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WIMI (NASDAQ: WIMI) realizes the technology of breaking the crosstalk limitation of dynamic holography through the orthogonality of high-dimensional random vectors.
Source
https://finance.sina.com.cn/tech/roll/2023-05-05/doc-imystpau3413832.shtml
May 5, 2023
Digital holography is the most promising technological path to achieve true 3D spatial imaging, but combining complex digital images with full depth control remains a challenging problem. With the development of technology, we have made great technological progress in 3D holographic projection, but the available methods are still limited to creating images on a few planes, only with narrow depth of field or low resolution. True 3D holography also requires full depth control and dynamic imaging, capabilities currently hampered by high crosstalk. Its applications are limited due to issues such as depth control and high crosstalk. One of the key issues is how to store all the information needed to render complex 3D images in 2D without crosstalking projected images at different depths.
The current holographic technology is affected and limited by data crosstalk because the holographic image information is compressed on one plane, which means that when we are ready to project and image images with different depths, these images will interfere with each other and generate crosstalk. In order to solve this problem, WIMI (NASDAQ: WIMI) researched a new method, that is, the technology of realizing crosstalk control of dynamic holography through the orthogonality of high-dimensional random vectors.
The technique works by pre-shaping the wavefront during Fresnel diffraction. That is, for each depth, a high-dimensional random vector is multiplied with the image, thus introducing a random phase for each depth. In this process, a spatial light modulator is used to create a pre-shaped wavefront with random phase. In this way, images at each depth are preprocessed into a complex amplitude multiplied with a random phase, which is introduced to eliminate crosstalk due to the near-orthogonality of large-dimensional random vectors. Therefore, when performing holographic image reconstruction, the information of each depth is presented independently without interference. This enables 3D projection with full depth control while eliminating crosstalk limitations. Another critical step is converting Fresnel holograms to Fourier holograms. Fourier holography can be achieved by pre-shaping the wavefront so that the Fresnel diffraction is locally reduced. Fourier holography allows the introduction of random phases for each depth without changing the image projection at a specific depth, thus eliminating the problem of crosstalk. Therefore, large-volume 3D images with high density, full depth control, and dynamic 3D projection capabilities can be generated using this method.
WIMI holography breaks the crosstalk limitation of dynamic holography through the orthogonality of high-dimensional random vectors. This technology can include random phases for each depth without affecting the image projection at a specific depth, eliminating the Crosstalk due to near-orthogonality. The resulting Fresnel hologram, or Fourier hologram, can then be transferred to a suitable holographic medium, and then a 3D image can be generated by shining a laser on the holographic medium. During this process, the light intensity and angle of the projection need to be adjusted to produce the desired 3D effect. If dynamic projection is required, it can be achieved by adding control circuitry to the laser and optics. This technique breaks the crosstalk limitation of dynamic holography by combining wavefront preshaping with high-dimensional random vectors. This approach enables high-density, large-volume 3D images with full depth control and dynamic projection capabilities.
WIMI Holography (NASDAQ: WIMI) uses the orthogonality of high-dimensional random vectors to break the crosstalk limitation of dynamic holography, which is an innovative solution. Through this technology, full depth control and dynamic projection capabilities can be achieved, while eliminating random vectors due to large dimensions can provide more advanced, accurate, and intuitive images and experiences for multiple industries. With the continuous development and improvement of this technology, it is believed that it will play a more important role in more fields.
WIMI (NASDAQ:WIMI) develops a machine-intensive reinforcement learning simulator to improve the efficiency of autonomous driving training.
Source
https://finance.sina.com.cn/tech/roll/2023-04-27/doc-imyrvfyt3148265.shtml
April 27, 2023
In recent years, self-driving car technology has made great progress with the development of technology, but how to ensure the safety of self-driving cars in various complex scenarios is still a very challenging problem. Traditional verification methods based on manual and drive tests have great limitations in terms of time and cost. The occurrence of traffic accidents, especially in extreme situations, is a key bottleneck hindering the development and deployment of autonomous vehicles. Since safety-critical events are rare, the economic and time costs required to verify their safety in natural driving environments are prohibitively high. Daunting.
According to reports, WIMI (NASDAQ: WIMI) is developing an intensive reinforcement learning technology for safety verification of self-driving cars. Fast validation and training in the emulator.
According to the data, WIMI Hologram's simulator based on machine-intensive reinforcement learning is a model-based machine-intensive reinforcement learning technology for safety verification of autonomous vehicles. The technology trains an agent in a simulator and puts it through a dense reinforcement learning algorithm for validation in a natural driving environment.
Dense reinforcement learning (DRL) is a machine learning technique that enables machine intelligence agents to learn and make optimal decisions from their interactions with the environment. In the field of self-driving cars, dense reinforcement learning is used to develop safety verification systems to ensure that self-driving cars can drive correctly in various situations. When using machine-dense reinforcement learning (DRL) for self-driving car safety verification, it is usually divided into two phases:
training and verification.
During the training phase, the DRL agent interacts with the environment and learns from it. During the validation phase, the DRL agent is tested in a simulator or in the real world to see if it can drive correctly and make optimal decisions. The safety verification of autonomous vehicles is a very complex and time-consuming process, as its safety needs to be verified in various road and traffic scenarios. Dense Simulator Reinforcement Learning is a technique for safety verification of self-driving cars using a simulator, which can greatly reduce the time and cost of verification.
It is reported that the intensive reinforcement learning technology of WIMI (NASDAQ: WIMI) adopts the model-based reinforcement learning (Model-Based Reinforcement Learning) method, which combines the idea of ??model predictive control. Specifically, we built a model in the simulator to predict the agent's actions and possible consequences in the current environment, and calculate various possibilities. We then use reinforcement learning algorithms to optimize the agent's policy to best meet goals such as safety and efficiency.
Compared with traditional reinforcement learning methods, machine-dense reinforcement learning-based simulators have higher efficiency and stability. By using the model, we can quickly generate a large amount of training data in the simulator, and can better control the environment and state in the simulator, so as to better approximate the real world situation. In addition, the method of Multi-Agent Reinforcement Learning is adopted to allow different agents to cooperate with each other in the simulator, so as to better adapt to complex autonomous vehicle scenarios. In training, we also use technical means such as Experience Replay (ER), Priority Experience Replay (PER), Dynamic Time Discount (DTD), etc. to improve the efficiency and stability of training.
At present, WIMI (NASDAQ: WIMI) is based on a machine-intensive reinforcement learning simulator. Through the process of defining the agent's goal and environment, establishing an agent model, training the agent, and using the dense simulator reinforcement learning technology for training and verification, the simulation Large-scale testing and verification in the device greatly reduces the cost and time of testing and verification in the real world, and improves the development efficiency and quality of autonomous vehicles.
The technical implementation process is as follows:
Construction of driving scene simulator:
firstly, it is necessary to build a driving scene simulator, which can simulate various road and traffic scenes. A simulator needs to include elements such as vehicles, pedestrians, roads, traffic lights, and the physics and behavioral rules associated with them.
Define the agent's goals and environment:
It is necessary to clarify the agent's goals and the environment to face. For example, an agent's goal might be to reach a destination in the shortest possible time while minimizing accidents. The environment includes roads, traffic lights, other vehicles, pedestrians, etc.
Establish an agent model:
establish an agent model, including input, output, network structure, etc. For example, the input might include information such as the agent's current speed, location, and the location and speed of surrounding vehicles; the output might be the next action the agent should take, such as accelerating, decelerating, turning, etc. When building an agent model, the working environment of the agent in the real world needs to be considered, and relevant traffic rules and safety requirements need to be followed.
Training Agents:
Agents require extensive training and experimentation in an emulator. An algorithm based on reinforcement learning can be used to improve the performance of the agent through continuous trial and error and learning. The agent needs to constantly explore new strategies and adjust its behavior according to the reward signal to maximize the long-term cumulative reward.
Dense Reinforcement Learning Simulator:
Dense reinforcement learning simulator refers to accelerating the learning and validation process of an agent by conducting a large number of training and experiments in a simulator in a short period of time. Specifically, some technologies can be used to speed up the operation of the simulator, such as parallel computing, distributed computing, and so on. At the same time, some technologies can also be used to automatically generate various road and traffic scenarios to improve the efficiency of training and verification.
Validate the agent:
After training in the simulator, the agent needs to be deployed in the real world for validation. During the verification process, some techniques can be used to speed up the verification of the agent, such as gradually relaxing the environmental restrictions, gradually increasing the complexity of the scene, artificially introducing interference, etc. If the agent performs well in the real world, the complexity of the scenario in the simulator can be further increased to verify the safety of the agent with stricter standards.
Typically, the development and deployment of autonomous vehicles requires extensive testing and validation that needs to be done in the real world, which is time- and cost-prohibitive. Through the WIMI holographic intensive reinforcement learning simulator technology, large-scale testing and verification can be carried out in the simulator, which greatly reduces the cost and time of testing and verification in the real world, and improves the development efficiency and efficiency of autonomous vehicles. quality. Secondly, self-driving cars face many complex scenarios and environments in the real world, such as weather changes, road conditions, behaviors of other vehicles and pedestrians, etc.
