Riaz ∇
1.6K posts

Riaz ∇
@LLMathematician
LLMs · Transformers · RL https://t.co/TIpJyBBsm7
Katılım Eylül 2024
192 Takip Edilen205 Takipçiler

@shiri_shh no its just a better product imo
(and i had a stressful week so needed diversion)
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Stanford's latest seminar is a deep dive into the evolution of world modeling in AI.
Focuses on the shift in the world model from traditional reconstruction methods toward latent space prediction.
Covers topics like:
- Introduction to JEPA & World Models
- Causal JEPA
- LOWER Model
- Practical Applications & Planning
- Future Outlook

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That is How does the USA government save NVIDIA GPUs from export!
.stuff@vintagestuff4
A young girl carrying an airsoft gun to defend her food from the local monkeys Lop buri, Thailand
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trying to connect with more people in computer science, especially in:
AI / Deep Learning
Systems / CUDA
Backend / Infra
Compilers / ML Systems
Distributed Systems
Performance Engineering
Algorithms / Data Structures
Operating Systems
If that’s your space (or you’re exploring it), let’s connect 🤝
Pruthviraj P@spidernvdev
200 -> 300 in 2 days. If you are in tech let’s connect. 🤝
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the goblin article is so funny openai.com/index/where-th…
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We're looking for a Research Assistant (Embedded AI Systems) at Language Technologies Research Center, IIITH.
This role is focused on building and optimizing real-world on-device AI systems. The work involves developing embedded Linux pipelines (Buildroot-based devices), handling real-time audio/video data transfer, and running AI models directly on edge hardware. On the mobile side, you'll work with on-device models (Gemma with LiteRT, MLKit, speech systems), and upcoming work includes optimizing inference using Qualcomm's QNN stack on NPUs/GPUs.
This is hands-on systems work. You should be interested in low-level programming (C/C++), comfortable exploring Linux/embedded systems, and curious about performance optimization and hardware-accelerated AI. Prior experience helps, but willingness to learn and build matters more.
The work is tied to building AI-enabled accessibility systems for visually and speech-impaired users, so there is a clear real-world impact alongside the technical depth.
Duration is 2 months (on-campus), with possible extension. Stipend is ₹10,000/month.
If this aligns with what you want to work on, reach out.
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@NVIDIA_AI_PC Watching brain rot youtube videos and having it summarize them, and research
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