it's called an economic compliment,因为这叫做经济赞美,
91so the 30, 40% is now cheaper.因此,30%,40% 现在更便宜。
92And so what will happen is people that use AI,接下来是使用人工智能的人
93maybe people that use AI will replace people也许用人工智能的人会代替别人
94that don't use AI, but AI is not in a position但是AI没有地位
95for the vast majority of jobs to replace people.给绝大多数的工作来代替人。
96Of all the different professions,在不同的职业中
97the one that's most affected by AI now is software engineering现在受AI影响最大的是软件工程
98because AI is actually fantastic at writing code.因为人工智能在写代码方面的确很棒
99And what we see is that the number of job openings我们所看到的是 职位空缺的数量
100in software engineering is up,在软件工程上,
101contrary to what the doom fear mongers would say, right?和末日的恐惧相反 对吧?
102AI is not actually able to replace software engineers,AI实际上无法替换软件工程师,
103and all the good software engineers I know还有我认识的所有优秀的软件工程师
104are busier than ever.比以往任何时候都更忙。
105Now, the flip side of it is,现在,它的反面是,
106if someone's still write code like this 2022如果有人还写这样的代码2022年
107before track GPT, they're in trouble.在追踪GPT之前 他们有麻烦了
108They need new skills, like don't do stuff他们需要新技能,就像不做东西一样
109that 30, 40% of AI can automate.30,40%的人工智能可以自动化.
110You've got to start doing that, let AI do that,你必须开始这样做, 让AI做到这一点,
111but then gain your skills to do the other 60, 70%然后获得技能 做其他60,70%
112that AI cannot do.这是大赦国际不能做的。
113What would your advice be to new graduates?你给新毕业生的建议是什么?
114Cause I talked to Eric on this podcast因为我跟艾瑞克谈过这个播客
115and he was talking about that there's not really他当时在说真的没有
116a lot of impact on the job market,对就业市场影响很大,
117except for, I think he mentioned people from 18 to 25,除了,我想他提到 从18到25,
118who just graduated.谁刚毕业。
119What would be your advice to those people你对这些人的建议是什么?
120who don't have the expertise谁没有专长
121maybe to strategize in their job yet?也许他们的工作有策略吗?
122They can only do manual work that AI can do as well.他们只能做人工工作,而AI也可以做.
123So one real challenge for fresh college grads所以,一个真正的挑战 对于新鲜的大学毕业
124is that the university system is slow to adapt.大学系统适应性很慢
125And so, I love academia.所以,我喜欢学术界。
126I think we should all support academia and universities.我认为我们都应该支持学术界和大学。
127And when AI comes and transforms当AI出现并改变
128the way software is written,写软件的方式,
129universities often take like a year or two大学通常要花一两年时间
130for the faculty to master the skills,以便教职员掌握技能,
131then create new courses,然后创造新的课程,
132get curriculum committee approval or whatever,得到课程委员会的批准或什么的,
133get the faculty senate to vote.让参议院投票
134It just takes years.只是需要几年时间
135And that speed of change in academia学术界的变革速度
136is very poorly matched to the speed of change in AI.与AI的改变速度非常差。
137So sadly, many universities are still teaching students可惜许多大学还在教学生
138to be ready for the jobs of 2022,准备好2022年的工作,
139when we shouldn't even be teaching them我们不应该教他们
140for the jobs of 2026,为2026年的工作,
141we should be teaching them for the jobs of 2028 and beyond.我们应该教他们2028年及以后的工作
142And what this means is the job openings are there.这说明职位空缺就在那里。
143Tons of employers I know just can't find enough skill,我知道很多雇主都找不到足够的技能
144you know, people at any level of seniority.你知道,任何级别的人。
145But it turns out in my office right now,但是现在在我的办公室里
146we have a lot of interns.我们有很多实习生
147There are current college students, fresh college grad,有现在的大学生, 新鲜的大学毕业,
148we also have one high school intern,我们还有一个高中实习生,
149and they're amazing and productive.和它们惊人和生产。
150But the key is they're all very AI native.但关键是他们都是AI本地人
151They all use AI tools to do the things that I could do,他们都用人工智能工具来做我能做的事,
152but then also, you know,还有,你知道,
153lean in to doing the things that humans can do做人类能做的事
154that AI can't for a long time.AI不能在很长一段时间。
155So there's plenty of work for people to do.故众生有余功德.
156But so my advice to fresh college grads但我建议大学毕业
157or the people currently in college is,或者目前大学里的人
158by all means, work hard in classes, you know,在课堂上努力工作
159get good grades, learn from the instructors,学好成绩 向老师学习
160but to the extent that there are still additional skills但只要还有更多的技能
161that the university has not yet adapted to teaching,大学还没有适应教学,
162then find other ways to learn online,然后找其他方法在网上学习,
163无论是来自Coursera还是深入学习AI还是Udemy
164or other places where you can gain the more cutting edge skills,或其他可以获得更先进技能的地方,
165especially AI skills,特别是人工智能,
166that universities have not yet worked on the curricula.大学尚未制定课程。
167Quick pause, because what Andrew just said about workflows暂停一下,因为安德鲁刚才说的工作流程
168connects to something that HubSpot just put out for free.连接到HubSpot刚刚免费推出的东西.
169The thing is, the real opportunity right now问题是,真正的机会,现在
170is not just in the models themselves,不只是模型本身,
171but in what you build on top of them,但你们在他们的上面所创造的,
172how you turn AI from a chat window从聊天窗口打开AI
173into workflows that actually do work for you.进入工作流程 真正为你工作。
174And the good news is,好消息是,我们
175you don't have to start by building a full agent.你不必开始 建立一个完整的代理。
176You can start much simpler with better prompts.你可以用更好的提示开始简单得多。
177HubSpot刚刚发布了高级聊天GPT
178Prompt Engineering Playbook, and the idea is very simple.即时工程游戏本 这个想法很简单
179In seven days, it helps you move from getting generic AI answers7天后,它能帮助你摆脱普通AI的解答
180{\fn黑体\fs22\bord1\shad0\3aHBE\4aH00\fscx67\fscy66\2cHFFFFFF\3cH808080}你更能保持一贯 {\fn黑体\fs22\bord1\shad0\3aHBE\4aH00\fscx67\fscy66\2cHFFFFFF\3cH808080}我很高兴你
181and useful options, because we've all had this moment.和有用的选择,因为我们都有这一刻。
182You type in one vague sentence,你输入一个模糊的句子,
183get something mediocre back,拿些平庸的东西回来
184and then spend the next 20 minutes fixing it yourself.然后再花20分钟自己修
185This playbook is basically built for that exact problem,这本游戏本基本上是为这个问题而建的
186and it walks you through a single progression.它让你经历了一个单一的进化。
187First, you learn how to structure prompts首先,你学会如何构建提示
188with things like role, context, format, and parameters.包括角色、上下文、格式和参数。
189Then it gets more advanced.然后它会更先进。
190Few shot examples, chain of thought reasoning,很少有例子 思想推理链
191more precise prompt structures,更精确的快速结构,
192and ways to make outputs more reliable.以及如何使产出更加可靠。
193What I like is that it doesn't stop at individual prompts.我喜欢的是它不会停止 个别的提示。
194It also shows you how to build reusable AI personas,也告诉你如何建造可重复使用的AI人物,
195modular prompt components,模块快速组件,
196and eventually your own signature prompt engineering system.最后你自己的签名即时工程系统。
197So instead of starting from scratch every time,所以不是每次从零开始
198you're building a repeatable way to work with AI,你正在建立一个可以重复的方式 与AI合作,
199whether you're creating content, analyzing data,你是否正在创建内容 分析数据
200or making business decisions.或做出商业决定。
201The playbook is free, links in the description.游戏本是免费的,在描述中的链接.