These complex scenarios and environments are difficult to reproduce and verify in the real world. Through the intensive simulator reinforcement learning technology in the simulator, these complex scenarios and environments can be simulated, and the performance and safety of the self-driving car can be trained and verified in the simulator, so that it can better cope with the challenges in the real world. In the verification process, the verification process can also be accelerated by gradually relaxing the environmental restrictions, gradually increasing the complexity of the scene, and artificially introducing interference. This technique could greatly reduce the time and cost of safety verification while improving the safety and reliability of autonomous vehicles.
In short, WIMI (NASDAQ: WIMI) adopts intensive reinforcement learning simulator technology, which can help the autonomous driving industry to verify and train the safety of autonomous vehicles more quickly, efficiently and accurately. This will bring more reliable and safer self-driving car products to users, and will also accelerate the development and popularization of self-driving car technology. Intensive reinforcement learning technology provides a brand-new solution for the development and verification of self-driving cars, laying a solid foundation for advancing the development and application of self-driving cars. It is believed that self-driving car safety verification technology based on intensive reinforcement learning will be An important trend and direction in the future.
Virtual Human Creates a Super Entrance to the Metaverse, WIMI.US Explores Multiple Applications of Digital Human.
Source
https://cj.sina.com.cn/articles/view/1704103183/65928d0f020035lvf?from=finance
April 27, 2023
The digital people are the first to become popular in the Metaverse, why? If the Metaverse does not have the capabilities of AI, convenient mass production, and interactive digital humans, then it cannot actually be called the Metaverse. That is just a very mature virtual simulation technology ten years ago, and it has nothing to do with the value that the metaverse can generate in the future.
In the future, the metaverse can gradually change all walks of life. It is precisely because of its intelligent production capacity that it becomes possible under the trend of intersecting scientific evolution. As one of the popular application scenarios in Metaverse, Digital Human has attracted hundreds of millions of traffic attention, government and enterprise focus, and capital pursuit. Digital people such as virtual anchors, virtual idols, and virtual employees have made frequent appearances in recent years. With their "good-looking skin" and "interesting soul", they have become cutting-edge topics in the field of science and technology.
Technology driven revolution
Therefore, based on rapid production capabilities, such as the generation of AI-based digital humans, it is possible to generate 70% similarity in 40 seconds, and it is possible to apply it in various business scenarios, thus enabling metaverse applications in office, industry, and social interaction become possible.
Further analysis shows that ChatGPT has become so popular recently, it can be said that it is absolutely explosive! In the few months since ChatGPT was launched, the number of active users has increased continuously, and even some related concept stocks have followed suit.
The strong rise of ChatGPT has brought "intelligent evolution" to virtual digital humans. Virtual digital humans featuring high intelligence, self-learning ability, and high efficiency will be applied in more scenarios and fields.
Virtual Human Classification
At present, there are many ways to classify virtual humans:
the first type is classified according to technology, and virtual humans can be divided into algorithm-driven (AI real-time or face pinching, etc.) and real-life-driven (motion capture); People can be divided into 2D and 3D types.
The third type is classified according to the structure and composition, and virtual humans can be divided into digital type (users watch online) and holographic type (users watch with naked eyes on site); the fourth type is classified according to business model, virtual humans can be divided into IP type (KOL type, Song and dance type, brand type, idol type launched by entertainment companies, star clone type) and non-IP type (functional type, academic type and identity type).
Virtual digital human has strong plasticity in product design. Combined with cutting-edge technologies such as AR and artificial intelligence technology, it can enable new formats such as virtual anchors to bring goods to meet the diverse needs of users, generate huge market opportunities, and promote the high-speed development of the digital human industry. develop.
When iiMedia Consulting analyzed the market size of the digital human industry, it calculated the market size driven by digital human beings and the market size of the core industry of digital human beings. According to its statistics, the market size of the surrounding market driven by virtual human beings will be 186.61 billion yuan in 2022, and it is expected to be 640.27 billion yuan in 2025. billion.
iiMedia Consulting analysts believe that virtual digital humans have strong plasticity in terms of content and peripheral product output, and can continuously develop new explosive points according to the development of the trend of the times. will maintain a steady growth trend.
WIMI Holographic "Digital Human +" empowers commercial applications to blossom
At this stage, the digital human industry is in the initial stage of growth, and the growth rate of the industry is relatively fast. Against the background of the rapid development of the digital human industry, following the development trend, WIMI Hologram (WIMI.US) is well versed in the operation and realization of virtual human, focusing on the "digital human" +" track, using AI interaction, real-time motion capture, VR/AR and other technologies to create a digital human comprehensive operation plan, active in all aspects of corporate branding, marketing and consumer services, providing strong support for promoting the digital transformation and upgrading of the digital human industry .
Specifically, the application of WIMI holographic virtual digital humans in various industries will empower traditional industries and promote the development of the real economy in a new digital form. For example, it has outstanding performance in the virtual human + cultural tourism industry, and the application of virtual characters represented by virtual commentators may contribute vigorously to it. As a virtual anchor, WIMI holographic digital human breaks the time and space constraints through online live broadcasting and other methods, leads the audience to travel online, watch cultural and creative products, realizes the promotion and production of innovative content for the cultural industry in a digital way, and presents culture in multiple dimensions charm.
On the one hand, WIMI’s holographic virtual human has become an important engine for the transformation and upgrading of the cultural tourism industry. On the other hand, it actively promotes the joint development of digital human and new models such as smart tourism and virtual tourism. It is worth noting that in the future, as the number of entering enterprises increases, the development of virtual digital technology needs continuous innovation.
However, WIMI has been locked in advance, relying on full-stack technical capabilities, researching data-driven virtual digital human construction technology, collecting and processing the action data of real people, generating action data sets, and using machine learning algorithms Model training and optimization to generate a highly realistic virtual digital human model. And the action data of the real human body is applied to the virtual digital human model, so that it can show various actions of the real human body, so that the digital human has a more realistic appearance and performance ability.
It can be said that digital humans are an important interactive carrier under the Metaverse system. Currently, the business models of virtual idols, service types, and social types of digital humans are gradually becoming clear, involving content creation, live broadcast interaction, advertising endorsement, e-commerce sales, etc. multiple fields. The acceptance of WIMI's digital human scene is increasing, and it is expected to usher in an explosive period at the commercial level.
epilogue
The business form of virtual digital human relies on multiple technologies, including computer vision, speech synthesis, and multi-modal interaction technologies. Whether it is AI modeling or driving technology, digital human will become an infrastructure technology within the next three years, and it will become a technology that can be used in various industries such as cultural tourism, industry, and education. All in all, digital human is a master of various cutting-edge technologies, and will be the super entrance of WEB3.0 and metaverse. Digital human will become a new productive force for shaping competitive advantages in various industries, integrating virtual and real, and empowering entities.
WIMI develops wearable EEG electronic equipment for brain-AI closed-loop system.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab30200114c6?from=tech
April 15, 2023
It is reported that WIMI is developing a wearable EEG electronic device for the brain-AI closed-loop system, which can enhance autonomous machine decision-making. The device monitors an electroencephalogram (EEG) of human brain activity and transmits this data to a computer system connected to it. The device uses electroencephalography (EEG) technology, which captures the electrical activity of the brain by attaching electrodes to the scalp. These signals can reflect the state of human perception, including the degree of brain activation, frequency and time domain characteristics, etc. These signals are very weak, generally at the level of microvolts to millivolts.
Therefore, high-sensitivity electrodes and signal enhancement equipment such as amplifiers are required in the signal collection process to ensure accurate signal collection and reliable transmission. After the data acquisition is completed, the device needs to transmit the data to an external computer system for analysis and processing. Therefore, the device is equipped with a communication module that uses wireless technology for data transmission, which allows real-time data transmission and processing. At the same time, signal interference and distortion during transmission can be avoided.
WIMI's wearable EEG electronic device for brain-AI closed-loop system is a complex system integrating sensors, high-sensitivity electrodes, signal enhancement and processors, communication modules, etc., which can capture the brain's electrical activity signals and transmit it to an external computer system for analytical processing. Accurate signal acquisition and real-time data transmission and processing can be achieved, thus providing a reliable data source and decision support for the brain-AI closed-loop system. Wearing comfort and portability were also important considerations in the design of the device. Since the device is worn for extended periods of time, it must be comfortable to wear. At the same time, in order to facilitate portability and use, the device uses lightweight materials and a flexible design that can adapt to the shape of the head, thereby ensuring wearing comfort and stability.
Through the wearable EEG electronic device used by WIMI for the brain-AI closed-loop system, we can realize two-way communication from the human brain to the computer system to realize autonomous machine decision-making. An example of such a system is a brain-machine interface (BMI), which allows people to control external devices such as computer games, artificial limbs, etc. through purely mental activities. In a closed-loop system, the EEG device detects changes in brain activity and transmits this information to a computer system. Computer systems may analyze this data to determine whether certain actions are warranted or to be taken. For example, if the system detects that the user's brain activity indicates that they are experiencing cognitive overload, the system can automatically adjust the difficulty of the task or provide appropriate prompts to help the user complete the task.
The technology to realize the brain-AI closed-loop system requires the following steps and components:
Wearable EEG device:
This device can monitor brain activity through sensors and electrodes, and transmit the signal to a computer system.
