Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Ask HN: What have you built with LLMs?

news.ycombinator.com

Post reply on HN
Print view View original

81–90 of 349 posts

Re: Ask HN: What have you built with LLMs?

#81

Post by a5huynh »

I've been using a combo of LLMs + live transcription to build a passive assistant that keeps track of talking points and can pull out data/tasks from a conversation you're having (https://sightglass.ai or here's a demo of me using it: https://www.loom.com/share/0220ca03bce341669d314d4254872226)

So far this is being used for:

- Sales -> guiding new recruits during more complex client calls

- HR -> Capturing respones during screening interviews

If you'd like to try this out feel free to DM me or email me at andrew at sightglass.ai, we're looking for more testers!

Re: Ask HN: What have you built with LLMs?

#82

Post by beginning_end »

eurekin wrote: post #70
hazard wrote: post #51

A Twitter filter to take back control of your social media feed from recommendation engines. Put in natural language instructions like "Only show tweets about machine learning, artificial intelligence, and large language models. Hide everything else" and it will filter out all the tweets that you tell it to. Runs on a local LLM, because even using GPT3 costs would have added up quickly. Currently requires CUDA and us…

That could actually be a universal ad-whacker for similarily stubborn sites (reddit)

I've been thinking the same thing. It'll be interesting to see if we end up with prompt-injecting ads

Re: Ask HN: What have you built with LLMs?

#83

Post by bonamiko »

chetjan wrote: post #59
bonamiko wrote: post #49

I am working on building out a better voice interface for LLMs. It is still a work in progress (early beta), but you can check it out at https://www.bonamiko.com Currently I have mainly been using it as a tandem conversation partner for a language I'm learning, but it can be used for many more things. As it is right now, you can use it to bounce ideas of, practice interviews, and help answer quick general questions.…

Very cool, just signed up. What advantages does this have over the one built into the ChatGPT app? Also, it would be great if I could see the text output in addition to the voice.

The main differences fundamentally come down to OpenAI treating it more like a party trick demo, rather than a core functionality. I think it has a lot of potential if I can just fine tune a couple rough edges. (When you chat with someone in person, you don't pull out notebooks a write messages to each other. I see writing as a fallback medium.)

To answer your question more specifically,

Pro Bonamiko:

  - Faster average first response latency (but higher first audio latency since OpenAI uses a ding). This is the main focus currently, reducing latency as much as I can. I'd like to be able to avoid the ding, but we'll see how low I can get it.
  - Can be used anywhere with a browser, OpenAI requires a mobile app installed. (I.E. Desktop support)
  - In the future we can support deeper customization since we are focused on the audio medium. As soon as you have to run a function in the ChatGPT app there is a long response latency, which could easily be fixed by something as simple as the AI saying "Let me perform a search to get the details"
Pro ChatGPT:

  - Nice animation
  - Already has built in tool support such as web search
  - Supports language switching automatically between messages, Bonamiko requires manually changing the language

Re: Ask HN: What have you built with LLMs?

#84

Post by ianbicking »

s-macke wrote: post #61
ianbicking wrote: post #52

Earlier quoted context omitted.

Fun, I tried to do this back with GPT-3: https://llm.ianbicking.org/interactive-fiction/ But Zork wouldn't be a very accurate measure of skill because GPT definitely knows Zork. Unfortunately the emulator ( https://github.com/DLehenbauer/jszm ) doesn't work with most games newer than Zork. I haven't revisited the code with newer GPT models either.

GPT-3 doesn't even manage the first few steps of the tested text adventure. And GPT-4 is not good at playing these adventures either. However, my code run a newer version of the Z-machine. So Zork and many other text adventures will work. I have not tried many other games though.

I was surprised how high your costs were. I assume you are putting the entire transcript into each prompt, but even then that seems high. Is GPT's planning also taking up a lot of room?

I did find giving GPT some hints about the known commands helped a lot, and I put in some detection of error messages and kept a running log of commands that wouldn't work. Getting it to navigate the parser is kind of half of the skill of playing one of these games. It would be interesting to have it play some, then step back and have it reflect and enumerate things about how the play itself works.

Re: Ask HN: What have you built with LLMs?

#87

Post by mfalcon »

I'm making two LLM's negotiate the exchange of a product, price is the main issue but I'm trying to make them negotiate another issues too in order to avoid the "bargaining" case.

I've tried several models and gpt4 is currently the one that better performs, but OS LLM's like Mixtral and Mixtral-Nous are quite capable too.

https://github.com/mfalcon/negotia

Re: Ask HN: What have you built with LLMs?

#88

Post by jamesponddotco »

I built a couple of things, but the most useful is probably allalt[1], which describe images and generate alt tags for visually impaired users using GPT-4V. Next I want to add the option to use local LLMs using ollama[2], but I'm still trying to decide the UX for that.

There's also Moss[3], a GPT that acts as a senior, inquisitive, and clever Go pair programmer. I use it almost daily to help me code and it has been an huge help productivity-wise.

[1] https://git.sr.ht/~jamesponddotco/allalt

[2] https://ollama.ai/

[3] https://git.sr.ht/~jamesponddotco/moss

Re: Ask HN: What have you built with LLMs?

#89

Post by bengarney »

I wrote an autonomous AI space opera tv show generator. It takes a short topic phrase on one end and spits out a 10-15 minute 3D animated and AI voiced video suitable for upload to YouTube on the other end.

Super interesting learning exercise since it intersects with many enterprise topics, but the output is of course more fun.

In some ways it is more challenging - a summary is still useful if it misses a point or is a little scrambled, whereas when a story drops a thread it’s much more immediately problematic.

I’m working on a blog post as well as getting a dozen episodes uploaded for “season 1”.

Re: Ask HN: What have you built with LLMs?

#90

Post by guywhocodes »

I built a tool to create "average llm" probability of code for checking how aligned code is with what an LLM would output. Working on adding context from a project to check how the style of a section aligns with the style, content and domain of a project.

Idea is to use it to identify code that sticks out, because that usually what's interesting or bad.

Post reply on HN