Behind the Mirror: Understanding Kotlin Reflection
Explore Kotlin's powerful Reflection API, understanding its essential role in functional programming and property delegation, and how it's implemented in JVM bytecode.
Building Libraries for the Next 25 Years
Explore strategies for creating enduring, future-proof libraries that stand the test of time in software development.
Practical Introduction to OpenCV and TensorFlow Lite for Android
Explore OpenCV and TensorFlow Lite for Android, focusing on real-world computer vision applications, performance optimization, and practical implementation challenges.
On-Device Machine Learning for Android with MediaPipe
Explore on-device ML for Android using MediaPipe to add advanced features like image generation and object detection to your apps.
Securing Gradle Builds: Protecting Against Supply Chain Attacks
Secure Gradle builds against supply chain attacks with insights on vulnerabilities, protection strategies, and best practices for dependency and metadata verification.
Getting Started with GenAI for Android Apps
Explore GenAI integration in Android apps, covering basic concepts, major AI solutions, and practical mobile use cases. Learn to leverage AI capabilities effectively.
Practical Optimizations in Jetpack Compose - Performance Improvement Techniques
Discover techniques to enhance Jetpack Compose performance through code flow, data structures, bytecode, and memory optimizations. Learn to analyze and improve Kotlin-generated bytecode and machine code.
How to Avoid Common Mistakes and Misconceptions When Working with AWS Lambda
Discover strategies to optimize AWS Lambda performance, reduce cold starts, manage costs, and implement effective caching for serverless applications.
Efficient Kotlin: Optimizing Performance and Resource Usage - GeeCON 2022
Learn efficient Kotlin coding techniques to optimize performance, reduce resource usage, and improve scalability for critical applications and large-scale deployments.
CompletableFuture and Its Quirks in Java
Explore CompletableFuture's quirks, traps, and surprises in Java through live coding, covering thread pools, exception handling, cancellations, and unintuitive API methods.
Declarative HTTP Client in Micronaut Framework - Live Coding Session
Explore Micronaut's declarative HTTP client, learning to handle client-server communication, prepare for network issues, and effectively test your implementations.
Simple, Modern Java Microservices in the Cloud
Explore modern Java microservices development for startups, focusing on simplicity, productivity, and cloud deployment. Learn architectural approaches and unconventional design choices.
CompletableFuture and Its Quirks in Java - Live Coding Session
Explore CompletableFuture's quirks, traps, and surprises in Java through live coding, covering thread pools, exception handling, cancellations, and unintuitive API methods.
SPy - Static Python Language: Fast as C, Pythonic as Python
Explore SPy, a statically typed Python variant aiming for C-like performance while maintaining Pythonic style. Learn about its design, features, and current status.
... and Justice for AI - Understanding the European AI Act
Explore the European AI Act's impact on developers, focusing on ethical AI systems, regulatory compliance, and protecting fundamental rights while fostering innovation.
Multimedia Processing with FFmpeg and Python
Explore multimedia processing using FFMpeg and Python. Learn to handle various codecs and formats efficiently, leveraging FFMpeg's powerful capabilities through Python integration.
Large Language Models for Compiler Optimization
Explore how large language models can enhance compiler optimization, focusing on a custom 7B parameter Transformer model that generates optimal compiler options for minimizing code size.
Elastic Decision Transformer Explained
Explore cutting-edge Elastic Decision Transformer, combining transformers and reinforcement learning. Learn how it enhances traditional models by adaptively modifying historical context during inference.
Attention with Linear Biases Explained
Explore attention mechanisms with linear biases in transformer models, enabling efficient extrapolation to longer sequences without explicit positional embeddings.
LoRA Explained - Efficient Fine-Tuning of Large Language Models
Explore LoRA, a technique for efficient fine-tuning of large language models. Learn about its low-rank matrix decompositions and reduced trainable parameters for task-specific adaptations.
Deep Dive: Gradients in Ivy - Tutorial 20
Explore gradients in Ivy, mastering advanced techniques for deep learning and neural network optimization.