Are you planning to offer a search API at some point?
Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
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Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#22Are you planning to offer a search API at some point?
Potentially. Given the latency and the cost/compute we put into each result, it doesn't fit the usual API mechanics.
What use case are you thinking of?
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#23How would you compare your product to elicit.ai?
In my opinion elicit has better looking UI and much more features and further along
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#24How is this different than the work that semantic scholar is doing around AI?
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#25How would you compare your product to elicit.ai? In my opinion elicit has better looking UI and much more features and further along
I think the biggest difference is our focus on search quality, and being willing to spend a lot on compute to do it, while they focus on systematic extraction of data from existing sources and on being fast. It's a bit of an oversimplification (they of course have search, and we also have extraction).
Feature-wise, we definitely have a lot of work to do :) What crucial pieces do you think we're missing?
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#26Awesome! I just took you up on your offer and compared roughly similar questions using Claude 3.5 Sonnet and Undermind.
Claude 3.5 is reluctant to provide references—-although it will if coaxed by prompting.
Undermind solves this particular problem. A great complement for my research question —- the evidence that brain volume is reduced as a function of age in healthy cognitively normal humans. In mice we see a steady slow increase that averages out to a gain of 5% between the human equivalents of 20 to 65 years of age. This increase is almost linear as a function of log of age.
Here is the question that was refined with Undermind’s help:
>I want to find studies on adult humans (ages 20-100+) that have used true longitudinal repeated measures designs to study variations in brain volume over several years, focusing on individuals who are relatively healthy and cognitively functional.
I received 100 ranked and lightly annotated set of 100 citations in this format:
>[1] Characterization of Brain Volume Changes in Aging Individuals With Normal Cognition Using Serial Magnetic Resonance Imaging S. Fujita, ..., and O. Abe JAMA Network Open 2023 - 21 citations - Show abstract - Cite - PDF 99.6% topic match Provides longitudinal data on brain volume changes in aging individuals with normal cognition. Analyzes annual MRI data from 653 adults over 10 years to observe brain volume trajectories. Excludes populations with neurodegenerative diseases; employs true longitudinal design with robust MRI techniques.
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#27How is this different than the work that semantic scholar is doing around AI?
Semantic Scholar seems more focused on
1. being the data provider/aggregator for the research community, and
2. long term, I think they plan to develop software at the reading interface that learns as a researcher uses it to browse papers (a rich PDF reader, with hyperlinks, TLDRs, citation contexts, and a way to track your interactions over time, and remind you of what you've seen or not).
Their core feature now is a fast keyword search engine, but they also have a few advanced search features through their API (https://api.semanticscholar.org/api-docs/) like recommendations from positive/negative examples, but neither KW search nor these other systems are currently high enough quality to be very useful for us.
FYI our core dataset for now is provided by Semantic Scholar, so hugely thankful for their data aggregation pipeline and open access/API.
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#28Awesome! I just took you up on your offer and compared roughly similar questions using Claude 3.5 Sonnet and Undermind. Claude 3.5 is reluctant to provide references—-although it will if coaxed by prompting. Undermind solves this particular problem. A great complement for my research question —- the evidence that brain volume is reduced as a function of age in healthy cognitively normal humans. In mice we see a stead…
It's worth highlighting that first result is exactly what you asked for, given all 4 of your criteria:
1. It's on adults.
2. It's longitudinal over multiple years.
3. It studies variations in brain volume.
4. It focuses on healthy individuals.
You can see the full results for that search text here: https://undermind.ai/query_app/display_one_search/e1a3805d35...
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#29How is this different than the work that semantic scholar is doing around AI?
Semantic Scholar seems more focused on 1. being the data provider/aggregator for the research community, and 2. long term, I think they plan to develop software at the reading interface that learns as a researcher uses it to browse papers (a rich PDF reader, with hyperlinks, TLDRs, citation contexts, and a way to track your interactions over time, and remind you of what you've seen or not). Their core feature now is…
Do you plan on adding an API? I already have an inhouse knowledge discovery, annotation and search system that could be augmented by your service. Not super critical at this point, but a would be nice.
And yes, Semantic Scholar is a wonderful part of the academic commons. Fingers crossed they don't go down the jstor/oclc path.
Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers
#30How is this different from Scite, Elicit, Consensus, and Scopus AI for Generating Literature Reviews