zeroshotlearning.ai

#Zero Shot Learning AI | Artificial Intelligence powered Zero Shot Learning

#Anyverse | Synthetic data software platform | Hyperspectral render emgine | Sensor simulation | Scene generation

#Solomon | SolVision | AI Visual Inspection | Deep Learning Software

#Viso | Viso Suite | No code application development platform | Computer vision

#SEA.AI App | Detecting floating objects early | Using thermal and optical cameras to catch unsignalled craft, floating obstacles, containers, buoys, inflatables, kayaks and persons over board

#NVIDIA | GPU Deep Learning | GPU acting as the brain of computing | Robots and self driving cars can perceive and unferstand the world | Accelerating the entire AI workflow | AI agents designed to reason, plan, and act | Conversational AI: multilingual speech and translation AI | Vision AI: multimodal real-time insights | AI factories: manufacturing intelligence at scale | Purpose-built AI factories | AI life-cycle | Humanoid robotics research and development platform | Machine Learning | Neural networks | Natural language processing | Speech recognition | Recommender systems | Biomedical image segmentation | Object detection | Image classification | Reinforcement learning

#IEEEE | Recurrent Vision Transformers for Object Detection with Event Cameras

#Aalto University | Intelligent Robotics | Robotic Perception | Robot to robot interaction | Robotic grasping, knowing the object shape

#Advanced Navigation | AI-based marine navigation systems | AI-Based underwater navigation solutions and robotics technology | Hydrography | Underwater acoustic positioning solutions | Autonomous Underwater Vehicle (AUV) | Inertial navigation systems (INS) | Sidney, Australia

#Glidance | Walking companion | Passive kinetic guidance through pole | Handle connected to small mobile platform | Wheels that steer and break | Identifies user location | Detects both static and dynamic obstacles | Steers user | Applyis and releases brakes

#Sanctuary AI | Humanoid robot | Touch and grasping | Coordination between touch sensors and vision systems | Visual servoing | Real-time simulation of the grasping process | Mapping between visual and haptic data

#OndoSense | Radar distance sensor | Sensor software: integrated into control system or used for independent quality monitoring | Object detection | Distance measurement | Position control | Agriculture: reliable height control of the field sprayer | Mining industry | Transport & Logistics | Shipping & Offshore | Mechanical and plant engineering | Metal and steel industry | Energy sector | Harsh industrial environments | Dust & smoke: no influence | Rain & snow: no influence | Radar frequency: 122GHz | Opening angle: ±3° | Measuring range: 0.3 – 40 m | Measuring rate: up to 100Hz | Output rate: up to 10 ms / 100 Hz | Measurement accuracy; up to ±1mm | Measurement precision: ±1mm | Communication protocol: RS485; Profinet, other interfaces via gateway | Switching output: 3x push-pull (PNP/NPN) | Analogue output: Current interface (4 – 20 mA) | Protection class: IP67

#Anybotics | Workforce App | Operate ANYmal robot from device | Set up and review robot missions | Industrial Inspection

#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

#LookOut | AI vision system | Synthesized data from charts, AIS, computer vision, and cloud fusing it into one 3D augmented reality view | Connects to existing boat display | Mountable camera system to the top of any boat | Lookout App for laptop, phone or tablet | Infrared vision | Night vision sensor | Spotting small vessels, floating debris, buoys, people in water | Blind spot detection | Backup camera | Temperature breaks, bird cluster locations, underwater structures for anglers | Camera streaming over WiFi to phones and tablets on the boat | Over-the-air (OTA) updates | Marine-grade water-proof enclosure | Integrated with satellite compass | National Marine Electronics Association (NMEA) communication standard interface | Multifunction Display (MFD) | Multi-core CPU driving augmented reality compute stack | ClearCloud service | NVIDIA RTX GPU for real-time computer vision | DockWa app

#SiLC | Machine Vision solutions with FMCW LiDAR vision | FMCW at the 1550nm wavelength | Eyeonic Vision Sensor platform | Detecting vehicles and various obstacles from long distances | Honda Xcelerator Ventures | Honda Marine

