autonomousdevice.dev

#Autonomous Device | Development

#Smart Xhub | IoT | RFID |Tracking | Workflows | Safety

#ElaInnovation | Industrial beacons and sensors

#Axonius | Asset inventory

#NXP | Semiconductors

#NVIDIA | Self driving cars | MLPerf | Measuring time to train neural networks | Natural language processing | Speech recognition | Recommender systems | Biomedical image segmentatione | Object detection | Image classification | Reinforcement learning | NVIDIA benchmarking suite | MLPerf Training | MLPerf Inference | MLPerf HPC | NVIDIA Platform | Generative AI | Natural language processing

#Open Remote | Open source IoT platform

#Eca Group | Robotics | Autonomous Systems, Simulators, Industrial Equipment

#NDC | IoT

#Ericsson | Telecommunication

#Carbon Robotics | Autonomous LaserWeeder Robot | Deep Learning | Laser | Lidar Sensor | Nvidia | Cumming

#Kistler | Dynamic measurement technology for pressure, force, torque and acceleration applications

#BTS Bio Engineering | Motion analysis systems for medical practice

#Aivero | 3D machine vision based automation

#1ot | M2M and IoT

#Teksbotics | Autonomous driving solutions

#OndoSense | Radar sensor technology

#Realwear | Voice operated headset

#Texas Instruments | TI

#InertialSense | Precision and autonomous movement

#Movigo Robotics | Fleet Management

#Renu Robotics | Vegetation management

#Spm Instrument | Portable instruments

#Redshift | Autodesk | Digital Twins | Generative Design | Extended Reality

#Revibe Energy | Vibration analysis

#Desmasa | Autonomous Machines

#Norsat | Communication solutions

#Iridium | Satellite communications

#Onomondo | IoT Network

#IecTelecom | Satellite service operator

#Astrocast | Satellite IoT Tracking

#Metaverse | Virtual Reality | VR | Augmented Reality | AG | Virtual World | Web3 | Meta Platform | Digital Twins | Simulation | Autonomous Vehicles | Autonomous Systems | Robots | Artificial Intelligence | AI | Universal Scene Description | USD

#Ouster | High-resolution lidar sensors for long, mid, and short range applications | Smart infrastructure | Autonomous machines | Robotics applications | Digital lidar architecture | Digital device powered by a fully custom silicon CMOS chip

#JAKA Robotics | Graphic Programming | Set and adjust positions and tasks with ease | Drag Teaching | Moving the cobot to any position, and it will memorize it instantly | JAKA APP | Teaching the robot | Remote Monitoring | Monitor robot tasks and set alerts

#Structural color | Chameleon like, color shifting materials | Stretching a piece of film to reveal a hidden message | Checking an arm band color to gauge muscle mass | Sporting a swimsuit that changes hue as one does laps | Elastic materials that when stretched can transform their color | Printed films revealing the imprint of objects | Structural color arising as a consequence of a material microscopic structure | Robotic skin that has a human like sense of touch | Devices for things like virtual augmented reality or medical training | University of Cambridge | The Gillian Reny Stepping Strong Center for Trauma Innovation at the Brigham | Women Hospital | National Science Foundation | MIT Deshpande Center for Technological Innovation | Samsung | MIT ME MathWorks seed fund | MIT

#VARTA | Application Specific Batteries (ASB) | Energy Solutions

#Harmonic Drive | Precision servo actuators | Gearheads | Gear component sets

#Robotics Engineering | Intelligent Sensing for Object Recognition, Manipulation and Control | Design, Development and Simulation Tools for Robotics Development | Developing Intelligent Robots - Machine Learning on Edge, Cloud and Hybrid Architectures | Advanced Motion Control Solutions for Robotics Systems | Intelligent Vision and Sensing Solutions for Autonomous Mapping and Navigation | Motion Control for Healthcare Robotics Applications: Functional Requirements, Critical Capabilities

