Andrej Karpathy: Best IDE for programming | Lex Fridman Podcast Clips
Summary
TLDR这段视频脚本讨论了理想的计算机设置和编程环境,强调了使用大型显示屏和远程Linux集群进行深度学习任务的重要性。提到了VS Code作为当前最受欢迎的集成开发环境(IDE),并讨论了GitHub Copilot的集成,以及它如何帮助提高编程效率和发现新的API。同时,也表达了对未来编程自动化和程序合成发展的担忧,特别是在错误监控和验证方面。
Takeaways
- 🖥️ 个人计算机设置偏好因人而异,有人喜欢多屏幕,有人喜欢单一大屏幕。
- 💻 笔记本电脑和大屏幕是受访者熟悉的高效工作组合。
- 🖥️🐧 操作系统选择上,受访者平时主要使用macOS,但在进行深度学习任务时会使用Linux。
- 🔍 开发工作通常通过SSH远程连接到集群,而实际文件操作在远程位置进行。
- 📝 编辑器选择上,Visual Studio Code(VS Code)是受访者目前最喜欢的编辑器,因为它有大量的扩展和GitHub Copilot集成。
- 🤖 GitHub Copilot受到Python创始人Guido van Rossum的喜爱,它对编程有很大帮助。
- 🧠 与GitHub Copilot的交互需要学习如何判断其建议的有用性,以便更有效地利用它。
- 🔄 GitHub Copilot在代码补全和API建议方面特别有用,尤其是在模式识别和发现不熟悉的API时。
- 🔍 对于Copilot生成的代码,建议通过搜索引擎进一步验证其功能和用法。
- 🚀 程序合成的未来可能会发展为更加自动化,减少人为干预,可能会出现更多针对bug检测的自动化工具。
- 🌐 随着自动化编程工具的发展,程序员的数量和角色可能会发生变化,但目前看来,人类程序员仍不可替代。
- 🔄 语言模型的发展仍处于初级阶段,未来可能会有更多创新的工作方式出现,如与程序进行对话式编程。
Q & A
你认为理想的计算机设置是什么样的?
-理想的计算机设置因人而异,但根据这段话,一个常见的设置包括一个大屏幕,例如27英寸的显示器,以及一台笔记本电脑。这样的设置可以提高工作效率,尤其是在进行深度学习等复杂任务时。
为什么在深度学习任务中通常使用Linux操作系统?
-在深度学习任务中,Linux操作系统因其稳定性和对各种硬件和软件的广泛支持而受到青睐。此外,Linux提供了丰富的开源工具和库,这对于深度学习开发非常有用。
VS Code是如何与远程文件夹通过SSH进行连接的?
-VS Code可以通过SSH远程连接到服务器上的文件夹,这样开发者就可以在本地编辑器中直接操作远程文件。这需要在VS Code中配置SSH连接,然后挂载远程文件夹到本地项目中。
你认为VS Code是目前最好的IDE吗?为什么?
-是的,根据这段话,VS Code被认为是目前最好的IDE之一,因为它拥有大量的扩展插件,并且与GitHub Copilot集成,这为开发者提供了极大的便利。
GitHub Copilot对于编程有哪些帮助?
-GitHub Copilot可以帮助开发者自动完成代码,提供API建议,甚至帮助发现不熟悉的函数或库。它可以提高编程效率,尤其是在复制粘贴和模式匹配方面。
如何正确使用GitHub Copilot以提高编程效率?
-正确使用GitHub Copilot需要开发者学会判断何时应该接受其建议,何时应该忽略。例如,在模式清晰的情况下,Copilot在完成代码模式方面非常擅长;而在发现新API时,它可以提供学习的机会。但开发者应该对Copilot生成的代码进行验证,以确保其正确性。
你认为编程的未来会是怎样的?
-编程的未来可能会更加自动化,AI将在编程中扮演更重要的角色。例如,程序合成技术将使得编写更复杂的程序成为可能。同时,可能会出现新的工具来帮助发现和修复bug,以及进行代码审查。
自动化编程会对程序员的数量产生什么影响?
-尽管自动化编程可能会改变程序员的工作方式,但并不意味着会大幅度减少程序员的数量。相反,程序员的角色可能会发生变化,他们需要更多地与AI合作,提供指导和监督,确保生成的代码符合要求。
你认为未来的开发环境会有哪些变化?
-未来的开发环境可能会更加智能化和交互式。开发者可能需要与AI进行更多对话式交互,不仅仅是编写代码,还包括与AI讨论和调整程序逻辑。同时,开发环境的用户体验和交互设计将变得更加重要。
在自动化编程的趋势下,如何保证代码的质量和安全性?
