[HN Gopher] Show HN: Deep search of all ML papers
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       Show HN: Deep search of all ML papers
        
       Built an automated system to run a deep search of ArXiv and
       carefully find all the precise papers that exist on a complex
       topic.  It's different from simple RAG because it searches,
       classifies, and adapts based on relevant papers it uncovers, and
       then continues until it finds every paper on a topic (trying to
       mimic the human research process). Benchmarked 10x higher accuracy
       and total retrieval compared to Google Scholar for a median search
       (whitepaper on website). Also knows when it is complete, and misses
       virtually nothing (< 3% or so, once it's converged).  Website has a
       free trial and a bunch of example search reports. Want feedback and
       suggestions.
        
       Author : tomhartke
       Score  : 91 points
       Date   : 2024-01-24 14:44 UTC (8 hours ago)
        
 (HTM) web link (app.undermind.ai)
 (TXT) w3m dump (app.undermind.ai)
        
       | tomhartke wrote:
       | Here's an example report on: tokenization-free large language
       | model architectures, which have been shown to achieve
       | compute/accuracy tradeoffs comparable to or better than
       | traditional token-based models
       | https://app.undermind.ai/query_app/display_one_search/05f0b8...
        
       | axpy906 wrote:
       | What about compare to ArXiv Sanity Preserver?
        
       | axg11 wrote:
       | I would change the main CTA to "Try it now" and then use a
       | different style for "Read the stats". It currently looks like
       | there are two equally important CTAs.
       | 
       | If you can find a way to make the results closer to real-time,
       | this will be a really popular product.
        
         | tomhartke wrote:
         | Appreciate the advice. Re: timing, it's bottlenecked by the
         | sequential nature of the search. To be comprehensive, we
         | discover a few papers, and use that info to choose where to
         | look more closely next.
        
       | knicholes wrote:
       | Immediately bailed once it required I provide my email address.
        
       | huqedato wrote:
       | Nice but way too pricey.
       | 
       | https://chat.openai.com/g/g-dGz4aw9iA-research-refiner - the free
       | version (just ChatGPT Plus subscription needed)
        
         | canadiantim wrote:
         | Awesome had no idea this existed. Very useful, thanks!
        
         | tomhartke wrote:
         | The goal is to be systematic and handle complex topics. ChatGPT
         | + keyword search can't handle complex topics at all, and isn't
         | systematic either.
        
           | danielmarkbruce wrote:
           | It's still early days. Many folks think that GPT-4 + simple
           | RAG works well. It doesn't. Building a good tool like this is
           | hard.
        
         | 3abiton wrote:
         | I wonder how many of such services chatgpt undercuts already?
        
         | callalex wrote:
         | Free, just needs a subscription?
        
       | wackget wrote:
       | There's something disagreeable about charging a subscription to
       | search freely-available scientific papers.
       | 
       | Yeah I get you're technically paying for the "advanced" search
       | but it still leaves a bad taste in the mouth because this
       | service's entire existence depends on open source knowledge.
       | 
       | P.S. hiding pricing behind registration isn't cool
        
         | bbsz wrote:
         | I think that full text search queries over long text data is
         | already kind of expensive server side. Users are paying
         | specifically for this, not better UI or simple direct match
         | search available in free to use projects. I would say it's very
         | reasonable to charge for costs incurred here.
        
       | kingkongjaffa wrote:
       | It's a shame the research publishing industry is a bunch of
       | walled gardens.
       | 
       | Since this only supports arXiv, and not paper repositories from
       | other industries.
        
         | jakderrida wrote:
         | Maybe the model will get smart enough to go to SciHub and
         | Libgen? IP holders and distributors come after me with
         | evidence, I'll just pull out my belt and tell them I gotta go
         | teach some naughty GPUs another lesson.
        
       | krohling wrote:
       | "Our AI agent finds precisely what you ask for, 10-50x better
       | than Google Scholar"
       | 
       | I was curious how this was measured since benchmarking accuracy
       | for LLMs is tough. Found this in the paper: "This classification
       | accuracy was benchmarked by manually analyzing over 400 papers
       | across a range of representative searches, and comparing the
       | human evaluation to the language model's judgment"
       | 
       | I'm skeptical that their dataset of 400 papers with 3
       | classification labels (highly relevant, closely related, or
       | ignorable) is large enough to represent the diversity of queries
       | they're going to get from users. To be clear, I don't think this
       | undermine's (haha) the value of what they've built, still very
       | cool.
        
       | basb77 wrote:
       | How does this compare to a system like Elicit? Seems to be very
       | similar at first glance.
        
       | tomhartke wrote:
       | FYI system is a bit delayed because of traffic levels. May take a
       | bit longer to generate results at the moment (usually takes ~10
       | min).
        
       | frogamel wrote:
       | IMO if you're going to profit off open research, you should at
       | least make your own work available for other researchers. The
       | white paper has 10 pages of performance benchmarks but 5
       | sentences on methodology.
        
       | espadrine wrote:
       | It is certainly interesting, and I would love to try it for my
       | hobbyist use-cases. I don't do much research at work, but a fair
       | bit on the weekends.
       | 
       | Are you filtering users however? I cannot sign up in a personal
       | capacity with a GMail email. The page raises this error: "Please
       | use a valid institutional or company email address."
        
       | htrp wrote:
       | what is pricing?
        
       | WhitneyLand wrote:
       | I don't want to be negative but you asked for feedback, so I'll
       | give you a few impressions including the superficial and quite
       | subjective fwiw:
       | 
       | 1. The hyperbolic claims are going to be off-putting to some.
       | You've "solved" ML search? 50x better than Google scholar on a
       | metric no one's been benchmarking against? Consider your audience
       | and what they would find credible.
       | 
       | 2. The UX needs work. To give one aesthetic example, in the
       | results there are large, brightly colored, red and green circles
       | that are used inconsistently, and they clash the palette. This
       | stuff can affect how sticky your service is.
       | 
       | 3. Don't restrict signup by email domain. This is nuts. Never add
       | friction to gaining customer relationships. If you're capacity
       | constrained limit the trial. If you're trying to segment the
       | market there are better ways.
       | 
       | 4. The name "Undermind", is not working to my ear. It's worth
       | changing. At least find a product person whose opinion you
       | respect and ask their take.
       | 
       | 5. I think a lot of people here would be willing to give you
       | useful technical feedback on the architecture and approach if
       | more information were shared about how the service works, but I
       | didn't notice that was available.
        
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       (page generated 2024-01-24 23:01 UTC)