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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?

#71

Post by tudorw »

HeatrayEnjoyer wrote: post #63
tudorw wrote: post #36

Earlier quoted context omitted.

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.

What are you using to set up and run a multi ai interaction?

Python and GPT4ALL running Mistral 7b, only a CPU so fairly slow but adequate for my entertainment, I have a sort of roundtable, I feed in a topic then have 7 or so personas discussing the topic, the output is distilled into the prompt for the next 'person', it sort of works, sometimes quite convincingly, I also extract and construct a knowledge graph based on the responses, it's an interesting way to observe what a model know about a subject, if you check my profile there's a link to some video recordings of the output on twitch.

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

#74

Post by dongecko »

CharlieDigital wrote: post #58
dongecko wrote: post #27

The company I work for has tons of documentation and regulations for several areas. In some areas the documents are well over a thousand and for the ease of use of these documents we build RAG based chat bots. This is why I have been playing with RAG systems on the scale of "build completely from scratch" to "connect the services in Azure". The retrieval part of a RAG is vital for good/reliable answers and if you bui…

> You can also build a network of agents My experience has been that they are far too unpredictable to be of use. In my testing with agent networks, it was a challenge to force it to provide a response, even if it was imperfect. So if there's a "reviewer" in the pool, it seemed to cause the cycle to keep going with no clear way of forcing it to break out. 3.5 actually worked better than 4 because it ran out of contex…

That is an interesting observation. I have not gotten to the point of too long cycles and I can think of two reasons for that.

Maybe my use case is narrow enough, so that in combination with a rather constraining and strict system message an answer is easy to find.

Second, I have lately played a lot with locally running LLMs. Their answers often break the formatting required for the agent to automatically proceed. So maybe I just don't see spiraling into oblivion, because I run into errors early ;)

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

#75

Post by tudorw »

rosspackard wrote: post #35
janlukacs wrote: post #4

I keep asking the "experts" on Linkedin all the time, show me real life uses - radio silence.

Could this be a case like investment alpha? If you have a real life use case and share it then you could lose the opportunity. So some "experts" could be staying quiet because they don't have one. But some may stay quiet because they are working on or benefiting from it?

I thought this too initially, however by now I would expect one of those to 'break rank' and actually demonstrate some impressive use case, I've not seen anything in terms of 'fire and forget' agents actually achieving a task of any complexity. I had some success using AutoGPT to do some web scraping and it's ability to use powershell was impressive and powerful, and with no safeguarding somewhat hazardous, however it's unpredictability was intolerable.

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

#76

Post by geoduck14 »

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?)

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.

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

#77

Post by tetha »

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?)

Similar to the sibling comment, helpdesk ticket routing.

The volume of helpdesk tickets large enterprises deal with is very easily and vastly underestimated. If you can even route 30% away from the central triage with 90+% accuracy and drop everything else back to the central triage... you suddenly safe 2 FTEs in that spot in some places. And increase customer satisfaction for most of those tickets because they get resolved faster.

Or, as much as people hate it, chatbots as a customer front. Yes, everyone here as an expert in a lot of tech has had terrible experiences with chatbots. Please mark your hate with the word "Lemon" in the comments. But decently implemented chatbots with a few systems behind them can resolve staggering amounts of simple problems from non-techies without human interaction from the company deploying them. It remains important to eventually escalate to humans - including the history from all of these interactions to avoid frustrations, sure.

Or, ticket/request preprocessing. Remember how spelling that 10 digit account number to a call center agent hard of hearing sucks? Those 4 retries because of you not using a better way to communicate that number also costs the company. Now, you can push a few of these retries into an AI system. If you mail them, an AI system can try to extract information like account numbers, intent, start of the problem, problem descriptions and such into dedicated fields to make the support agents faster.

Companies are certainly overdoing it at the moment, I'm not denying that. But a lot of the support/helpdesk pre-screening can be automated with current AI/ML capabilities very decently. Especially if you learn to recognize and navigate it.

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

#78

Post by dongecko »

chenxi9649 wrote: post #50
dongecko wrote: post #27

The company I work for has tons of documentation and regulations for several areas. In some areas the documents are well over a thousand and for the ease of use of these documents we build RAG based chat bots. This is why I have been playing with RAG systems on the scale of "build completely from scratch" to "connect the services in Azure". The retrieval part of a RAG is vital for good/reliable answers and if you bui…

Interesting, it seems that using an LLM as an agent to help with knowledge retrieval is one concrete use case that I've seen people do repeatedly. It also feels like we are at a bottle neck when it comes to the knowledge retrieval problem. I wonder if the "solution" to all of these is just a smarter foundational model, which will come out of 100x more compute, which will cost approximately 7 trillion dollars.

I also think of the retrieval part as a bottleneck and I am super excited of what the future holds.

In particular, I wonder if RAG systems will soon be a thing of the past, because end to end trained gigantic networks with longer attention spans, compression of knowledge, or hierarchical attention will at some point outperform retrieval. On the other hand, I can also see a completely different direction coming, where we develop architectures that, like operating systems, deal with memory management, scheduling and so on.

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

#79

Post by Karrot_Kream »

tetha wrote: post #77
chenxi9649 wrote: post #43

Earlier quoted context omitted.

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?)

Similar to the sibling comment, helpdesk ticket routing. The volume of helpdesk tickets large enterprises deal with is very easily and vastly underestimated. If you can even route 30% away from the central triage with 90+% accuracy and drop everything else back to the central triage... you suddenly safe 2 FTEs in that spot in some places. And increase customer satisfaction for most of those tickets because they get r…

The last company I worked at eventually became a Big Tech. In the beginning though, we used to ask all engineers to pair with customer service folks to deal with ticket triage. When we got a bit bigger, we used to have rotations where eng would pair with customer service folks. Being on the other side of that was very eye-opening for all eng. Many used to come in with the same bias that you see on this site, that how dare you be routed to some automated service and how inhumane the service is. On the other side you see competent CS agents absolutely swamped with low-level questions that were often literally answered in docs and FAQ pages. I think getting transformer-based triage models correct can unlock tons of value.

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

#80

Post by topspin »

crowdyriver wrote: post #42

I am surprised no one is doing an llm code linter.

Wouldn't Microsoft's "Github Copilot" be an example of that? I don't know because I haven't looked at it, but I be surprised if that wasn't one of its functions.

I've been dumping large chunks of code into GPT-4 to spot things I've overlooked. That has been very useful, particularly with low level C work.

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