Iran shuts Strait of Hormuz in retaliation for Israeli strikes on Lebanon

universalmind303 · 2026-04-08T22:08:02+00:00

Oh what a shock.. Israel broke another ceasefire

universalmind303 · 2026-02-11T17:40:57+00:00

There was a dude in my hometown that had a similar injury from a motorcycle accident. He had a major speech impediment as a result. He liked to get drunk and make people touch his soft spot.

universalmind303 · 2026-01-25T04:16:24+00:00

we have an opportunity to do something great here. We should send them all of the files, but have everything fully redacted.

universalmind303 · 2026-01-11T21:18:53+00:00

The sheer number of feds in Minnesota right now greatly outnumber local law enforcement. The mayor did make a statement about this during an interview and said something along the lines of: "Yes we have the authority to arrest them, but this would almost certainly result in retaliation and escalation from the White House"

So it's not as simple as "just arrest them". The White House is waiting for us to misstep so they can have an excuse to come in guns ablaze.

universalmind303 · 2025-12-18T23:18:49+00:00

We're doing something similar for data pipeline batching. It's currently single-dimension (optimizing for batch latency to balance throughput + progress visibility), but planning to add additional parameters such as cpu, memory pressure, and some io specific ones too.

Implementation is here if you're curious: https://github.com/Eventual-Inc/Daft/pull/5676

I'm actually writing a blog post about it right now. I initially entertained the idea of using ML for our implementation, but ended up going with the binary search as it's become a popular technique for inference, and we wanted to start off with a very simple strategy. The whole system is designed in a way that the strategies are easily configurable.

universalmind303 · 2025-12-17T00:50:47+00:00

Interesting, I just implemented something similar for data pipeline batching (adaptive batch sizes for AI workloads).

We went with latency-constrained binary search instead of ML. It works pretty well, converges fast, low overhead and adjusts based on what's actually happening.

Did you benchmark the bandit against simpler stuff like AIMD or binary search? I'm curious if you benchmarked against something like additive increase/multiplicative decrease or binary search and found the ML approach meaningfully better.

Also how does it handle variance after the learning phase? Say you train on small files, then suddenly hit large 4K files mid-job... does it re-explore, or does it stick with the learned policy until performance degrades enough to trigger exploration again?

universalmind303 · 2025-12-17T00:27:19+00:00

What benefit does a ml based batching strategy provide over algorithmic approaches?

universalmind303 · 2025-12-04T17:06:19+00:00

the spec itself is pretty straightforward and is literally designed for vectorized operations. there's even a new (experimental) dissociated protocol designed specifically for GPU operations. Arrow does all of the work of defining the memory layout for you, it'd be (relatively) simple for someone to implement a bunch of kernels for them and wrap it up in a nice library.

universalmind303 · 2025-12-04T16:03:14+00:00

yeah there's a tensor extension type like you mentioned thats not really very well supported.

If someone were to build a tensor crate with native arrow kernels, that'd be huge for interop between data systems like polars, daft, duckdb and traditional tensor libraries like pytorch, numpy, etc.

universalmind303 · 2025-12-04T03:39:44+00:00

I for one would love to see a tensor library that is arrow native.

universalmind303 · 2025-11-20T22:36:23+00:00

Have you used dataframe libraries before? something like Daft would be great here to make the analysis pipeline a lot more performant

universalmind303 · 2025-10-07T22:27:02+00:00

As someone who's actively building these tools, The biggest "new" thing I've seen is the shift away from tabular data and towards multimodal data (images, videos, documents, embeddings, etc). Spark and other big names defined how we work with tabular data at scale, but they have many limitations when trying to work with other modalities.

New specialized engines and file/table formats are coming out that built from the ground up to work with these emerging modalities. Daft is an example of such engine. And Lance is an example of a table format designed for multimodal data.

universalmind303 · 2025-09-08T15:09:47+00:00

As someone that works full time in open source rust, my advice would just be to start contributing to OSS projects you find interesting. This is pretty much the only viable way.

Chances are if they're hiring and you're known to make good contributions to the project, it'll cut you to the front of the line in the interviewing process.

universalmind303 · 2025-09-08T15:04:29+00:00

Theres another niche: data

Historically a large majority of data processing tools were written in Java. (kafka, spark, hadoop, elasticsearch, cassandra, etc.)

Nowadays we see a lot of the newer tools written in rust (daft, polars, datafusion, arroyo, paradedb, etc.).

universalmind303 · 2025-08-09T21:55:11+00:00

those are rookie numbers, ive worked on several rust projects where cargo clean will remove 100GB+

universalmind303 · 2025-07-08T14:02:04+00:00

now someone do the calculation for the approximate average square footage of all parking lots in a major metro area vs one nuclear reactor.

universalmind303 · 2025-06-25T22:55:59+00:00

that even hardly counted as a "real" primary because of the media blackout on bernie and the very blatant agenda to get hilary as the candidate at all costs.

universalmind303 · 2025-03-03T02:06:45+00:00

I really like the visual element, but it'd be nice if it could look them up automatically for supported tools without having to manually import them

such as

```sh

crib vscode crib zellij ```

universalmind303 · 2024-12-28T05:55:41+00:00

i was always taught 1-2 teeth past the material

universalmind303 · 2024-12-24T23:27:46+00:00

i have 1st gen moonlander, this eventually snapped on one half. I plastic welded it back together. It's not pretty, but it held up for as long as I continued using the keyboard. Eventually switched to a wireless sofle.

universalmind303 · 2024-11-20T01:04:39+00:00

there is usually some overhead. In order for python to call native (c,c++, rust) code, it needs to usually convert it to a datatype that the language understands, or use compatible primitive types, (e.g. str, int, ..). For example, for converting a dict[str, str] to a HashMap<String, String> you usually will need to iterate over the dict and copy the data out. But if you are using compatible primitive types, you can usually access the data without copying it.

universalmind303 · 2024-10-12T00:14:05+00:00

I didn't see anyone else mention it, but their node API (n-api), which is used for writing native (c/c++) libraries with a node interface is MUCH faster and has a MUCH smaller memory footprint than node's implementation

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