[HN Gopher] Retrieval Augmented Generation for New Orleans City ...
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Retrieval Augmented Generation for New Orleans City Council
Transparency
Author : yhvstnpst
Score : 62 points
Date : 2024-01-03 17:39 UTC (5 hours ago)
(HTM) web link (eyeonsurveillance.org)
(TXT) w3m dump (eyeonsurveillance.org)
| thecosas wrote:
| Interesting idea for making public meetings more accessible to
| the public. I know 3pm on a random weekday doesn't work for most
| citizens and yet... that's when it feels like many council
| meetings are.
|
| Side note: Spotting a bit of lorem ipsum on the site which seems
| odd.
| datadrivenangel wrote:
| The basic use case here of making videos and transcripts more
| accessible is super valuable. Are LLMs better than full text
| search though?
| poxrud wrote:
| For many cases yes. With llm based embeddings you get "semantic
| search", so for example if someone searches for "pets" they
| will most likely get results that include "dogs" and "cats".
| This is not the case for regular text search.
| blihp wrote:
| The problem with a text search is that you have to get your
| keywords exactly right. With LLMs you ask inexact questions
| like 'has the topic of X ever been discussed?'[1] without
| needing to have an exact match on X. An LLM front end which
| could return references to the full text seems like the best
| use of both.
|
| [1] For example, your query might have had X be 'crime' and the
| transcript would have references to multiple specific types of
| crime such as 'muggings', 'vandalism' etc. which a full text
| search isn't going to match. Further, with the LLM front-end
| you could refine the query to ask about violent crime etc.
| thorum wrote:
| > Despite targeted outreach, we've noticed that community members
| are not returning to use the tool after their initial
| interaction. There has been minimal engagement apart from a spike
| during a mid-November focus group. This indicates that Sawt is
| not helpful enough yet for people to want to come back.
|
| Perhaps they have trouble thinking of additional questions to
| ask? Their first few interactions probably cover the things they
| care most about. They get an answer and that's it. Maybe a
| "subscribe to updates whenever this topic comes up in a meeting
| again" feature would be useful?
| araes wrote:
| Your tool is too effective. It actually answered our questions.
| Don't you know the money's in treating the symptoms? Partial
| joke, yet interesting to see the jump to a result (weird when
| they're all about bias).
|
| The suggestion's a cool idea. In addition to generic warning
| updates, you could also do "send me a summary" every time it
| appears. Kinda RSS feed summaries. Since they're integrating
| the news, they could also do full news coverage of the day
| summaries. Might actually be helpful for some people. Daily
| summary of "what happened in New Orleans yesterday?"
| simonw wrote:
| Right - my intuition is that most people don't have questions
| that they want answered in this way very often.
|
| Learning how to use this tool involves learning what kind of
| questions can be answered by this data, and formulating those
| questions requires a pretty in-depth knowledge of how city
| politics actually works.
| cdkmoose wrote:
| Perhaps it's more apathy. Outside of hot-button issues, it
| feels like many people don't care to pay attention to their
| local government
| animal_spirits wrote:
| This is the kind of tool that makes me excited about the AI boom.
| I can imagine this being helpful for journalists. Think of a tool
| that you can say "Watch all the CSPAN footage and send me an
| email when someone talks about $TOPIC"
| mobiuscog wrote:
| Good cop, bad cop
|
| Think of a tool that you can say "Listen to all phone
| conversations and notify when someone talks about $TOPIC"
| linsomniac wrote:
| "They" already have that tool, right?
| selimthegrim wrote:
| I think their Palantir contract is over and done with
| happyopossum wrote:
| "Listen to all phone conversations"
|
| The people who are in a position to do this are probably in a
| position to do anything else they want to do with said phone
| calls. What's changing is that random joes can do this stuff
| now.
| trinsic2 wrote:
| It feels more like it's going to make it easier to deceive
| people. It seems like, as people rely more and more on
| automated systems like this, it would be easy to own and change
| the output on the fly.
| 3d27 wrote:
| How did you calculate accuracy and bias?
| xrd wrote:
| I'm really fascinated by this.
|
| Attention is all you need. But not the way we here at HN expect.
|
| If you investigate police statistics, you'll see that the "story"
| about the statistics is often dictated by the availability of the
| statistics. Go to a "safe" city and review the statistics on the
| police department website. The availability of those statistics
| is all over the place, and one city will claim they can't publish
| the information from past years because of COVID-19, and the next
| city will say that they can only publish information from the
| past because of COVID-19. One city will claim impossible to
| verify outcomes. And, another city will publish information which
| will be used to prove political points by failing newspapers.
|
| This feels like it could really shift attention to processing
| information and bringing attention to when that information isn't
| available.
| onthecanposting wrote:
| Humorous fact: half of Asher Avenue was renamed to Colonel
| Glenn Avenue in Little Rock to confound crime reporting that
| was linked to street names. Lies, damned lies, and
| statistics...
| MattDaEskimo wrote:
| The described technique of RAG is not only expensive, but also
| prone to hallucinations.
|
| I would have liked more discussion on hallucinations, which is
| the ultimate pitfall of LLMs. This is critical for discovery-
| based public-facing chatbots.
|
| I'm also very skeptical of real-world HyDE applications as they
| depend on the underlying model to properly answer the question,
| and can easily drift from the intention.