#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

#National Technical University of Athens | MariNeXt deep-learning framework detecting and identifying marine pollution | Sentinel-2 imagery | Detecting marine debris and oil spills on sea surface | Automated data collection and analysis across large spatial and temporal scales | Deep learning framework | Data augmentation techniques | Multi-scale convolutional attention network | Marine Debris and Oil Spill (MADOS) dataset | cuDNN-accelerated PyTorch framework | NVIDIA RTX A5000 GPUs | NVIDIA Academic Hardware Grant Program | AI framework produced promising predictive maps | Shortcomings: unbalanced dataset, marine water and oil spills are abundant, foam and natural organic material are less represented

#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

#Genetec | Security Center Platform | Ouster Gemini integrated | Fusing lidar and video surveillance into a single interface | Unifying customer data from lidar, cameras and radar | Physical intrusion detection in real-time | Using 3D data to power automated detection, classification, tracking, and monitoring | Measuring the distance, trajectory or speed of people or vehicles | Quickly identifying and responding to real threats with confidence | Reducing false alarms

#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

#Allen Institute for Artifical Intelligence | 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

#Intergovernmental Negotiating Committee (INC-5) | Developing international legally binding instrument on plastic pollution | Raising awareness about the serious impacts of plastic pollution on both humans and nature | Global bans and phase-outs of the most harmful and problematic plastic products and chemicals | Global product design requirements to ensure all plastic produced is safe to reuse and recycle as part of global non-toxic circular economy

#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

#Cyclopharm | Nuclear medicine device | Patient breathing superheated radioactive, gas-like substance | Better lung imaging.| Detected pulmonary embolisms (blood clots) | Visualization of pulmonary ventilation | Chronic obstructive pulmonary disease (COPD) | Asthma | Long Covid.| Dry-carbon nano-particles irradiated with isotope technetium-99 | Particles are 150 nano-metres | Heating carbon crucible to 2,700 degrees Celsius | Only three to four breaths required | Gas works as imaging agent | Computed tomography (CT) camera | Nanoparticles have six-hour radioactive life | Technegas images fine alveoli, where oxygen and blood mix | Technegas suitable to pregnant, to those having poor kidney function or who are allergic to imaging agents | Device is fully reimbursed, stand-alone | Technegas generator

#JCB | Artificial intelligence designed to drastically reduce the risk of harm and injury on construction sites | Four cameras | Three AI cameras (two side mounted and one rear-facing) | Forward-facing standard camera | Object detection | Factory-fit solution on JCB loadall telescopic handlers

#Hexagon | AEON humanoid | Dexterous hands | Multimodal sensor suite | Mission control system | Top speed: 2.4m/s | Weight: 60kg | Height: 165cm | Battery: Auto-swap | Payload: 15 kg short-term, 8 kg constant carry | Degrees of freedom: 34

#BrainChip | Akida Pico ultra-low power AI acceleration co-processor | Enabling energy-efficient, use case-specific AI for applications like voice wake detection, wearables, and IoT devices | Edge LLM | State-spaced models for efficiently computing Large Language Models | Temporal Enabled Neural Networks (TENNs) | Eye tracking with edge devIces | Retrieval-Augmented Generation (RAG) for smarter, real-time AI applications | Neural network models for edge AI devices operating in small form factors, power, and cost | Akida Edge AI box for developers to create new edge AI use cases | Akida M.2 card providing turn-key design integration for the AI acceleration