202Thanks to HubSpot for sponsoring this video.感谢HubSpot赞助了这段视频.
203And now back to our conversation with Andrew.现在回到我们和安德鲁的谈话
204I want to say one other thing.我想说另外一件事。
205It turns out, if you look at the skill map changes,事实证明,如果你看 技能地图的变化,
206one of the most important changes is最重要的变化之一是
207it's so much easier to build with AI than before.和AI一起建起来比以前容易多了
208When something becomes much easier,当事情变得容易得多,
209a lot more people should do it.更多的人应该这样做。
210And so now, not only should professional software engineers所以现在,不仅专业的软件工程师
211build software with AI,与AI一起构建软件,
212it's becoming much easier for everyone to build with AI,对AI来说,每个人都更容易建起来
213and people that embrace that and do so和接受并接受的人
214will be more productive and will accomplish more,将会更加丰硕,并且更加成功,
215and I think have more fun than the ones that don't.我觉得比那些不开心的人更好玩
216And AI lets you build really fast.人工智能让你建得很快
217So for people that are not just software engineers,所以对于不仅仅是软件工程师的人来说
218but marketers, recruiters, HR professionals,但市场营销者、招聘者、人力资源专业人员,
219operations specialists,业务专家,
220I think if they learn to build with AI,我想如果他们学会和AI一起建设
221they'll really just do much more, whatever the job role is.他们真的会做的更多, 不管工作的角色是什么。
222How do you, by the way, measure the increase in productivity顺便说一句,你怎么衡量生产率的提高?
223when you deploy AI?当你部署AI时?
224Do you have a KPI in your company?你的公司有KPI吗?
225I wish it was a simple answer.我希望这是一个简单的答案。
226I find that the business outcome of AI我发现AI的商业结果
227is more a function of the business更属于企业的功能
228than a function of the AI.而不是大赦国际的职能。
229For some, it may be increased customer growth and retention,对一些人来说,这可能会增加客户的增长和保留,
230or maybe a faster to serve customers,或者更快地为顾客服务
231or it may be increased accuracy in some tasks.也可能提高某些任务的准确性。
232So the KPI tends to be related to the business因此,KPI倾向于与业务有关
233rather than the AI.而不是大赦国际。
234So you can't directly measure just AI,所以你不能直接测量AI
235because it's an interesting thing to do,因为它是一个有趣的事情做,
236because we've been deploying AI actively in my company,因为我们一直在积极部署AI在我的公司,
237and I think for me as a media company,我认为作为一个媒体公司,
238it's probably the amount of views, the output.可能是浏览量 输出量
239It's just interesting how different people measure,有趣的是不同的人如何衡量,
240even revenue, like if you're becoming more effective甚至收入,就像如果你越来越有效
241with how you make money.你如何赚钱。
242Actually, say more.其实,说更多。
243How are you using AI in your business?你怎么在你的生意中使用AI?
244Oh my God.天呐
245First of all, we have Claude for all of us,首先,我们有 克劳德为我们所有人,
246and we have certain projects我们有一些项目
247for every social media that we're on.我们所有的社交媒体。
248So for example, for this podcast,比如说,对于这个播客,
249we have a project that's called Guests,我们有个叫"客人"的项目
250and it knows all the analytics from previous guests,它知道所有分析 从前宾客,
251and it has certain criteria而且它有某些标准
252on which we rank every single person我们把每个人排在其中
253who comes to the podcast,他来见播客,
254whether he or she is cited,无论他或她被引用,
255whether they have a certain opinion on AI,他们是否对大赦国际持有某种意见,
256whether they've been active with AI in their company,他们是否一直活跃 在AI在他们的公司,
257or if they're a recent founder in AI.或者他们是AI的最近创始人
258So it gives them different weights,因此,它给他们不同的重量,
259and it comes up with a grade based out of 40.并得出一个等级 根据40。
26040 meaning tier one, 30 meaning tier three, et cetera.40表示一级,30表示三级等.
261And then we have another one礛и临Τ
262that analyzes every single podcast,分析每个播客,
263and gives me tips on how to ask questions.并给我如何提问的提示。
264与Instagram相同,与LinkedIn相同.
265It has my tone of voice, personal dossier,它有我的声音,个人档案,
266my business strategies.我的业务策略。
267So whenever it writes something,所以,每当它写的东西,
268it knows all the facts about me, how I sound.它知道关于我的所有事实 我的声音。
269Every social media is run by a person.每个社交媒体都由一个人管理.
270So a person makes a strategic call.所以一个人做出一个战略号召。
271And by the way,顺便说一句
272if you can give me feedback on this, if I can improve.如果你能给我反馈, 如果我能改进。
273So what I'm working on right now is closing the loop,所以,我现在的工作是 关闭循环,
274because sometimes they send me a text,因为有时候他们会给我发短信
275and I'm like, oh, we need to change this, this, and that.而我喜欢,哦,我们需要改变这个,这个,那个。
276But that happens in a chat, in Telegram.但是,这发生在聊天, 在Telegram。
277And we have this feedback.我们得到了这个反馈。
278We have a bot that scans all of our chats.我们有一个机器人 扫描我们所有的聊天。
279But I really want AI to be able to learn continuously但我真的希望AI能够不断学习
280from this feedback to just know my taste better.从这些反馈来了解我的品味
281There's one thing I see a lot in AI,我在AI里看到很多东西
282which is it turns out for AI's data scientists对AI的数据科学家来说
283or AI's brainstorming partner,或AI的集思广益伙伴,
284it often comes up with one or two good ideas,它经常提出一个或两个好主意,
285two or three mediocre ones, and four atrocious ones.两三个平庸的,四个残暴的。
286And sometimes you wonder,有时候你会想
287how could my AI have thought我的人工智能怎么会想到
288that could even be a plausible idea?这甚至可能是一个可信的想法?