| Der_Einzige wrote:
| Fat citation needed on RAG being expensive. Most embeddings
| models these days are smaller than most LLM models, and run
| more cheaply and more effectively than the ones provided by
| OpenAI.
|
| If you mean that increasing token counts in expensive, I
| suppose sure - but the retrieval side itself is not the cost
| center in general.
| MattDaEskimo wrote:
| I am speaking of the OPs implementation of RAG, not in
| general.
|
| The retrieval part can be expensive if an LLM is used to
| confirm that it is sufficient, and if it's decided to
| continue searching if it's not.
|
| OpenAIs retrieval is a perfect example. It works, but it's
| very expensive
| simonw wrote:
| I've seen a lot of people (including people who I trust) say
| RAG is the best current mitigation we have for hallucinations,
| because grounding the LLM in additional context makes it much
| less likely it will make something up as opposed to use the
| information that has been passed to it along with the user's
| question.
|
| Have you heard differently?
| simonw wrote:
| Related: just saw this paper https://arxiv.org/abs/2401.01313
| "A Comprehensive Survey of Hallucination Mitigation
| Techniques in Large Language Models"
| MattDaEskimo wrote:
| RAG conceptually is the solution for hallucinations. I'm
| being critical of the implementations used to achieve it and
| the lack of awareness for hallucinations.
|
| It's definitely not ready.... Yet.
| zmmmmm wrote:
| I spent a bit of time playing with h2ogpt, which is a popular
| RAG framework. I gave it all our architectural documentation
| for our software and then tried asking it questions that
| transcended basic search (so the answer is not directly in
| there, but you could formulate it if you put disparate parts
| together). It started hallucinating pretty fast and told me
| all kinds of BS about how our software works.
|
| I think RAG _can_ be used in a way that eliminates or
| drastically reduces hallucinations, but to do that you have
| to do quite a lot of work to constrain the context and
| structure the prompting to address very specific questions.
| When you apply these more general frameworks they pump in
| large amounts of context in an unstructured manner and you
| just end right back at hallucinations again because the
| context isn 't constrained enough.
|
| So RAG is useful to me but not a silver bullet. It doesn't
| solve the original problem of wanting all the features of an
| LLM but without the hallucinations. It gives you some
| targeted way to use the LLM that doesn't hallucinate but
| misses a lot of the functionality people want.
| araes wrote:
| Total aside, yet had no idea what cell-site simulators were. Why
| is simulating cell phones an issue? Turns out "mobile cell phone
| interceptors". [1]
|
| [1] https://www.eff.org/pages/cell-site-simulatorsimsi-catchers
|
| University of Washington actually has a neat project where they
| drove around Seattle and Milwaukee to try and do International
| Mobile Subscriber Identity (IMSI)-Interceptor detection.
| Basically, find cars or buildings with mobile towers that
| intercept and redirect your cell signal through a man-in-the-
| middle observation. [2] Notably, United States Citizenship and
| Immigration Services building (USCIS) apparently operates one.
| The pictures are rather pretty.
|
| [2] https://seaglass.cs.washington.edu/
| ajcp wrote:
| > To covertly transmit on the same frequencies as the normal
| cellular network, IMSI-catchers may mimic the identifying
| properties (mcc, mnc, cell id, etc.) of legitimate cell towers.
| [2]
|
| How is this not illegal?
| BobaFloutist wrote:
| Because it's largely being done by law enforcement.
| Dowwie wrote:
| sawt: https://github.com/eye-on-surveillance/sawt
| onthecanposting wrote:
| On the surface this is a great idea, but my experience with city
| councils and planning commissions is that real decision making is
| done outside chambers and in private. What happens at public
| meetings is performance art. I've never seen public discussion
| impact decisions, even when very compelling legal arguments were
| made. Searchable minutes are probably adequate for most purposes.
|
| My own opinion is that convening in-person meetings with Robert's
| Rules were necessary before telecommunications, but they're long
| past their useful life.
| mistrial9 wrote:
| this may be true but is also a "gravity always wins" sort of
| statement. Some legal venues have "sunshine rules" to
| _mitigate_ and _dampen_ the inevitable. I have seen exactly as
| you say, and on different councils, quite a lot of involvement.
| sjkoelle wrote:
| all time naming miss not going with ragtime
| selimthegrim wrote:
| The better one would probably be "Eye on your shoes"
| Eextra953 wrote:
| I think it would be great to augment this tool to diagram the
| council meetings with questions, discussions, and motions. This
| would make it easier to track what city staff presents, which
| questions are asked by which council members, and finally how the
| motions are made and modified for any action items. I find that
| keeping track of all this during a meeting is very hard to do. It
| can make your head spin.
| selimthegrim wrote:
| Thank the Lord, whoever is doing this- City Council meetings here
| are hardly beacons of transparency as it is
| mellosouls wrote:
| The prompt seems reasonable enough but considering the groups
| _somewhat partial_ agenda [1] and the massively loaded
| supplementary datasets [2, 3, etc], I 'd be very cautious about
| using this tool without significant testing for bias.
|
| [1]
|
| https://eyeonsurveillance.org/blog/nola-israel-connections
|
| [2]
|
| https://github.com/eye-on-surveillance/sawt/tree/main/packag...
|
| [3]
|
| https://github.com/eye-on-surveillance/sawt/blob/main/packag...
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(page generated 2024-01-03 23:00 UTC)