-保证代码质量和安全性需要开发者和AI工具的共同努力。开发者需要对AI生成的代码进行仔细审查,同时,可能会出现新的自动化工具来帮助检测和修复bug。此外,建立严格的测试和验证机制也是确保代码质量的关键。
Outlines
💻 个人计算机设置与开发环境
本段讨论了个人计算机设置的偏好,包括屏幕数量和类型、操作系统选择以及IDE的使用。提到了Linux在深度学习中的重要性,以及VS Code作为当前最受欢迎的IDE,特别是其扩展性和GitHub Copilot集成。还讨论了编程语言的选择,如Python和C++,以及对编程未来的看法,包括自动化和程序合成的发展。
🤖 编程自动化与未来趋势
这段内容探讨了编程自动化的未来发展,特别是像GitHub Copilot这样的工具如何改变编程工作。讨论了程序员数量的增长趋势,以及自动化是否会导致程序员数量减少。还提到了如何与AI系统交互,包括指导、审计和验证AI生成的代码。最后,提出了未来编程可能变得更加多语言和灵活,以及UI/UX设计在开发环境中的重要性。
Mindmap
Keywords
💡电脑设置
💡操作系统
💡集成开发环境(IDE)
💡GitHub Copilot
💡编程语言
💡机器学习
💡远程工作
💡自动化
💡人工智能
💡用户界面和用户体验(UI/UX)
Highlights
讨论了个人计算机设置的偏好,包括屏幕尺寸和操作系统的选择。
提到了在深度学习任务中通常使用Linux操作系统并通过SSH连接到集群。
强调了使用Visual Studio Code(VS Code)作为当前最受欢迎的集成开发环境(IDE)。
提到了Python之父Guido van Rossum对GitHub Copilot的喜爱。
讨论了GitHub Copilot的实用性,尤其是在代码补全和API建议方面。
提到了GitHub Copilot在学习曲线和如何有效利用其输出方面的考量。
探讨了编程自动化的未来,包括程序合成和自动化程度的提高。
预测了未来可能出现的自动化编程工具,如自动生成编译器和代码检查器。
讨论了程序员数量的增长以及自动化对程序员职业未来的影响。
强调了在与AI系统交互时,UI/UX设计的重要性。
提出了与编程语言模型进行对话的可能性,如将代码转换为不同的编程语言。
讨论了开发环境的复杂性,包括硬件、环境变量和自动化脚本的集成。
提出了未来编程可能需要的多语言能力和在不同编程范式间转换的能力。
强调了程序员与AI系统交互时的迭代提示和对话的重要性。
讨论了自动化编程对软件质量和潜在bug问题的担忧。
预测了未来可能出现的AI系统,用于发现和修复代码中的错误。
讨论了语言模型的发展阶段,以及未来可能的发展方向。
Transcripts
what's your computer setup what uh
what's like the perfect are you somebody
that's flexible to no matter what laptop
four screens yeah uh or do you uh prefer
a certain setup that you're most
productive um I guess the one that I'm
familiar with is one large screen uh 27
inch
um and my laptop on the side water
operating system I do Max that's my
primary for all tasks I would say OS X
but when you're working on deep learning
everything is Linux your SSH into a
cluster and you're working remotely but
what about the actual development like
that using the IDE so you would use uh I
think a good way is you just run vs code
um my favorite editor right now on your
Mac but you are actually you have a
remote folder through SSH
um so the actual files that you're
manipulating are on the cluster
somewhere else so what's the best IDE
a code what else did people so I use
emacs still that's cool uh so it may be
cool I don't know if it's maximum
productivity
um so what what do you recommend in
terms of editors you worked with a lot
of software Engineers editors for
python C plus plus machine learning
applications I think the current answer
is vs code currently I believe that's
the best
um IDE it's got a huge amount of
extensions it has a GitHub copilot
um uh integration which I think is very
valuable what do you think about the the
co-pilot integration I was actually uh I
got to talk a bunch with Guido and
Rossum who's the creator of python and
he loves Coppola he like he programs a
lot with it yep uh do you
yeah he's copilot I love it and uh it's
free for me but I will pay for it yeah I
think it's very good and the utility
that I found with it was is in is it I
would say there is a learning curve and
you need to figure out when it's helpful
and when to pay attention to its outputs
and when it's not going to be helpful
where you should not pay attention to it
because if you're just reading its
suggestions all the time it's not a good
way of interacting with it but I think I
was able to sort of like mold myself to
it I find it's very helpful number one
in uh copy paste and replace some parts
so I don't um when the pattern is clear
it's really good at completing the
pattern and number two sometimes it
suggests apis that I'm not aware of so
it tells you about something that you
didn't know so and that's an opportunity
to discover and you it's an opportunity
to see I would never take copilot code
AS given I almost always uh copy a copy
this into a Google Search and you see
what this function is doing and then
you're like oh it's actually actually
exactly what I need thank you copilot so
you learned something so it's been part
of search engine apart maybe getting the
exact syntax correctly that once you see
it yep it's that NP hard thing to say
once you see it you know yes exactly
correct exactly you yourself you can
struggle you can verify efficiently but
you you can't generate efficiently and
copilot really I mean it's it's
autopilot for programming right and
currently is doing the link following
which is like the simple copy paste and
sometimes suggest uh but over time it's
going to become more and more autonomous
and so the same thing will play out in
not just coding but actually across many
many different things probably but
coding is an important one right like
writing programs yeah what how do you
see the future of that developing uh the
program synthesis like being able to
write programs that are more and more
complicated because right now it's human
supervised in interesting ways yes like
what it feels like the transition will
be very painful
my mental model for it is the same thing
will happen as with the autopilot uh So
currently is doing link following is
doing some simple stuff and eventually
we'll be doing autonomy and people will
have to intervene less and less and
there could be like you like testing
mechanisms