Data acquisition and processing:
Process and analyze the signals collected from EEG equipment, such as removing noise, screening useful signals and extracting features. These operations can be done using some data processing tools and algorithms, such as filtering, time-frequency analysis, machine learning and other techniques.
Human brain activity decoding:
Decode the signals collected from EEG equipment into specific human brain activities, such as cognition, emotion, movement, etc. This requires the use of some human brain activity decoding algorithms, such as classifiers, neural networks and other technologies.
AI algorithms and models:
use decoded human brain activity data to train and optimize machine learning models and algorithms. These models and algorithms can be used to analyze human brain activity, predict user intentions, emotions, and needs, and make decisions and adjust tasks autonomously.
Autonomous machine decision-making:
By combining human brain activity decoding with AI algorithms, autonomous machine decision-making is realized. For example, the system could automatically adjust the difficulty of tasks or provide hints when a user's brain activity indicates they need help. These decisions can be made in a closed-loop system, enabling real-time interaction between humans and machines.
With the rapid development of AI technology, artificial intelligence plays an increasingly important role in various fields. However, the existing AI systems can have amazing performance in the feeding of large amounts of data and system algorithms, but they often cannot accurately capture human emotions and intentions, which limits the scope of application of AI technology. The wearable EEG electronic device used in the brain-AI closed-loop system by WIMI can measure the electrical activity signals of the brain, and through these signals, we can accurately capture human emotions and intentions. A closed loop is established between the AI ??system and humans. Through the data collected by the device, the AI ??system can make more intelligent decisions based on human emotions and intentions. Through wireless communication technology, it can communicate with the AI ??system in real time to achieve fast data transmission and response. In addition, the device can also detect the emotional state of human beings by monitoring the electrical signals of the brain, so as to adjust the working state of the AI ????system in time to better adapt to human needs.
WIMI (NASDAQ: WIMI) has a very broad market prospect and application space for wearable EEG electronic devices used in brain-AI closed-loop systems. It will promote more intelligent interactions between humans and machines, enhance autonomous machine decision-making, enhance the intelligence level of AI systems, and improve user experience and efficiency. At the same time, the device also has strong adaptability and comfort, and can be used more and more widely in fields such as medical treatment, entertainment, games, human-computer interaction, and robotics.
WIMI launches real-time network holographic microscope interaction technology, which can be widely used in education and scientific research.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab30200113mp?from=tech
April 12, 2023
It is reported that WIMI (NASDAQ: WIMI) has launched a real-time network holographic microscope technology, which can significantly improve the resolution along the optical axis (horizontal and axial resolutions: 0.4µµm and 0.8µµm respectively). LEDs, each with a different color (RGB), hit the sample from three different directions. Each channel of the camera records an independent hologram created by the interference between incoming light and light scattered by an object. These three holographic digital images are transferred to a GPU algorithm to compute three corresponding volumetric reconstructions. Each of the signals currently in the reconstruction suffers from poor axial resolution, but their overlapping returns a volumetric image whose isosurface profile closely approximates the surface of simple microscopic objects.
According to the data, WIMI WIMI holographic real-time network holographic microscope technology supports user interaction through virtual reality devices, and can use gestures (that is, "grab") or more complex remote control interaction methods to achieve independent creation, destruction, selection and movement. When the engine detects an event related to the creation, destruction, or displacement of a snap, data describing the updated snap configuration is sent to the "holographic engine" over a network connection. The holographic engine runs on a computer that controls the optical hardware in a separate lab.
When an update request is received from the "VR Engine", the Holographic Engine computes an optimized digital hologram on the GPU and displays it directly on the SLM. A collimated infrared laser beam is reflected from the SLM and acquires a phase modulation such that the resulting diffraction-limited spot has the same spatial arrangement as its virtual counterpart after propagating through the microscope objective. Each of these spots acts as an optical trap, which can be used to grasp and manipulate small dielectric objects. Typically, capture rearrangements will result in rapid motion of nearby objects, captured in a holographic image and processed in real-time by a "holographic engine". The obtained volumetric reconstructions are segmented to extract relevant geometric features of all identified objects. This geometric data is sent back to a "VR engine" to update the object's geometric parameters, providing a virtual representation of the real object interactively manipulated under the microscope, as shown here.
The SLM will be refreshed at a rate of 60 Hz, and the minimum delay time corresponding to the holographic image display is 17 milliseconds, which can ensure a smooth interactive operation experience. Simultaneously displayed phase modulation on the SLM to generate an optical capture at the position indicated by the 3D arrangement of the virtual handle, showing the original hologram recorded on the three color channels of the camera before being numerically reconstructed, tracked and rendered on the VR headset picture. Using a virtual hand to grasp objects and arrange them into 3D holographic configurations that can be inspected immersively and in real time, and allow direct manipulation through gestures and real-time immersive feedback. Microassembly tasks can be greatly simplified, especially for users with no previous microscope and capture experience.
WIMI (NASDAQ: WIMI) real-time network holographic microscope interaction technology. A series of tools are also implemented to track objects and observe the temporal evolution of their coordinates on a display. Using holographic optical tweezers capable of dynamically aligning multiple snaps in 3D, we can precisely arrange multiple colloidal particles or living cells in controlled spatial configurations to study their random behavior under reproducible initial conditions, or their Biological interactions during growth, grasping and rotation of microfabricated objects with complex shapes can also be used as tools for advanced microscopy applications. In this regard, virtual reality interfaces can simplify and accelerate the assembly of multicomponent microsystems and allow direct manipulation through gestures and real-time immersive feedback.
Holographically imaging objects as large as the wavelength of light, like bacteria, is quite a challenging task. Volumetric reconstruction represents the convolution of the actual object shape by a point spread function, which approximates a 3D Gaussian and leads to blurring of the final 3D image (especially along the vertical axis). WIMI WIMI holographic real-time network holographic microscopy technology has a reliable prior information about the shape, and infers the geometric parameters of these shapes through volume reconstruction, using the volume image reconstructed by the marching cube algorithm, which is executed on the "holographic engine" GPU, The output polygonal mesh, whose vertices and triangles are sent over the internet to a "VR engine" for real-time rendering.
WIMI's (NASDAQ: WIMI) real-time network holographic microscope interaction technology presents a powerful interface through virtual reality to merge 3D microscopy and holographic technology for micromanipulation. Provides an immersive interactive experience of microscopic phenomena. We can enter laboratories on a chip, walk on microscope slides, observe dynamic phenomena happening around us in real time, and use virtual hands to grasp, move and construct 3D spatial arrangements of microscopic objects and living cells. This approach can be extended in many different directions. All of this holographically interactive digital information can be used to explain to students, and to conduct experiments and observe the microscopic world in the first person, providing a unique and powerful experience of the physical laws governing the microscopic world populated by cells and colloidal particles.
WiMi prepares human-machine interface based on electrooculography for VR glasses.
Source
https://holographica.space/news/wimi-eog/
April 12, 2023
The Chinese company WiMi Hologram Cloud, known for projects of equipment for augmented and virtual reality, such as solid-state lidars , spoke about the work on a system for interacting with virtual reality through electrooculography (EOG), which tracks eye activity with high accuracy by monitoring the muscles and outer layers of the retina. for changes in electrical potentials during the movement of the eyeballs.
The system should consist of three parts:
- a signal collection node,
- a processing node, and
- a signal transmission node to the virtual reality scene.
When the system is turned on, the person reacts to the scene in real time and makes the appropriate eye movements. The equipment collects EOG data, analyzes and converts them into commands. In this way, applications can obtain both a new control principle and new behavioral data that could not be collected with a conventional optical oculography system.
The EOG signal is the electrical potential difference between the cornea and the retina and can be used to reflect eye movements with an amplitude ranging from 0.4 to 10 mV. The human eye produces different EOG signals by performing different actions. Data processing mainly consists of several main steps: preprocessing, feature extraction, waveform detection, and classification. Having developed appropriate algorithms for analyzing electrooculography readings, WiMi wants to convert them into device control commands to create a human-machine interface.
At the same time, a virtual reality application can provoke and receive data of a different plan. For example, a person, in addition to visual information, will respond to sound, feedback from controllers and other stimuli. Avoiding mixing random responses with control signals is one of the challenges for WiMi algorithms.
The company claims that its development is highly innovative and has potential applications in a wide range of areas such as entertainment, medicine and work.
Unfortunately, in the published materials there is no information about in what form and at what price the solution will go on sale. It can immediately become part of the virtual reality glasses. WiMi already has HoloVR glasses with Nolo controllers in its range. They were approved for distribution in the United States by the Federal Communications Commission in 2022 . The company itself trades shares on the US stock exchange NASDAQ, which also shows interest in a particular geographic market.
WIMI develops a sensor-based electronic holography (EH) gesture control system.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab30200110ww?from=tech
March 31, 2023
It is reported that WIMI (NASDAQ: WIMI) has developed a gesture control system based on sensor-based Electro-Holography technology. The sensor-based gesture interaction technology can realize the interaction between the user and the electronic holographic (EH) image, and improve the user's interactive experience. The realization of gesture interaction technology requires a combination of various technologies, including sensors, digital signal processing, gesture recognition, control commands and other technologies.