289And to me, this relates to the job-pocalypse point of view,对我来说,这涉及到 工作启示论的观点,
290which is that for a long time, humans, you, me,人类,你,我,
291everyone watching this,大家看这个
292will have a significant context advantage over AI,与大赦国际相比,在环境方面具有显著优势,
293which is that you know something就是你知道一些东西
294that's incredibly obvious to you这对你来说是显而易见的
295that that was an awful idea, but the AI did not.那是个糟糕的主意 但人工智能没有
296And it turns out that one of the reasons结果发现一个原因
297why AI will not replace our jobs or whatever,为什么AI不会取代我们的工作什么的,
298a lot of times not anytime soon,很多时候,不是任何时间很快,
299is because humans have a massive context advantage因为人类拥有巨大的环境优势
300compared to AI.与大赦国际相比。
301We know so much that from our years of experience我们从多年的经验中知道这么多
302that we talked to customer,我们和顾客谈过
303we saw the funny facial expression that told us,我们看到了有趣的面部表情 告诉我们,
304ah, they don't like this.啊,他们不喜欢这样。
305Or we talked to business or our manager said,或者我们跟生意谈了 或者我们的经理说
306hey, blah, blah, blah, I really care about this.嘿,嘿,嘿,我真的关心这个。
307And so it turns out that almost all humans,结果发现几乎所有的人
308what all humans just know a lot of stuff所有人类都知道很多东西
309that the plumbing does not exist,使管道不存在,
310and I don't think exists for the foreseeable future.我认为在可预见的未来不存在
311I know sometimes people talk about the importance我知道有时候人们会谈论重要性
312of human judgment or human taste,人类的判断或品味,
313and sometimes we wonder, all right, what is taste?有时候我们想,好吧,什么是味道?
314Is this fuzzy thing?这是模糊的东西吗?
315But to me, the technical thing that underlies但对我来说, 技术问题的基础
316why humans have better judgment and better taste than AI,为什么人类比AI有更好的判断和品味,
317is this context advantage.这是上下文的优势。
318And because this is a long-term advantage,因为这是一个长期优势,
319like no one's gonna solve this, you know, in a few years,就像几年后 没人能解决这件事
320this is why we just need a lot more humans所以我们需要更多的人
321with that judgment and taste to keep on complimenting AI.以判断和品味 继续称赞AI。
322And doesn't this make education even more important?这难道不使教育更加重要吗?
323Because education gives us context.因为教育给我们提供了背景。
324This is another thing I'm hearing about AI,这是另一件事 我听到关于AI,
325like you won't need education就像你不需要教育一样
326because all the information is at your fingertips.因为所有信息都在你的指尖上
327You just ask, Chad GPT.你只是问,乍得GPT。
328But when you say context and taste, for me,但当你说上下文和品味,对我来说,
329that's years of acquiring knowledge那是多年 获取知识
330and learning from the best and seeing how they perform向最好的人学习,看看他们的表现
331versus just asking a chat.而不是只是问话
332I'm gonna say something that may be controversial.我要说一些有争议的话
333I don't know if I've said this publicly,我不知道我是否公开说过
334but I think it's true, which is frankly,但我认为这是真的 老实说
335AI models are terrible for learning.AI模型对于学习来说是可怕的.
336I know people think AI is wonderful at getting things done,我知道人们觉得AI很擅长做事情
337use it all the time, love it.总是用它,爱它。
338But all the data that's coming out is that但所有数据都显示
339when say college students use AI, we know this.当说大学生使用AI, 我们知道这一点。
340It's just the studies now back up as well,只是现在的学习也有所恢复
341so we also have numbers, but the data is very clear.因此,我们也有数字, 但数据非常清楚。
342Students go higher on homeworks when they use AI,学生用人工智能做功课会更高
343yay, higher homework schools.是的,高等家庭作业学校。
344But retention, their long-term performance is much worse但保留,他们的长期表现更差
345because their AI do the work for them.因为他们的人工智能为他们工作。
346More and more studies are coming out to back this up now越来越多的研究 出来支持现在
347that I think people think, oh, it turns out,我认为人们会认为, 哦,结果,
348I think Wikipedia is a wonderful tool, it has tons of facts.我认为维基百科是一个很棒的工具, 它有大量的事实。
349Web search is a wonderful tool, it has tons of facts.网络搜索是一个很棒的工具,它有很多事实。
350But it turns out that when you ask AI to do work for you,但事实证明 当你要求AI为你工作时
351you are cognitive offloading to AI,你将认知卸载到AI,
352which is great because that's how society moves forward这是伟大的,因为 社会如何前进
353and it gets work done.并且它得到了工作完成。
354But human retention is much worse.但人类保留的情况更糟。
355It's just so clear that LLMs, as they are most commonly used,很明显,LLMS, 因为最常用的是,
356are terrible for learning.学习是可怕的。
357I'm not saying there's no way to use it我不是说没有办法用它
358in a way that is good for learning.以有利于学习的方式。
359I think there are ways to use it that are good for learning.我认为有方法使用它,对学习有好处.
360But even for myself, there's so many things但即使是我自己, 有很多事情
361that are also AI modeled over the last six months过去六个月的人工智能模型
362or whatever, like building some project,或者什么的,像建设一些项目,
363how does this front-end backend component work, whatever.这个前端后端组件是如何工作的,什么的。
364Give me the answer, get the job done, it was fantastic.给我答案,把工作做好,真是太棒了
365But six months later, I don't remember the answer但半年后 我不记得答案了
366when I need to redo that front-end backend component,当我需要重做前端后端组件时,
367I ask the AI again.我又问AI。
368So data's really clear.所以数据非常清晰。
369We should stop thinking of AI as helpful for learning.我们不应该把人工智能视为有助于学习。
370At least the vast majority of ways至少绝大多数的方法
371that the vast majority of people are using AI models today绝大多数人今天都在使用AI模型
372is absolutely terrible for learning.这对学习是绝对可怕的。
373But you're building a company, helping solve that, right?但你正在建立一个公司,帮助解决,对不对?
374Because the one-to-one tutoring with AI因为跟AI的一对一辅导
375is that where you just announced是你刚刚宣布的
376和Coursera的一亿投资
377Yes, so I'm excited about leading a new organization是的,所以我很高兴领导一个新的组织
378called Learn Vector that is focused名为“ 学习矢量” 的焦点
379on building new learning experiences积累新的学习经验
380that is much more one-to-one than one-to-many.这比一对一多得多
381So 15 years ago, I was privileged to participate所以15年前,我有幸参加
382in the online courses movement在线课程运动
383that I think changed the way a lot of people learn.我认为改变了很多人的学习方式
384But that was, and still remains,但这曾经是,现在仍然是,
385largely a one-to-many experience主要是一对一的经验
386where everyone kind of watches the same video,所有人都看同样的视频
387which is actually okay, it actually works well.这其实是好的, 它实际上工作很好。
388But the technology now exists但技术已经存在
389to create much more personalized,创造更个性化,
390customized one-to-one experiences.定制的一对一体验.