#General Atomics | Air to Air Laser Communication System | Crosslinks from aircraft to other platforms such as unmanned aircraft, maritime vessels, and space systems

#MIT | White graphene nanotubes | Stronger, heat resistant composites | Membranes for renewable energy | Hollow aligned fibers, or nanotubes, made from hexagonal boron nitride | Hexagonal boron nitride ( hBN) | Fabricating aligned boron nitride nanotubes in bulk | hBN is transparent and electrically insulating | hBN to electrically insulate sensors within electronic devices | Blue energy, electricity produced from the ionic filtering of salt water into fresh water | Nanotube engineering | Hypersonic and space applications

#SatelIoT | IoT connectivity over standard 5G NB-IoT

#Jetson AGX Orin Developer Kit | NVIDIA | 275 Trillion Operations per Second (TOPS) | Multiple concurrent AI inference pipelines | High speed interface support for multiple sensors

#NATO | Innovation Fund | Defence Innovation Accelerator for the North Atlantic (DIANA) | Dual use emerging technologies of priority to NATO | Artificial intelligence | Quantum enabled technologies | Autonomy | Biotechnology |Novel materials | Energy | Propulsion | Space

#Optimax Systems | Robot polishing platform | Optics prototypes | PickNik | Robot Operating System (ROS) | ABB robot arm | ROS 2 Control library | ABB StateMachine | ABB

#ROS | Robot Operating System | Open source software development kit for robotics applications | Standard software platform to robotic application developers | Research | Prototyping | Deployment | Production

#Intel | Kapoho Point Board | Four Loihi 2 chips on its top side | Four on its underside | Up to a million neurons | Up to a billion synapses | Up to 8 million variables | Up to 1000× better energy efficiency than a state of the art CPU solver | Stackable up to eight boards | Expansion port on the board | Four boards getting up to 32 million neurons | Drones | Robotics | Gesture recognition | Scene understanding | Smell identification | Solving optimization problems | Research

#Intel | Neuromorphic computing | Biological neural computation | New algorithmic approaches | Emulating human brain interactions | Spiking neural networks (SNNs) | Simulating natural learning | Dynamically remapping neural networks | Making decisions in response to learned patterns over time | Powering autonomous AI solutions | Supporting energy efficiency and continuous learning | Sensing | Robotics | Healthcare | Large scale AI applications

#K.U.M. | ISOPOD | Autonomously recording ocean seismic data

#Advanced Navigation | Inertial measurement unit (IMU) | Heading reference system (AHRS) | Acoustic navigation | AI-based acoustic processing techniques | Subsea transponder | Sidney, Australia

#BrainChip | Licenses AI accelerator hardware designs combined with state-of-the-art development tools and advanced neural network models | Bringing on device intelligence to any chip design | Processor IP uses sparsity to focus on the most important data, inherently avoiding unnecessary computation and saving energy at every step | State-space model architecture tracks events over time instead of sampling at fixed intervals, skipping periods of no change to save energy and memory | Edge AI audio processing | Enablinging real-time video and image processing directly on-device | Processing data from sensors like accelerometers, gyroscopes, microphones, radar, and environmental monitors directly on-device | Continuous health tracking that fits Into small wearables | In cabin sensor-based occupant detection system | No unending cloud fees | Support real-time streaming data | Keeps working, even without a network connection | Data stays on device, not in cloud | No transmissionsvmeans less risk of interception | Akida Development Environment (MetaTF) machine learning framework | Processor IP simulator | Python API for neural networks | Conversion Tool (cnn2snn) to convert models to a binary format for model execution on an Akida platform | PCIe Development Board featuring AKD1000 neuromorphic processor in standard PCIe form factor | Akida AKD1000 card features built in capabilities to execute networks without host CPU | BrainChip and VVDN created Akida Edge AI Box for applications such as video analytics, face recognition, and object detection | Event-based neural processor | Models include audio denoising, automatic speech recognition, and language models