The interaction technology of WIMI's sensor-based electronic holography (EH) gesture control system can realize the interaction between users and three-dimensional holograms. It uses sensors and computer algorithms to detect and recognize the user's gestures, so as to realize the control and operation of the holographic image. This uses sensors to capture the user's gestures, and uses infrared sensors, depth cameras and other devices to realize gesture recognition. These sensors can capture the user's gestures in real time, then convert them into digital signals, and then process and analyze them through algorithms, and finally realize the control and operation of holographic images.
WIMI Electronic Holography (EH) is a method that uses electrical signals and optical technology to generate three-dimensional holograms. Its basic logic is to use computer-generated digital signals to control the light source, so that the light passes through the data of the recorded object, and then passes through a series of optical elements to form a real three-dimensional image.
Electron holography (EH) needs to scan or record the object with a laser light source first, and store the recorded optical information in the digital three-dimensional image data. These digital signals are then converted into electrical signals, and parameters such as the intensity, phase, and frequency of the light source are adjusted through an electrical controller to accurately reproduce the shape and color of the original object. Eventually, these rays will be reconstructed through optical elements such as lenses and mirrors to form a real three-dimensional image. The advantage of WIMI's electronic holographic technology (EH) is that it can generate high-quality, high-resolution three-dimensional holographic images with a strong sense of reality and three-dimensionality. It has a wide range of applications in medicine, engineering, entertainment and other fields, such as three-dimensional imaging of internal organs of the human body, visualization of engineering design, etc.
WIMI's sensor-based electronic holography (EH) gesture control system uses a phase-modulated SLM, a laser with a wavelength of 1nm is used as a light source, and a motion sensor is an interactive interface for holographic objects. The holographic 3D image is projected in front of the SLM as a real image to enhance its visibility, and it can be observed on the image sensor of the camera, and the holographic 3D image can be easily converted into a virtual image. By the compiler, with single floating-point calculation precision.
WIMI's (NASDAQ:WIMI) sensor-based electronic holography (EH) gesture interaction technology includes the following steps:
Collect gesture data: use sensors, such as infrared sensors, depth cameras and other devices, to capture user gestures. These sensors capture user gestures in real time and convert them into digital signals. Gesture data may include finger trajectory, gesture shape, speed, and the like.
Gesture signal processing: perform digital signal processing on gesture data, use digital signal processing algorithms, such as fast Fourier transform (FFT), wavelet transform (Wavelet Transform), etc., to filter, denoise, feature extract, etc. Extract useful information, such as gesture speed, direction, shape, etc.
Gesture recognition: Match the processed gesture data with a predefined gesture template to realize gesture recognition. A gesture template is usually pre-stored standard gesture data, which can be a gesture or a group of gestures. Gesture recognition algorithms include K-nearest neighbor algorithm, support vector machine, decision tree, etc.
Gesture control: Once the gesture is recognized, it can be converted into a control command to realize the control of the electronic hologram. For example, the three-dimensional holographic image can be moved, rotated, and scaled, or a different display mode can be selected through gestures.
Sensor-based electronic holographic technology gesture interaction technology has broad application prospects in the market. With the development of technologies such as virtual reality and augmented reality, 3D holographic images, as an important means of 3D visualization, have received more and more attention. The gesture interaction technology is an important means to realize the interaction between the user and the 3D holographic image, which can improve the user's interactive experience and operation efficiency.
WIMI's (NASDAQ:WIMI) sensor-based electronic holography (EH) gesture control system can be applied in games, entertainment, education, medical care and other fields. For example, in the medical field, doctors can use gesture interaction technology to manipulate 3D holographic images for surgical planning and operation. In the field of education, students can learn knowledge about human body structure, geography and landforms through gesture interaction technology. In the field of games and entertainment, players can use gesture interaction technology to control the movement, attack and other behaviors of game characters. With the further development and maturity of technology, WIMI WIMI Hologram's sensor-based electronic holography (EH) gesture control system will have a wider application space in the future.
WIMI develops a dedicated computer system chip SoC-FPGA for real-time single-pixel holographic imaging.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab30200110bw?from=tech
March 2, 2023
Holographic single-pixel imaging is a computationally intensive technique that requires compact and efficient devices for specific applications. Embedded computers may be a potential solution, but they are not suitable for reconstruction calculations due to their low computational performance. Therefore, there is a need to realize a small computer with high computing performance in a single large scale integration (LSI) chip. WIMI has developed a dedicated system chip for single-pixel holographic imaging using Field-Programmable Gate Array (FPGA, Field-Programmable Gate Array).
FPGA is an LSI chip that can freely rewrite logic circuits on site. FPGAs can perform high-performance computing by designing application-specific circuits. WIMI hologram implements iterative calculation method, Hadamard transform and differential ghost imaging (DGI) on FPGA, and the whole process from reconstruction calculation to display is completed on FPGA, which speeds up image reconstruction.
It is reported that in this research and development project, WIMI has developed a special computer system chip (SoC, System on a Chip) FPGA for real-time single-pixel holographic imaging. SoC FPGA is a type of LSI in which an embedded CPU and FPGA are implemented on a single-chip system. It has higher computing performance than an embedded CPU alone, more flexibility than an FPGA alone, and can be much smaller than a computer. Furthermore, the choice of a reconstruction algorithm that should be implemented as a computational circuit is important for designing a computer dedicated to single-pixel imaging. Although FPGA has high computing performance, its hardware resources are limited, and it is not good at complex calculations such as division and square root calculations. The optimization method and deep learning in the algorithm can obtain high-quality reconstruction in single-pixel imaging, and the optimization method has the problem of computational load due to the iterative method.
WIMI Holographic SoC FPGA test process for real-time single-pixel holographic imaging:
The camera lens forms an image of the target object on the DMD. The image of the target object is modulated by encoding the mask pattern displayed on the DMD. The modulated light is collected by a lens and measured by a single-element detector before being converted to a digital signal. In addition, a dedicated computer reconstructs an image of the target object based on the light intensity.
The FPGA partially reconstructs the image, while the embedded CPU on the WIMI Holographic real-time single-pixel holographic imaging dedicated computer system chip SoC-FPGA generates and initializes the drawing on the holographic display.
The object light is formed on the DMD by the camera lens. A coded mask pattern is displayed on the DMD by which the subject light is modulated. The modulated light is collected by a lens and measured as light intensity by a single-element detector. The obtained light intensity is converted from an analog intensity signal to a digital signal by an analog-to-digital converter. Repeat this when switching encoding masking modes. The receive circuitry in the FPGA saves the converted signal in the FPGA's internal memory when the sync signal is asserted, which is generated when the DMD switches to a new encoding mask mode. After the receiving circuit saves the signal for a specified number of times, the reconstruction circuit starts to calculate the holographic image of the target object. Then, the embedded CPU on the SoC FPGA chip receives the reconstruction result and displays it on the dedicated display panel to realize real-time observation of the holographic image of the target object on the dedicated holographic display panel.
In order to improve computing efficiency, WIMI adopts a ghost imaging related algorithm in the SoC-FPGA of single-pixel holographic imaging, which is suitable for FPGA. The algorithm has low memory usage and simple calculation form. The algorithm introduces an encoding mask pattern optimization. This ghosting algorithm improves image quality, but has higher memory requirements.
Specifically, the implementation of the ghost imaging algorithm requires the use of two spatially separated beams:
- a reference beam and an object beam. It is an imaging method based on cross-correlation or cross-correlation-like techniques, which enables image reconstruction by using single-photon detectors. The basic principle of the algorithm is to take a cross-correlation measurement between two spatially separated beams and then use a computer algorithm to reconstruct the target image. For example, a reference beam passes through a random perturbation device, which produces a random pattern of light intensity. These light intensity patterns are transmitted into the object beam, where they are detected by single-photon detectors after passing the object. The light intensity values ??measured by the single-photon detector are recorded and cross-correlated with the light intensity pattern of the reference beam. The information of the target image can be obtained by averaging multiple cross-correlation measurements.
The ghost imaging algorithm has some unique advantages in imaging, such as the ability to realize three-dimensional holographic imaging without an objective lens, suitable for imaging at low light levels, and suitable for multiple imaging modes such as transmission and reflection imaging.
WIMI Holographic's real-time single-pixel holographic imaging dedicated computer system chip SoC-FPGA can obtain higher image quality than traditional holographic imaging technology, and through SoC-FPGA integrated structure optimization and algorithm optimization can achieve size, image quality and speed Real-time holographic imaging is realized through the improvement. And because the SoC-FPGA dedicated to real-time single-pixel holographic imaging is very compact compared with typical computer servers, it can extend the application of single-pixel imaging to the Internet of Things and outdoor applications. Dedicated specific applications also include the implementation of satellite topographical surveys, and can also be used for object tracking to build car navigation IoT systems.
Explosive Growth Of Lidar Industry: WiMi Innovates Its Automatic Drive Tech.
