Kailash Ahirwar

Building AI for Fashion & E-Commerce | Virtual Try-On | Co-founder - TryOn Labs | Raven Protocol | Mate Labs | Author-Generative Adversarial Networks Projects

[Kailash Ahirwar @Ahkailash1]

10/

What do you think of this direction? Let me know your thoughts in the comments below.

#AI #MachineLearning #LLM #AIResearch #ModelCompression #SmallLanguageModels #Quantization #EdgeAI #DeepLearning

[Kailash Ahirwar @Ahkailash1]

1/
There's a new kind of AI researcher showing up.

Not someone racing to build the next giant model.

Someone who takes a model that already works and asks: how do I make this small, fast, and cheap enough to actually use?

[Kailash Ahirwar @Ahkailash1]

9/
Not "how smart can we make it."

But "how much of that intelligence can we keep, at a fraction of the size and cost."

[Kailash Ahirwar @Ahkailash1]

6/ Still experimental and early-stage, but definitely worth watching for people working on:

1. AI infrastructure
2. CUDA kernels
3. Compilers
4. HPC
5. ML systems

would you write GPU kernels in Rust instead of CUDA C++?

#GPUProgramming #SystemsProgramming

[Kailash Ahirwar @Ahkailash1]

1/ NVIDIA Labs(@nvidia) just released cuda-oxide - an experimental Rust-to-CUDA compiler.

You can now write CUDA GPU kernels directly in idiomatic Rust.

No C++.
No DSLs.
No foreign language bindings.

https://t.co/LzF9GWLpUg

#CUDAProgramming #SystesProgramming

[Kailash Ahirwar @Ahkailash1]

5/ The bigger trend is interesting:

AI infrastructure is increasingly becoming:

1. Compiler-driven
2. Kernel-driven
3. Memory-bandwidth constrained

Languages and tooling around GPU kernels are becoming strategically important again.

#MachineLearning #Cuda

[Kailash Ahirwar @Ahkailash1]

3/ Subscribe to get my posts and articles delivered directly to your inbox.

Let’s explore the future of AI together!

#AI #ArtificialIntelligence #TechTrends #AITools #AIBenchmarks #MachineLearning #Substack #AIResearch #FutureOfAI #TechInsights

[Kailash Ahirwar @Ahkailash1]

1/ 🚀 I’ve started publishing on Substack!

If you're into AI: algorithms, research papers, benchmarks, datasets, agents, and more, you’ll love it.

https://t.co/x4P0zcUS3z

[Kailash Ahirwar @Ahkailash1]

2/ On Substack, I dive deeper into tech and AI trends than ever before.

If you’ve been following my insights on LinkedIn, this is the next step.

[Kailash Ahirwar @Ahkailash1]

5/ Curious—do you think predictive representation learning will become more significant as models evolve beyond pure generation?

Paper: https://t.co/ZuGfBDH0OE

#MultimodalAI #SelfSupervisedLearning #AIResearch #RepresentationLearning #PredictiveModels

[Kailash Ahirwar @Ahkailash1]

1/ Not all progress in AI is generative.
VL-JEPA serves as a strong reminder of that.

I recently explored the paper “VL-JEPA: Vision–Language Joint Embedding Predictive Architecture,” which takes a fascinating non-generative approach to multimodal learning. 🧵

[Kailash Ahirwar @Ahkailash1]

4/ The broader takeaway for me:
We don’t need to generate everything to understand everything.

Predictive representation learning could enhance efficiency, stability, and generalization as multimodal systems scale.