#Niobium Canada | Niobium

#IDS | Industrial image processing | 3D cameras | Digital twins can distinguish color | Higher reproducible Z-accuracy | Stereo cameras: 240 mm, 455 mm | RGB sensor | Distinguishing colored objects | Improved pattern contrast on objects at long distances | Z accuracy: 0.1 mm at 1 m object distance | SDK | AI based image processing web service | AI based image analysis

#Navy Research Laboratory (NRL) | Laboratory for Autonomous Systems Research (LASR) | Prototyping High Bay | Littoral High Bay | Desert High Bay | Tropical High Bay

#Flyability | Drones for industrial inspection and analysis | Confined space inspection | Collision and crash resistant inspection drone | 3D mapping | Volumetric measurement | Inspections of cargo ships, bridges, ports, steel mills cement factories, liquid gas tanks, nuclear facilities, city wide underground sewage systems | Ouster lidar

#HEBI Robotics | Robot development platform | Smart robotic actuation hardware and building blocks | Streamlininh the process of developing robots | Space-rated hardware deployed for missions in space | NASA: SBIR

#Boston Dynamics | Ultrasonic inspections of rotating equipment with Fluke SV600 | Early detection of bearing failures before they lead to costly breakdowns | Operators can capture critical data without the need for additional inline sensors or manual inspections | Leica BLK ARC payload | Autonomous routines | Repeatable laser scans | Precise 3D data for tasks like factory design, equipment installation, and change management | Spot can identify and avoid obstacles requiring additional caution in dynamic environments, including carts, wires, and ladders | Spot Hardware Updates | Tablet Controller Pro | Ergonomic joysticks, longer battery life, and HDMI pass-through | Spot robit operates in temperatures up to 55°C | Core I/O antenna upgrade enhances range and reliability | AI Institute | Artificial intelligence (AI) | Robotics | Intelligent machines | Cognitive AI | Athletic AI | Organic hardware design

#Google DeepMind Technologies Limited | Creating advanced AI models and applications | Artificial intelligence systems ALOHA Unleashed and DemoStart | Helping robots perform complex tasks that require dexterous movement | Two-armed manipulation tasks | Simulations to improve real-world performance on multi-fingered robotic hand | Helping robots learn from human demonstrations | Translating images to action | High level of dexterity in bi-arm manipulation | Robot has two hands that can be teleoperated for training and data-collection | Allowing robots to learn how to perform new tasks with fewer demonstrations | Collectung demonstration data by remotely operating robot behavior | Applying diffusion method | Predicting robot actions from random noise | Helpung robot learn from data | Collaborating with DemoStart | DemoStart is helping new robots acquire dexterous behaviors in simulation | Google collaborating with Shadow Robot

#Movu Robotics | Robotics | Automated pallet storage solution | Accessible cold storage automation | Temperature-controlled food and pharmaceutical industry | Space optimisation in storage | Streamlined materials handling process | Energy efficiency for cold storage | Robotics for low temperatures with icy and slippery surfaces | Automated Storage and Retrieval System (AS/RS) | Automating picking | Fleet management software

#Neptune Labs | neptune.ai | Tracking foundation model training | Model training | Reproducing experiments | Rolling back to the last working stage of model | Transferring models across domains and teams | Monitoring parallel training jobs | Tracking jobs operating on different compute clusters | Rapidly identifying and resolving model training issues | Workflow set up to handle the most common model training scenarios | Tool to organize deep learning experiments

#SIMa.ai | Platform for edge AI | Enabling edge-ML application-pipeline acceleration on single chip | MLSoC accelerates deep learning workloads | ModelSDK forvmodel loading, quantization and compilation in Python | Python APIs and VSCode remote execution for rapid application development and prototyping | GStreamer plugins enabling high-performance video processing pipelines | ML Pipeline Package for application deployment

