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Ask HN: What are some actual use cases of AI Agents right now?

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Re: Ask HN: What are some actual use cases of AI Agents right now?

#111

Post by da4id »

alexawarrior3 wrote: post #2

None of these I've seen actually works in practice. Having used LLMs for software development the past year or so, even the latest GPT-4/Gemini doesn't produce anything I can drop in and have it work. I've got to go back and forth with the LLM to get anything useful and even then have to substantially modify it. I really hope there are some big advancements soon and this doesn't just collapse into another AI winter,…

Why do you want it to generate web pages from images? I'm having trouble understanding the workflow here. You see a component you like on another website and want to obtain the code from it? Or if you have a design already, why not just use a Figma to Code tool?

Re: Ask HN: What are some actual use cases of AI Agents right now?

#113

Post by gremlinsinc »

PheonixPharts wrote: post #37

> I'd love to know what are some of the hidden challenges to making a useful product with agents? One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI". The biggest thing any ML practitioner realizes when they step out of a research setting is that…

> You can do handwritten digit recognition with 90% accuracy? Sounds pretty good, but if you need to turn that into recognizing a 12 digit account number you now have a 70% chance of getting at least one digit incorrect. This means a product worthy digit classifier needs to be much higher accuracy.

Language is essential for human civilization, so are tools. We wouldn't get far without either.

maybe a language model can understand what it needs to do but not how to do it, so you give it a tool.

Humans can get pretty far without 100 percent accuracy, we can get a lot from AI models before they reach 100 percent, but being that at some point AI will be able to improve itself even remake itself daily with 2x the abilities, 100 percent or at least 99.7 percent is attainable.

Right now I can take any YouTube video summarize it and turn it into a podcast, short form videos, and a blog post.

There's definitely a lot of marketing uses right now for ai agents. If you think about embodied AI, it's only as good as it's body. if it doesn't have good grippers it will struggle to pick things up.

Also with a lot of things, accuracy is subjective one person might think ad copy is great and maybe their manager thinks it's shit. One person could give it a 100 percent score and another a 70 percent.

My point is we're so close here, and it's already amazing technology and we can augment failures by creating larger toolboxes.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#114

Post by carlossouza »

Kerbonut wrote: post #110
alexawarrior3 wrote: post #2

None of these I've seen actually works in practice. Having used LLMs for software development the past year or so, even the latest GPT-4/Gemini doesn't produce anything I can drop in and have it work. I've got to go back and forth with the LLM to get anything useful and even then have to substantially modify it. I really hope there are some big advancements soon and this doesn't just collapse into another AI winter,…

> 1. An agent to automate generating web pages from design images - Given an image, produce the HTML and CSS. LLMs couldn't do this for my simple page from a web designer. Not even close, even mixing up vertical/horizontal flex arrangement. When I cropped the image to just a small section, it still couldn't do it. Tried a couple LLMs, none even came close. And these are pretty simple basic designs! I had to do it all…

https://www.youtube.com/watch?v=bRFLE9qi3t8

Here's the CEO of Builder.io supporting your comment: he says they tried LLMs/agents, and it didn't work. Then, they collected a dataset and developed an in-house model only to assist where they couldn't solve with imperative programming

Re: Ask HN: What are some actual use cases of AI Agents right now?

#115

Post by gremlinsinc »

da4id wrote: post #111
alexawarrior3 wrote: post #2

None of these I've seen actually works in practice. Having used LLMs for software development the past year or so, even the latest GPT-4/Gemini doesn't produce anything I can drop in and have it work. I've got to go back and forth with the LLM to get anything useful and even then have to substantially modify it. I really hope there are some big advancements soon and this doesn't just collapse into another AI winter,…

Why do you want it to generate web pages from images? I'm having trouble understanding the workflow here. You see a component you like on another website and want to obtain the code from it? Or if you have a design already, why not just use a Figma to Code tool?

say you draw up your rough vision of things that you drew up paper, a very simple mock-up. That could be a nice use case.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#116

