often multiple 10Ks or 10Qs can have highly similar chunks especially those that describe what the company does
example from Nvidia, these 2 are the top 2 re-ranked chunks
(truncated chunks)
Company: NVIDIA Corporation
Ticker: NVDA
Filing: 10-K, filed 2023-02-24
Filing quarter: 2023Q1
Section: PART I > ITEM 1. BUSINESS > Our Company
NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. Since our original focus on PC graphics, we have expanded to several other large and important computationally intensive fields. Fueled by the sustained demand for exceptional 3D graphics and the scale of the gaming market, NVIDIA has leveraged its GPU architecture to create platforms for scientific computing, artificial intelligence, or AI, data science, autonomous vehicles, or AV, robotics, metaverse and 3D internet applications.The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of the physical world. Its parallel processing capabilities, supported by thousands of computing cores, are essential to running deep learning algorithms. This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots and self-driving cars that can perceive and understand the world. GPU-powered deep learning is being adopted by thousands of enterprises to deliver services and products that would have been immensely difficult with traditional coding.
Company: NVIDIA Corporation
Ticker: NVDA
Filing: 10-K, filed 2025-02-26
Filing quarter: 2025Q1
Section: Part I > Item 1. Business > Our Company
NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. NVIDIA is now a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.Our full-stack includes the foundational CUDA programming model that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, software development kits, or SDKs, and Application Programming Interfaces, or APIs. This deep and broad software stack accelerates the performance and eases the deployment of NVIDIA accelerated computing for computationally intensive workloads such as artificial intelligence, or AI, model training and inference, data analytics, scientific computing, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.Our data-center-scale offerings are comprised of compute and networking solutions that can scale to tens of thousands of GPU-accelerated servers interconnected to function as a single giant computer; this type of data center architecture and scale is needed for the development and deployment of modern AI applications.The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of the physical world. Its parallel processing capabilities, supported by thousands of computing cores, are essential for deep learning algorithms.
often multiple 10Ks or 10Qs can have highly similar chunks especially those that describe what the company does
example from Nvidia, these 2 are the top 2 re-ranked chunks
(truncated chunks)
Company: NVIDIA Corporation
Ticker: NVDA
Filing: 10-K, filed 2023-02-24
Filing quarter: 2023Q1
Section: PART I > ITEM 1. BUSINESS > Our Company
NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. Since our original focus on PC graphics, we have expanded to several other large and important computationally intensive fields. Fueled by the sustained demand for exceptional 3D graphics and the scale of the gaming market, NVIDIA has leveraged its GPU architecture to create platforms for scientific computing, artificial intelligence, or AI, data science, autonomous vehicles, or AV, robotics, metaverse and 3D internet applications.The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of the physical world. Its parallel processing capabilities, supported by thousands of computing cores, are essential to running deep learning algorithms. This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots and self-driving cars that can perceive and understand the world. GPU-powered deep learning is being adopted by thousands of enterprises to deliver services and products that would have been immensely difficult with traditional coding.
Company: NVIDIA Corporation
Ticker: NVDA
Filing: 10-K, filed 2025-02-26
Filing quarter: 2025Q1
Section: Part I > Item 1. Business > Our Company
NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. NVIDIA is now a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.Our full-stack includes the foundational CUDA programming model that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, software development kits, or SDKs, and Application Programming Interfaces, or APIs. This deep and broad software stack accelerates the performance and eases the deployment of NVIDIA accelerated computing for computationally intensive workloads such as artificial intelligence, or AI, model training and inference, data analytics, scientific computing, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.Our data-center-scale offerings are comprised of compute and networking solutions that can scale to tens of thousands of GPU-accelerated servers interconnected to function as a single giant computer; this type of data center architecture and scale is needed for the development and deployment of modern AI applications.The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of the physical world. Its parallel processing capabilities, supported by thousands of computing cores, are essential for deep learning algorithms.