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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?

#91

Post by heyalexej »

hubraumhugo wrote: post #13
jstummbillig wrote: post #9

Earlier quoted context omitted.

I am confused to where this leaves us. Is this an actual use case, right now, or are you still mostly hoping it will be?

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.

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

#92

Post by vergessenmir »

Reasoning across many stages, converging on a user provided goal with the required level of accuracy is beyond commercially available LLMs. Take the travel agent use case, a recent paper showed that Llms tested would get dates and prices wrong. So the promise of AutoGPTs, GodGPTs etc is still quite far away

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

#93

Post by brendongeils »

majority of our users are seeing value from heavy co-pilot workflows in documents, jupyter notebooks and form generation. we built a data analytics platform for context. early use was chat with your SQL database and web research. now we are seeing more multi-modal uses for chart analysis. we have a whole list of tasks on our application homepage https://app.athenaintelligence.ai/

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

#94

Post by altdataseller »

LarsDu88 wrote: post #83
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 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?

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

#95

Post by chenxi9649 »

Liron wrote: post #70

There are countless use cases for a good AI agent. The problem is temporary: good AI agents don't exist, because sufficiently intelligent AI doesn't yet exist. (Agency and broad-domain intelligence are basically the same thing. Being able to answer questions relevant to planning is planning.) This state of affairs is in stark contrast to the crypto/Web3 space, where no one ever presented a use case even conditional o…

I guess a good enough AI agent is essentially a human worker.

I wonder if all the work that's being put in right now by agent projects will become more or less "useless" similar to those specialized classification models before LLMs. Or will it be an AI with OK intelligence + 100 novel tricks/hacks that creates an Upwork level general agent.

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

#96

Post by PheonixPharts »

jhbadger wrote: post #82
mFixman wrote: post #40

Earlier quoted context omitted.

> 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. You are assuming that the probability of failure is independent, which couldn't be further from the truth. If a digit recogniser can recognise one of your "hard" handwritten digits, such as a 4 or a…

And the US Post Office and other postal services have been using this tech to sort letters for several decades now (although postal codes with both letters and numbers like Canada's are harder). It was viewed as the "killer app" for ML in the 1990s.

This thread is an object lesson in the point I'm making: people have forgotten everything we've learned about making ML based products.

Parent comment doesn't understand the concept of expectation, and this comment is apparently unfamiliar with the fact that SotA for digit recognition [0] has been much higher than 90% even in the 90s. 90% accuracy for digit recognition is what you get if you use logistic regression as your model.

My point was that numbers that look good in terms of research often aren't close to go enough for the real world. It's not that 90% works for zip codes, it's that in the 90s accuracy was closer to 99%. You have validated my point rather than rejected it.

0. https://en.wikipedia.org/wiki/MNIST_database

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

#98

Post by __loam »

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.

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

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

#99

Post by rpmisms »

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,…

Besides writing boilerplate, I used AI to generate a color scheme and imagery for a charity website I built.

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

#100

Post by rozap »

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…

This has been a perfect description of my experience doing this. I had written some code to go through reasonably complex web onboarding flows and it basically played out exactly like you predicted in your comment. In addition, I've been working with some vendors that have been trying to do the same thing and they're finding that it works out just like you describe.

The handwritten automations have performed better and the issues are reproducible, so even when there are issues, there's some sense of forward progress as you fix them. With handing it all over to an agent, it really feels like running around in circles.

I think there's probably something here, but it's less trivial than just tossing a webpage at chatGPT and hoping for the best.

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