#Linux Foundation | LF AI & Data | Fostering open source innovation in artificial intelligence and data | Open Platform for Enterprise AI (OPEA) | Creating flexible, scalable Generative AI systems | Promoting sustainable ecosystem for open source AI solutions | Simplifying the deployment of generative AI (GenAI) systems | Standardization of Retrieval-Augmented Generation (RAG) | Supporting Linux development and open-source software projects | Linux kernel | Linus Torvalds

#Tampere University | Pneumatic touchpad | Soft touchpad sensing force, area and location of contact without electricity | Device utilises pneumatic channels | Can be used in environments such as MRI machines | Soft robots | Rehabilitation aids | Touchpad does not need electricity | It uses pneumatic channels embedded in the device for detection | Made entirely of soft silicone | 32 channels that adapt to touch | Precise enough to recognise handwritten letters | Recognizes multiple simultaneous touches | Ideal for use in devices such as MRI machines | If cancer tumours are found during MRI scan, pneumatic robot can take biopsy while patient is being scanned | Pneumatic device can be used in strong radiation or conditions where even small spark of electricity would cause serious hazard

#Canon | Micro stepping motors ranging from Φ 5 mm to 6 mm | DC micro motors with gears, pinions, encoders, and lead wires already attached | Brushless servomotors | Ultra sonic piezo motor | Frameless motors | Optoelectronic Components | 3D Machine Vision System

#ZAPI GROUP | Charging solutions | Battery chargers under Delta-Q and ZIVAN product brands

#Allen Institute for Artifical Intelligence | AI for the Environment | Robot planning precise action points to perform tasks accurately and reliably | Vision Language Model (VLM) controlling robot behavior | Introducing automatic synthetic data generation pipeline | Instruction-tuning VLM to robotic domains and needs | Predicting image keypoint affordances given language instructions | RGB image rendered from procedurally generated 3D scene | Computing spatial relations from camera perspective | Generating affordances by sampling points within object masks and object-surface intersections | Instruction-point pairs fine-tune language model | RoboPoint predicts 2D action points from image and instruction, which are projected into 3D using depth map | Robot navigates to these 3D targets with motion planner | Combining object and space reference data with VQA and object detection data | Leveraging spatial reasoning, object detection, and affordance prediction from diverse sources | Enabling to generalize combinatorially.| Synthetic dataset used to teach RoboPoint relational object reference and free space reference | Red and ground boxes as visual prompts to indicate reference objects | Cyan dots as visualized ground truth | NVIDIA | | Universidad Catolica San Pablo | University of Washington

#HuggingFace | SmolLM2 | Language models suitable for deployment on smartphones

#SIKO | Magnetic sensor | Max. resolution 0.4 μm | Works with MB200/1 magnetic tape, MR200 magnetic ring, MBR200 magnetic tape ring | Reading distance ≤1 mm | IP67 protection class | Optionally with reference point R or flexible reference marks FR | Interface LD | Interface RS485 with Panasonic or Yaskawa protocol

#Astera Labs | UALink | High-speed interconnect standard | Scalable connectivity for AI infrastructure | UALink specification for GPU-to-GPU communication | Active Electrical Cables to enable GPU clusters and low-latency memory fabrics applications within and across data center racks | Smart Fabric Switch

#Weebit Nano | Resistive RAM (ReRAM) technology | onsemi signed licensing deal | Treo platform to provide embedded non-volatile memory | ReRAM integration into Bipolar CMOS DMOS (BCD) process | Potential alternative to flash memory | Demand for faster, more efficient, and scalable memory solutions increasing | Lower power consumption | Less vulnerable to common hacking tactics | ReRAM can be integrated easily into chip designs without interfering with power analog components

#Flow Robitics | Pipetting robot | Designed to simplify and automate repetitive manual pipetting tasks

