Please don't listen to all of these folks who are trying to bring conflict into your life. You did something interesting, and learned a lesson about how big institutions actually work. It is a great story, and one that you can tell your friends.
The easiest path forward is to do what it takes to graduate, it sounds like you are one quarter away. Smile, play nice, help out where you can. Get everything in writing.
Definitely TALK to a lawyer and have that in your back pocket. It is likely there is some sort of legal aid through the law school and you can. However, only use this as a last resort. It would be no problem for a university to drag something like this out for months or years and you will be left without a degree.
That's reasonable advice if he could cease to work on his project and status quo were resumed, but from his telling of events, it sounds like they're saying he can't study at all unless he works for them for free. Such a scenario would be extortion, and is worth taking the stand on IMO.
There is already conflict in his life at this point. The question is how best to resolve it. The school is in a position of authority and is telling the student that after spending tens of thousands of dollars at his school, he can't register for his final quarter necessary to graduate, unless he provides additional free work for them. This absolutely should not be tolerated.
Everyone in this thread is simply suggesting he talk to a lawyer. The lawyer can help guide him on the next action to take.
Elasticsearch has recently added a data type called semantic_text, which automatically chunks text, calculates embeddings, and stores the chunks with sensible defaults.
Queries are similarly simplified, where vectors are calculated and compared internally, which makes a lot less I/O and a lot simpler client code.
I've got a crapload of json q & a formatted discussions on a topic, and am trying to figure out if I just store it somewhere and query it, or do I also do vector embeddings, kinda lost with all the possible options.
Embeddings are what encode the “meaning” of a given text. Similarity search works by computing the angle between your query vector and the rest of the vectors already stored.
DuckDB (and columnar stores in general) is great at aggregation. It’s particularly well suited because DuckDB is a single file. There’s no server to muck with.
It’s impossible to answer that question without knowing what content/query domain you are embedding. Checkout MTEB leaderboard, dig into the retrieval benchmark, and look for analogous datasets.
So we're talking maximizing embedding model per use case? Medical dats would require differnet model than say sales data? Sounds very fragmented approach.
21 direct reports is far too many to be an effective manager. I currently manage 8 technical people and 8-10 seems to be the sweet spot, where I have time to do things like have 1-1s, help with career planning, get people promoted, deal with escalations or cross-team issues, hire replacements, etc.
I have had as many as 15 and after 10 you really just have to start picking what you want to fall off of your plate as a manager. Unfortunately, the things that fall off first are the things that help your direct reports the most. Eventually, you just get behind on everything and end up being completely reactive and only able to focus on short-term solutions.
21 direct reports are a lot if you want to be a good manager and support your people.
The easiest path forward is to do what it takes to graduate, it sounds like you are one quarter away. Smile, play nice, help out where you can. Get everything in writing.
Definitely TALK to a lawyer and have that in your back pocket. It is likely there is some sort of legal aid through the law school and you can. However, only use this as a last resort. It would be no problem for a university to drag something like this out for months or years and you will be left without a degree.
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