Post by emodendroket »

spenczar5 wrote: post #48
PheonixPharts wrote: post #37

> I'd love to know what are some of the hidden challenges to making a useful product with agents? One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI". The biggest thing any ML practitioner realizes when they step out of a research setting is that…

> The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has to be very high for it be productizable. I think that ChatGPT's success might be partly attributable to its chat interface. For whatever reason, a lot of people - including me! - are much more forgiving of inconsistencies, slip-ups, and inaccuracies when in a conversational format. Kind of lik…

Though I wonder how much of that is just that the format doesn’t encourage you to look closely enough at what you’re getting to see if it is right.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#117

Post by hubraumhugo »

heyalexej wrote: post #91
hubraumhugo wrote: post #13

Earlier quoted context omitted.

We're actively using this approach at scale, although still improving :) You can try out a simplified version of this in our playground: https://www.kadoa.com/add

Gave this a go. Just so happened that I had the page of an eBay seller open. Wondered if it could manage to do something as simple as extracting all 240 listed products on that page. Instead of determining that the most important data on this page would be the products, it identified these properties: categoryName, subCategories, link.

I'll look into this, we have a specific workflow template for ecommerce as it's always a similar data schema.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#118

Post by muzani »

spenczar5 wrote: post #48
PheonixPharts wrote: post #37

> I'd love to know what are some of the hidden challenges to making a useful product with agents? One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI". The biggest thing any ML practitioner realizes when they step out of a research setting is that…

> The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has to be very high for it be productizable. I think that ChatGPT's success might be partly attributable to its chat interface. For whatever reason, a lot of people - including me! - are much more forgiving of inconsistencies, slip-ups, and inaccuracies when in a conversational format. Kind of lik…

Personally having been a big fan of GPT-3, I was quite against ChatGPT because of this.

Completion models are obviously wrong very often. Instruct model was kinda ok, but you know it's a dumb machine.

Chat was a bit of an uncanny valley. I treated the instruct model like a child, but chat felt like having a conversation with someone of 80 IQ. It felt frustrating, and you ended up going "no no no, what I meant WAS ..." It felt like dealing with an incompetent colleague.

But I guess there's lots of views on it. Some expected it to be an oracle, even a god. Some treated it like Stack Overflow, then got frustrated that it was giving poor quality answers to poor quality questions. Some were just abusive to it. I suppose it's a mirror in a sense.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#119

Post by LarsDu88 »

altdataseller wrote: post #94
LarsDu88 wrote: post #83

Earlier quoted context omitted.

The first think any ML practictioner realizes is that accuracy is about the single worst performance metric you can use for most real-world tasks, lol

Can you explain this? Why is that?

Let me sell you an amazing cancer test my friend. It's 99.5 percent accurate.

It works through an incredibly novel mathematical technique. You simply go to the patient and tell them they don't have cancer.

Since 99.5 percent of people don't have cancer, this classifier is 99.5 percent accurate.

Completely bullshit classifier for a completely bullshit metric.

Use sensitivity/specificity or precision/sensitivity instead

Re: Ask HN: What are some actual use cases of AI Agents right now?

#120

Post by vintermann »

chenxi9649 wrote: post #43
PheonixPharts wrote: post #37

> I'd love to know what are some of the hidden challenges to making a useful product with agents? One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI". The biggest thing any ML practitioner realizes when they step out of a research setting is that…

Yea that's a good point. Now I am curious, what are some tasks that can accept a model that is at 80% as good as a human, but is 100x cheaper?(or, 100x faster?)

Well, an old one is OCR, especially handwritten OCR. I'm doing genealogy. There is SO MUCH old handwritten material that is never transcribed, and which requires special expertise to read (old and exotic handwriting styles) and interpret (place names, writing conventions, abbreviations).

It doesn't have to be perfect. It's not as if the actual data in there is perfect. It just has to be in a form where I can search it, ideally with named entities mapped.

Quality - like deciphering the writing on scrolls buried in volcanic ash in Herculaneum - gets all the attention. But what I really want is quantity - I want to be able to search through those 5000 pages of 200 year old mildly damaged cadastral records in dense handwriting. I want to relieve the army of kind retirees who currently transcribe these sorts of documents one by one based on their own needs.

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