Source
https://www.newstrail.com/explosive-growth-of-lidar-industry-wimi-innovates-its-automatic-drive-tech/
March 24, 2023
How hot is the lidar radar? Not only are more and more new models competing for configuration, but some models that were released earlier and did not planned to install lidar before, are also trying to keep up with the boom of “replacement” lidar. Car companies have also launched an “arms race” on the number of lidar assembled, from the initial one, to the conventional two to three, to the recent news that Xiaomi cars may be equipped with five lidar when it is launched.
Thanks to the rapid growth of the on-board lidar market, the names of lidar manufacturers such as Huawei and Luminar have also entered the public view and followed the fast track. Automotive technology has been improving in recent years, especially with the development of autonomous driving technology, with the help of lidar. With its help, the car collects the information on the road at the fastest speed, and uses the on-board chip processing to realize autonomous driving.
One of the key factors in the development of self-driving cars is on-board sensors, which enable the car to “see” the road and help it understand what’s happening around it. —— In most cases, this sensing capability is better than anyone can do.
Self-driving cars need to be able to identify people or things on their way, identify features of the road system, and constantly deal with various traffic problems and other challenges that users deal with on the road every day. To overcome these obstacles, self-driving cars require a range of technologies such as cameras, radar, lidar and infrared.
The advantages and applications of lidar
The LIDAR, the Light Detection and Ranging, can be found in almost every self-driving car that is tested. The lidar is designed to provide a complete 360-degree panoramic view, using laser pulses to visualize the vehicle’s surroundings in the form of a three-dimensional “point cloud”. The technology has been extremely successful in helping many OEMs into practice their ambitions in self-driving cars.
From the perspective of the industrial chain, the rapid growth of the on-mounted lidar market is mainly due to several factors.
- First, the accelerated penetration of autonomous driving has led to the rapid growth of the lidar market. According to IDC, the penetration rate of L2 autonomous driving passenger vehicles was 23.2 percent, up 7.5 percent year on year. Since last year, a number of models that can support L3-L4 class autonomous driving, including Mercedes-Benz and BMW, have been delivered. Mercedes-Benz is the first car company in the world to truly realize the mass production of L3 class autonomous driving in many countries and regions. These vehicles have accelerated the mass-production speed of the lidar to some extent.
- Second, the various technical routes of lidar can meet the different needs of autonomous driving in different scenarios. At present, except for Tesla, other oems are actively deploying autonomous driving solutions with lidar as its main sensors. For example, low-speed closed scenarios such as ports and mines have high requirements on the cost and reliability of lidar, and the mirror rotating or MEMS schemes with high maturity can be given priority.
- Third, the price of lidar is expected to drop due to various factors, and it may become a standard sensor for autonomous vehicles in the future. As more car companies cooperate with lidar manufacturers, the cost of lidar is expected to be further reduced under the scale effect, and the mass production of lidar is expected to be further accelerated in the future.
Lidar is very promising
According to market research firm Allied Market Research, the global driverless technology market will reach $556.67 billion in 2026, achieving a compound annual growth rate of 39.47% compared with 2019.
As the key to the realization of high-level unmanned driving technology, the development prospect of lidar is also very promising. According to Frost & Sullivan, the global market for lidar will be us $13.54 billion in 2025. Across the world, China could be the fastest-growing market for lidar. By 2025, China’s lidar market size will reach 4.31 billion US dollars.
WiMi helps the autonomous driving industry grow
It is understood that in the face of such a broad market prospect, in many lidar related enterprises, WiMi Hologram Cloud (NASDAQ: WIMI) stands in the first echelon of technology. According to the data, WiMi’s technology is mainly concentrated in on-board AR holographic HUD, 3D holographic pulse LiD AR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic vehicle navigation, universe holographic AR / VR equipment, universe holographic cloud software and other professional fields. Relying on the independent and complete core technology system, the extension of WiMi business involves intelligent driving (such as vehicle-road collaboration, autonomous driving, etc.) and digital twin (such as mapping and collection of high-precision maps).
According to the report, the leading WiMi of software and hardware technology strength support, the research and development of 3D holographic pulse laser radar to realize the road identification detection, dynamic and static obstacle detection, driving area detection, radar perception fusion such as perfect environment function, and through the “one-stop” service support, fu to automatic driving project implementation “point to point” whole scene environment perception, to achieve the large-scale application of laser radar in the market, help project authors efficiency, promote large-scale rapid form of autopilot project.
In addition, in order to further explore the field of intelligent driving and accumulate more rich experience, WiMi tries to unlock 3D visual perception technology and expand the application of AI vision in the automotive field. It can be said that technology giants like WiMi have entered the field of intelligent driving with their strong technical strength as well as the original accumulation formed in the original business, which has greatly contributed to the development of the industry and gained the attention and expectation of capital. In the medium and long term, the continuous technological innovation, the continuous pursuit of the ultimate enterprise core, as well as WiMi’s continuous innovation in technology, in the future or will become the leader in the field of intelligent driving.
future trend
On the whole, in the context of the high popularity of autonomous driving, both start-up players and big manufacturers have chosen to promote the mass production of lidar to accelerate the car, and they also have quite similarities in their realization path. Objectively, tech giants and start-ups have unique advantages and have their own directions.
Lidar is entering the scale boarding cycle, and the boarding effect is still receiving the market feedback, which also directly affects whether the lidar will quickly usher in a larger volume. In any case, 2023 is a crucial year for players in the lidar subdivision track, with players bound to stand out from the first wave of growth.
Yuan Universe office scene is expected to be the first to land, and WIMI holographic technology empowers to open up new formats.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab3020010xa6?from=tech
March 17, 2023
The Metaverse is a virtual world built by humans using digital technology that can interact with the real world. "Metaverse" integrates a large number of existing technologies, including 5G, cloud computing, artificial intelligence, virtual reality, blockchain, digital currency, Internet of Things, human-computer interaction, etc.
According to Gartner's prediction, by 2026, fields such as learning, shopping, and social networking will be connected to the metaverse, and about a quarter of the world's population will spend at least one hour in it. The website of Forbes biweekly in the United States reported that the market size of the global metaverse is expected to reach 5 trillion US dollars in 2030.
The future of office has come
Metaverse technology can be used for corporate employee training. For example, consulting giant Accenture has created a metaverse environment with the main features of a real office, allowing employees to perform many human resources-related tasks in the virtual world. From the perspective of changes in office models, office models such as online text communication and teleconferencing can no longer meet the needs of modern office. The metaverse office derived from the metaverse concept has more advantages.
At present, some companies can conduct Metaverse office by building online Metaverse digital office buildings and other methods. In this office model, Metaverse will multiply the capabilities of remote work platforms, allowing users to access a complete office suite, interact with colleagues, and more, no matter where they are. This digital metaverse office model has the advantages of high efficiency and flexibility.
In addition, Zuckerberg, CEO of META (META.US), once showed the world a holographic virtual conference at the end of 2021. Through VR/AR, holographic projection and other technologies, three-dimensional conference scenes can already be realized. It is expected that with the development of technology, this will also be a new form of metaverse office.
Not only that, Alphabet (GOOG.US) Project Starline, the parent company of Google, has been in development for 5 years. The subject of the research is 3D video calling, which provides users with a three-dimensional deep video chat system. Microsoft (MSFT.US) has also launched its own mixed reality service, Microsoft Mesh, which can transmit information such as users and working environments to smart glasses or other head-mounted display devices in the form of generating three-dimensional images.
Judging from the above phenomena, the metaverse office technology of conference calls seems to be developing towards popularization. Compared with traditional video calls for office work, 3D holographic images can enable both sides of the call to enhance expression and understanding through body language. The important thing is that holographic projection technology will bring us a brand-new remote office communication method, making user interaction more interesting and frequent.
WIMI holographic remote collaboration opens up a new way of efficient office
As for the technology of holographic projection, many companies have been researching and trying it for a long time, especially in the past two years, the demand for this technology has become more urgent. It is understood that WIMI.US, the first holographic AR stock, has a self-developed holographic content library, including holographic projection technology scenes, displayed models, virtual characters and other content. At the same time, the holographic cloud platform under WIMI can maintain applications in various scenarios, and realize online and offline remote office work forms, without being rigid or limited by space.
It can be said that the application of holographic technology has given birth to a new office model, that is, remote call holographic technology has emerged as the times require. WIMI provides a smarter, more efficient, and more convenient way of communication, realizing a hybrid office model. In the visualized 3D meeting room space, participants can also perform operations such as greeting, applauding, and moving, making the entire meeting communication more warm and interactive. For the layout of the holographic remote call market, WIMI will strive to promote the wide application of holographic technology in metaverse office meetings.
Holographic technology has been a very popular technology in recent years, and it is realized through the principle of polarization of light. In terms of industrial applications, WIMI helps museums better explain the origin and history of collections based on holographic projection technology, and uses holographic technology with hundreds of billions of large pixels to explain traditional culture on dynamic screens.
In the future, WIMI will continue to combine cutting-edge hardware and innovative software to bring complete immersive solutions, bringing new development ideas to the fields of training, conferences, art, entertainment, film and television, and industry, and also bringing new ideas to the digital economy era. Inject new impetus into the transformation and development of the enterprise under the current situation.
end
The future office is bound to present a more diversified form of integration, not only remote office, holographic projection and other technology-assisted remote office, meeting scenes. With the development of technology and expansion to more business scenarios such as announcements, exhibitions, and marketing, head platform companies will also continue to iteratively upgrade and become the right-hand man of enterprises in the metaverse era.