#VORAGO | Radiation hardened and radiation tolerant microcontrollers and microprocessors | High-volume manufacturing to harden commercially designed semiconductor component | Empowers mission success | Radiation-hardened ICs that excel in extreme environments | ARM | Texas Instruments | Brainchip | Custom hardware and firmware solutions tailored to withstand extreme environments | Ensuring that mission-critical components remain resilient | Custom solutions, armed with space-grade electronics and an ARM Cortex microcontrollers | International Space Station: dies measuring the effects of protons and cosmic rays | Satelites: devices utilized in Department of Defense Space Test Program (STP) missions | CubeSats: ARM microvontroller | Semiconductor components and solutions for extreme temperature environments up to +200°C

#Robotics & AI Institute | Collaborates with Boston Dynamics | Developed jointly Reinforcement Learning Researcher Kit for Spot quadruped robot | Developing sim-to-real for mobility | Transferring simulation results to real robotic hardware | Bridging sim-to-reality gap | Training policies generating a variety of agile behavior on physical hardware | Trying to achieve novel, robust, and practical locomotion behavior | Improving whole body loco-manipulation | Developing robot capability to manipulate objects and fixtures, such as doors and levers, in conjunction with locomotion significantly enhancing its utility | Exploring new policies to improve robustness in scenarios | Exploring full-body contact strategies | Exploring high-performance, whole-body locomotion and tasks that require full-body contact strategies, such as dynamic running and full-body manipulation of heavy objects, necessitating close coordination between arms and legs | Aiming to utilize reinforcement learning to generate behavior during complex contact events without imposing strict requirements | Develop technology that enables future generations of intelligent machines | Streamlining processes for robots to achieve new skills | Developing perception, situational understanding, reasoning, cognitive functions underpinning robot abilities and combining them with advances in their physical capabilities | Conducting research in four core areas: cognitive AI, athletic AI, organic hardware design, and ethics related to robotics

#UC Berkeley, CA, USA | Professor Trevor Darrell | Advancing machine intelligence | Methods for training vision models | Enabling robots to determine appropriate actions in novel situations | Approaches to make VLMs smaller and more efficient while retaining accuracy | How LLMs can be used as visual reasoning coordinators, overseeing the use of multiple task-specific models | Utilizing visual intelligence at home while preserving privacy | Focused on advancements in object detection, semantic segmentation and feature extraction techniques | Researched advanced unsupervised learning techniques and adaptive models | Researched cross-modal methods that integrate various data types | Advised SafelyYou, Nexar, SuperAnnotate. Pinterest, Tyzx, IQ Engines, Koozoo, BotSquare/Flutter, MetaMind, Trendage, Center Stage, KiwiBot, WaveOne, DeepScale, Grabango | Co-founder and President of Prompt AI

#Trossen Robotics | Pi Zero (π0) | Open-source vision-language-action model | Designed for general robotic control | Zero-shot learning | Dexterous manipulation | Aloha Kit | Single policy capable of controlling multiple types of robots without retraining | Generalist robotic learning | Pi Zero was trained on diverse robots | Pi Zero was transferred seamlessly to bimanual Aloha platform | Pi Zero executed actions in a zero-shot setting without additional fine-tuning | Pi Zero run on standard computational resources | Hardware: 12th Gen Intel(R) Core(TM) i9-12950HX | NVIDIA RTX A4500 16G | RAM 64G | OS: Ubuntu 22.04 | Dependencies: PyTorch, CUDA, Docker | PaliGemma | Pre-trained Vision-Language Model (VLM) | PaliGemma allows Pi Zero to understand scenes and follow natural language instructions | Image Encoding: Vision Transformer (ViT) to process robot camera feeds | Text Encoding: Converts natural language commands into numerical representation | Fusion: Aligns image features and text embeddings, helping model determine which objects are relevant to task | Pi Zero learns smooth motion trajectories using Flow Matching | Pi Zero learns a velocity field to model how actions should evolve over time | Pi Zero generates entire sequences of movement | Pi Zero predicts multiple future actions in one go | Pi Zero executes actions in chunks | ROS Robot Arms | Aloha Solo package | Intel RealSense cameras | Compact tripod mount | Tripod overhead camera | Ubuntu 22.04 LTS