391And so our team is working hard on that.因此,我们的团队正努力进行这项工作。
392I think we'll have a lot more to show by early next year.我想到明年初我们还有很多事情要做
393When think about human skill development,想想人类技能的发展
394I feel like because AI has so heavily impacted我觉得因为人工智能影响很大
395software engineering, what we see happening软件工程,我们看到的
396in the job market for software engineering在软件工程的就业市场上
397is a harbinger, or it's a forerunner是预兆,还是预兆
398of what we'll see in other disciplines as well.我们在其他学科也会看到的东西
399And in software engineering,在软件工程方面
400people need to learn new skills, but when they do,人们需要学习新的技能,但当他们学习时,
401they are thriving and creating more value他们正在繁荣,创造更多的价值
402and frankly getting raises坦率地说,我得到了高薪
403and doing even more exciting projects.和做更令人兴奋的项目。
404And what I'm seeing the early signs of我所看到的早期迹象
405in other disciplines as well,其他学科,
406for example, in software engineering,例如,在软件工程方面,
407most developers, like front-end, back-end developers,大多数开发者,如前端,后端开发者,
408have now become full-stack developers.现已成为全存储开发者。
409Because of AI help, you could take on broader scope.由于AI的帮助,你可以承担更广泛的范围.
410I'm seeing early signs of this in other disciplines as well,我在其他学科也发现了早期的迹象,
411where, for example, someone in marketing例如,市场营销中的人
412that did marketing coordination,做营销协调,
413coordinated marketing campaigns, with AI help,在大赦国际的帮助下,协调开展营销活动,
414they can now become more of a full-cycle marketer他们现在更能成为全周期的营销者
415and take on a broader scope.并且扩大范围。
416And I'm seeing, frankly, sources in recruiting坦率地说,我看到 招募的来源
417become more full-cycle, do end-to-end recruiting.成为更完整的循环, 做端到端的招募。
418So now the good news and bad news is所以现在好消息和坏消息是
419for people to step up to these broader roles,让人民承担起这些更广泛的角色,
420you do need to learn AI skills,你需要学习人工智能技能,
421but also it's not just learning AI.不只是学习人工智能
422You also need to learn these other skills,你还需要学习这些其他技能,
423like how do you do the other parts of marketing,就像你如何做市场营销的其他部分,
424of recruiting, or software engineering, or AI engineering.招聘,或软件工程,或AI工程。
425So I think this actually creates a heavy need,所以我认为这实际上造成了一个沉重的需要,
426a big need for people to gain new skills,需要人们获得新的技能,
427but when they do, which is both AI skills,但当他们这样做, 这既是AI的技能,
428but also disciplinary skills,同时也有纪律技能,
429then they can do much more, hopefully have more fun,然后,他们可以做更多的, 希望有更多的乐趣,
430work on more exciting projects,在更刺激的项目上工作,
431hopefully get paid more as well.希望也能得到更多的报酬。
432And one reason I kind of worry about the fear monitoring还有一个原因 我担心恐惧的监控
433is I got an email from someone我收到别人的邮件
434that was about to enter college,即将进入大学,
435and he emailed me saying,他给我发邮件说
436hey, Andrew, taking online courses,嘿,安德鲁,上在线课程
437but I'm really struggling with what I should major in college但我真的在为大学本科生而挣扎
438because in four years, won't AI do all this,因为四年之内 AI不会做这一切
439and everything I learn will be obsolete?我学到的一切都会过时?
440And the answer is no, of course it won't all be obsolete,答案是没有,当然不会都是过时的
441but when we keep on pushing these fear messages,但是当我们不断推波助澜时
442we make people wonder if they will even be relevant,我们让人们怀疑他们是否相关
443and it makes people not lean in to gain these skills,它使得人们不 倚靠获得这些技能,
444they'll put them in a much better position.他们会让他们处于更好的地位。
445So I see very clearly that these fear monitoring messages所以我非常清楚地看到 这些恐惧监测信息
446are distorting how many people,扭曲了多少人,
447including high school students, college students,包括高中生、大学生、
448fresh grads, think about the economy,刚毕业,想想经济,
449and frankly, making people give up坦白地说,让人们放弃
450is one of the worst things we've been doing是我们做过的最糟糕的事之一
451in this era when people that lean in will thrive.在这个时代, 人倾斜将繁荣。
452Andrew has taught over 8 million people AI.安德鲁教过超过800万人AI.
453He started teaching machine learning online back in 2011,他从2011年开始在网上学习机器,
454years before the current AI boom.距当前AI繁荣还有好几年
455Now one of the companies he's building现在他正在建设的公司之一
456is focused on AI agents.重点是人工智能特工
457From the way that it sounds,从听起来,
458it can still feel way too technical.感觉还是太技术了
459So I put together a step-by-step guide所以我编了一部"一步一步"的指南
460to building your first AI agent with no coding required.来建立第一个不需要编码的AI代理.
461It walks you through what to automate, how to set it up,它让你通过什么 自动化,如何设置它,
462and how to make it actually useful.如何让它真正有用。
463It is in my newsletter this week.我这周的通讯里有这个
464The newsletter is called Future Proof.该通讯名为"未来证明".
465It's free.自由无碍.
466Link is in the description.链接在描述中.
467What would you reply back to that email你对那封邮件有什么反应?
468that somebody sent you?有人派你来的?
469What would you say is the best major to study now,你会说什么是最好的主 现在学习,
470to thrive in AI era?在AI时代蓬勃发展?
471Do you think it's like going deep into a niche你觉得这就像深入到一个小地方
472or just broader computer science或者只是更广泛的计算机科学
473so that you can acquire AI skills really fast?这样你才能很快获得人工智能技能?
474You know, I don't know what's the best major.你知道,我不知道什么是最好的主修课。
475There are awful lot of great majors.有很多伟大的专业。
476It's like, I kind of feel like我觉得...
477what's the best job in the world?什么是世界上最好的工作吗?
478What's the best major in the world?何等为最上大修.
479Something that you love, right?你爱的东西,对不对?
480Yeah, my daughter wants to be an astronaut.对,我女儿想当宇航员
481I don't know if she can major in becoming an astronaut.我不知道她能否成为宇航员
482I have to think about that.我得考虑一下
483When she gets older, she may change her mind.她长大后可能会改变主意
484I see so many opportunities across so many job roles.我看到很多机会 贯穿这么多的工作角色。
485It all seems very exciting to me.这一切似乎都让我兴奋。
486But do learn AI, do learn to build with AI.但要学AI,要学与AI一起建设.
487The other thing that my team's been working还有一件事,我的团队一直在工作
488on an AI engineering skills map to try to map out在AI的工程技能地图上尝试映射
489the most important skills for AI engineering.AI工程最重要的技能.
490One thing that I felt intuitively,有件事我直觉地觉得
491but I was surprised to see it show up in the data,但我惊讶地看到它出现在数据中,
492was that a lot more job descriptions seem to be saying更多的职务说明似乎在说
493that they want people that demonstrate他们想要展示的人
494a very high sense of agency.一种很高的代理意识。
495Because it turns out with AI,因为有AI的发现
496there are a lot more opportunities for individuals个人有更多机会
497to spot problems and go build something发现问题,去制造一些东西
498or do something to go solve it.或做一些事情来解决它。
499So I think we're really evolving.所以,我认为我们真的在进化。
500Well, we've long been evolving,我们早就在进化了
501but we're accelerating past the era但我们正在加速穿越时代
502where people sit around and wait for their boss在那里人们坐着等待他们的老板
503to tell them what to do.告诉他们该怎么做。
504This is what I've been feeling a lot,这就是我一直以来的感受,
505especially when we started doing remote work.特别是我们开始做远程工作的时候
506I want people to be entrepreneurs within their niche.我希望人们在自己的专长内成为企业家.