WIMI.US develops an intelligent model LMM-VFC that supports edge migration of the virtual function chain of the next generation Internet of Things.
Source
https://finance.sina.com.cn/tech/roll/2023-03-15/doc-imykxpqz4865684.shtml
March 15, 2023
We are striding into the era of the Internet of Everything, and the development of the Internet of Things (IoT, Internet of Things) is accumulating explosive development with the advancement of science and technology and the rapid development of the Internet. The development of next-generation IoT sensing devices for the Internet of Things, along with advancements in their low-power computing capabilities and high-speed networking, has led to the introduction of edge computing.
The real-time generation of massive data will become the norm in the future society. The gradual intelligence of the equipment enables the equipment itself to have the ability to process data in real time. In the edge cloud environment, services can generate and use data locally without involving cloud computing infrastructure. Improve data processing efficiency and feedback time. WIMI (NASDAQ: WIMI) proposes to propose and evaluate an intelligent migration model based on this, which can support virtual function chains at the edge of the network based on the Internet of Things.
It is reported that WIMI (NASDAQ: WIMI) proposed an edge LMM-VFC (Virtual function chain) model, which can enable complex AI models to be executed on heterogeneous edge networks, combined with real-time QoS (Quality of Service) that triggers real-time migration. ) monitoring model, the WIMI Hologram LMM-VFC model is enhanced through the migration model.
According to the data, WIMI Holographic LMM-VFC model is a novel distributed framework, which is based on the concept of virtual function chain (VFC) of software-defined network, and supports real-time reasoning of edge AI analysis. Edge Learning Services provides support to monitor, evaluate and predict the Quality of Service (QoS) of supported services. In this model, AI analytics is decomposed into a set of virtual functions (VFs), which can be deployed on different edge devices. Using these VFs, it is possible to create a VFC that processes streaming data in a distributed manner. VFO (Virtual Function Orchestrator) is responsible for deploying VFC. VFC deploys multiple modules through the framework, optimizes design services, monitors their QoS indicators and fine-tunes their configurations to avoid failures.
More specifically, the calculation engine is responsible for proposing optimal settings for the VFC, while the edge learning service monitors the performance of edge devices and proposes possible changes. The LMM-VFC model uses this to build an intelligent model for edge migration, optimize link capabilities, and support the development of next-generation Internet of Things technologies.
In addition, WIMI's (NASDAQ: WIMI) edge LMM-VFC model supports machine learning and proposes a model based on reinforcement learning to determine the best strategy for service migration. The migration problem is usually formulated as a sequential decision problem aimed at minimizing the overall response time. The calculation migration scheme based on the reinforcement learning strategy can learn the optimal strategy of the dynamic environment in real time to ensure low computing delay.
And the WIMI holographic edge LMM-VFC model proposes a user classification mechanism based on user movement patterns to reduce decision-making complexity. A reinforcement learning-based framework is then introduced to make service migration decisions in real-time in dynamic environments. Through data-driven experiments, the efficacy of WIMI holographic edge LMM-VFC model in reducing the average delay of the system is proved. The WIMI Holographic Edge LMM-VFC model is based on the IoT mobile edge/cloud computing offloading framework for lightweight process migration. The framework does not require application binary files on the edge server, so native applications can be migrated seamlessly. The WIMI holographic edge LMM-VFC model framework shows great potential in resource-intensive IoT application processing in mobile edge/cloud computing.
In an edge cloud environment, services can generate and consume data locally without involving cloud computing infrastructure. Aiming at the problem of low computing resources of IoT nodes, WIMI proposes a virtual function chain as an intelligent distribution LMM-VFC model to maximize the use of edge computing capabilities to support demanding services. It is an intelligent migration model capable of supporting virtual function chains. According to this model, edge migration can support individual functions of the virtual function chain.
First, if a virtual function fails unexpectedly, it can be automatically repaired through cold migration.
Second, a quality-of-service monitoring model can trigger live migration, aiming to avoid overloading edge devices. An evaluation study of the proposed model demonstrates its ability to improve the robustness of edge-based services on low-power IoT devices.
The Internet of Things (IoT) is a rapidly growing field with a wide range of applications in industries such as healthcare, transportation, and agriculture. As the number of IoT devices and their associated data continues to grow, there is an increasing need for efficient and intelligent models to manage and process this data. One of the key challenges of IoT is to support edge migration of virtual function chains.
Edge migration of WIMI Holographic Edge LMM-VFC model involves moving processing tasks from centralized servers to edge devices closer to data sources, such as routers or gateways. Reduce bandwidth requirements and enable real-time processing of data. The LMM-VFC model can implement an intelligent model that supports VFC edge migration in next-generation IoT. The model will leverage machine learning to optimize VFC migration decisions based on factors such as network latency, available resources, and data privacy requirements.
WIMI's (NASDAQ: WIMI) edge LMM-VFC model can continuously monitor network conditions and data flow, and decide in real time which functions should be migrated to the edge and which functions should be kept on the centralized server. This can be achieved through a combination of rule-based and machine learning algorithms that analyze data from a variety of sources, including network performance metrics, user behavior patterns and data usage statistics.
Overall, an intelligent model that supports edge migration of virtual function chains in next-generation IoT will be a powerful tool to manage the ever-increasing volume of data generated by IoT devices. By leveraging the latest advances in artificial intelligence and machine learning, the model can help organizations optimize their data processing workflows and increase the efficiency and effectiveness of their IoT deployments.
WIMI.US develops a hybrid structure of a distributed image storage protocol for image storage.
Source
https://cj.sina.com.cn/articles/view/7651844612/1c815e20402001g10e?from=finance
March 13, 2023
In recent years, with the rapid development of blockchain technology applications, more and more application scenarios have begun to use distributed ledgers to store and verify data. In terms of image storage, traditional centralized storage methods may have some security and reliability issues, so the distributed pool blockchain protocol can be an effective solution. WIMI (NASDAQ: WIMI) has developed a Distributed Image Storage Protocol (DISP) for image storage, and uses the Interplanetary File System (IPFS) to effectively improve blockchain storage space and reduce computing costs.
The distributed pool blockchain protocol can divide the stored data into multiple small blocks and distribute these small blocks on different nodes to realize distributed storage and backup. At the same time, the protocol can also use blockchain technology to ensure data security and credibility, making the stored image data difficult to be tampered with or lost. However, since image data is usually relatively large, storing it in multiple small blocks on the blockchain may result in inefficient storage and transmission.
WIMI proposes a blockchain distributed storage protocol based on the pooling algorithm and its inverse process, combined with the IPFS (InterPlanetary File System) protocol to store large image data, and uses the distributed pool blockchain protocol to manage and Validate blocks of data stored in IPFS. The IPFS protocol can divide image data into multiple small blocks and store them on different nodes in the network in a distributed manner to achieve efficient storage and transmission. The distributed pool blockchain protocol can ensure the integrity and credibility of the data by performing hash operations and blockchain storage on the data blocks stored in IPFS.
The WIMI Holographic DISP protocol is designed to be optional and non-mandatory. Users who do not accept the DISP protocol can still use the traditional full redundant storage method. Users who accept the agreement can enjoy the benefits of saving space without compromising security performance. The DISP protocol changes the fully redundant storage relative to individuals to community-level full redundancy, that is, the data stored in each node of a community has no redundancy. In DISP, distributed storage ensures that all data will not be lost when a small number of nodes are attacked or fails, thereby enhancing the performance of data security. The distributed pool algorithm reduces the data redundancy of distributed storage and greatly saves storage space.
WIMI (NASDAQ: WIMI) DISP protocol, in the preprocessing stage before implementing the distributed pooling algorithm, first divides the original image into several pooling areas according to the shape of the pooling kernel to form a group of pools to be processed area. The image can then be divided into several parts by a distributed pooling algorithm and stored in multiple nodes.
Addresses that accept the protocol will be collected to form different communities, and the number of nodes in each community is determined by the number of pooled images obtained after the decomposition algorithm. Under a certain compression ratio, each piece of data is still identifiable and can be represented losslessly by compressed sensing or super-resolution. If all the data fragments in the community are collected, the original data can be restored losslessly through the algorithmic reverse operation. The data saved by each node is different from the data of other nodes in the community, otherwise, the node will be divided into another community. Every node in the community can see the whole picture of the data. If the corresponding data fragments stored by each node in the community are collected together, the source data can be recovered without loss after the evidence phase is invoked.
The implementation steps of WIMI holographic DISP protocol are as follows:
Image segmentation:
Divide the image data to be stored into multiple small blocks, and the size of each small block can be adjusted as needed.
IPFS storage:
Store the divided image data in the IPFS network, and use the IPFS protocol to realize distributed storage and backup.
Blockchain verification:
Use blockchain technology to manage and verify data blocks stored in IPFS, thereby ensuring data integrity and credibility. Specifically, each data block has a hash value, which can be stored on the blockchain, and the blockchain is used to record the modification history of the data block.
Accessibility control:
Use smart contracts to implement accessibility control over image data, such as restricting certain users or applications from accessing certain image data.
