> It’s [sql] just not built for the complex relationships that exist in a massive organizations like NASA. This is an absurd claim. > Extracted Skills from Team Resumes > Extracted Skills > Subject Matter Experts Finder Question: designed to identify employees with expertise in specific domains or mission-critical capabilities. I can't think of anything that screams "incompetent management" more than this. So, to fin…
How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
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Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#22> It’s [sql] just not built for the complex relationships that exist in a massive organizations like NASA. This is an absurd claim. > Extracted Skills from Team Resumes > Extracted Skills > Subject Matter Experts Finder Question: designed to identify employees with expertise in specific domains or mission-critical capabilities. I can't think of anything that screams "incompetent management" more than this. So, to fin…
Every large consulting org does this. It’s a market for enterprise and home-grown solutions.
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#23I have two major issues with virtually all graph DBMSs that are not RDF/SPARQL-based:
1) They do not allow structure-preserving querying. That is, I query a graph and want the results to be a smaller graph. This is trivial in SQL, you just 'SELECT * FROM x WHERE ...' and the result set you get is tabular just like the table x. In SPARQL, there are a CONSTRUCT/DESCRIBE queries that do just that - give you the results as a graph.
2) They don't use any (internationally recognized) standard to represent graph data. RDF is the only such format known to me (ignore all the semantic web stuff associated with it and just consider the format).
230k edges is peanuts for a graph db. It's like when the number of rows times columns in your SQL DB is 230k. NASA could (should?) have just used Oxigraph, RDF4J, or Jena. Stardog and Ontotext are the paid options. However, it is quite nice to see more interest in graph-based DBMSs in general!
> “Which employees have cross-disciplinary expertise in AI/ML?”
Regarding the study itself, I did not understand who is the target user of this. I would rather be more interested in the Lessons Learned 2.0 study (I understand it was attempted once before [1]). I don't think the study at hand would be able to correctly answer questions about expertise.
On the technical side, as far as I understand, the cosine similarity was computed per triplet? In that case, I could see how pgvector could be used for this. Relevance expansion is the only thing in the article that made me think that it would be cool if it works well. But I could see how in a combo of a regular RDF DBMS + pgvector, one could first do a cosine similarity query via pgvector and then compute an (S)CBD [2] of the subject (the from node) of the triplet.
[1]: https://youtu.be/QEBVoultYJg?t=1653
[2]: https://patterns.dataincubator.org/book/bounded-description....
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#24I think I found a place Dodge can save some money. Memgraph pricing is ridiculous.
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#25Memgraph is laughably expensive - I honestly wonder what anyone actually uses it for outside of companies that just don't care about infra spend.
DISCLAIMER: The co-founder and CTO of Memgraph here. To add more context, Memgraph Enterprise pricing is explained under https://memgraph.com/pricing : "Starting at $25,000 per year for 16 GB, Memgraph has an all-inclusive, simple pricing model that scales with your workload without restrictions. No charge for compute. No charge for replicas. No charge for algorithms. No Surprises.". In addition, Memgraph Community i…
To be fair, it is quite nice for the pricing to be transparent. And I think it's somewhat competitive w.r.t. Stardog, for example. The community version is less restricted than Ontotext, for example.
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#26Memgraph is laughably expensive - I honestly wonder what anyone actually uses it for outside of companies that just don't care about infra spend.
In the relational space, it took OSS options like Postgres many decades (and somehow paid-for person-years) to get to a place where enterprises seriously consider migrating off Oracle to it.
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#27Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#28Memgraph is laughably expensive - I honestly wonder what anyone actually uses it for outside of companies that just don't care about infra spend.
If you want a production-grade graph DBMS, you don't have that many OSS options that are reliable and well-supported. In the relational space, it took OSS options like Postgres many decades (and somehow paid-for person-years) to get to a place where enterprises seriously consider migrating off Oracle to it.
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#29As an alternative to a pure graph db (e.g. here, memgraph), has anyone here used Apache's AGE graph-database extension for Postgresql? For making a knowledge graph that can live alongside SQL?
Re: How NASA Is Using Graph Technology and LLMs to Build a People Knowledge Graph
#30Why? because there is never a reward attached. Oh you want to make me the AI resource for the agency but not remove former duties or increase my pay? Ummmm no thanks. Also things tend to happen in waves ie "AI" so everyone needs a lot from a very few people at the same time. No one ever asks how those people can be empowered. Just how can we put the screws to them so they work harder.
HR and Mgmt can f-off with their "skill resource bank" or whatever nonsense they call it this year. My skills are what I was hired for on the job description. If you want to discuss a new position or higher pay for different skills I'm very happy to talk about how I can work with the org to make that happen. Thats never the case though.