Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Building a no-code toxicity classifier by talking to GitHub Copilot

surgehq.ai

Post reply on HN
Print view View original

61–70 of 152 posts

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#61

Post by esjeon »

jayceekay wrote: post #47
BeefWellington wrote: post #45

Earlier quoted context omitted.

A few years ago I did some work with IBM's Watson Twitter integration. One of the fun things you could do was sentiment analysis. It was reasonably accurate for the extremes but anything in the gray area would be wildly off. A politely worded tweet that was scathing would come across high on the positive sides of the scale, whereas a perfectly reasonable sentence that included profanity as used in a quote would immed…

didn't watson turn out to be useless and spaghetti code inside? aka ibm's marketing arm

Welp, you're downplaying IBM too much. IBM got the product direction right earlier than anyone. Watson is a querying system w/ advanced NLP/IR/KRR capability running on dedicated compute chips, and large corps are more or less following this path. It's just that IBM did it too early and used rather old approaches, which doesn't grow well (thus "spaghetti").

Still, Watson is pretty much the only one in its class. There are good alternatives out there that worked well for many people, but they offer only a subset of Watson's feature set. If an organization need some real bang, Watson is the only option.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#62

Post by eurasiantiger »

caymanjim wrote: post #59
junon wrote: post #53

Earlier quoted context omitted.

If this is what software engineering turns into, put a bullet through my head please.

I haven't tried Copilot, and based on what I've read, I don't think I'd want to use it in its current form, but I'd love for software development to evolve to the point that I never have to write any boilerplate code again. Even with DSLs, code generation, autocompletion, snippets, and countless libraries and frameworks to draw upon, the bulk of what I do as developer is write the same boring code over and over again…

Copilot can already write your boilerplate for you once it has a single example of how to do it.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#63

Post by eurasiantiger »

fsargent wrote: post #49

I seriously thought that GitHub CoPilot was suggesting how to find new kinds of sarin gas. https://www.theverge.com/2022/3/17/22983197/ai-new-possible-... How long until it does?

You could already ask it to do this.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#64

Post by esjeon »

Not really no-code. Let's be honest. The OP is taking steps just like how an experienced SW developer would. Copilot simply cut the need for reading through documentations. This doesn't really say that Copilot can replace programmers.

p.s. Does anyone know when Copilot will update the insecure example on their website? Or are they just trying to be honest with the possible quality issues with the generated code?

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#65

Post by Mountain_Skies »

hombre_fatal wrote: post #60

This is absolutely insane. I had no idea Copilot was this good. The negativity here just seems like sour grapes or weird goal posts. Sure, it makes mistakes and needs verification. But know what also makes mistakes and needs verification? All the code I already manually write as I tediously ratchet towards a solution. Removing some cycles from that process is a win. Just stubbing out close-enough boilerplate is a win…

Even though it is based on mostly human written code, Copilot makes mistakes that are different from the type human coders typically make. It will take a different skill set to detect and correct the errors made by systems like Copilot. The same is true for self-driving cars. This doesn't mean that we shouldn't use these technologies, just that there will be adaptations to our behavior we'll need to make if we want to make use of them.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#66

Post by ShamelessC »

tomerv wrote: post #34

The first comment asks Copilot to import all the libraries needed for a toxicity classifier, and it imports libraries such as re (regex engine) and nltk (natural language toolkit). But what if I wanted a classifier for toxic chemicals and not toxic speech? That was my first thought when I saw "toxicity" in the title. I'm now imagining a very frustrated junior developer a few years from now trying to argue with Copilo…

> I'm now imagining a very frustrated junior developer a few years from now trying to argue with Copilot to write code for a classifier for chemical compounds, but it just spits out code for classifying text.

So just the future version of a junior developer not knowing how to use their tools? Yeah, that scans. Still sounds incredibly useful however. The alternative is, of course, a junior developer fumbling as they try to write said program entirely from their learned skills and experience.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#67

Post by fn1 »

Mountain_Skies wrote: post #65
hombre_fatal wrote: post #60

This is absolutely insane. I had no idea Copilot was this good. The negativity here just seems like sour grapes or weird goal posts. Sure, it makes mistakes and needs verification. But know what also makes mistakes and needs verification? All the code I already manually write as I tediously ratchet towards a solution. Removing some cycles from that process is a win. Just stubbing out close-enough boilerplate is a win…

Even though it is based on mostly human written code, Copilot makes mistakes that are different from the type human coders typically make. It will take a different skill set to detect and correct the errors made by systems like Copilot. The same is true for self-driving cars. This doesn't mean that we shouldn't use these technologies, just that there will be adaptations to our behavior we'll need to make if we want t…

> Even though it is based on mostly human written code, Copilot makes mistakes that are different from the type human coders typically make.

Can you give an example for this?

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#68

Post by [deleted] »

tomerv wrote: post #34

The first comment asks Copilot to import all the libraries needed for a toxicity classifier, and it imports libraries such as re (regex engine) and nltk (natural language toolkit). But what if I wanted a classifier for toxic chemicals and not toxic speech? That was my first thought when I saw "toxicity" in the title. I'm now imagining a very frustrated junior developer a few years from now trying to argue with Copilo…

[deleted]

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#69

Post by BeefWellington »

jayceekay wrote: post #47
BeefWellington wrote: post #45

Earlier quoted context omitted.

A few years ago I did some work with IBM's Watson Twitter integration. One of the fun things you could do was sentiment analysis. It was reasonably accurate for the extremes but anything in the gray area would be wildly off. A politely worded tweet that was scathing would come across high on the positive sides of the scale, whereas a perfectly reasonable sentence that included profanity as used in a quote would immed…

didn't watson turn out to be useless and spaghetti code inside? aka ibm's marketing arm

I'll preface this by saying that my time working with it was while I was working at IBM, so feel free to take this with a grain of salt. In my time since I've worked in a few Data/ML and Security positions, so I do have a basis for comparison with other systems.

From what I saw, the actual language-processing part of it was top-tier. It's just it's a hard problem to come up with a demo for that people will actually respond positively to, hence the Jeopardy stint. It has limited real applications. It's really good at what it does but what it does isn't really widely useful.

Nobody wants to see "We're going to replace all our online help / support chat stuff with Watson" because people find those systems frustrating already, even if it would make things vastly better than some of the alternatives.

So you end up with weird stuff like Chef Watson, Doctor Watson, and so on -- things in areas where an ML model isn't going to replace a human anytime soon.

Then Marketing gets involved and suddenly anything that uses any kind of ML needs to have Watson slapped on it, even if it's not doing any language processing.

Re: Building a no-code toxicity classifier by talking to GitHub Copilot

#70

Post by ShamelessC »

hombre_fatal wrote: post #60

This is absolutely insane. I had no idea Copilot was this good. The negativity here just seems like sour grapes or weird goal posts. Sure, it makes mistakes and needs verification. But know what also makes mistakes and needs verification? All the code I already manually write as I tediously ratchet towards a solution. Removing some cycles from that process is a win. Just stubbing out close-enough boilerplate is a win…

> The negativity here just seems like sour grapes or weird goal posts.

Indeed. Every negative comment I have seen here has been a shallow dismissal by someone who clearly hasn't engaged with the tool. I'm not sure why people here are so primed to shit all over anything potentially innovative, seemingly even without background knowledge. Like, is there something inherently offensive to coders about a model that threatens to do their job? Or is it just years and years of people getting burned by previous "AI" projects without knowing that this one is actually rather impressive and comes from good research?

Keep shallow dismissals to yourselves people. It's in the site's rules.

Post reply on HN