WIMI (NASDAQ: WIMI) DISP protocol can realize efficient, safe and reliable image storage. Compared with the traditional blockchain storage method, this protocol divides the image data into multiple small blocks and stores them in IPFS, thus effectively reducing the storage space occupied by the blockchain. At the same time, blockchain technology is used to verify the integrity and credibility of data blocks, so that the stored image data is not easy to be tampered with or lost. More efficient, safer, and more reliable image storage can be achieved using a hybrid scheme. In order to make full use of their respective advantages, so as to achieve better performance and effect.
WIMI develops a hybrid enhanced intelligent system based on human-computer collaboration, moving towards deep human-computer integration.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab3020010vm8?from=tech
March 9, 2023
In recent years, with the improvement of computer data collection, storage and computing capabilities, artificial intelligence (AI) has developed rapidly, which is profoundly affecting and changing our lives and shaping the future. Artificial intelligence is profoundly changing the relationship and interaction patterns between humans and between humans and the natural environment and society. It helps human beings solve various high complexity and uncertainty problems in various fields of engineering technology, scientific research and social activities. It brings many disruptive innovations in many fields.
The long-term goal of artificial intelligence is to make machines learn and think like humans. The most important ability of humans is to learn new things and have self-adaptation and knowledge reasoning abilities beyond experience. Introduce human cognitive abilities or human-like cognitive models into artificial intelligence systems to develop a new form of artificial intelligence, namely hybrid augmented intelligence.
The R&D team of WIMI (NASDAQ: WIMI) is developing a hybrid enhanced intelligence system based on human-computer collaboration, which combines human perception and cognitive capabilities with computer computing and data storage capabilities to build a hybrid system based on human-computer collaboration. Enhance the intelligent system, which will improve the decision-making ability, cognitive complexity and adaptability of the artificial intelligence system to deal with problems.
A hybrid augmented intelligence system based on human-computer collaboration covers the functions of a computable interaction model, including dynamic reconstruction and optimization, autonomy and adaptability during interaction, interactive cognitive reasoning, and evaluation, etc., and can effectively realize human-computer communication. It integrates machine learning, knowledge base and human decision making. It uses machine learning to learn a model from training data, or a small number of samples, and uses that model to make predictions on new data. When confidence is low, humans intervene to make judgments. The confidence estimate or the state of the computer's cognitive load will determine whether the prediction requires manual adjustment or human intervention, and the system's knowledge base will be automatically updated. Human predictions and interventions in algorithms improve the accuracy and credibility of the system.
The introduction of human intelligence into the artificial intelligence system can realize the tight coupling between the advanced cognitive mechanism and the machine intelligence system. The two adapt and cooperate with each other to form two-way information exchange and control. By integrating human perception, cognitive ability, machine computing and storage capabilities, and then processing large-scale, incomplete and unstructured knowledge base information, avoiding the risk of loss of control brought about by artificial intelligence technology.
Integrating the perceptual advantages of computers in processing large-scale data and the cognitive advantages of human reasoning and decision-making. With computer computing as the core, enhance people's understanding of complex data, use human reasoning and auxiliary decision-making support to enhance the computer's cognitive learning ability, and implement information perception, understanding, reasoning, prediction, decision-making and learning process.
Relying on artificial intelligence algorithms for rapid identification and understanding, and maximizing the computing potential of "machines", and relying on timely and appropriate artificial reasoning, prediction and decision-making, it can effectively enhance the accuracy and reliability of system cognition, and maximize the It has great potential to give full play to human cognitive advantages, greatly improve the ability of situation estimation, and provide solutions for large-scale cognitive task coordination. Human-machine collaborative decision-making may lead to more valuable solutions and innovations.
In the future, WIMI will continue to develop cognitive reasoning, emotional interaction and auxiliary decision-making hybrid enhanced intelligent applications of human-machine collaboration. Its hybrid enhanced intelligence system based on human-machine collaboration will have a wide range of applications in the fields of game entertainment, advertising media, enterprise management, and smart cities. For example, in the field of game entertainment, technologies such as augmented reality and virtual reality are used to enhance human participation by superimposing the real scene of the user and the virtual scene of the game, which promotes the development of the game industry. In the advertising media industry, social platforms and shopping websites can introduce human-machine collaborative hybrid enhanced intelligence systems to push relevant information to users more effectively and accurately through personal preference analysis.
In the field of enterprise management, the human-computer collaborative hybrid enhanced intelligent system can create a human-computer interaction environment that supports learning, understanding, reasoning and decision-making, which can greatly improve the risk management capabilities of modern enterprises, and provide application solutions for large-scale workflow coordination solutions to enhance its value creation and enhance corporate competitiveness.
Ubiquitous computing and intelligent machines are driving people to seek new artificial intelligence models and implementation forms, and hybrid augmented intelligence is one of the important directions of artificial intelligence development. Human-machine cooperation and mutual complementarity can maximize the potential of artificial intelligence systems at the current level of technology and move towards deep human-machine integration, which will bring valuable creativity and improve the competitiveness of humans and machines. Intelligent machines have become intimate companions of human beings, and the interaction and collaboration between humans and intelligent machines will become the norm in our future society.
WIMI (NASDAQ: WIMI) develops a virtual wearable system based on Web3.0 technology.
Source
https://cj.sina.com.cn/articles/view/7651844612/1c815e20402001fyx6?from=finance
March 6, 2023
With the rapid development of e-commerce, online shopping has become very common. More and more consumers, especially students and office workers, are used to buying clothes, shoes, hats, accessories, cosmetics, etc. online. The change of consumption habits has promoted the upgrading of the consumption market, but at present, our online shopping system is still at the stage of flat display, which is different from the offline shopping experience, and users can only imagine the effect after use, which also causes some problems. People's shopping troubles, selection difficulties, and product returns.
WIMI (NASDAQ: WIMI) develops a virtual wearable system based on Web3.0 technology, which consists of a display module, a product control module, a product selection module, a product simulation module, an interaction module, a transaction system module, an information statistics module, and a sharing evaluation system The modules constitute a complete holographic virtual wearable system.
WIMI holographic virtual wear system can improve the overall shopping experience. Based on Space Web of Web3.0 technology, retailers can create a new virtual shopping experience. Users can try on clothes, cosmetics and accessories virtually, and interact with products in a virtual environment . For example, customers can use virtual reality technology to try on clothes, shoes, jewelry and cosmetics before purchasing, and view the effect after trial through 3D holographic technology in an online virtual way.
The WIMI holographic virtual wearable system reserves two experience technology entrances for users: real person try-on entrance and virtual try-on entrance.
Real-life try-on users can integrate and display the 3D holographic product model and user image through the camera. The product control module is responsible for adjusting the position, size and angle of the 3D holographic model of the product, obtaining the user image in the scene, and then reading the product. 3D holographic model, and integrate and display the 3D holographic model of the product with the user's image.
Virtual try-on, the user can upload a photo, the system can generate a set of user's holographic 3D digital model information, and wear and match on the user's 3D holographic digital model, you can see the product on the body without trying it on yourself Combine and move the situation.
In order to make the product model more realistic, WIMI hologram adds more detailed simulation effects such as texture, light and shadow. For example, clothing adopts texture mapping technology, by drawing a variety of different texture maps for the same clothing model to imitate different colors, patterns, materials, etc. In this way, multiple pieces of clothing with different colors, patterns and materials share one model, which can greatly reduce the cost of clothing model manufacturing and save the storage space of the somatosensory virtual system.
WIMI Holographic (NASDAQ: WIMI) virtual wearable system will be based on Web 3.0 and artificial intelligence (AI) technology, through data decentralization, distributed ledgers, smart contracts, etc. to effectively protect system security and user privacy, focusing on creating a A more decentralized and secure internet that addresses some of the issues associated with online shopping, such as fraud and privacy concerns. And improve the user's trial experience through semantic Web, AI, ML (machine learning), etc.
Data decentralization:
WIMI Hologram is based on the Web 3.0 virtual wearable system and supports a decentralized architecture, which means that data and applications are not controlled by a single centralized organization. This can provide greater security for online shopping and reduce the risk of data breaches.
Distributed ledgers:
Distributed ledgers can be used to provide a more secure and transparent payment system for online shopping. This provides better protection against fraud and chargebacks, and reduces payment processing times.
Smart contract:
WIMI Hologram is based on the Web 3.0 virtual wearable system, which can use smart contracts in online shopping. This is an automatically executed contract. The terms of the agreement between the buyer and the seller are directly written into the code line, and the smart contract can automatically complete online shopping. Many tasks that are typically done manually in the web server, such as payment processing and order tracking.
Semantic Web:
Create the Semantic Web, which means data is structured in a way that is easily understood by humans and machines. This can provide customers with a more personalized shopping experience and improve the accuracy and relevance of search results. For example, chatGPT can be understood as the prototype of the Semantic Web, enabling better interaction and understanding between the Internet and people.
Artificial intelligence and machine learning:
Use AI and ML to provide a more personalized shopping experience, improve the accuracy and relevance of search results, and provide the most suitable match based on user needs. AI, ML techniques can also be used to detect fraud and predict consumer behavior.
