tom_hartke
No user record in our sample, but tom_hartke has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
No user record in our sample, but tom_hartke has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
A decent fraction of research is open access these days (it's highly dependent on the field, though). That fraction is also growing. We're building systems to access full texts whenever possible.
That makes sense. You should be able to right click - save as PDF and it will preserve the links, etc.
We'd love to talk and see if we can provide this. Seems like it would be really helpful. Can you email us (support@undermind.ai)?
Hadn't seen that. Very complementary. We don't address staying up to date or pull in community value metrics (other than total citations). It's a somewhat different goal to broadly gather emerging ideas and stay…
Can you be more specific? Like break it out into AND and OR statements? Or just more iteration back and forth? We find people more familiar with the system learn better strategies than the LLM can suggest.
If it's easy/fast to check the literature, hopefully people's instinct changes. If we had time, we should be doing that for any small idea.
Just save the report url! It will persist. Also, on the usual system if you're logged in (instead of the HN free link), all your searches automatically get saved on a "history" page.
I think we associate learning/discovery with those moments because they happen together, not because they're causally related. I think this is somewhat equivalent to how we used to have to learn 100 different integrals…
Thanks! That's helpful to hear. Honestly just did numbers because the LLM has no trouble remembering which is which, and it's easier to programmatically parse out the citations to build hyperlinks (compared to…
Emphasis is meant to be on "mind", like supporting better reasoning, but point taken.
We removed the signup requirement for HN today - try this link: https://www.undermind.ai/query_app/promotion/
Not at the moment -- we're currently searching the abstracts of most major journals (which are public even for paywalled papers) which have been compiled in the Semantic Scholar database…
Not a bad idea. Want to avoid too much complexity in pricing, though. Decision fatigue.
Latency, compute required, and lack of full texts (paywalled publisher content).
In short, yes, though it's geared toward topic search. From a strategy perspective, we designed it for topic search because it makes more sense to find everything on a topic first, then filter for the most recent, if…
The few minute time delay is primarily because of the sequential LLM processing steps by high quality LLMs, not database access times. The system reads and generates paragraphs about papers, then compares them, and we…
Ours is slow, but accurate, even for complex topics. The rest are fast, but generally can't handle complex topics. (There's more nuanced explanations in other comments)
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…
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…
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…
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?
Agreed, exa is great - particularly, it's the best thing I've found for fast web retrieval of slightly more complex topics than Perplexity, Google, etc can handle.
I ran these two example searches we have on our homepage on AnswerThis: (3D ion shuttling) https://undermind.ai/query_app/display_one_search/b3767fb7b6... (laser cooling to BEC)…
For a meta-analysis, you might want to try the "extend" feature. It sends the agent to gather more papers (we only analyze 100 carefully initially), so if your report might say "only 55% discovered", could be useful.…
You should be able to try it here without loggin in: https://www.undermind.ai/query_app/promotion/ (set up for HN today). If not message support@undermind.ai and I'll set you up.