Explore the intricacies of NASA's embedded coding practices in this revealing video. Delve into the "Power of 10," NASA's rule set for crafting dependable software for space missions. Uncover the reasons behind NASA's avoidance of intricate control flow, insistence on fixed loop bounds, and exclusive use of stack memory. The video underscores the significance of concise functions, meticulous variable declaration, and thorough return value checks. Essential viewing for programmers keen on understanding how NASA upholds code safety for space exploration.
#video #programming
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how NASA writes space-proof code
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I've been told the worst thing that can happen to a developer is their code crashes in production? Well.... what happens if that production environment is outer space?
Safety…
I've been told the worst thing that can happen to a developer is their code crashes in production? Well.... what happens if that production environment is outer space?
Safety…
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Embedded Systems
📰 A company's new robot can change from four wheel drive to bipedal in seconds A company called Swiss-Mile has created an innovative robot that combines legs and wheels to create, what they hope, will be the most versatile last-mile delivery robot on the…
Zürich-based Swiss-Mile has enhanced the ANYmal quadruped robot with powered wheels for speed and efficiency, enabling it to handle curbs and stairs. The robot has been taught to stand up, facilitating more versatile movement and manipulation using its wheel-hand-leg-arms. Researchers at ETH Zurich's Robotic Systems Lab employed curiosity-driven learning, a form of reinforcement learning, to train the robot in tasks like opening doors and placing packages into boxes.
The robot's curiosity about specific elements, such as the door handle or package motion, helps it explore and innovate solutions independently. The use of sparse rewards in training results in diverse and reliable behaviors, allowing the robot to recover from real-world mistakes. While relying on visual code-based systems like AprilTags, Swiss-Mile aims to further develop the robot's capabilities, indicating potential practical applications for the ANYmal.
#news #robots #machine_learning
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Explore the nuances of firmware static analysis with CodeChecker! Delve into the familiar challenges of C programming, from undefined behavior to memory leaks. This article introduces CodeChecker, an open-source tool built on clang's static analyzer. Uncover the simplicity of integrating CodeChecker into firmware projects to catch bugs before they reach end-users. Navigate false positives with practical strategies like adding assertions and CodeChecker-specific comments. Join the conversation on static analysis tools in the comments and anticipate insights on running analysis in CI. Elevate your coding practices with CodeChecker, bolstering your code's resilience against potential vulnerabilities.
#articles #programming #software #tools
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Tesla has unveiled the Optimus Gen 2 humanoid robot, showcasing improved humanlike dexterity and mobility. The robot features 11 degrees of freedom in its hands with tactile sensors in each finger, a 2-DoF neck, in-house-designed actuators and sensors, and integrated electronics. The enhancements include a 30% increase in walking speed, force/torque sensing, articulated toe sections in its feet, and a 10 kg weight reduction for improved energy efficiency, cost, and safety.
The company plans to initially deploy the robot in its automotive and battery factories. However, amidst the positive news, Tesla is also recalling over 2 million vehicles due to concerns surrounding its Autopilot system. The National Highway Traffic Safety Administration (NHTSA) is investigating safety issues related to Autopilot, and critics argue that Tesla didn't adequately communicate the risks.
Despite the recall, Tesla CEO Elon Musk has released an impressive video of the Gen 2 Optimus robot, emphasizing its capabilities and addressing skepticism. Musk believes the Optimus business could eventually surpass the value of Tesla's car business and full self-driving technology.
#news #robots
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Stanford Doggo is a cost-effective, four-legged robot developed by Stanford students from the Extreme Mobility team. It is designed for traversing challenging terrain, performing acrobatic tricks, and encouraging an open-source community by providing comprehensive plans and code online.
Features of the robot:
With open-access plans and code, Stanford Doggo beckons tech enthusiasts and researchers to explore its intricacies, offering a hands-on opportunity to contribute to the ever-evolving landscape of robotic locomotion.
More information:
#projects #robots
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Andrej Karpathy, from OpenAI, developed Baby Llama as a weekend project to demonstrate the possibility of running the Llama 2 model on edge devices. The project, inspired by Georgi Gerganov's llama.cpp, involves training the Llama 2 model using PyTorch and then saving the weights in a binary file. Karpathy created a compact C file ('run.c') for loading and running the model with single-precision calculations, ensuring a low-memory footprint and independence from external libraries.
