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Browsing: Optimization
RightNow AI Releases AutoKernel: An Open-Source Framework that Applies an Autonomous Agent Loop to GPU Kernel Optimization for Arbitrary PyTorch Models
Writing fast GPU code is one of the most grueling specializations in machine learning engineering. Researchers from RightNow AI want to automate it entirely. The RightNow…
Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning
In this tutorial, we build a complete end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a deep learning model directly in Google Colab.…
A few days ago, a group of researchers at Google dropped a PDF that didn’t just change AI: it wiped billions of dollars off the stock…
A Complete End-to-End Coding Guide to MLflow Experiment Tracking, Hyperparameter Optimization, Model Evaluation, and Live Model Deployment
best_C = best[“params”][“C”] best_solver = best[“params”][“solver”] final_pipe = Pipeline([ (“scaler”, StandardScaler()), (“clf”, LogisticRegression( C=best_C, solver=best_solver, penalty=”l2″, max_iter=2000, random_state=42 )) ]) with mlflow.start_run(run_name=”final_model_run”) as final_run: final_pipe.fit(X_train, y_train)…
How to Design an Agentic Workflow for Tool-Driven Route Optimization with Deterministic Computation and Structured Outputs
In this tutorial, we build a production-style Route Optimizer Agent for a logistics dispatch center using the latest LangChain agent APIs. We design a tool-driven workflow…
How to Align Large Language Models with Human Preferences Using Direct Preference Optimization, QLoRA, and Ultra-Feedback
In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We…
Microsoft AI Proposes OrbitalBrain: Enabling Distributed Machine Learning in Space with Inter-Satellite Links and Constellation-Aware Resource Optimization Strategies
Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink…
A Coding Deep Dive into Differentiable Computer Vision with Kornia Using Geometry Optimization, LoFTR Matching, and GPU Augmentations
We implement an advanced, end-to-end Kornia tutorial and demonstrate how modern, differentiable computer vision can be built entirely in PyTorch. We start by constructing GPU-accelerated, synchronized…
Microsoft Research Releases OptiMind: A 20B Parameter Model that Turns Natural Language into Solver Ready Optimization Models
Microsoft Research has released OptiMind, an AI based system that converts natural language descriptions of complex decision problems into mathematical formulations that optimization solvers can execute.…
Private equity firm Everstone Capital is bringing together India’s Wingify — a company that helps businesses test different versions of their websites to improve sales and…
