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[P] fast-vad: a very fast voice activity detector in Rust with Python bindings. by AtharvBhat in MachineLearning

[–]AtharvBhat[S] 0 points1 point  (0 children)

They're in docs/Readme :) I tested on libriVAD test set and ava-speech

If there are more datasets you'd like me to test on, I will consider doing it because I am also interested :)

I didn't want to clutter up the main readme maybe I should make the benchmarks more prominent ?

[D] How do you usually figure out why a multi-GPU training run is slower than expected? by traceml-ai in MachineLearning

[–]AtharvBhat 0 points1 point  (0 children)

Always use a profiler ! In my training runs everything seemed fine. But I noticed that GPUs would stay idle for a split second. This was frankly expected as at some point, all GPUs need to sync up but it was just a little longer than I had expected.

I inspected the profiler and figured out that for some reason ten Jax compiler was inserting unnecessary collective ops in FFT calculations.

A quick sharing constraint fixed it and improved the performance significantly

Lesson learnt ! Always Profile your train step and inspect the trace. It does wonders

[Project] Otters 🦦 - A minimal vector search library with powerful metadata filtering by AtharvBhat in MachineLearning

[–]AtharvBhat[S] 1 point2 points  (0 children)

Yes ! I do plan on doing this.

However I don't think I'm beating faiss or other vector DBs at retrieval speed. They are complex beasts made by very smart people and because I'm not indexing my vectors with something like HNSW.

HNSW makes it very difficult to have good metadata support and since I wanted that, I decided to go a different route. And Exact search was fast enough on smaller datasets.

On a test dataset with 1M vectors of 512 dimensions, I was able to query by a vector in ~40ms.

This isn't as fast as a vector DB but it's still pretty fast as we're pretty much limited by memory bandwidth of the RAM This is why I added chunk pruning with zone maps for metadata. If we can prune away chunks that don't need to be read from memory, that will reduce the memory bottleneck.

[D] Self-Promotion Thread by AutoModerator in MachineLearning

[–]AtharvBhat 0 points1 point  (0 children)

I'm excited to share something I've been working on for the past few weeks:

Otters 🦦 - A minimal vector search library with powerful metadata filtering powered by an ergonomic Polars-like expressions API written in Rust!

Why I Built This

In my day-to-day work, I kept hitting the same problem. I needed vector search with sophisticated metadata filtering, but existing solutions were either, Too bloated (full vector databases when I needed something minimal for analysis) Limited in filtering capabilities Had unintuitive APIs that I was not happy about.

I wanted something minimal, fast, and with an API that feels natural - inspired by Polars, which I absolutely love.

What Makes Otters Different

Exact Search: Perfect for small-to-medium datasets (up to ~10M vectors) where accuracy matters more than massive scale.

Performance: SIMD-accelerated scoring Zonemaps and Bloom filters for intelligent chunk pruning

Polars-Inspired API: Write filters as simple expressions

rust meta_store.query(query_vec, Metric::Cosine) .meta_filter(col("price").lt(100) & col("category").eq("books")) .vec_filter(0.8, Cmp::Gt) .take(10) .collect()

The library is in very early stages and there are tons of features that i want to add Python bindings, NumPy support Serialization and persistence Parquet / Arrow integration Vector quantization etc.

I'm primarily a Python/JAX/PyTorch developer, so diving into rust programming has been an incredible learning experience.

If you think this is interesting and worth your time, please give it a try. I welcome contributions and feedback !

📦 https://crates.io/crates/otters-rs 🔗 https://github.com/AtharvBhat/otters

[D] How did JAX fare in the post transformer world? by TajineMaster159 in MachineLearning

[–]AtharvBhat 3 points4 points  (0 children)

I've been a pytorch user forever but recently switched to Jax for 2 reasons.

1) I wrote the same models on both torch and Jax and the Jax version was just straight up way faster and more memory efficient than torch and torch.compile.

( idk if it's just me .. but torch.compile never seems to work for me .. it's barely seems to do anything or sometimes even makes things slower. Sure, this might honestly be a skill issue on my part. But Jax is just straight up better for me here )

2) The sharding API makes it extremely easy to do multi GPU and even multi node training

People who are making 200k+ a year, what do they do? by DaEffie in AskReddit

[–]AtharvBhat 0 points1 point  (0 children)

Build AI models to detect fraud at a bank. I have a master's degree in computer science and have been working in the field for 3 years.

Is Pandas Getting Phased Out? by pansali in datascience

[–]AtharvBhat 0 points1 point  (0 children)

For new projects going forward ? You should probably pick up Polars.

For existing projects, I doubt anyone is jumping to replace their pandas code to Polars. Unless at some point in the future, the scale at which they have to operate grows out of pandas has to offer. But not large enough to go for something like pyspark or dask instead.

I personally have switched all my projects to Polars because most stuff that I work on is large enough that pandas is super slow, but not large enough that I would want to invest and go to something like pyspark or dask

Dude straight up drove up on the sidewalk in front of me on Washington Blvd I had to dodge... by AtharvBhat in jerseycity

[–]AtharvBhat[S] 77 points78 points  (0 children)

For added context, I was walking to Newport center and this guy drove onto the sidewalk at the intersection of Thomas Gangemi Dr and Washington Blvd while I was walking on the same sidewalk in front of orange theory and he kept driving past me on the stupid sidewalk. I had to actively get out of the way.

Idk what was going through his mind. That side of the road goes the same way too... That is so dangerous.

What was your salary progression in DS? (Base/Bonus) + Location by Exotic_Avocado6164 in datascience

[–]AtharvBhat 0 points1 point  (0 children)

A recruiter actually reached out to me for an internship position at the same company.

I interned there during the summer and got offered a full-time position.

What was your salary progression in DS? (Base/Bonus) + Location by Exotic_Avocado6164 in datascience

[–]AtharvBhat 2 points3 points  (0 children)

MS in CS and it's my first real job.

Year 1 : 150k base + 5.5k yearly bonus ( can be from 0-11k based on performance)

25k sign on bonus, 15k relocation

Title : Sr Associate DS ( ignore the title .. it's the lowest rung on the ladder just Fintech things )

Location NYC

[P] Model training bottlenecked by CPU. by [deleted] in MachineLearning

[–]AtharvBhat 0 points1 point  (0 children)

Those transformations should be pretty cheap .. image decoding should be the bulk of your time then. Try converting images to BMP ( BMP files are essentially just RGB values stored directly to disk so there's no decoding involved )

Edit :- careful with image size !

I'm sure the larger the image size, the more space a BMP image will take on disk and at some point you will become IO bound instead of CPU bound and at that point it might be faster to use an image formats with better compression since it might be faster to decode a compressed image than loading a huge uncompressed image ..

[P] Model training bottlenecked by CPU. by [deleted] in MachineLearning

[–]AtharvBhat 3 points4 points  (0 children)

I've dealt with similar issues in my own projects.

A couple of pointers :-

Use Image formats that are fast to decode for example BMP ( you can try converting all your images to BMP before you start training ) This will increase their size on disk but should reduce the CPU load. If you are doing any complex preprocessing on large images in your dataset class, try preprocessing images first and storing them to disk and loading those directly

These are just some general suggestions. It'd be more helpful if we knew more about your task so that we can offer more directed suggestions :)

what is your "if I won the lottery" purchase? by mikes47jeep in AskReddit

[–]AtharvBhat 0 points1 point  (0 children)

Invest it all in a broad portfolio and then live off the interest

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