507Like if you're helping me with LinkedIn,就像你帮我处理LinkedIn一样
508you're an entrepreneur there.你是一个企业家在那里。
509You can hire more contractors.你可以聘请更多的承包商。
510You can deploy different tools.你可以部署不同的工具。
511You make the strategic decision你来决定战略
512whether this topic is good or not.不论这个议题是否良好。
513Shall we proceed with it?我们继续吧?
514I really think, and tell me if you agree with me,我真的觉得 如果你同意的话 告诉我
515we're moving into that job market我们要进入这个职业市场
516where everyone is kind of independent in their workplace.在那里,每个人都在他们的工作场所是独立的。
517I think people will have much more autonomy and creativity.我认为人们会有更多的自主权和创造力.
518So I agree with that.所以我同意这一点。
519And I'd even go one step further,我甚至更进一步,
520which is I talked to a lot of people,我和很多人谈过
521engineers and others in large companies大公司的工程师和其他人
522that told me that the manager tells them这告诉我,经理告诉他们
523to stay in their swim lane.留在他们的游泳道。
524They'll say, oh, I have this creative idea,他们会说,哦,我有一个创意的想法,
525but the manager says, no,但经理说,不,
526and they should have focused on this one thing, frankly,他们应该把注意力集中在这件事上 坦白地说
527often because the manager's career depends on it.经常是因为经理的职业生涯取决于此.
528But I feel like the number of opportunities但我觉得机会之多
529for people to spot things outside their swim lane在游泳道外发现东西
530and then in a responsible way explore how to get it done,然后以负责任的方式探索如何完成它,
531that feels very exciting to me.感觉很刺激
532And I think that in the future,我认为在未来,
533the businesses that set up a culture建立文化的企业
534that encourage people to learn AI, build fast, responsibly,鼓励人们学习AI, 建设快速,负责,
535talk to customers would drive a lot more value和顾客聊天会吸引更多的价值
536than the more hierarchical silo organizations.而不是更分级的组织。
537Yeah, it starts with hiring the right people是啊,它从雇用合适的人开始
538and then nurturing this in your organization.然后在你的组织里培育这个
539When you say learn how to use AI当你说学习如何使用AI
540and become proficient with AI,并且精通AI,
541can you give me some benchmarks?你能给我一些基准吗?
542Like of a person who's like say marketer,就像说市场营销员一样
543knowledge worker, advanced with AI,知识工作者,高级AI,
544what are you looking for你们在找什么?
545when you're interviewing this person?当你采访这个人时?
546I'm pretty sure my team's ahead of the curve.我敢肯定,我的团队 领先曲线。
547All of my marketers know how to code.我所有的推销员都知道如何编码
548So as part of how I interview marketers,因此,作为我如何采访营销员的一部分,
549we ask them what they've built我们问他们建造了什么
550and if they have not built any software.如果他们没有建造任何软件,
551If it's a dashboard, is it good or bad?如果是仪表板,是好是坏?
552Like is it too basic or?这太基本了还是?
553A dashboard, again, my team's pretty,仪表板,再次, 我的团队很漂亮,
554you know, somewhat ahead of the curve,你知道,有些在曲线前,
555but all of my marketers have built但我所有的推销员都造了
556much more sophisticated things than dashboards.比仪表板更精密的东西
557Oh, I feel like, I don't know,哦,我觉得,我不知道,
558the other day, one of our,那天 我们中的一个
559someone on the marketing team有人在营销团队
560was talking about the tools that he had built.他正在谈论他建造的工具。
561When he's considering writing an article on something,当他考虑写一篇关于某事的文章时,
562it will crawl the web, find related work,它会爬网 找到相关的工作
563has a custom desktop app,有自定义桌面应用程序,
564actually build a desktop app that runs on his Mac实际构建一个运行在其 Mac 上的桌面应用程序
565to highlight related articles for him.为他突出相关文章.
566Then he can chat to the whole system,然后他可以和整个系统聊天
567navigate, you know, the thing he's writing,导航,你知道, 东西他写,
568as well as the related work及有关的工作
569and he had a large dashboard for crawling the internet他有一个巨大的仪表板 爬上网
570to highlight to him exciting things that are popping up.告诉他一些激动人心的事
571Now, even on my team,现在,即使在我的团队,
572I think that marketplace is ahead of the curve.我认为市场领先于曲线。
573But that's great to hear.但这是伟大的听到。
574Any other interesting use cases任何其他有趣的使用案例
575that will inspire people to build something similar?那会激励人们 建立类似的东西?
576Let's see, maybe my finance team uses AI extensively.让我们看看,也许我的金融团队 广泛使用AI。
577So I think one of my CFOs realized that,所以我认为我的首席财务干事意识到,
578you know, her team was spending hours every week你知道,她的团队 每周花几个小时
579clicking through documents, open this copy,点击文档,打开本副本,
580paste this number here.在这里粘贴这个号码。
581And so she started building automation scripts于是她开始制作自动化脚本
582that runs on a routine that automatically opens files,运行在自动打开文件的常规上,
583checks what's in there,检查里面有什么
584校对:Soup
585if there's something they need to be paying attention to如果有什么需要他们注意的
586of a new document that showed up.显示的新文件。
587So I find that rather than waiting around所以,我发现这 宁可等待周围
588for an engineer to do the work for them,一个工程师为他们工作,
589the team's ability to kind of not just build dashboards,团队的能力 那种不只是建造仪表板,
590but build kind of a data management infrastructure但建立某种数据管理基础设施
591that's taking ingest data,这是摄入数据,
592alert them if something's happening.发生什么时通知他们
593I think my finance and marketing teams are doing that.我认为我的金融和营销团队正在这样做。
594Oh, my recruiting team,哦,我的招募团队,
595well, we actually have recruiting engineers,其实我们招聘了工程师
596which are really professional engineers他们是真正的专业工程师
597that sit in a recruiting team.在一个招募团队。
598They're building very sophisticated tools for recruiting.他们正在建造非常复杂的招募工具.
599And this is actually the other trend.这是另一个趋势。
600I think marketers, recruiters, HR professionals,我认为市场营销者,招聘者,人力资源专业人士,
601ops people should all learn AI.行动人员应该学会人工智能
602But the other thing is when you take an engineer但另外一件事是当你接受工程师
603and embed them in these teams,把他们安置在这些队伍中,
604then that further accelerates what you can do.然后,这进一步加快了你能做的。
605We do the same.我们也是
606We start with something basic, build it ourselves.我们从基本的东西开始, 建造它自己。
607Then we hit the wall and engineer comes in.然后我们撞上了墙 工程师进来了
608We build it further.我们进一步建造它。
609Frankly, when you look at not just software engineers,老实说,当你看到 不只是软件工程师,
610but recruiting engineers, marketing engineers,但招聘工程师,营销工程师,
611HR engineers, I think there's so much valuableHR工程师,我觉得有很多有价值的东西
612engineering work that can now be done.现在可以做的工程工作。
613I'm just not worried about running out of,我只是不担心 跑出来,
614frankly, all my friends were so busy.坦白说,我的朋友都很忙
615We think, boy, how could we run out of engineering jobs?我们想,孩子,我们怎么能用完工程工作?
