On AI Lounge since Oct 2026
MinHtet Myet
Member #920DeveloperL3ML Systems Engineer, AWS
ML Systems Engineer · Distributed Training · LLM Infrastructure · Multimodal Systems
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Plugged In ×3Connected sources: GitHub, Hugging Face, LinkedIn, X, website.How: Connected 3 sources (GitHub, LinkedIn, X or a website) in Settings
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Production-grade multimodal RAG for financial document intelligence. Chart understanding · hybrid retrieval · numeric guardrails · multi-tenancy · full observability.
async-processingdocument-intelligenceenterprise-aifinancial-aillmmachine-learning
One library, four surfaces. Production-grade Kolmogorov-Arnold Networks || TensorFlow + PyTorch + ONNX. || A small KAN beats a 10× larger MLP on smooth, separable target. One library. Two backends. Real ONNX export. Docker + Kubernetes ready.
deep-learninggpu-accelerationinterpretabilitykankolmogorov-arnold-networksmachine-learning
Reusable world-model-based domain-gap quantification — for perception pipelines and actuator/mechanism models — before any hardware is touched.
joint-embedding-predictive-architecturerepresentation-learningrobotics-perceptionworld-models
60+ ML/AI/DL/RL/Bayesian algorithms implemented from scratch in NumPy -- plus mlscratch, a pip-installable package (pip install scratchkit) with a consistent, scikit-learn-style API and 1,100+ tests.
algorithms-from-scratchbayesian-inferencedeep-learningeducationalfrom-scratch-implementationslibrary
Space · 0 downloads · 6 likes
gradiofinanceragnlpdocument-question-answeringmultimodal
About
ML engineer bridging research and production. Focus: Triton kernels & GPU performance, distributed training, KAN architectures, LLM safety & inference. Open-source contributor across major ML frameworks.
