Shauray Singh

Computers can see, hear and learn. Welcome to the future !

An idiot admires complexity. A genius admires simplicity. A physicist tries to make it simple. Anything that is gaining complexity, more the idiot will admire it. If you make something more clusterfuck that he can't understand, he will think you are a god because you made it so complicated nobody can understand it. That's how they write academic journals to make others think you are a genius.
Terry Davis

BUT if you want to be an Idiot here's a more clusterFUCK version of this website !
Maybe that's the reason most of us don't believe that we live in a simulation.



12/2023 - present
ML guy at ModelsLab (Prev StableDiffusionAPI), My daily grind involves keeping the diffusers_plus_plus library in top shape, ensuring those diffusers and transformers are faster than a speeding bullet (or at least, faster than they were yesterday). And when I'm not busy patching and optimizing, I'm digging through research papers to find the latest and greatest SOTA models to add to our library and play with a lot of sweet compute

Technical Details:

  • I'm all about PyTorch, so if you're familiar with those ecosystems, we're off to a great start.
  • I've got a love-hate relationship with CUDA and Triton - love the performance, hate the debugging headaches - maybe not the torch profiler
  • I'm always on the lookout for ways to parallelize model inference, so if you've got experience with parallel processing, let's chat.

    • All state of the art, research / model inferences on twitter

    01/2023 - 04/2023
    I was a Senior Staff at Zummit InfoLabs, where I gave some talks and took some sessions on GIT/GitHub and how version control works with a brief introduction to CI/CD environments.

    Helped design companies' ML pipelines for better and faster deployment and improved access times.

    Reviewed some pull requests and helped solve some code-related issues in some major projects.

    10/2022 - 1/2023
    I joined Zummit InfoLabs as a Jr. Data Scientist where I led a team of 5 interns and made some significant advancements in Taxi Demand Predictions which used some statistical methods and was then migrated to work with graph neural networks.

    Learned a lot about graph neural networks and how spatial-temporal graphs can make things faster and easier than some other traditional methods.

    8/2020 - 6/2024
    B.Tech at Manipal University Jaipur with a major in Data Science and a minor in Finance. This is where I got really deep into deep learning by browsing the internet and attending random lectures on youtube in my dorm room.

    HuggingFace
    I have a deep deep love for OpenSource, It's like lifeblood of the tech world, and I'm all in! I'm a regular contributor over at Hugging Face, rolling up my sleeves and getting things done. From Transformers to tokenizers, I'm in the trenches, making things better.
    Sharing some of the wisdom here with Blogs and some low quality tweets!

    So, remember, open source is where it's at.
    YouTube
    In 2022 I started streaming on YouTube just some random coding shit and programmed some useless projects live. I like keeping things raw just like this website so every video on YouTube has some kind of copyright and is stupidly insane to watch them all but it shows my raw nature when I code.
    Larynx Research
    At Larynx we develop state of the art deep learning architectures through which we can convert text to speech without hearing any of that computer generated sound bulshit ! Our first major project include converting any pdf text book to it's audiobook format. You can then use if for listning to financial reports of some company, some student can use it to learn some kinda useful shit and most importantly it's open source so you don't have to pay a single dime in order to learn !! FUCK AMAZON AUDIBLE !!

    Go Contribute
    My Poorly Written Blog
    Refer Twitter for microblogs, refer THIS for full length blogs only if you have a good attention span ! Contains a lot of STEM stuff
    My Project Graveyard
    Semantic Search Engine was a GSoC project
    Turing was supposed to be just a simple library built on top of numpy which would calculate gradients for your neural network with some additional features that would help in the development BUT since then my vision for Turing got a little bigger and now Turing has a C backend for tensor support with custom matmul accelerators, AVX512 for multi-core CPU's and now supports CUDA backend. Basically, this is what PyTorch is but way way way more complex, I wanted something not so complex but powerful enough!
    GET-MORE! is an archive of what language models looked like a while back and how they look now. Just takes a third-eye view of how we went from bi-gram models to transformer-based models. Basically, this is a little extension of what Andrej Karpathy did on his YouTube channel. This project demonstrates the SIGMOID curve of innovation and I wonder where are we right now on that curve.
    OnlyGans is currently under development and is NSFW. OnlyGans uses a fleet of SOTA generative models to generate naked individuals which would work something like thispersomdoesnotexist.com. uses some version of StyleGan to generate images and may support videos in the future. Support this noble cause by contributing to the repo and make this world a better place to live !.
    Trachea transforms your speech to a text output. It uses a simple convolution model on mel spectrograms generated by a custom library which when presented with an audio sample would create a mel spectrogram and then the pixel data would get squished and smashed by the neural network to generate a text representation of that particular sample! It was a simple project for my deep learning class that I took in college
    Context Tree Weighting was again a college project in which I tried implementing different compression algorithms as a baseline and then tried implementing Context Tree Weighting which was not very easy and I would like to get back to it someday maybe I can have a better understanding of how compression works !!
    Calib-Challenge was a challenge organized by Comma AI. The repo contains the code for predicting the YAW and Pitch of a moving car from the dashcam video. The project kept on going after the contest as well and now it contains some very basic code for a self-driving car. Just the software part of it, there are no bound conditions yet and it just gives out raw data that has to be processed before giving it to the car's computer. Pedal is the Operating System for the same and is UNIXish. I wanna drive a fully autonomous car with this code someday (with some improvement course!)
    Quadruple Inverted Pendulum was my first attempt at writing a research paper that failed (OF COURSE) it was pretty straight forward actually. It's basically 4 pendulums attached to one another and the task was to balance them on top of the prev pendulum without falling. But turns out calculating Lagrangian equations for this setup is pretty straightforward but has a lot of calculations and just to simulate the pendulums there are hundreds of thousands of calculations every sec. But then I found something very useful called GameGAN but again there was no open source code for that and I DROPPED THE IDEA !
    misc: I built a lot of other random stuff over time. GO check it on my GitHub and if you wanna make a change in the world and as George Hotz says "wanna win over nature" find a project on GitHub or maybe I can help you find one visit https://github.com/shauray8 and fork some repositories and start adding stuff!
    misc unsorted
    RIP TERRY