#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

#Thinking Machines Lab | thinkingmachines.ai | Building artificial intelligence models and products | Competing on high end of large language models | Human-AI collaboration | Building AI that can adapt to full spectrum of human expertise | Multimodal systems that work with people collaboratively | AI models that can work across text, audio, video | AI models designed to excel in science and programming | Publishing technical blog posts, papers, program code | Mira Murati: CEO | John Schulman: Chief Scientist | Barret Zoph: CTO | Alexander Kirillov: Multimodal Research Head | John Lachman: Head of Special Projects | Alex Gartrell: Linux kernel, networking, and containerization | Andrew Tulloch: ML systems research and engineering | Brydon Eastman: Human and synthetic data, model alignment and RL | Christian Gibson: Supercomputers used in training frontier models | Devendra Chaplot: VLMs, RL, & Robotics | Ian O Connell: Infrastructure engineering | Jacob Menick: ML researcher | Joshua Gross: Products and research | Kurt Shuster: Reasoning | Kyle Luther: ML researcher | Lilian Weng: Research | Luke Metz: Research scientist and engineer | Mario Saltarelli: IT and Security leader | Myle Ott: AI researcher | Nikki Sommer: HRBP | Noah Shpak: ML Engineer, GPUs | Pia Santos: Executive Operations Leader | Randall Lin: Algorithms | Rowan Zellers: Realtime multimodal posttraining | Sam Schoenholz: Scaling, optimization | Sam Shleifer: Inference | Stephen Chen: Infrastructure engineer | Stephen Roller: Full-stack pre-training | Yinghai Lu: ML system engineer

#OpenSpace | openspace.ai | OpenSpace Spatial AI engine maps photos to plans automatically | As-built record of the building from preconstruction to handover and operation | Stay on top of progress | Verify work-in-place | Improve coordination | Reduce risk | AI automatically calculates progress of specific construction activities | Verify work completed for payment applications and better scheduling | Machine learning and computer vision to recognize, track, and quantify work-in-place | Heatmaps on floor plan | Progress Chart plots quantity installed over time | Live dashboards | Export OpenSpace Track progress data

#Cerebras | AI inference and training platform | Specialized AI chips | Wafer-scale engine (WSE) | 900,000 cores deliver high levels of parallelism required to train large-scale models faster and more efficiently | On-chip memory integration provides high-bandwidth access to data | Processing speeds exceeding 2,500 tokens per second | Real-time processing capabilities for autonomous systems, vehicles, devices

#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

#ARM | Advanced RISC Machines | RISC instruction set architectures (ISAs) for computers | ARM processors for portable, battery-powered devices, smartphones, embedded systems | SoftBank Group | AI ecosystem | Renesas | ResCon Technologies, LLC | GitLab | Embedl | Mapbox | Roofline | ENERZAi | 221e | AnchorZ Inc | Excelfore | ax Inc | weeteq | Eeasy Tech | Cerence AI | u-blox | SECO | Klepsydra Technologies | Ampere Computing | Senary Technology Limited | Ceva | Sensory | GitHub | Raspberry Pi Ltd | Untether AI | Eyeris | AiM Future, Inc | Dori AI | DeGirum Corp | OmniSpeech | ADLINK | Yobe | SLAMcore | Elliptic Labs AS | alwaysAI | Edge Impulse | SoundHound AI | Cyberon Corporation | Qeexo AutoML | Fortifyedge | TERAKI | NVIDIA | Neuton.AI | Aizip Inc | BrainChip | Roviero | RelaJet | Visidon

#SFA Oxford | Research | Critical minerals in Artificial Intelligence

#Export-Import Bank of the United States | The official export credit agency of the United States | Supporting American job creation, prosperity and security through exporting | Issuing letters of interest for over $2.2 billion in financing for critical mineral projects | Supply Chain Resiliency Initiative (SCRI) to help secure supply chains of critical minerals and rare earth elements for U.S. businesses | Maintaining access to critical materials to secure U.S. jobs in sectors like battery, automobile, and semiconductor manufacturing | SCRI provides financing for international projects with signed long-term off-take contracts with U.S. companies, providing these U.S. companies with access to critical minerals from partner countries | SCRI: EXIM financing is tied to import authority and the financed amount depends on the amount of the off-take contract between the foreign project and the U.S. importer | Off-take agreements ensure that EXIM financing for critical minerals projects benefits American companies and workers | For U.S. domestic production in critical minerals and rare earth elements, EXIM can provide financing through Make More in America Initiative (MMIA) | SCRI: project must have signed off-take contracts that will result in the critical minerals and rare earth elements output being utilized in the United States, for products that are manufactured in the United States