Nice read
Ask HN: What are some actual use cases of AI Agents right now?
131–140 of 154 posts
Re: Ask HN: What are some actual use cases of AI Agents right now?
#132- Suggesting better variable names
- Cleaning up / changing something in bulk ( eg. cleaning attributes from a class)
- Generating unit tests ! ( just follow up on what it actually tests though)
Re: Ask HN: What are some actual use cases of AI Agents right now?
#133> 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…
> There are cases where lower accuracy results are acceptable, but most people don't even consider this before embarking on their journey to build an AI product/agent.
what do you think would help people consider this before going down that path?
Re: Ask HN: What are some actual use cases of AI Agents right now?
#134Earlier 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…
and this is why consumers lose a bunch of money, so corporations can save $3-6 per help desk ticket. then consumers get stuck in a bot interface and can never break out of it (speaking from personal experience)
Re: Ask HN: What are some actual use cases of AI Agents right now?
#135Earlier 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.
yeah i tried with a type of website that i commonly write scrapers for and i'm not sure if i can do anything with these results.
ai + web scraping is hard, i've tried and gave up, but that doesn't mean it's impossible, it just means i'm not a good engineer, so i will stay tuned to kadoa project.
Re: Ask HN: What are some actual use cases of AI Agents right now?
#136Earlier quoted context omitted.
> 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…
The use case we have is that we are asking the LLM to write articles.
As part of this, we tried having a reviewer agent "correct" the writer agent.
For example, in an article about a pasta-based recipe, the writer wrote a line like "grab your spoon and dig in" and then later wrote another line about "twirl your fork".
The reviewer agent is able to pick up this logical deviation and ask the writer to correct it. But given an instruction like "it doesn't have to be perfect", the reviewer will continue to find fault with the output from the writer for each revision so long as the content is long enough.
One workaround is that instead of fixing one long article, have the reviewer only look at small paragraphs or sections. The problem with this is that the final output can feel disjointed since the writer is no longer working with the full context of the article. This can lead to repeated sentence structure or even full on repeated phrases since you're no longer applying the sampling settings across the full text.
In the end, it was more efficient and deterministic to simply write two discrete passes: 1) writer writes the article and 2) another separate call to review and correct.
Re: Ask HN: What are some actual use cases of AI Agents right now?
#137Earlier quoted context omitted.
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.
yeah i tried with a type of website that i commonly write scrapers for and i'm not sure if i can do anything with these results. ai + web scraping is hard, i've tried and gave up, but that doesn't mean it's impossible, it just means i'm not a good engineer, so i will stay tuned to kadoa project.
Absolutely not knocking this project. Was just a somewhat unexpected result from such a simple site. Asked GPT-4 to write a scraper just to compare and it produced a quite usable boilerplate.
Re: Ask HN: What are some actual use cases of AI Agents right now?
#138Earlier 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?)
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.
Re: Ask HN: What are some actual use cases of AI Agents right now?
#139> 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…
> 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 like how you might forgive a real human for making a mistake in conversation.
The key term here is "conversation". If I query something from the machine and it disappears and rumbles and then prints off something like a 1980s mainframe, with paper that has those holes on the side that you tear off... and then it's wrong, it's wasted time.
Meanwhile with the conversation I'm watching it in real time, and can stop it, refine it, or ask or clarification immediately and effectively. There is an expectation of give and take and "talking through" things to get to an answer, which I find is effective. I don't need it to be 100% right all the time, just 80% and then start parsing answers out of it to refine it to 90% accuracy with high confidence.
Re: Ask HN: What are some actual use cases of AI Agents right now?
#140Earlier quoted context omitted.
I speak English clearly. These things always tell me to repeat what I said. Never once has it ever worked for me. I want to throw my phone at the wall. Also I think this has been around for longer than chatgpt. It is often accompanied by a fake keyboard clicking noise.
> I speak English clearly. These things always tell me to repeat what I said. Never once has it ever worked for me. I want to throw my phone at the wall Now imagine how well it works for people with non-"native" accents (even for native, I'd guess that a good Scouse/Glaswegian/Kiwi accent might confuse the hell of those systems as well). It's a disaster and I hate those.
There's a general problem across the tech industry with replacing existing simple and reliable (in a sense of conveying the user's intention) interfaces like physical buttons with stuff that is supposedly "more natural" like speech recognition or swipe gestures that in practice has a much higher error rate.
See also: replacing physical buttons with convoluted swipe gestures on mobile devices in the never-ending quest to make screen as large as possible. When was this ever a user ask?
I feel sometimes like the present UX design is one large LLM-like hallucination.