
Explore Prestissimo, Presto's new C++ query execution engine, offering improved performance, reliability, and efficiency for data analytics and open data lakehouses.

Gain insights on submitting, preparing, and delivering C++ talks from industry experts Phil Nash, Inbal Levi, and Jens Weller.

Discover strategies for preparing and delivering impactful technical talks, with a focus on C++ topics. Gain insights to enhance your speaking skills and engage audiences effectively.

Learn effective techniques for starting a C++ presentation, enhancing your public speaking skills and captivating your audience from the beginning.

Explore the mathematics behind ray tracing, focusing on rays, spheres, and their intersections. Learn key concepts and equations essential for implementing realistic 3D graphics rendering.

Introduction to ray tracing techniques for generating photo-realistic digital imagery, covering setup, rendering, performance optimization, and GPU acceleration using C++ and Vulkan.

Learn to implement a dynamic array data structure in C++, covering reallocation, push/pop operations, and memory management techniques.

Learn to render a sphere using ray tracing techniques in C++. Covers creating a Renderer class, structuring code like a pixel shader, and implementing sphere rendering with optimized performance.

Explore the Linear Algebra Mapping Problem and its solutions in programming languages. Gain insights into high-performance computing and matrix operations for scientific applications.

Explore when software rewrites can be beneficial, choosing tech stacks, and transitioning to leadership as a junior dev. Learn from a real-world project transforming academic C++ code.

Explore challenges and prospects of low-level end-to-end reconstruction using machine learning in high-energy physics, focusing on innovative techniques and future applications.

Explore data-driven approaches in cosmology, leveraging statistical methods and machine learning to analyze vast datasets and uncover insights about the universe's structure and evolution.

Explore neural simulation-based inference techniques for high energy physics, focusing on advanced machine learning applications in data analysis and new physics discovery.

Explore applications of deep machine learning in high energy physics, covering classification, identification, and estimation strategies for analyzing LHC data and searching for new physics.

Explore machine-learned symmetries in high-energy physics with Konstantin Matchev. Discover innovative approaches to uncover hidden patterns and symmetries in particle physics data using advanced machine learning techniques.

Explore cutting-edge statistical methods and machine learning applications in high energy physics through expert presentations, fostering collaboration and innovation in data-driven research.

Explore machine learning applications in high-energy physics, focusing on Higgs boson research. Learn about successful ML techniques and future prospects in analyzing LHC data for new physics discoveries.

Explore generative models in high-energy physics, focusing on applications for data analysis and new physics discovery. Learn techniques to handle large datasets and improve classification strategies.

Explore ray casting fundamentals and practical applications in 2D game lighting, visibility systems, and line segment intersection calculations for creating dynamic lighting effects.

Master the practical implementation of C++20 modules with comprehensive coverage of build processes, named modules mechanisms, and CMake integration, plus strategies for working with header-based code.

Discover practical memory safety mitigation techniques for C++ applications, including Standard Library hardening and typed memory allocation, with insights on implementing these security measures in production environments.