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Programming with natural language is going to work (2010)

95 点作者 mrleinad将近 2 年前

9 条评论

armchairhacker将近 2 年前
Remember the phrase &quot;developers spend 10% of the time writing code and 90% of the time debugging?&quot;<p>Even if it isn&#x27;t 90%, most developers <i>like</i> writing code more than debugging, so most would prefer to automate the latter.<p>AI translating natural language into code probably isn&#x27;t as important as AI generating bug-free code and&#x2F;or debugging its code. Even GPT-4 struggles with this: sometimes you point out a bug and it works, but sometimes it just can&#x27;t find the issue and starts hallucinating even more as it gets confused.<p>Everyone&#x27;s trying to train GPT models to write code, but maybe we should be training them how to use a debugger. Though its a lot harder to map text generation to debugging...<p>Also, it&#x27;s a bit ironic how one way to prevent bugs is using stronger type systems and formal methods. But, AI is particularly bad at formal methods. But maybe with a system like MCTS combined with much faster generation...
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lcuff将近 2 年前
I suspect as things evolve with the Large Language Models, there will be integration with existing computer languages and frameworks. That the ability to say &quot;Create a web site using language X with framework Y&quot; will become a reality. This ability to get Hello World done in 5 minutes instead of 1&#x2F;2 a day to walk through a intro book&#x2F;tutorial, well, that&#x27;s a win.<p>Then, down the road, each AI might have a preferred&#x2F;default language, technology and framework. Quite possibly newly created. This has a parallel to intermediate representations (the earliest of which I&#x27;m aware of is p-code in UCSD Pascal). But it is also analogous to compiling C to assembler, and then machine code. Similarly with Java. Wolfram is correct when he talks about needing it to be a representation that the creator can inspect and verify. Not necessarily the least bit easy with a complex project. It will be an engineering journey, but it does spark in me the hope that English (or anyone&#x27;s native language) becomes the high level language of choice for guiding machines in tasks. Mathematica? Humph. Stephen Wolfram is very pleased with things he&#x27;s thought of or perhaps synthesized, but I&#x27;m gonna say, I think Mathematica is not the generic solution we will want.
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dboreham将近 2 年前
We&#x27;ve been doing this for 200+ years. All the programming languages we use, and mathematical notation, are based in some way upon natural language concepts (yes even FP languages). So really we&#x27;re talking about a continuum. And also worth noting that human languages evolve over time. So both programming languages will evolve to be more natural, and natural language will evolve to be more machine-parsable.
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dusted将近 2 年前
One way to view a programming language, that differs from the traditional math-oriented perspective, is that a programming language is a subset of a natural language which has become sufficiently unambiguous.<p>Ambiguity is in my opinion the biggest reason why &quot;plain {insert natural language} programming won&#x27;t be a thing&quot;.. The major challenge in normal commercial software development is not writing working code, it&#x27;s aligning expectations and identifying assumptions and eliminating ambiguities.. At that point, the coding part is more or less mapping the description to whatever particular words the implementation language is using.
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omginternets将近 2 年前
Sure, if the natural language we&#x27;re talking about is formalized to the point of basically being math. Let&#x27;s not confuse that with &quot;everyone will be able to program&quot;, though.
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dang将近 2 年前
Discussed at the time:<p><i>Generating code from natural language is closer than you think</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=1912530" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=1912530</a> - Nov 2010 (80 comments)
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heikkilevanto将近 2 年前
Long time ago they tried to develop a system where the users could explain things in &quot;plain&quot; English instead of the difficult codes used so far. It was called cobol.<p>As has already been pointed out, 90% of time is spent on debugging and modifying existing code, not writing new stuff. And of the 10% of coding, 20% is writing the happy path, and 80% is spent in handling errors, corner cases, input validation, and inconsistent domain rules.<p>Maybe we can have AI tools to help with all this, but there is still a long way to go. And when we get there, it will still take professional developers to use those tools, and to understand all the special cases.
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pyrale将近 2 年前
It seems like this article is an advertising for Wolfram Alpha&#x27;s then-new feature. It brings few elements to support the headline thesis, aside from showing these features.
makz将近 2 年前
This is not new. There is something called rethorical algebra.<p>Rhetorical Algebra<p>It was developed by ancient Babylonians where the equation was written in the form of words that remained up to the 16th century.<p>Example: x + 5 = 8, is written as &quot; The thing plus five equal to eight&quot;.