pjot

6 ms·

31.
by pjot 2y ago
This compounds with each _team_ modeling the work in jira/excel too!
32.
by pjot 2y ago
Through the arm, I believe, is still the way it’s performed today!
33.
by pjot 2y ago
I don’t know, I feel like there is much more room for positive incentives than negative. Prisons put people on a pretty level playing field. Like, the well behaved could be served pork chops and peas instead of slop and mush.
34.
by pjot 2y ago
Maybe leading with a stick instead of a carrot isn’t the right approach?
35.
by pjot 2y ago
When Forest Gump said “I’m pretty tired, I think I’ll go home now” was he breaking an obligation to keep running just because others were following him?
36.
by pjot 2y ago
The impacts of this on today’s music is unreal. WWOZ is the local station and its djs are musical historians. Enjoy https://www.wwoz.org/listen/player/
37.
by pjot 2y ago
We did this in elementary school in Seattle. I feel like the muscle memory might still be there!
38.
by pjot 2y ago
From New Oxford dictionary: > combine (a number of things) into a coherent whole: pupils should synthesize the data they have gathered | Darwinian theory has been synthesized with modern genetics.
39.
by pjot 2y ago
A little know Google product is called Tables[0]. Very similar to what you’re describing. Another is AppSheet[1] for a more drag and drop application builder. [0]: https://tables.area120.google.com/ [1]: https://
40.
by pjot 2y ago
Similarly, I found the kickstart.nvim immensely helpful as a jumping off point. https://github.com/nvim-lua/kickstart.nvim
41.
by pjot 2y ago
Made me spit my coffee out
42.
by pjot 2y ago
So many think they (their company) have “Big Data” but don’t.
43.
by pjot 2y ago
Apache Substrait is doing exactly this. Paired with Arrow makes for powerful composable data architectures https://substrait.io/
44.
by pjot 2y ago
For weeks after my grandmother brought me to a Chuck E. Cheese for the first (only) time, I had recurring nightmares fueled by this band.
45.
by pjot 2y ago
I love it for these meta-type use cases that aren’t necessarily about solving the puzzles. For instance I’m using it this year to dial in new neovim configs. Last year was to get comfortable with a split keyboard.
46.
by pjot 2y ago
This happened to my parents in the late 90s. No recourse back then - or at least I don’t think there was. Roughly 20 pairs of shoes were delivered to our door.
47.
by pjot 2y ago
Just to point it out, but there’s a native terminal command `caffeinate` that does the same as Amphetamine. I use the -disu flags
48.
by pjot 2y ago
Personally I feel they are overkill. For example I’m using duckDB as a vector store for similarity search and RAG. It works really well. https://github.com/patricktrainer/duckdb-embedding-search
49.
by pjot 2y ago
This book lives on my desk. And I’ve proudly filled its pages with annotations and sticky notes. It’s really well done.
50.
by pjot 2y ago
The default is #FF6600
51.
by pjot 2y ago
I recently upgraded from a 2020 Intel MBP to an M3 Pro. I’ve been been blown away. Even more, I’ve yet to hear the fans turn on.
52.
by pjot 2y ago
And macros! Which you can overload too https://duckdb.org/docs/sql/statements/create_macro#overload...
53.
by pjot 2y ago
> He gave me a coderpad link. I started to read through the question. I could already feel my mind moving like molasses. On the surface the question seemed straightforward enough. It presented a simple data structure and asked me to
54.
by pjot 2y ago
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.
55.
by pjot 2y ago
Yep! It was added in v0.10.0 - which was released a month or two after I made this. This is using v0.9.1
56.
by pjot 2y ago
I made something similar, but used duckDB as the vector store (and query engine)! It’s impressively fast https://github.com/patricktrainer/duckdb-embedding-search
57.
by pjot 2y ago
> The Downing Street website describes Larry's duties as "greeting guests to the house, inspecting security defences and testing antique furniture for napping quality". It says he is "contemplating a solution to
58.
by pjot 2y ago
When I was a kid my neighbors (who were from Ontario) taught me this game - we played all the time! It’s been over 20 years since and every few I try and recall what “that game” was. So glad to have seen this!
59.
by pjot 2y ago
Got it! I saw this in the code and assumed you were using embeddings def evaluate(input: shared.EvaluationInput): ds = Dataset.from_list(input.dataset) metrics = [metric_map[metric] for metric in input.metrics] llm = ChatOpe
60.
by pjot 2y ago
Can you talk about how you implemented search-as-you-type? Doing so with semantic search seems tricked given the roundtrips needed to compute embeddings on the fly (assuming the use of OpenAI embeddings)

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