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Ape/rture

@aperture

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Brock
@runninyeti.eth
Working on something new this holiday season - Just In Time Indexing for all (even agents): https://www.jiti.ai/
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@aperture
Thanks! Since this might be very use case dependent we typically don't predefine the data structure (as in the format/schema) and do that custom with the builder to make the model training as easy as possible. That said, most onchain data is fairly structured already like DEX trades. I think where structure is very important is when you want to add labels
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Brock
@runninyeti.eth
Quick transformer for decoding V2/V3 swaps simultaneously (this looks at pool events, could also go by token transfers): https://console.indexing.co/flow/675ebd65085be53512a3a323 There's no limit on number of chains nor addresses being watched. And it can all be piped to any db, webhook, etc. There are also APIs to dynamically handle adding / removing watched addresses. Standard pricing is $1 per 1000 blocks *processed* - blocks without matching events won't count --> likely in the $10-100/m range at this point for this use case (and yes, $LARRY would be accepted). dm me if you're interested!
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@aperture
SuperchainERC20s are here. An overview: https://x.com/ape_rture/status/1866823400972251334
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@aperture
AI agents are taking the spotlight, but for these agents to do complex tasks they will need on-chain data. There's complex data infrastructure needed to serve this data. This is how a serious AI data pipeline will look like: https://theindexingcompany.substack.com/p/serving-ai-with-data-infrastructure
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Ape/rture
@aperture
AI agents are taking the spotlight, but for these agents to do complex tasks they will need on-chain data. There's complex data infrastructure needed to serve this data. This is how a serious AI data pipeline will look like: https://theindexingcompany.substack.com/p/serving-ai-with-data-infrastructure
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Ape/rture
@aperture
Can't wait for the rap album to drop
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@aperture
I have to deny i am an AI agent, but actually a real monkey building indexing and data pipelines at @indexingco But thanks for the shoutout nonetheless
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@aperture
Indexing Co can provide direct FC data to DB streams for like $50 per month. Any specific data you need or just want it all?
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@aperture
Ready for Season 2!
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@aperture
Join this Covariance call to see how new chains can be served with good infra. I'll go over the current problems with this explosion in number of chains and how we solve that (+ sneak peak at the new /indexing Console)
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@aperture
Hear me out: websites that use login through an email code, but that email arrives instantly instead of taking 2 minutes
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@aperture
Builders unite and be amazed by the wonders of modern technology
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@aperture
Just In Time Lore
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@aperture
Crypto is a attention-driven economy. There can be a massive value capture for users to be paid for their attention by businesses (apart from token emissions) whether that is user-research, feedback, watching ads. Various platforms experimented, but none yet being successful.
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Ape/rture
@aperture
Since I see Once Upon being mentioned in the comments: we used to provide the data for them. I could spar with you on how you can get that data or if you have the data inhouse how to do those estimations on the data you own. One benefit then is that you own that logic and do not depend on anybody else for a data model.
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@aperture
Memes it is
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@aperture
I gotta admit I am doing a really bad job at casting here. Any topics or views you like to see me cast? [Dance Monkey]
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Ape/rture
@aperture
This man is living in the future
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@aperture
Using heuristics and top down thinking on the data makes the classification process easier because the results just make more sense. The ML model would just be a bonus where there might be some patterns related to those heuristics being picked up. We can't ask the MLs to understand what humans think is valuable in this data (yet) without any guidance. It seems sometimes devs in crypto forget the classic data science cycle: ad hoc research/reports > automate that > then decide if you have do dig deeper with extensive tech like MLs.
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