#Qt Group | Digital solutions for industrial vehicles | High-Performance Graphics for Industrial Vehicles Digital Twins | High quality and safety standards in heavy machinery environments | Import Figma Variables into Qt Design Studio for faster integration of design systems and theming into UI application via property binding | QtQuick3D | HDR environment for extra photorealism

#Caterpillar | Cat 775 | Off-highway truck | MineStar Command for hauling | 360-degree surround cameras with object detection | Cat Detect radar system | Frame design reducing empty weight delivering | Redesigned suspension for lower centre of gravity | Electronic powertrain controls | Automatically detecting hazards within critical areas around truck | Ability to access and analyse accurate real-time data from truck | Access to the latest software updates | Truck software updates scheduled and executed at a time that does not interrupt the production schedule | Remote Troubleshoot enabling dealer to perform diagnostics remotely while truck is still in operation

#Hugging Face | SmolVLM | Vision Language Model (VLMs) | Natural language processing (NLP) | Transformers Library | Model and Dataset Hub | Spaces | Community and Open Science | Rapid prototyping | Enterprise Solutions | Funding: Amazon, Google, and Nvidia | Acquired: Gradio (for ML app development), Pollen Robotics (for open-source AI robotics) | BLOOM: large multilingual language model | Partnered with Meta and UNESCO for global language translation tools

#MemryX | Edge accelerated AI System software | SDK APIs for efficient AI processing | Hardware | Compile AI model(s) making executable file | PCIe or USB interface | x86, ARM, RISC-V processors | Windows, Linux operating systems

#LangChain | Platform helps teams deploy, scale, and manage AI agents | Native GitHub integration | Debugging and iterating faster visualizing agent trajectories and experimenting on the fly with LangGraph Studio, the agent IDE | Managing agents across teams | Generative AI ecosystem | Comparison View | Hotkeys in Annotation Queue | Tools to evaluate response quality: correctness | Pinecone | Specialized agents work better than bloated generalists | Shift toward multi-agent ecosystems designed for specific workflows

#NVidia | Dexterous robot development | Manipulating objects with precision, adaptability, and efficiency | Fine motor control, coordination, ability to handle a wide range of tasks, often in unstructured environments | Key aspects of robot dexterity include grip, manipulation, tactile sensitivity, agility, and coordination | Robot dexterity development for manufacturing, healthcare, logistics | Dexterity enabling automation in tasks that traditionally require human-like precision

#e-con Systems | Camera solutions for NVIDIA platforms | Full HD Global Shutter Camera for Jetson AGX Orin | Jetson AGX Orin: 64GB module, 275 TOPS with power configurable 15W and 60W | Multiple 4k ultra-lowlight camera for NVIDIA Jetson AGX Orin | Global shutter | Rolling shutter | Autofocus and fixed focus | High resolution and frame rate | High dynamic range | High sensitivity in both visible and NIR regions | Superior color reproduction | MIPI and GMSL2 interfaces | Camera SDK configured to support Isaac SDK | Multi-camera support | NVIDIA Isaac GEMs ROS: GPU-accelerated packages for ROS2 application | Isaac ROS GEMs help to assess camera position with regard to its starting point | Isaac ROS GEMs empower robotic applications to maneuver and navigate through complicated environments | Installing ROS 2 requires Ubuntu 20.04 | Board cameras | USB 3.0 cameras | Autonomous mobile robots, autonomous shopping

#TSMC | AI hardware | Leading-edge logic, memory, and packaging technologies | Research pipeline for technology to enable leading-edge AI devices, circuits, and systems for decades to come | Near- and in-memory computing | Embedded non-volatile memory technologies | 3D integration | Error-resilient computing | AI hardware research

