Suggestions
Sudeep Pillai
Co-founder / CEO at Autonomi AI | ex ML-eng. Lead at ToyotaResearch | CS PhD at MIT | BS at UMich
Sudeep Pillai is a prominent figure in the tech and AI industry, currently serving as a Founder Fellow at South Park Commons (SPC).14 He is the co-founder and CEO of VLM Run, a company focused on developing and optimizing AI models, particularly in the realm of Visual Language Models (VLMs).6
Background and Expertise
Sudeep holds a PhD in Computer Science from MIT CSAIL, showcasing his strong academic foundation in the field.6 His areas of expertise include:
- Artificial Intelligence and Machine Learning
- Computer Vision
- Visual Language Models (VLMs)
- PyTorch optimization and scaling
Professional Experience
Before his current role, Sudeep worked as an ML Lead at Toyota Research.6 This experience likely contributed to his deep understanding of AI applications in various industries.
Current Projects
At South Park Commons, Sudeep is working on several cutting-edge projects:
-
VLM Run: As the co-founder and CEO, he's developing tools to optimize and scale PyTorch models, enabling AI developers to transition smoothly from development to production.2
-
NOS: Along with Scott Loftin, Sudeep presented a demo of NOS, a tool designed to accelerate PyTorch models tenfold with minimal code alterations.2
-
Document AI: Sudeep has been exploring the use of VLM Run for internal Document AI agents, integrating with automation tools like n8n.5
Community Involvement
Sudeep is an active member of the AI community:
- He participates in conferences like CVPR (Conference on Computer Vision and Pattern Recognition).3
- He shares insights and updates about his work on social media platforms like LinkedIn and Twitter.56
Sudeep Pillai's work at South Park Commons and his contributions to the field of AI, particularly in visual language models and PyTorch optimization, position him as a significant innovator in the tech industry.
Highlights
📣 In our latest guide on Image Cataloging, we show how VLMs can simultaneously perform multiple computer-vision tasks such as image captioning, tagging and classification with a custom Pydantic schema!
🎯 Perfect for e-commerce, visual content management, and more! Check out our image-cataloging example using a sample product dataset from Hugging Face. https://lnkd.in/gPEqMkqS
TL;DR 📝 Generate captions, tags, and descriptions easily from images 🏷️ Create structured JSON for product catalogs 🔍 Enable powerful hybrid semantic image search with existing DBs like MongoDB
Key features: ✅ Tailored visual captioning, extraction and classification ✅ Structured JSON outputs with custom Pydantic schemas ✅ Scalable to large image catalogs with our fine-tuning API (for enterprises)
✍️ Interested in trying it out? Sign up for a free trial at VLM Run (https://vlm.run)
#ComputerVision #ImageProcessing #AI #ProductCataloging #llm
🌎 By popular demand, we’ve added OpenAI compatibility to VLM Run! https://lnkd.in/gv6i4mYk
👩💻 This means that with just 2 lines of code-change, you'll be able to access our VLM-1 model directly using the existing OpenAI SDK (JS, Python etc). We think this will be a game-changer for developers who are already using OpenAI and want to quickly take VLM Run for a spin and see the obvious benefits.
OpenAI API Compatibility Reference https://lnkd.in/gjWKNdgq
API Docs https://docs.vlm.run
Let us know what you think!
#openai #llm #vlm