616Yeah, there's so many cool ideas you can experiment on,是啊,有很多很酷的想法 你可以实验,
617but you touched upon something但你碰了个东西
618that is actually one of the fears.这其实就是其中之一的恐惧。
619When we talk about like financial information,当我们谈论像财务信息,
620how much you're giving to AI.你要给AI多少钱?
621So I gave my perplexity permission所以我才允许我感到困惑
622to scan my fidelity account so it can track my portfolio,扫描我的忠诚账户 这样它就可以追踪我的投资组合
623tell me when to rebalance.告诉我什么时候再平衡
624It doesn't do anything on my behalf, but it has access.它不代表我做任何事,但它有权限。
625Do you think there is any problem with that?你觉得有什么问题吗?
626This is complicated.这很复杂
627I think AI and privacy is a complex area.我认为AI和隐私是一个复杂的领域.
628And it depends a lot on the company这要靠公司
629that you are sharing your data with.您正在分享您的数据。
630So for example, I trust all the hyperscalers比如说,我信任所有的超标器
631to really 100% follow their terms of service百分之百遵守他们的服务条款
632and to do what they say.并按他们说的做。
633My personal opinion, not giving legal business advice,我个人的意见,不提供 法律业务建议,
634but I'd be shocked if the largest hyperscalers但是,如果最大的超标,我会震惊
635publish the terms of service with some privacy notice发布一些隐私通知的服务条款
636and if they reach that,如果他们到了那里,
637because that'd be not the culture,因为那不是文化
638it'd be so damaging to the long-term business model.这会对长期商业模式造成如此大的伤害。
639Now that's on the largest hyperscaler side.现在,这是最大的超规模。
640If you look at the AI company side,如果你看看AI公司那边
641there's been at least one company that I won't name至少有一家公司我不点名
642that seems to occasionally change the terms of service这似乎偶尔改变服务条件
643and if you're using it, you go to the website,如果你在使用它, 你到网站,
644so you pop up, hey, we changed the terms of service所以,你出现了,嘿, 我们改变了服务条件
645to retain your data or train your data.保留数据或训练数据。
646And if you aren't paying attention如果你不注意的话
647and click the wrong button,点击错误的按钮,
648then they suddenly gave themselves permission然后,他们忽然答应了。
649to access your data访问您的数据
650in a way that I'm not that comfortable with.我不太喜欢这样
651I feel like I handle some sensitive information.我觉得我处理一些敏感的信息。
652So then I tend to be very careful with the businesses所以,我总是非常小心 与企业
653that I just don't feel their culture and their DNA.我只是感觉不到他们的文化和DNA
654And frankly, the long-term business model坦白说,长期商业模式
655is as tied to protecting individual user privacy与保护个人用户隐私一样
656than the hyperscalers.比超标者还要大
657And I see businesses get this as well.我认为企业也得到了这个。
658例如,我的一个团队,AI Aspire,
659we work with very large corporations,我们和大公司合作
660including banks with incredibly sensitive financial data.包括拥有极其敏感金融数据的银行。
661And as you can imagine, AI Aspire and our clients你可以想象,AI Aspire和我们的客户
662do not willingly share really sensitive,不愿分享真正的敏感,
663often material non-public information, right, NMPI,经常提供非公开资料,对,NMPI,
664with frontier labs without really careful thinking与前沿实验室 没有真正仔细的思考
665about the guardrails in privacy.私底下的护栏
666So I think it's complicated.所以我觉得这很复杂。
667So trusting hyperscalers,如此信任超标者,
668but also another thing that you can do,但还有一件事你可以做,
669you can download an open-source model您可以下载一个开源模型
670and just run it on your computer在你的电脑上运行
671and then it just stays on your computer, right?然后它只是留在你的电脑上,对不对?
672Yes, I think, yes, it turns out a lot of banks是的,我想,是的,结果很多银行
673will actually run the things将实际运行的东西
674in the virtual private cloud or on-prem,在虚拟的私密云中,或在梦中,
675so they never even leave their control.所以他们从不离开他们的控制。
676But I think for individuals,但我认为对于个人来说,
677for the really sensitive things,对于真正敏感的东西,
678I sometimes run a local model.我有时会经营本地模特儿
679And it's been interesting with the open-way models.并且对开通车型颇感兴趣.
680So the latest open-way models因此,最新的开放模式
681are approaching frontier capability正在接近边境能力
682and that are actually small enough.这其实足够小。
683There are actually really good models now现在真的有很好的模型了
684they can run on.他们可以继续前进。
685Yeah, the one from Meta, right?是啊,梅塔的那个,对吧?
686The recent one.最近那个
687Oh yes, Metamuse is a good model.哦,是的,Metamuse是一个很好的模型。
688And I'm thinking also the latest version of Quen我还在想最新版的Quen
689is also very good.也很不错。
690But I think frankly, these models change every other week.但坦率地说,这些模型每隔一周就改变一次。
691So I think the best practice is to not get stuck on one,所以我认为最好的做法 就是不要被困在其中
692but keep on trying new models.但继续尝试新的模型。
693So basically when there is a situation所以,基本上当有情况
694that you don't trust anyone,你不信任任何人,
695you run a local model您运行本地模式
696and this is how you keep your data safe.这就是你保护数据安全的方法
697I do trust the hyperscalers,我确实相信那些超规模的人
698but sometimes for literally NMPI,但有时对NMPI来说
699material non-public information,* 非公开资料,
700that I won't even send to that,我甚至不会送去,
701I just can't even send that to the cloud.我甚至不能把那个寄到云里
702So that, I'll either do it manually without AI help所以,我要么手动做,没有AI帮助
703or if I really need to use AI,或者,如果我真的需要使用AI,
704then really carefully only use a local model.然后非常小心地使用一个本地模型。
705Interesting.有意思,这很有趣
706Okay, this is an interesting one.好吧,这是一个有趣的。
707Okay, what about loss of human control over AI?好吧,那人类失去对AI的控制呢?
708因为我和Yoshua Benja谈过了
709who is very negative when it comes to free AI在自由AI方面,谁是非常消极的
710without any regulation.没有规定。
711And he painted me some very scary pictures他给我画了一些非常恐怖的照片
712of AI taking over control,由大赦国际接管,
713because basically the whole scenario is因为基本上整个情景
714we can't control something that's smarter than us.我们不能控制比我们聪明的东西
715And if AI gets smarter and smarter,如果AI变聪明了
716where do we end up?我们到哪里去?
717What do you think about that?你觉得怎么样?