#Automate | Robotics and automation event | AI and robotics | Automation trends

#British Encoder | Encoders | Incremental encoders | Absolute encoders | Linear encoders

#Untether AI | Accelerating AI inference | PCI-Express form factor and power envelope | Over 2 PetaOps per card | Accelerator card | AI chip | Intel backef | Toronto, Canada

#OLogic | Robotics | Pumpkin Pi i350 EVK | Edge AI platform | Designed for mainstream AI + IoT applications | Vision and voice edge processing | Facial, object, gesture, motion recognition | LPR, voice activation and speed recognition | Sound isolation, bio-tech and biometric measurements

#GAM | Robotic and servo gear | GPL Robotic Planetary | GCL Cycloidal | GSL Strain Wave | Precision Rack & Pinion | Linear Mount Products for Cartesian Robots

#Anybotics | Manipulation payload | Autonomous maintenance tasks | Powerful and torque-controlled arm | Flexible sensor integration | Open software architecture | Access to low-level joint control for developers | System equipped with NVIDIA Jetson GPU | Onboard execution of AI models and real-time perception algorithms | Integrated platform enables advanced mobile manipulation, such as agile tool use, object handling, and real-time interaction in unstructured environments | Human–robot collaboration | Heavy payload handling | Complex tasks | Intelligent, autonomous legged robotics | Legged robotics research package | Collaboration with Duatic, an ETH Zurich spin-off | Workforce App | Operate ANYmal robot from device | Set up and review robot missions | Industrial Inspection

#Duatic | Rugged, weatherproof robotic arm | Actuator architecture | Quasi-direct, water-resistant, actively-cooled drive modules with integrated electronics | Maximum Payload: 12 kg | Continuous Payload: 6 kg | Reachability: 1.0 m | Total Weight: 9.2 kg | End Effector Speed: 10 m/s | Pose Repeatability:< 1 mm | Degrees of Freedom: 6 | Power Input: 48 V | Protection: IP66 | Joint Torque Accuracy (all): ± 0.5 Nm

#Alliance for OpenUSD (AOUSD) | Promoting interoperability of 3D content through OpenUSD (Universal Scene Description) | Providing written specification for OpenUSD core functionality | Coordinated development of new OpenUSD functionality | Providing repository to house reference implementations | Technology, platform, and ecosystem built to empower 3D creativity and visualization at cinematic scales | Framework and ecosystem for describing, composing, simulating, and collaboratively navigating and constructing 3D scenes | Created by Pixar Animation Studios, OpenUSD is being embraced by industries beyond the film industry, including architecture, engineering, construction, automotive, and manufacturing

#Weebitnano | AI inference is shifting from cloud to edge devices like phones and cars | Weebit ReRAM shaping up as memory tech that could quietly power billions of them | Artificial intelligence noot just living in cloud, it lives at edge | AI traiking happens in massive data centres, where models learn from huge datasets | AI inference happens on edge devices like smartphones, smartwatches, autonomous cars, drones, factory sensors, and wearables – right where action is | Shift to edge happening because latency, power, privacy, and bandwidth all matter | You can not afford 300-mis delay when your autonomous car needs to spot pedestrian | Edge inference is juggernaut in motion | Flash memory can not scale below 28nm when embedded | Most AI applications already require smaller geometries | Weebit Nano (ASX:WBT) Resistive RAM (ReRAM) technology comes into picture | ReRAM is non-volatile memory (NVM) that stores data faster, uses less power and offers stronger security than Flash | ReRAM can scale to the most advanced semiconductor manufacturing processes | NVM memory retains data even when power is switched off | ReRAM is less vulnerable to tampering, better suited for storing AI model weights, and easier to embed right onto the same chip as processor | Gesture recognition system developed with EMASS | Weights for detection model are stored in ReRAM for processor | South Korea DB HiTek | US semiconductor company onsemi