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Show HN: Graph-based AI for longform writing

jotte.ai

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Re: Show HN: Graph-based AI for longform writing

#21

Post by Broge »

evo_9 wrote: post #13

Looks great, and def something I would try. What's the story on the waitlist, how soon do you anticipate granting accounts? I have two novels I'm working on, both have very detailed chapter breakdowns and a few chapters written for each. I have more story ideas that are roughed out and a more brief outline that could also be further developed with a tool like this. I wonder if it would be possible to seed something l…

Hey! For the waitlist, cross my fingers, we'll have something in a week or so. Worst case, it'll be within the next month.

If you're fine with the current capabilities, the text is stored in your browser's localstorage, so you should be able to use it.

Regarding the voice, there's no technical barriers, only implementation. It's definitely something we're considering, but please let us know in the waitlist! https://forms.gle/SmrnBgfygCLPXrFK8

Re: Show HN: Graph-based AI for longform writing

#22

Post by [deleted] »

aprinsen wrote: post #17
aiappreciator wrote: post #16

Earlier quoted context omitted.

At very minimum, better novels. Current text transformers are horrendous in writing long form stories (ie, longer than 1 page). Because they don't have a concept of long-term memory. It has to keep everything in its short term memory (the context window), which is at most 2k words right now. Everything else is discarded, so the AI is unable to keep track of past events. This AI probably tries to summarise past events…

Why would we want an AI that writes novels though? Is this a "to see if we can" thing? Let's say this or some future AI system writes better novels than any human author at a fraction of the cost. Novel writing is solved. What will we have achieved? I wish I could opt out of this world you want to create, where if you achieve your vision, I will be utterly useless and obsolete.

[deleted]

Re: Show HN: Graph-based AI for longform writing

#23

Post by ed_mercer »

Broge wrote: post #9
howon92 wrote: post #5

Congrats on the launch! I'm not your target market but am curious to learn how this gives AI "unlimited" memory. Whenever I try to use GPT-3 API, I'm blocked by the token limit for most practical applications. My two cents for the product itself is it seems more like a tool for developers than novel writers. Have you done any beta testing with your target users?

Thanks for the kind words! The unlimited part comes from the AI knowing just enough context to stay coherent in any situation. Current long-form text techniques usually just summarize the past n tokens, and maybe the previous summary as well. The problem with this is that it quickly loses specifics of anything that happened just outside the window. What Jotte's graph-based approach does is have weighted summaries, al…

Hi! Jotte looks amazing, and I can't wait to try it out. Unless its proprietary, can you elaborate what you mean with "weighted summaries"?

Re: Show HN: Graph-based AI for longform writing

#24

Post by Broge »

davidthewatson wrote: post #18

I'm excited to give this a try. Long story short, I worked through a series of concepts with a designer friend last year using GPT-3 with a similar target: longform. Our approach was not interactive, but rather that the need was for a batch mode, overnight tool. I'm not really interested in having yet another JS library interrupt my real-time flow, which is quite quick, but is easily interrupted and I feel like we're…

Regarding the training data, thanks so much! We're definitely gonna be looking into improving and specializing it so it's less... whatever we could come up with at 2AM in the morning.

Now I guess is my time to learn. Why do you think grammarly and gmail help flow? If anything, those red lines make me lose my train of thought.

And finally, regarding DFS, seems like you're right! Fixed!

Once we release for writers, we're planning to tighten up the positioning and make the UX a bit more intuitive.

Re: Show HN: Graph-based AI for longform writing

#25

Post by cardine »

This is a very cool idea.

We are doing something similar except we are also predicting the nodes.

In the end, the winning combination will likely be doing both. There will be a predicted graph structure which serves as a high level guide to make sure the long text doesn't lose focus, but everything will still be written with full context using something like Compressive Transformers or Expire-Span.

Re: Show HN: Graph-based AI for longform writing

#27

Post by eternalban »

Mizza wrote: post #2

I am glad to see more stuff with graph based AI here. I have a running bet with a friend about whether future is going to be OBM (One Big Model) or LoLM (Lots of Little Models). I'm strongly in the LoLM/graph camp and have been working in that direction as well: https://github.com/Miserlou/Helix

It looks amazing. (Choice of Elixir is inspired. Great match to problem space.)

Re: Show HN: Graph-based AI for longform writing

#28

Post by YeGoblynQueenne »

erichocean wrote: post #15
gjstein wrote: post #10

Earlier quoted context omitted.

Just as ChatGPT seems pretty capable at summarizing text, an AI with "unlimited memory" could potentially answer analytical questions about larger datasets and non-linear data (in the sense that prose is read from start-to-finish). The OP is most excited about this ability to remember to create more structured longford outputs with internal consistency (e.g., asking questions about a fantasy universe that respects th…

E.g. you can imagine implementing an AI D&D dungeon master this way. It could even trigger things like (AI-synthesized) music at the right time. Or you could build an AI girlfriend/conversation partner.

I don't understand exactly how that would work. At some point, the generation would introduce new events and characters, new places or objects, and name them, but then when summarising, won't the names of some of them be lost, just because there's not enough space in the summary to name them all? The same goes for all sorts of detail, not necessarily named. At that point, what happens to the narrative about those forgotten characters, objects, etc?

The main idea, of continuously feeding the model a summary of its generation (and its dialog with the user of course) sounds interesting, but it's still not a memory. At some point, the continuous summarisation will have to grow big enough that it again exceeds the system's buffer (its "short term memory"). Either that, or it will drop so much detail from the summary that it will lose the plot.

So while this may result in longer generations, it doesn't look like it will really solve the problem of "long term memory", or long-distance dependency. It's a smart trick, but that's not enough.

Re: Show HN: Graph-based AI for longform writing

#29

Post by metadat »

danielbln wrote: post #3
Mizza wrote: post #2

I am glad to see more stuff with graph based AI here. I have a running bet with a friend about whether future is going to be OBM (One Big Model) or LoLM (Lots of Little Models). I'm strongly in the LoLM/graph camp and have been working in that direction as well: https://github.com/Miserlou/Helix

Seeing how langchain is gaining popularity and development rapidly, I would agree. Chaining lots of specific models and tools seems to be the way forward.

Hadn't heard of langchain, here's a link: https://github.com/hwchase17/langchain

Re: Show HN: Graph-based AI for longform writing

#30

Post by danShumway »

Mizza wrote: post #2

I am glad to see more stuff with graph based AI here. I have a running bet with a friend about whether future is going to be OBM (One Big Model) or LoLM (Lots of Little Models). I'm strongly in the LoLM/graph camp and have been working in that direction as well: https://github.com/Miserlou/Helix

Agreed, from what I can see pushing the size of models higher and higher gets you better results but also scales up problems at the same rate. Smaller models are more controllable and more predictable, and just like anything else, specialization tends to produce better results than having one jack-of-all-trades tool that handles everything.

There are fundamental weaknesses with LLMs that aren't present in other approaches. There are strengths to LLMs too, but that's the whole point. I am much more optimistic about the potential to get multiple models focusing on different problems to coordinate with each other than I am about the possibility of getting a single LLM to just be good at everything.

There's a lot of really unbelievably hard problems that are showing up just with GPT-3, and as the model gets bigger, those problems are going to get worse, not better because in some ways they are a consequence of the model being so large. But like... there are domains where you don't care about those downsides, or where those downsides only matter for one specific part of whatever application you're building. So if you can away with just not having GPT-3 involved in that part of your process and doing something else... Don't pound in a nail with a screwdriver.

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