jarulraj

6 ms·

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by jarulraj 1y ago
:)
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by jarulraj 1y ago
Agreed, I just updated it to "Elements of System Design".
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by jarulraj 1y ago
I added it now :)
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by jarulraj 1y ago
Yes :)
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by jarulraj 1y ago
Exactly. It is intentionally open-ended: new "principles" can emerge, split, or retire as the taxonomy evolves. This is just version 1. The grid is a visual index and the fun part is mappin systems to "molecules" in diff
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by jarulraj 1y ago
Yes, I just borrowed the periodic table metaphor. "Elements of System Design" is a better name.
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by jarulraj 1y ago
Author here, great question :) If principles are the elements, we can think of each system as a "molecule" with some imagination. For example, an SQL database system has many principles: 1. Abstraction Lifting (Al) + Policy/M
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by jarulraj 1y ago
Totally fair.. I am not claiming periodicity here :) I just wanted to use the "periodic table" as a visual metaphor. The goal is to outline a mostly orthogonal set of system design principles and illustrate cross-domain connection
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by jarulraj 1y ago
Author here, appreciate the share :) I was not expecting this to get so much attention. To clarify: this is indeed just a taxonomy of classic system-design principles. The periodic-table styling is a familiar metaphor; there is no claim tha
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by jarulraj 3y ago
It is based on the feedback shared by an undergraduate student -- pretty subjective. For instance, it is possible to graduate with a CS degree without even taking an introductory course on systems.
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Ask HN: Has the CS curriculum been dumbed down over the past decade?
1 points by jarulraj 3y ago|3 comments
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by jarulraj 3y ago
It is currently not possible to get rigorous summaries of paper chunks using GPT-4.
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by jarulraj 3y ago
Wouldn't more semantically related neighbors be retrieved by just increasing K?
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by jarulraj 3y ago
Cool project! Can you elaborate on "scalable" AI deployment? We are exploring the data + AI space in EvaDB and would love to exchange notes [1]. [1] https://github.com/georgia-tech-db/evadb
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by jarulraj 3y ago
Very cool project, @MatthausK! What are your thoughts on reducing LLM cost? We are also exploring LLM-based data wrangling using EvaDB and cost is an important concern [1, 2, 3]. [1] https://github.com/georgia-tech-db/e
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by jarulraj 3y ago
Nice :) What were the interesting problems you faced in processing the survey data? If possible, can you share the prompt?
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by jarulraj 3y ago
As we do not have ground truth, we only qualitatively checked for accuracy -- no quantitative metrics. We did find a significant drop in accuracy with GPT 3.5 as opposed to GPT 4. Are you measuring accuracy with data wrangling prompts? Woul
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by jarulraj 3y ago
Yes, there is definitely a human-in-the-loop element here. It would be great if you could share an example of the inconsistent output problem -- we also faced it. GPT-4 was much better than GPT-3.5 in output quality.
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by jarulraj 3y ago
Great question! We iterated on the prompt for several days and manually verified the results for ~100 users. The results were pretty good: https://gist.github.com/gaurav274/506337fa51f4df192de78d1280... Another interes
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Ask HN: How is the community using LLMs for data cleaning/enriching/structuring?
7 points by jarulraj 3y ago|10 comments
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by jarulraj 3y ago
Thanks for your kind words, @skeptrune! It was certainly a fun project. We found some interesting insights. In the Langchain community, ~40% of the stargazers are from India. In the GPT4All community, we found that web developers love open-
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by jarulraj 3y ago
Thanks for your kind words, @treebeard5440! :)
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Show HN: Stargazers Reloaded – LLM-Powered Analyses of Your GitHub Community
20 points by jarulraj 3y ago|5 comments
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by jarulraj 3y ago
Hi Andrey. Thanks for your feedback. We should have better emphasized that we are benchmarking Qdrant in local mode. We have updated the post to clarify that Qdrant is being evaluated in local mode. We plan to next evaluate the server mode.
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by jarulraj 3y ago
Neat AI app! 1. What feature extractor is used to derive code embeddings? 2. Would support for more complex queries be useful inside the app? --- Retrieve a subset of code snippets SELECT name FROM snippets WHERE file_name LI
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by jarulraj 3y ago
The discord link seems to be not working. Just a heads up. The YOLO example on your Github page is super interesting. We are finding it easier to get LLMs to write functions with a more constrained function interface in EvaDB. Here is an ex
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by jarulraj 3y ago
Can LLMs help in cleaning up the logistics database -- like handling different variants of an address? Here is an example: https://medium.com/evadb-blog/augmenting-postgresql-with-ai-... .
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by jarulraj 3y ago
Nice writeup! Here is another example of using LLMs is to augmenting existing software that we are exploring -- specifically SQL database systems. We are using LLMs inside a SQL query to power a "soft join" between SQL tables for
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by jarulraj 3y ago
You might be interested in another way to use LLMs inside a SQL query. For example, LLMs can be used to power a "soft join" between SQL tables for when a correspondence is only implied (e.g. different address formats, etc.). More
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by jarulraj 3y ago
Thanks for sharing that observation on customer chatbots. 1. Will that query look like this: SELECT LLM("{user_question}", order_info) FROM postgres_data.order_table WHERE user_id = “101”; 2. How will a feature stor

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