Yatharth Sharma

YatharthS

P(doom) <0.01%

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AI & ML interests

TTS, speech generation, Agents, MCP

Recent Activity

upvoted an article 13 days ago

Introducing Voice Acting Arena

reacted to TravisMuhlestein's post with 🔥 about 2 months ago

One of the most underrated parts of AI-assisted engineering may have nothing to do with the model. It's the infrastructure around the engineer. Shriyash Balshetwar and Shubham Jangle, engineers at GoDaddy, were spending roughly 16 mechanical pull requests per week managing localization branches. None of the work was particularly difficult—it was repetitive, easy to forget, and occasionally capable of blocking releases. They built a GitHub App to remove the entire workflow. What I find interesting is what happened underneath the simple idea of "automate the PRs." The production system needed idempotent webhook handling, installation-scoped authentication, retry logic around GitHub's asynchronous mergeability state, per-repository configuration, and safe pattern matching. The app itself is under 900 lines of JavaScript. The interesting lesson is that the hard part of automation isn't always the automation. It's building the reliability around it. As AI agents take on more software engineering tasks, I expect this distinction to become even more important. The systems surrounding an agent—events, permissions, state, retries, validation, and feedback—may matter as much as the model making the decision. 🔗 https://www.godaddy.com/resources/news/how-a-github-app-saved-us-hours-of-manual-effort Curious what other engineering workflows people have found worth automating end-to-end.

reacted to theirpost with 🚀 about 2 months ago

Open sourcing Coala Embeddings! It can compress 20 million documents which can take 80gb ram down to just 1gb RAM. Why is this important? Embeddings are used everywhere(RAG, semantic search, etc.) by many. Coala Embeddings massively cheapen cost to host them while being simply and easy to use. GitHub: https://github.com/ysharma3501/CoalaEmbeddings Notebook Demo: https://colab.research.google.com/drive/1TXip-vZg72e_2AB185MINufVVav8Oo9T?usp=sharing

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Posts 7

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Open sourcing Coala Embeddings! It can compress 20 million documents which can take 80gb ram down to just 1gb RAM.

Why is this important? Embeddings are used everywhere(RAG, semantic search, etc.) by many.

Coala Embeddings massively cheapen cost to host them while being simply and easy to use.

GitHub: https://github.com/ysharma3501/CoalaEmbeddings
Notebook Demo: https://colab.research.google.com/drive/1TXip-vZg72e_2AB185MINufVVav8Oo9T?usp=sharing

Articles 2

Article

61

LLM based Audio models

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spaces 4

LavaSR

Ultra fast universal speech enhancement model.

LuxTTS

Space for LuxTTS: a 150x realtime voice cloning TTS model

NovaSR

An incredibly fast and tiny audio upsampler

GLM ASR Nano

A space to transcribe audio files with the new sota GLM-ASR

models 8

YatharthS/CoalaEmbedding

Updated Aug 14 • 3

YatharthS/LavaSR

Audio-to-Audio • Updated Feb 27 • 1.41k • 87

YatharthS/LuxTTS

Text-to-Speech • Updated Jan 23 • 5.98k • 209

YatharthS/NovaSR

Audio-to-Audio • Updated Jan 19 • 107 • 88

YatharthS/LinaCodec

Audio-to-Audio • 0.1B • Updated Jan 3 • 27 • 24

YatharthS/FlashSR

Audio-to-Audio • Updated Dec 26, 2025 • 67

YatharthS/MiraTTS

Text-to-Speech • 0.5B • Updated Dec 24, 2025 • 198 • 192

YatharthS/LayaCodec

Audio-to-Audio • 0.1B • Updated Dec 14, 2025 • 17 • 14

datasets 0

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