The model runs efficiently even on a single M1 laptop without GPUs, with performance enhancements achieved through various compilation flags for code optimization. A Twitter user successfully demonstrated Baby Llama running on a Samsung Galaxy Watch 4.
Karpathy's repository provides the pre-trained model and code, allowing anyone to experiment with Baby Llama on their devices. It's important to note that this project is experimental and not meant for production use, aiming to showcase the viability of running advanced models on low-powered devices with C, a language typically not associated with machine learning due to its GPU incompatibility.
#news #artificial_intelligence
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This project stands out in the realm of DIY camera technology. At its core, the camera integrates a Raspberry Pi Zero (with a preference for the Pi Zero 2) and the High-Quality (HQ) Camera module, coupled with a compact 1.5" Waveshare OLED display. Its unique features include live preview, zoom-crop panning for manual focus assistance, file viewing capabilities, and an integrated 10-axis IMU for potential horizon level overlay applications.
This creation is less about competing with high-end cameras like the Sony Alpha series and more about providing a platform for custom software development and experimentation in camera design. The estimated cost of the camera, considering major components and a 35mm lens, stands around $185.00.
More information:
#projects #camera #raspberry #python
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This article discusses three major technology trends expected to shape 2024:
#news #artificial_intelligence
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This small but mighty single board computer is powered by a high-performance quad-core processor and offers various connectivity options, including full-size HDMI 2.0 and gigabit Ethernet. In addition to that, the board includes a unique design featuring a carrier board and a replaceable LM3H CPU module containing the SoC, RAM, and eMMC flash.
Key Specifications:
Sipeed provides Debian and Android 12 images for the board, with SDKs available on GitHub. Mainline Linux support is expected in Q1 2024. Sipeed has begun pre-orders on Aliexpress, with prices ranging from $23.90 (2GB RAM, no eMMC flash) to $34.90 (4GB RAM and 32GB eMMC flash), and the LM3H module alone starting at $17.90. Shipping is expected to start on February 11.
#boards
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The pcb2blender tool revolutionizes the way KiCad projects are rendered in Blender. It streamlines the process of creating professional-looking product renders by allowing users to export their KiCad boards as .pcb3d files and then directly import them into Blender.
This innovation eliminates the tedious cleanup work usually involved, enabling users to focus on scene composition and lighting. Notably faster than previous methods, pcb2blender supports rendering work-in-progress boards or those undergoing last-minute revisions.
More information:
#libraries #tools #3d_modeling #design #electronics
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In an innovative exploration of AI's reach beyond high-end hardware, this video delves into the feasibility of deploying advanced language models on accessible technology like the Raspberry Pi 5. The presenter, a seasoned enthusiast in small-tech advancements, embarks on a journey to test a variety of language models including Orca, Fi, and the groundbreaking GPT-4.
With a focus on practicality, the video demonstrates how these models, typically associated with powerful computing resources, can operate on a device as compact and affordable as the Raspberry Pi 5. This approach not only democratizes access to cutting-edge AI but also opens up a realm of possibilities for tech enthusiasts and hobbyists.
The video highlights the Raspberry Pi's capacity to handle models with up to 1.7 trillion parameters, a feat that traditionally requires substantial computing power. The presenter's experiments with local, private AI deployments raise intriguing questions about the potential of small-scale, private AI systems.
#video #raspberry #artificial_intelligence
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I Ran Advanced LLMs on the Raspberry Pi 5!
Honestly, I'm shocked...
Step-by-step tutorial guide: https://buildwithparallel.com/products/run-advanced-llms-on-your-raspberry-pi
Product Links (some are affiliate links)
- Flirc Pi 5 Case 👉 https://amzn.to/3UbcOq6
- Flirc Pi 4 Case 👉 https…
Step-by-step tutorial guide: https://buildwithparallel.com/products/run-advanced-llms-on-your-raspberry-pi
Product Links (some are affiliate links)
- Flirc Pi 5 Case 👉 https://amzn.to/3UbcOq6
- Flirc Pi 4 Case 👉 https…
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