like if it writes a function and that
function looks pretty damn correct but
how do you know it's correct because
you're like getting lazier and lazier as
a programmer like your ability to
because like little bugs but I guess it
won't make a little no it will it
copilot will make uh off by one subtle
bugs it has done that to me but do you
think future systems will or is it
really the off by one is actually a
fundamental challenge of programming in
that case it wasn't fundamental and I
think things can improve but uh yeah I
think humans have to supervise I am
nervous about people not supervising
what comes out and what happens to for
example the proliferation of bugs in all
of our systems I'm nervous about that
but I think there will probably be some
other copilots for bug finding and stuff
like that at some point because there
will be like a lot more automation for
uh oh man
so it's like a program a co-pilot that
generates a compiler for one that does a
linter yes one that does like a a type
Checker yes
it's a committee of like a GPT sort of
like and then they'll be like a manager
for the committee yeah and then there'll
be somebody that says a new version of
this is needed we need to regenerate it
yeah there were 10 gpts that were
forwarded and gave 50 suggestions
another one looked at it and picked a
few that they like a bug one looked at
it and it was like it's probably a bug
they got re-ranked by some other thing
and then a final Ensemble uh GPT comes
in it's like okay given everything you
guys have told me this is probably the
next token you know the feeling is the
number of programmers in the world has
been growing and growing very quickly do
you think it's possible that it'll
actually level out and drop to like a
very low number with this kind of world
because then you'll be doing software
2.0 programming
um and you'll be doing this kind of
generation of copilot type systems
programming but you won't be doing the
old school
software 1.0 program I don't currently
think that they're just going to replace
human programmers
um
it's I'm so hesitant saying stuff like
this right because this is going to be
replaced in five years and no it's going
to show that like this is where we
thought because I I agree with you but I
think we might be very surprised
right like what are the next
I I what's your sense of where we stand
with language models like does it feel
like the beginning or the middle or the
end the beginning 100 I think the big
question in my mind is for sure GPT will
be able to program quite well
confidently and so on how do you steer
the system you still have to provide
some guidance to what you actually are
looking for and so how do you steer it
and how do you say how do you talk to it
how do you um
audit it and verify that what is done is
correct and how do you like work with
this and it's as much not just an AI
problem but a UI ux problem yeah um so
beautiful fertile ground for so much
interesting work uh for vs code plus
plus where you're not just it's not just
human programming anymore it's amazing
yeah so you're interacting with the
system so not just one prompt but it's
iterative prompting yeah you're trying
to figure out having a conversation with
the system yeah that actually I mean to
me that's super exciting to have a
conversation with the program I'm
writing
yeah maybe at some point uh you're just
conversing with it it's like okay here's
what I want to do actually this variable
maybe it's not even that low level as
variable but you can also Imagine like
can you translate this to C plus plus
and back to python yeah that already
kind of exists no but just like doing it
as part of the program experience like I
think I'd like to write this function as
C plus plus
or like you just keep changing for
different uh different programs because
they're different syntax maybe I want to
convert this into a functional language
yeah and so like you get to become
multilingual as a programmer and dance
back and forth efficiently yeah I mean I
think the UI ux of it though is like
still very hard to think through because
it's not just about writing code on a
page you have an entire developer
environment you have a bunch of hardware
on it uh you have some environmental
variables you have some scripts that are
running in a chrome job like there's a
lot going on to like working with
computers and how do these uh systems
set up environment flags and work across
multiple machines and set up screen
sessions and automate different
processes like how all that works and is
auditable by humans and so on is like
massive question at the moment
تصفح المزيد من مقاطع الفيديو ذات الصلة
Intro to Algorithms: Crash Course Computer Science #13
Lecture 1.1 — Why do we need machine learning — [ Deep Learning | Geoffrey Hinton | UofT ]
你不一定非得Cursor不可,Claude dev和Continue的组合也棒极了!| AI IDE | 破除迷思
The Unfixable ARM Memory Bug
Software Engineering: Crash Course Computer Science #16
Possible End of Humanity from AI? Geoffrey Hinton at MIT Technology Review's EmTech Digital
5.0 / 5 (0 votes)