tinyML Trailblazers - Success Stories in TinyML with Thierry Moreau
Explore tinyML success stories with Thierry Moreau, discussing OctoML's journey, Apache TVM, deployment challenges, and the future of edge AI in an interactive conversation.
1 kB and Not a Bit More - The Ideal Weight for a TinyML Model
Explore automated creation of ultra-compact ML models for tiny smart devices, enabling efficient embedding in memory-constrained hardware without data science expertise.
Streamline Deep Learning for Video Analytics with DeepStream SDK 2.0
Explore AI-based video analytics using DeepStream SDK 2.0 for Tesla, transforming video into insights for smart cities with a modular plugin architecture and scalable framework for multi-stream processing and application development.
Accelerate ML Development With Cloud-Based Arm Cortex-M Models
Explore cloud-based Arm Cortex-M models for accelerated ML development, featuring Virtual Hardware integration, Python-scriptable peripherals, and TensorFlow optimizations.
Learning Robust Policies for Self-Driving
Explore robust policies for self-driving vehicles, covering TransFuser for sensor fusion, PlanT for learned planning, and KING for identifying critical scenarios in autonomous driving.
OpenGL and CUDA-Based Tessellation
Explore advanced tessellation techniques using CUDA to overcome OpenGL limitations, enabling higher-order surfaces, custom UV coordinates, and trimming curves for improved visual quality in graphics rendering.
tinyMLPerf: Benchmarking Ultra-low Power Machine Learning Systems
Explore benchmarking for ultra-low power ML systems, focusing on tinyMLPerf's methodology, tasks, and ecosystem impact. Learn about quantization and community-driven efforts in this emerging field.
Build Your Own AI Assistant - Creating a Voice-Activated System
Learn to create your own AI assistant using Python and Raspberry Pi. Covers architecture, hardware/software setup, and implementation of key features like speech recognition and natural language processing.
ZigZag - An Architecture-Mapping Design Space Exploration Framework for Deep Learning Accelerator
Explore ZigZag, a framework for optimizing deep learning accelerator design through architecture-mapping space exploration, enhancing efficiency in embedded systems.
TinyML Talks - Building TinyML Applications Using Rune
Explore containerization for TinyML apps using Rune and Hammer. Learn to build efficient, portable solutions for healthcare, field ops, and telecom, with a focus on cough detection in public spaces.
How to Create an Arduino Library - Easy
Learn to create Arduino libraries to organize code, simplify sketches, and improve development efficiency. Covers library creation process, class implementation, and practical testing.
Understanding an Arduino Library - Arduino Library Series
Explore Arduino library structure, class creation, functions, and practical implementation in this comprehensive tutorial.
Home Assistant - How to Install HACS
Learn to install and use HACS (Home Assistant Community Store) for easy access to community-developed integrations and frontend features. Includes GitHub setup and step-by-step installation guide.
De-risking Embedded Machine Learning Projects Using Novel Technologies
Explore novel technologies for successful embedded machine learning projects, addressing challenges and ensuring customer success through innovative design and engineering philosophies.
Automated Software Vulnerability Detection with Deep Learning for Natural Language Processing
Explore deep learning techniques for automated software vulnerability detection using natural language processing, covering data sets, pretraining, architecture, and results.
How to Install XFormers and Run Stable Diffusion Faster on 4GB RAM
Optimize Stable Diffusion performance with XFormers: Learn to install and implement this efficiency-boosting library, achieving 1.5x faster processing on 4GB RAM systems.
How to Run Stable Diffusion on Your Computer Without Writing a Single Line of Code - Using Krita
Learn to run stable diffusion in Krita without coding. Step-by-step guide covers installation, setup, and basic image generation using this powerful AI art tool on your local machine.
GitOps Deployments from VS Code With Little to No Kubernetes Knowledge
Learn to deploy from VS Code using GitOps and Kubernetes without extensive expertise. Discover how to set up safe, reliable, and automated systems for efficient app development and deployment.
Jaeger - Present and Future in Distributed Tracing
Explore Jaeger's distributed tracing capabilities, its integration with OpenTelemetry, and new features like the monitoring tab. Learn about deployment strategies and how to contribute to this open-source project.
Automate Your SLO Validation with Prometheus and Flagger
Explore automated SLO validation using Prometheus and Flagger for Kubernetes applications. Learn how to leverage progressive delivery, canary deployments, and KEDA ScaledObjects for confident code releases.
Building a Runbook Automation System for Prometheus and Kubernetes
Learn to automate Kubernetes and Prometheus alerts with Robusta.dev. Discover how to write YAML for self-investigating alerts, enhancing system reliability and reducing manual interventions.