This article explains how to benchmark using the criterion crate and how to benchmark across different compiler settings, providing insights on performance effects and comparisons across CPUs. The range-set-blaze crate is used as an example to measure SIMD settings, optimization levels, and various input lengths.
Boosting data ingestion in the range-set-blaze Crate by 7x by delegating calculations to little crabs. Rule 7: Use Criterion benchmarking to pick an algorithm and discover that LANES should (almost) always be 32 or 64.
Dive into the world of artificial intelligence â build a deep reinforcement learning gym from scratch. Gain hands-on experience and develop your own gym to train an agent to solve a simple problem, setting the foundation for more complex environments and systems.
Amazon Comprehend offers pre-trained and custom APIs for natural-language processing. They have developed a pre-labeling tool that automatically annotates documents using existing tabular entity data, reducing the manual work needed to train accurate custom entity recognition models.
Amazon SageMaker Studio now offers a fully managed Code Editor based on Code-OSS, along with JupyterLab and RStudio, allowing ML developers to customize and scale their IDEs using flexible workspaces called Spaces. These Spaces provide persistent storage and runtime configurations, improving workflow efficiency and allowing for seamless integration of generative AI tools.
OpenAI's ChatGPT, a groundbreaking AI language model, sparked excitement with its impressive abilities, including excelling in exams and playing chess. However, skeptics argue that true intelligence should not be confused with memorization, leading to scientific studies exploring the distinction and making the case against AGI.
ICL, a multinational manufacturing and mining corporation, developed in-house capabilities using machine learning and computer vision to automatically monitor their mining equipment. With support from the AWS Prototyping program, they were able to build a framework on AWS using Amazon SageMaker to extract vision from 30 cameras, with the potential to scale to thousands.
Text-to-image generation is a rapidly growing field of AI, with Stable Diffusion allowing users to create high-quality images in seconds. The use of Retrieval Augmented Generation (RAG) enhances prompts for Stable Diffusion models, enabling users to create their own AI assistant for prompt generation.
Talent.com collaborates with AWS to develop a job recommendation engine using deep learning, processing 5 million daily records in less than 1 hour. The system includes feature engineering, deep learning model architecture design, hyperparameter optimization, and model evaluation, all run using Python.
The US Federal Trade Commission warns against QR code scams that can take control of smartphones, make fraudulent charges, or obtain personal information. Scammers are targeting QR codes on parking lot kiosks, leading to look-alike sites that funnel funds to fraudulent accounts.
Data projects often fail to deliver real-life impact due to macro-elements such as data availability, skillset, timeframe, organizational readiness, and political environment. The availability and accessibility of relevant data are fundamental, and if data is unattainable, the feasibility of the project should be reconsidered.
Getir, the ultrafast grocery delivery pioneer, has implemented an end-to-end workforce management system using Amazon Forecast and AWS Step Functions, resulting in a 70% reduction in modelling time and a 90% improvement in prediction accuracy. This comprehensive project calculates courier requirements and solves the shift assignment problem, optimizing shift schedules and minimizing missed orders.
NVIDIA celebrates milestone with 500 RTX games and applications, revolutionizing gaming graphics and performance. Ray tracing and DLSS technologies have transformed visual fidelity and boosted performance in titles like Cyberpunk 2077 and Minecraft RTX.
MLOps is essential for integrating machine learning models into existing systems, and Amazon SageMaker offers features like Pipelines and Model Registry to simplify the process. This article provides a step-by-step implementation for creating custom project templates that integrate with GitHub and GitHub Actions, allowing for efficient collaboration and deployment of ML models.
Mathew Schwartz, an assistant professor at the New Jersey Institute of Technology, is using NVIDIA Omniverse and OpenUSD to help designers address the challenge of accessibility in building design. Schwartz's team developed open-source code that generates a complex accessibility graph, providing feedback on human movement and energy expenditure. With Omniverse, designers can visualize the graph...