cpard

5 ms·

1.
One Pass to Parse Them All: Fused Parallel CSV Processing [pdf](vldb.org)
1 points by cpard 2d ago|0 comments
2.
by cpard 1mo ago
When I saw the title the first thing I thought of was schema on read versus schema on right when in data platforms. You can make writes faster and part of that is by not dealing with schema resolution but you do push the work somewhere else
3.
Distilling proprietary model reasoning into open-source search agents(arxiv.org)
5 points by cpard 2mo ago|0 comments
4.
Extending Polars with Rust Expression Plugins(fenic.ai)
61 points by cpard 2mo ago|0 comments
5.
Breaking Database Lock-In: Agentic Regeneration of Storage Readers for Databases(arxiv.org)
2 points by cpard 2mo ago|0 comments
6.
by cpard 2mo ago
This was mostly because Sonnet 5 worked longer and read more to get there, consuming 1.9x more tokens. I have experienced similar behavior between opus and haiku when benchmarking Dara engineering tasks. The “cheaper” model takes many mor
7.
by cpard 2mo ago
There’s an emerging pattern in agentic systems and this project is a great example. A deterministic layer like a compiler or generator of code with some kind of IR that the LLM generates and feeds it with. I feel we will be seeing this more
8.
Show HN: fenic – LLMs as dataframe operators, query meaning and structure(github.com)
3 points by cpard 3mo ago|0 comments
9.
by cpard 3mo ago
Human mathematicians could become “priests to oracles.” Priests were interpreting the oracles (at least at a place like Delphi) according to the context of the people asking the questions aka participating in politics of that ancient time
10.
The model is swappable the ontology compounds(typedef.ai)
1 points by cpard 3mo ago|0 comments
11.
by cpard 3mo ago
Most framework vendors don’t have an incentive to make things less obscure. The agent framework is free/open source and they make money primarily from selling observability products for agents. Even if they don’t intentionally obscure
12.
by cpard 3mo ago
Do you enumerate the options of the algorithms to the models? I've tried to do "algorithmic discovery" with these systems, e.g. openevolve, and to be honest the models didn't really focus on that part. Instead they were
13.
by cpard 3mo ago
I'm personally interested in this problem and it's a quite active research area right now. My feeling is that the research is converging to what the paper claims, that the combination of two is the right way to do it and it's
14.
by cpard 3mo ago
but is it worth the effort from a PR perspective for them? I guess we will have to wait and see.
15.
by cpard 3mo ago
Row level and summary stats are both diffs over values that can tell you that something changed but not whether the * meaning * has changed. What I'm working on is providing more information on how the meaning changes. What questions I
16.
by cpard 3mo ago
This is really neat. I’m working on something similar but for data artifacts not just code. It’s very encouraging to see that this kind of tooling helps both humans and models, that was what made me starting to work on that.
17.
by cpard 3mo ago
Curious to see when a post from OpenAI will appear with the corrected theory or something. This seems to be an ideal scenario for them to go after another scientific case. They have the theory, they have the experimental proof that it’s wro
18.
by cpard 3mo ago
I don’t think the flex here is the amount of code alone. Their goal is to show that AI can improve productivity, the number of lines is just the proxy to that. This article is a marketing piece after all. Now someone can argue that lines of
19.
by cpard 3mo ago
Thank you!
20.
by cpard 3mo ago
* …tools, UMP does for memory - negotiated operations over a portable, signed, bi-temporal record … * What is a bi-temporal record? I don’t think I’ve heard the term before and I’d love to learn more.
21.
by cpard 3mo ago
It’s clear that Anthropic is building harnesses for specific use cases now and turns them into products. This is the equivalent of Claude Design but for security. Different harness, different packaging and obviously different distribution b
22.
by cpard 3mo ago
I'm more curious about going from text to Prela instead of going from text to SQL and measuring any difference in the performance there. On one hand models have been trained on a lot of SQL on the other hand they are really good in mat
23.
by cpard 3mo ago
SQL, JS, Excel are really hard to substitute because of how widely used they are by people. Even if something new comes up that it's objectively better, so far has always failed gaining traction because of this reality. I wonder though
24.
by cpard 4mo ago
I think I didn’t articulate myself very well on my reply. I actually wanted to say that I agree with you and emphasise again the need for educating users for the complexity of these projects. What you describe has been pitched by many diffe
25.
by cpard 4mo ago
Of course it is. What you describe is one of the reasons that ELT became popular, if you couple it with a variant type and schema on read, you have a very powerful and flexible architecture. But there’s no free lunch, building and maintains
26.
by cpard 4mo ago
Replicating the Postgres WAL to S3 and Iceberg reliably is a hard problem but it’s not accurate to say that no ETL is needed here. maybe you can say it’s more of an ELT pattern but anyone who’s interested into using this for realistic analy
27.
by cpard 4mo ago
The comments are definitely not worth reading. It’s a very sad thread, you literally had to go through all of them to find one that wasn’t about hate and stating some facts about the issues of the code.
28.
by cpard 4mo ago
This is a good article and hopefully it served its purpose of generating awareness for the platform but I have to disagree with the core claim of the article. Distribution was always the hardest part in building a business, sure today it’s
29.
From Benchmarketing to Benchmaxxing(typedef.ai)
1 points by cpard 4mo ago|0 comments
30.
by cpard 4mo ago
This article is very well written and you can enjoy it regardless you agree or not. It made me think, considering how much content is being written with AI, would an LLM ever write something like this? For some reason they I can’t explain,

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