718I think about something else that we can't control,我想到别的东西,我们不能控制,
719which is airplanes.这是飞机。
720No one can build an airplane没人能造飞机
721that you can fly perfectly.你可以完美飞行。
722Winds will buff it around.风会吹动它周围。
723And then candidly,然后坦率地说,
724in the early days of developing airplanes,在发展飞机的初期,
725some airplanes crashed and people died有些飞机坠毁,有人丧生
726and it was tragic and awful.悲剧和可怕。
727But through the early lessons learned,但通过早期的教训,
728we then learned to control airplanes better and better然后我们学会了更好控制飞机
729so that today we can mostly get in an airplane这样今天我们就可以乘飞机了
730and not fear too much for our lives.也不要太害怕我们的生活。
731And it's really like that too with AI.对AI来说也是这样
732No one can perfectly control AI没有人能完全控制AI
733because it generates tokens or outputs因为它会产生符号或输出
734that are a little bit random,这有点随机,
735so we don't really know what exactly it'll do.所以我们不知道它到底能做什么
736But as we run them,但当我们运行他们,
737and there's been a small number of mishaps,发生了少量的意外
738which is unfortunate,这是不幸的,
739and some number of mishaps have done some real damage,和一些灾祸 已经做了一些真正的损害,
740but the way we engineer almost any system,但是我们设计系统的方式,
741from an airplane to electric circuits to now AI,从飞机到电路到现在的AI
742is carefully grow their capabilities仔细地提高他们的能力
743so that we can have a controlled environment以便我们有一个控制的环境
744in which to measure what's wrong用来衡量什么是错的
745and then to shape it,然后造出来,
746to make sure we can control it well enough确保我们能很好地控制它
747that it behaves responsibly and safely.它的行为是负责和安全的。
748And to this day,时至今日,
749we can't perfectly control any airplane我们不能完全控制任何飞机
750and we will never perfectly control AI either.我们也不会完全控制AI
751But I think we are certainly controlling them well enough但我认为我们控制得够好了
752that this loss of control doesn't feel like science,这种失控的感觉不像是科学
753if it's a science fiction.如果这是个科幻小说
754Yeah, yeah.对 对
755What about deep fakes?那深层假货呢?
756Deep fakes are a problem.深假是烦恼.
757Well, one of the most disgusting things最恶心的事情之一
758I've ever seen or heard of我见过或听说过
759is non-consensual, intimate deep fake imagery.是未经同意的 亲密的深层假象
760I'm really glad that U.S. Congress has been moving我很高兴美国国会在搬家
761to let's pass laws, get rid of that, penalties for that.让我们通过法律, 摆脱它,惩罚它。
762I think there's some really problematic uses of AI我觉得人工智能的用法有点问题
763that we should outlaw, heavily penalize,我们应当严惩他们,
764let's just get rid of that.我们把那个扔掉吧
765What do you think about children and social connection你对孩子和社会联系有什么看法?
766when it comes to AI with kids当涉及到AI与孩子
767using more of AI?用更多的人工智能吗?
768Because we've seen social media,因为我们看过社交媒体
769how there are people who are dumb-scrolling all day.怎么会有人整天都傻傻地滚
770And my daughter, who is five years old now,还有我女儿 她现在五岁了
771whenever I don't have an answer,当我没有答案时
772she's like, ask Chad GPT.她喜欢,问查德GPT。
773Who's that person?那个人是谁?
774I'm like, I don't know.我很喜欢,我不知道。
775问查德GPT.
776She thinks Chad GPT knows everything.她觉得Chad GPT什么都知道
777What would you say about kids' future with AI?你会怎么说 孩子们的未来与AI?
778First, I think kids have a bright future.首先,我觉得孩子有一个光明的未来。
779It's such an exciting time这么刺激的时候
780to be a child to grow up in this environment在这样的环境下长大的孩子
781with tools that none of us ever had before.拥有我们从未有过的工具
782At the same time, we've seen that social media,同时,我们看到社交媒体,
783I think social media has probably been blamed我觉得社交媒体可能已经被指责了
784a bit more than it deserves,比它应得的要多一点
785but it does deserve blame,但它确实值得责备,
786has kind of not been great for kids.有点对孩子不好
787I actually worry a lot about, it's a wonderful tool,其实我担心的很多, 这是一个很好的工具,
788but AI damaging learning is something I worry a lot about.但是,AI破坏的学习 是我担心的很多。
789So it turns out, I have a five-year-old and a seven-year-old,原来我有一个5岁和7岁的孩子
790when I teach them math, they're so young enough当我教他们数学时,他们那么年轻
791that I can basically not let them use the calculator,我不能让他们使用计算器,
792can say, how do you multiply these numbers?可以说,你如何乘以这些数字?
793And I don't give them a calculator我不给他们一个计算器
794and practice that with them.和他们一起练习。
795But as they're a little bit older,但是,由于他们有点老,
796I worry a lot about students using cognitive offloading我非常担心学生使用认知卸载
797to AI in a way that damages the long-term learning retention.以损害长期学习保留的方式向大赦国际提出。
798But then at the same time, I actually built an app.但与此同时,我实际上还制作了一个应用程序。
799I did not like any of the free online learning我不喜欢任何免费的网上学习
800to type types of things, so I actually built my own来打几类东西, 所以我实际上建造我自己
801to have my daughter learn to type,让我女儿学会打字
802and I'm hoping that she's actually getting pretty decent now我希望她现在变得相当体面
803for a seven-year-old.给一个七岁的孩子。
804Oh, so she's typing already?哦,所以她已经打字了?
805Oh yeah, she actually typed all the lowercase letters.哦,是的,她实际上打 所有小写字母。
806She's a little bit, her shift uppercase letters她有点小, 她的换班大写字母
807are a little bit not quite there,有点不完全在那里,
808but I think that this unlocks responsible adult-supervised use但我认为这解锁 负责任的成年人监督使用
809of online tools, and I think it's really tricky.我认为这是非常棘手的。
810I think adult-supervised use of digital tools我认为是成年人监督使用的数字工具
811seems a great thing for kids,似乎对孩子们来说是件好事
812but too many adults don't have time但太多的成年人没有时间
813to supervise the use of the tools,监督工具的使用,
814and then the incentives of, say, social media, right,然后是社交媒体的激励
815to do funny things.来做一些有趣的事情。
816Yeah, has to be the right incentive when it comes to AI.对,对AI来说,应该有正确的激励
817Okay, you mentioned, we talked about the fears,好吧,你提到, 我们谈论了恐惧,
818we talked about how you can improve your work with AI.我们谈过如何改善你和AI的工作
819Can you name some of the biggest opportunities in AI in 2026你能说说2026年AI里最大的机会吗?
820for people who want to build?给那些想建楼的人?
