rwhaling

7 ms·

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Show HN: Logbooks, notebook computing for coding agents(github.com)
5 points by rwhaling 7mo ago|0 comments
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by rwhaling 11mo ago
That's a great question - right now it is only looking at the results from a battery of several dozen indicators that we compute upstream of the model itself (which saves massively on tokens) As small models continue to improve, and ed
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We built a 270M local model to detect phishing URLs(charlemagnelabs.ai)
7 points by rwhaling 11mo ago|2 comments
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by rwhaling 1y ago
CLAVIER is amazing, the wire system alone is such a huge improvement over ORCA, and it's now feasible to make much larger patches and refactor safely, kudos to River for all the hard work on the polish and quality-of-life. I was testin
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by rwhaling 1y ago
Yep absolutely! It reminds me of writing cryptic perl one-liners or something.
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by rwhaling 1y ago
Love 100r! There aren't a ton of examples online, but their livecoding music software/language, ORCA, is a remarkable instrument. https://100r.co/site/orca.html I posted a clip to bsky a few weeks back: h
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by rwhaling 3y ago
clearly Factorio
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by rwhaling 4y ago
Really cool - the stuff they are doing with the Excel API to inspect editing modes is super interesting: https://www.sharpcells.com/docs/blog/monitoring-edit-mode I work with data warehouses, but I'm really j
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by rwhaling 4y ago
Airbnb wrote a few great blog posts about why they built a standardized metrics layer - I think this one gives better technical context on the "what" and "why" than this announcement does: https://medium.com&#
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by rwhaling 4y ago
In practice - complicated time series metrics, especially on top of derived temporal-logic attributes like funnels, activation, etc., are phenomenally difficult to write by hand in SQL for most analysts. We are in the process of switching
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by rwhaling 4y ago
One of Transform's strong suits is their Tableau integration - they have really good tooling for pushing metrics out to Tableau, rather than relying on Tableau to pull them in. Apparently AirBnb was/is still a very dedicated Tabl
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by rwhaling 4y ago
The biggest win to me is: when your data pipelines are in SQL, changes and maintenance can be somebody else's problem. I've had a ton of success asking our marketing and business teams to own changes and updates to their data - ve
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by rwhaling 4y ago
Speaking as a data practitioner - data lineage is a profoundly hard and still unsolved problem. In the last few years, I feel like we've begun to crack it - dbt's data lineage graph is a huge advance over anything I've ever
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by rwhaling 4y ago
One change I have seen in recent years is that I find fewer and fewer new engineers learn SQL, especially folks entering the industry from bootcamps. And conversely, more and more folks from a business/econ/etc background learn at
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by rwhaling 4y ago
I've been thinking about this a ton lately - I think the holy grail is something that extends the spreadsheet UX with the capability to address much larger data sets, roughly equivalent in power to a Jupyter notebook. This probably me
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by rwhaling 5y ago
Algol 60 had lexical scoping in 1960 (while Lisp was in development) and this was known to be equivalent to the lambda calculus by the folks working on it by 1965 or so - https://dl.acm.org/doi/10.1145/363744.3637
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by rwhaling 5y ago
Always an interesting read. A ton of insights, but I always find it a bit hard to make sense of, and it feels so disconnected from a modern distributed systems context. In retrospect, I think a lot of the Spark SQL Dataframe workflow comes
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by rwhaling 5y ago
I think I shared this last time Sonic Pi got posted here, but Sonic Pi is also extremely flexible when you bus the MIDI output to other tools - Ableton, external synthesizers, etc. I posted a clip on IG a while back - https://ww
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by rwhaling 6y ago
Looks great! I have a question the planned Alpha 7 feature: "smaller than 32-bit values (char/byte)" - I'm so used to bytes being a fundamental primitive in programming languages that it's hard for me to imagine not
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by rwhaling 6y ago
for background, the original author of nbdev has a good post outlining exactly how it relates to jupyter - https://www.fast.ai/2019/12/02/nbdev/
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by rwhaling 6y ago
This is really exciting! I've been building a data engineering practice around jupyter notebooks, Netflix's papermill, and k8s cronjobs for scheduling, and it's been great...except for code review, weird dependency/virt
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by rwhaling 6y ago
Coming to Factorio from a Scala/streaming/data background, I got the connection pretty immediately - so much of Factorio is about designing correctly for backpressure, such that your factory works stably at different levels of cap
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by rwhaling 6y ago
I recently got obsessed with some music made for the OPN2, one of the chips modeled here - Yuzo Koshiro's soundtracks for the Sega Genesis: Streets of Rage 2: https://www.youtube.com/watch?v=E5g-QHq925o Streets of Rage
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by rwhaling 6y ago
Great to see Orca on here! Really really fun to play with for generative music; I made a song with it last year that I posted: https://www.instagram.com/p/BzVjW7LBv1K/ I also learned a lot from watching Allieway
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by rwhaling 7y ago
That was my immediate thought as well - CQRS doesn't fit well with the "everything should be deterministic" principle, unless they have a very different definition of CQRS than what is in common use. In theory, it is possible
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by rwhaling 7y ago
I used to work with HathiTrust and attended a few workshops; my experience was that the notion of a "data capsule" that ensures "non-consumptive use" is quite onerous, in practice, and that getting that access can acquir
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by rwhaling 7y ago
I've been using Scala Native for two years now, and I find that it's C interop is state-of-the-art. The way I would pitch it is: Scala Native gives you the capabilities and performance of C, embedded in a Scala DSL. In particular
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by rwhaling 7y ago
We use CQRS and event sourcing for most of our backend services at my current employer ( https://m1finance.com); it's generally been a good experience, but we've learned a lot along the way. My thoughts on the process a
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by rwhaling 8y ago
One benefit that is repeatedly mentioned in the papers is the ability to do tail-call optimization, which is more or less impossible with compile-to-c interpretations, and mandatory for functional languages.
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by rwhaling 8y ago
It's always nice to see the papers that come out of Tiark Rompf's group. For background, here are some other great ones: Lightweight Modular Staging: A Pragmatic Approach to Runtime Code Generation and Compiled DSLs https:/

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