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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?

#141

Post by red-iron-pine »

charleslmunger wrote: post #138
geoduck14 wrote: post #76

Earlier quoted context omitted.

Scan a menu, look for the different entrees, identify the most probable ingredients, determine health content. Then: allow people to search for food based allergies, food aversions, calories. Generate pictures of what the food might look like, display the pics next to the food to make it more likely a user will buy that food.

Until one of your customers' children eats a peanut that the AI didn't infer would be an ingredient, and dies. Generating fake pictures also seems like it would be more ordinary false advertising.

also requires the resto or manufacturer to list all ingredients, and most already list potential allergens.

but yeah liability would scare me, esp. because without it you can put the liability squarely on the restaurant or in some cases the person ordering / asking / buying.

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

#142

Post by int_19h »

dongecko wrote: post #122
TheLegace wrote: post #109

Earlier quoted context omitted.

How do you get the output to be formatted correctly or without any branches. Say for example I want a step-by-step instruction for an action. But the response will have 1. 2. 3. and sometimes if there are multiple pathways there will long answer with 2.a,b,c,d. This is not ideal I would rather have the most simple case(2.a.) and a short summary for other options. I have described it in the prompt but still cannot get…

I have not encountered this problem yet. When I was talking about the format of the answer I meant the following: No matter if you're using Langchain, Llamaindex, something self made, or Instructor (just to get a json back); under the hood there is somewhere the request to the LLM to reply in a structured way, like "answer in the following json format", or "just say 'a', 'b' or 'c'". ChatGPT tends to obey this rather…

It's pretty easy to force a locally running model to always output valid JSON: when it gives you probabilities for the next tokens, discard all tokens that would result in invalid JSON at that point (basically reverse parsing), and then apply the usual techniques to pick the completion only from the remaining tokens. You can even validate against a JSON schema that way, so long as it is simple enough.

There are a bunch of libraries for this already, e.g.: https://github.com/outlines-dev/outlines

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

#143

Post by digitcatphd »

Right now in my opinion the most potential is the large action model designed by Rabbit or a similar general learning framework that can be rapidly configured without a ton of code. I anticipate such a tool or model and therefore will not invest significantly into building things the hard way. Already learned my lesson with that for LLMs.

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

#144

Post by godelski »

dougb5 wrote: post #90
spenczar5 wrote: post #48

Earlier quoted context omitted.

> 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…

I don't know if I'm more forgiving of inaccuracies in a conversational interface, but I'm way less likely to notice them in the first place. Especially since the current crop of RLHF'd models are so eager to please that they say nearly everything with high confidence.

I think this is a more realistic notion of what AI danger is rather than the X-risk. It's our tendency to trust things given a certain means of presentation. There are certain things where error is okay, but many things where even a small error is huge (like the OP is mentioning). The danger is not so much in the tool itself but us using the tools in a lazy manner. It isn't unique to ML/AI, but ML/AI uniquely are better at masking the errors. It's why I dislike the AI hype.

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

#145

Post by godelski »

__loam wrote: post #98
dougb5 wrote: post #90

Earlier quoted context omitted.

I don't know if I'm more forgiving of inaccuracies in a conversational interface, but I'm way less likely to notice them in the first place. Especially since the current crop of RLHF'd models are so eager to please that they say nearly everything with high confidence.

Yeah I think a lot of people think RLHF is a tool for increasing accuracy but it really is training it to be convincing.

Which should be rather obvious if you understand that it's basically a GAN. You have a discriminative model who's objective function is based on Justice Potter's description of porn: I know it when I see it. If you ask what types of errors might emerge from such a formulation I think it becomes rather obvious.

Which isn't to say that the tools aren't useful. But I have to add this fact because many people conflate any criticism with being dismissive of the technology. But technology is about progress, not completion. Gotta balance criticism and optimism. Optimism drives you and criticism directs you.

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

#146

Post by int_19h »

tudorw wrote: post #36
lebean wrote: post #10

Don't downplay the value of watching agents talk to each other for amusement. I got a lot of mileage out of that and will continue to do so.

This, I am quite happy to watch a dozen 'agents' thrash out some ethical issues purely for my own wn amusement, it's fascinating! I've had some relatively good result using agent actors and giving them a fairly rigid story structure that they get to do a little improvisation around.

If you enjoy this kind of thing, take a look at https://chirper.ai. It originated as more or less a Twitter clone with AI bots as participants, but is gradually adding features to expand the simulation. Their end goal is basically "sim life".

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

#147

Post by foolswisdom »

carlossouza wrote: post #114
Kerbonut wrote: post #110

Earlier quoted context omitted.

> 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

Not really, he's saying that the solution is to not have the entire process in a single model, it's better to have the model work on specific pieces that you broke down, rather than feeding the whole thing and expecting the model to be able to break it down and generate correctly by itself.

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

#148

Post by deathmonger5000 »

rosspackard wrote: post #34
deathmonger5000 wrote: post #26

I taught https://github.com/KillianLucas/open-interpreter how to use https://github.com/ferrislucas/promptr Then I asked it to add a test suite to a rails side project. It created missing factories, corrected a broken test database configuration, and wrote tests for the classes and controllers that I asked it to. I didn't have to get involved with mundane details. I did have to intervene here and there, but not much.…

What do you mean when you use the word taught for open-interpreter? Looking at the OI docs wasn't too helpful. "I did spend a non-trivial amount of time fiddling with the prompts" was it writing prompts? I am really interested and this seems like a cool use case that I want to explore. Could you share the prompts on a github gist?

Here's the fork of Open Interpreter that I was experimenting with: https://github.com/ferrislucas/open-interpreter/pull/1/files

The system prompt that adds the Promptr CLI tool is here: https://github.com/ferrislucas/open-interpreter/pull/1/files...

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

#149

Post by renonce »

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 last widely used AI tool was facial recognition, a technology widely used in fields such as company clock-ins, access control, surveillance, and more, and it is so trusted that facial recognition is often the sole method for clocking in. These facial recognition systems can maintain an extremely high accuracy rate for every entry and exit of thousands of people in a database every day. Now when will LLMs achieve such accuracy?

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

#150

Post by EVa5I7bHFq9mnYK »

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,…

One area that has been useful for me, is writing simple code in languages I am not familiar with, and not willing to learn. For example, I needed to write a small bash script to automate things in Ubuntu, it really saved me time on googling all those commands. Same with Task Scheduler XML language. It knows very well the popular use cases of all the languages.
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