821For an individual that wants to build,对于一个想要建设的人来说,
822I don't think it's one size fits all,我不认为它是一个尺寸适合所有,
823but because the cost of building has plummeted,但由于建筑成本暴跌,
824I encourage people to learn AI, build fast,我鼓励人们学习人工智能 快速建设
825and talk to customers.和客户交谈。
826I find myself building things, I don't know,我发现自己建造的东西, 我不知道,
827every week, every weekend,每个礼拜,每个周末,
828because I or someone on our team will have some problem因为我或我们团队中有人会有问题
829and I have some idea for building some AI thing我有点想法 建造一些AI的东西
830to automate it.把它自动化。
831Last weekend, I had, really, I was using a Frontier model上个周末,我真的在用边疆模型
832to analyze a lot of our key business metrics来分析我们许多关键的商业标准
833because I didn't have time to do it myself,因为我没有时间自己做,
834but it was kind of measuring, you know,但它是一种测量, 你知道,
835deep standardized key business metrics,深入标准化的关键业务衡量标准,
836and I didn't have time to go find a data scientist我没有时间去找数据科学家
837to go work me on it,去工作我做到这一点,
838so I just did a variety of Frontier models,所以我刚刚做了各种边疆模型,
839being really careful on their data retention policies.对数据保存政策非常小心
840I did not use models with data retention policies我没有使用有数据保存政策的模型
841that I don't like in order to analyze data.我不喜欢分析数据
842But, and then I find that what's happened with AI但是,然后我发现 发生了什么事AI
843is the cost of building has plummeted,建筑成本暴跌,
844and so the challenge is shifting to deciding what to build,因此,挑战正在转向决定建设什么,
845which I've been calling我一直在打电话
846the product management bottleneck.产品管理瓶颈。
847And so people, founders, engineers, product managers,于是人们,创始人,工程师,产品经理,
848they can talk to customers,他们可以和顾客交谈,
849get a sense for the taste of judgment on what to build,体会到判断如何构建的滋味
850and then build with AI and iterate quickly.然后用人工智能快速建造
851I think there's just a ton of exciting things to do.我觉得只有一吨刺激的事情要做。
852And you've been starting so many companies.你开了这么多公司
853You're like, when I looked at your portfolio,你就像,当我看着你的组合,
854do you think, for beginners,你认为, 对于初学者,
855when you said you built something during the weekend,你说你在周末造东西的时候
856how do you decide what to focus on?你如何决定什么是重点?
857Or you can pursue multiple ideas because of AI now,或者你可以追求多种想法 因为AI现在,
858and you can just be playing in different companies你可以在不同的公司里玩
859at the same time.同时。
860It turns out building a company is still really, really hard.事实证明,建立一家公司仍然非常困难。
861And so there's a lot to be said所以有很多话要说
862for a single-threaded leadership单线领导
863or someone that's fully focused on just one thing.或者某个完全专注于一件事的人
864I find that over a weekend,我周末发现,
865I can often build an own wrapper,我常常可以自己做包装
866build a simple application,建立一个简单的应用程序,
867but I wish it was that easy to build a large company.但我希望有那么容易 建立一个大公司。
868I find that building something meaningful我发现建造一些有意义的东西
869often takes either real technical depth往往需要真正的技术深度
870and or deep customer insight and integration of customers.或客户的深刻见解和融入。
871And yes, we can now use AI to code something是的,我们现在可以用AI 来编码一些东西
872in a few hours,几小时后
873but that's a small piece of the puzzle.但这是谜题的一小块
874So spending time understanding the technical complexity所以花时间了解技术的复杂性
875and building the really complex software,和建造非常复杂的软件,
876that takes us like months, maybe years,我们花了几个月,也许几年,
877or having that deep customer insight或者是客户的深刻见解
878to decide what to build.决定建设什么。
879That also just takes a lot.这也需要很多钱。
880Talking to people, reading facial expressions, surveys,与人们交谈,阅读面部表情,调查,
881it's doing that over and over它的做 一遍又一遍
882until we figure out what to build.直到我们想出 建造什么。
883And so I think sometimes there's a lot of value所以我觉得有时有很多价值
884to sampling widely,广泛采样,
885but then having that focus for an individual但后来又以个人为重点
886to go really deep in a couple of sectors,深入到几个部门,
887that still seems important for building a business.这对建立企业来说仍然很重要。
888My last question, I know we don't have much time,我最后一个问题,我知道我们时间不多了
889but I wanted to ask you about AGI,但我想问你关于AGI的事
890just because people use this word so much.只是因为人们使用这个词这么多。
891And some people say, I think Jensen Huang said,有人说 黄詹森说
892we already reached AGI.我们已经到达AGI。
893You said it's decades away.你说过还有几十年
894What's the one criteria when you're gonna say当你要说,一个标准是什么?
895we reach AGI?我们找到AGI了吗?
896So different people say we reach AGI at different times不同的人说我们在不同的时间到达AGI
897because of different definitions of AGI.因为AGI的定义不同.
898The definition I'm most familiar with我最熟悉的定义
899is AI that could do any intellectual tasks是AI,可以做任何智力任务
900that a human can.人类可以。
901But so the human brain can take say five years但是人类的大脑需要五年的时间
902to study and do a PhD thesis.学习和做博士论文。
903And so can AI write a PhD thesis?AI也能写博士论文吗?
904Or a human can learn to drive a truck或者人类可以学会开车
905through a dense rainforest穿过茂密的雨林
906with tens of minutes of practice.和数十分钟的练习。
907So when can AI do that to drive a new environment因此,什么时候AI可以这样做 驱动新的环境
908with tens of minutes of practice?练习数十分钟?
909It feels like there's a long list of these things感觉有一大堆这些东西
910that AI cannot do for what feels to me decades.对我而言,大赦国际不能做几十年的感受。
911I hope it's only decades.惟愿数十载.
912Maybe it will turn out to be longer.也许它会变成更长。
913So that's what I think for that definition of AI or AGI,所以,这就是我的想法 对于AI或AGI的定义,
914AGI还很远
915But it turns out because of economic incentives,但结果却因为经济刺激
916I think open and Microsoft had an agreement.我认为开放和微软有协议。
917There's actually been renegotiated now,已经重新谈判过了
918so that's gone away.所以这已经消失了。
919但OpenAI有经济刺激
920to try to declare reaching AGI earlier.试图更早地宣布到达AGI。
921And so it turns out that if you come up结果发现如果你上来
922with other definitions of AI,与大赦国际的其他定义,
923depending on how far you lower the bar,看你把酒吧放低多远
924then you could totally have reached AGI already那你就完全可以联系到AGI了
925or even 30 years ago,甚至在30年前,
926depending on how you want to define it.取决于您要如何定义它。
927Yeah, true.是的,没错。
928Andrew, thank you so much for this positive conversation.安德鲁 非常感谢你这么积极的谈话
929Very applicable.非常适用。
930I like when you watch something我喜欢你看东西
931and then you go and you measure yourself然后你去测量自己
932against what people are doing with AI,与人们对AI的所做所为相对应,
933look at your process and maybe expand it.看看你的过程,也许可以扩展它。
934So thank you so much for showing what your team is doing所以,非常感谢你展示 你的团队在做什么
935and thank you for your insights.谢谢你的洞察力
936Yeah, I think given the huge benefits of AI to come,是啊,我认为考虑到AI的巨大好处 来,
937I hope whoever's watching this is motivated希望看这个的人有动机
938to really go learn AI, apply it,真正去学习AI,应用它,
939and even to go build some things.甚至去制造一些东西。
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