WIMI(NASDAQ: WIMI) based on Web 3.0 virtual wearable system can bring more convenience to customers and retailers. Users get a better try-on experience through the system to make the best purchase decision, while retailers can save on physical inventory and storage space costs, and reduce returns. In addition, WIMI holographic virtual wearable system can provide customers with a more personalized shopping experience, thereby improving customer satisfaction and loyalty. And WIMI WIMI Hologram's Web 3.0-based virtual wearable system enables users to better control their data and personal information through the setting of decentralized distributed ledgers, and can purchase products more securely and privately without worrying about data leakage or misuse. Provide more transparency and accountability in online transactions. Reduce incidents of fraud and build more trust between buyers and sellers, improving the online shopping experience and safety.
WIMI.US, a new force in lidar concept stocks, makes efforts to overtake on curves.
Source
https://finance.sina.com.cn/jjxw/2023-03-02/doc-imyinimr7806386.shtml
March 2, 2023
With the development of automobile intelligence, the global lidar industry is actively undergoing changes, hoping for a longer-term development.
Why do car companies favor lidar?
When it comes to autonomous driving, the battle between pure vision and radar systems continues. In recent years, new domestic forces have used lidar. Generally speaking, laser radar is vehicle-mounted laser radar, a radar system that uses laser light as a detection method to detect the position, speed and other characteristics of the target by emitting light beams.
Lidar is known as the "eye" of a smart car. Its core advantage is to use the high-frequency characteristics of lasers to measure a large number of high-speed position and speed information to form accurate and clear 3D modeling of objects. Since Velodyne applied lidar to the DARPA driverless car challenge, it brought lidar into the field of autonomous driving for the first time. Since then, with the continuous development of downstream applications such as ADAS, the industry has ushered in great development.
The "burst year" of lidar in 2023
Starting from 2021, car companies have gathered together to announce that lidar will be "on the car". By 2022, many models equipped with lidar will begin mass production and delivery. The outside world also calls 2022 the "first year of mass production" of lidar. From cost reduction, to mass production and delivery, to the "explosion" of lidar, many people in the industry have regarded 2023 as the "explosion year" of lidar.
In terms of market prospects, some companies predict that the automotive ADAS lidar market will usher in rapid growth in the next five years, with an average annual compound growth rate of up to 73%. By 2027, the global lidar delivery volume is expected to reach 5.3 million units, and the ADAS lidar market size will increase to US$2 billion. Obviously, lidar is moving from the stage of technological breakthrough to the stage of mass production and on-board vehicles.
Behind the growth space is the new energy vehicle market that has continued to explode in recent years. Advanced automatic driving has become the "future" of automobile development, and lidar is an indispensable sensor in automatic driving systems. Therefore, although the L4/L5 level of autonomous driving has not been implemented quickly, consumers have already expected autonomous driving. In order to meet the market demand, car companies have also proposed new concepts on the level of intelligent driving, such as L3.5 level, etc. When smart cars move from L2 to L3 and L4, the speed of LiDAR will naturally increase simultaneously.
Broad market prospects
In addition, it is precisely because of the broad expectations for the prospect of the lidar market that the world's leading provider of holographic AR application technology WIMI (WIMI.US) bravely enters the autonomous driving and lidar market with technological innovation, and urgently needs to tap the market potential. In order to seize the era when the automatic driving window is on the rise, WIMI has invested in research and development in the field of lidar in advance, which has greatly increased the company's long-term corporate competitiveness.
In terms of actual actions, WIMI has been closely connected with the automotive industry in the fields of intelligent manufacturing transformation, intelligent vehicle research and development and application, new energy and intelligent vehicle application and promotion. A long time ago, after obtaining the patent of the 3D holographic pulse laser processing device for optical holography, and customers in many industries showed strong market demand, WIMI immediately developed the 3D holographic pulse laser radar product "WiMi HoloPulse LiDAR" to further expand the company's radar product portfolio matrix.
According to the information, WiMi HoloPulse LiDAR is a multifunctional holographic pulse lidar sensor with a unique scanning mode, which is small in size and light in weight. Comes with a point cloud interface, no need to connect an additional adapter box during operation. This LiDAR solution provides software development kits that are matched with hardware products, including functions such as target detection, classification, and counting. System (ADAS), traffic management, etc. provide solutions.
It is reported that after years of intensive cultivation and development, WIMI has accumulated profound experience in core components, smart chips, and lidar perception based on depth science, and has built a closed loop of the three core technologies of lidar hardware, AI algorithms, and semiconductors. , has become one of the more prominent companies in the lidar industry. WIMI provides an integrated solution of "hardware + software", gradually expanding its business to the field of autonomous driving. Considering the popularity of smart driving in the future, and lidar may be the standard sensor for smart driving, this is also a big market, and the penetration rate of WIMI will increase significantly in the future.
end
In today's competition in the smart car market, greater opportunities spur greater competition. There is no doubt that lidar is the future development direction of the industry, and it is also the development direction of the autonomous driving industry. However, the next test for lidar companies is still the speed, endurance and rhythm of this marathon, and the end of the market is far from coming.
WIMI develops a holographic building model reconstruction algorithm based on oblique photogrammetry point clouds.
Source
https://t.cj.sina.com.cn/articles/view/1765776051/693f9ab3020010t94?from=tech
February 27, 2023
The process of urbanization is developing rapidly all over the world, and large-scale and super-large-scale cities are still expanding and developing, posing constant challenges to the construction of public services in urban management. With the development of technology and technology, smart cities have been proposed and put into practice in recent years. With the application of urban big data and urban physical space technology, it is possible to construct urban holographic 3D overall data. WIMI Holographic Development A holographic 3D building model reconstruction algorithm based on oblique photogrammetry point clouds, which can help city managers make better use of urban space, and make the most reasonable construction and planning and effective management.
3D models of buildings can be divided into multiple levels of detail with different geometric and semantic information for different application levels. Models that distinguish between building roofs and facades constitute the structural system data for smart cities and are most widely used in urban construction and management. With the rapid development of aircraft and sensors, point cloud has become the main data for 3D urban reconstruction, and automated 3D urban reconstruction has been realized at the same time. As an important means of 3D point cloud data acquisition, laser radar technology (LiDAR) can directly obtain the position of the target, eliminating the complicated process of solving image correspondence, and has been widely used in urban 3D building reconstruction. However, airborne laser scanning ALS Building facades are often missing from the data, especially for tall buildings.
WIMI's holographic building model reconstruction algorithm based on oblique photogrammetry point cloud, combined with photogrammetry point cloud from aerial oblique images and 2D footprints of buildings, photogrammetry point cloud can be combined with structure in motion (SFM) and multi-view Holographic Stereoscopic (MVHS) pipeline for fully overlapping image generation. Oblique photogrammetry point clouds to reconstruct architectural models. Photogrammetry involves creating a 3D model using photos. By tilting a point cloud to capture a set of 3D points from different angles, by using a point cloud captured from multiple angles, a more accurate holographic 3D model of a building can be created.
In the preprocessing step of WIMI's holographic building model reconstruction algorithm based on oblique photogrammetry point cloud, the vertical plane is extracted from the point cloud, and then projected onto the coordinate plane to generate the line structure of the building. Afterwards, the footprint data is brought in and precisely aligned with the point cloud in the coordinate plane, since differences in origin and representation between the two data types inevitably lead to positional bias. Using line features as primitives is the preferred alternative to two-based data representations.
- In the first stage, the floor plan of the building is constructed using the footprint data of the building generated from the point cloud and the line structure of the building. Reorient edges based on footprint and filter based on spatial consistency.
- In the second stage, for each edge in the plan layout, the elevation points lying on it are projected onto its vertical plane, resulting in a point density distribution. The optimal profile for each edge is then generated through clustering, regularization, and binary integer programming functions. Finally, WIMI WIMI Hologram's holographic building model reconstruction algorithm based on oblique photogrammetry point cloud generates a 2D topology from the combination of plane layout and outline to reconstruct the holographic 3D model of the building. Once a holographic 3D urban building model is created, it can be used in various smart city applications such as urban planning, disaster response, and facility management.
WIMI's holographic building model reconstruction algorithm based on oblique photogrammetry point clouds can greatly optimize the construction of urban holographic 3D models and provide a more efficient and convenient solution for urban model reconstruction. Urban planning and construction use the model to visualize and analyze impacts.
This helps optimize land use, infrastructure planning and transportation systems. Such as urban traffic management, reconstruction through this technology can be used to create detailed maps of traffic patterns and congestion, which can help city authorities optimize traffic flow and reduce congestion. In terms of urban public safety, reconstruction through this technology can be used to create holographic 3D models of public spaces such as parks and streets, which helps identify potential safety risks such as blind spots and dark areas. This information can be used to optimize lighting and surveillance systems to improve public safety.
In general, WIMI (NASDAQ: WIMI)'s holographic building model reconstruction algorithm based on oblique photogrammetry point cloud provides a more efficient processing solution for urban models through surface reconstruction, texture mapping, point cloud registration, etc., and improves urban holographic The update efficiency of 3D models can be used to optimize urban planning, improve infrastructure management and improve the quality of life of residents, playing a key role in the development of smart cities.
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