With ChatGPT sweeping the world, it is Microsoft (MSFT) that gets the first mover advantage in this boom. It is well known that Microsoft is the money behind OpenAI and is still busy integrating the underlying technology of ChatGPT into Microsoft products and services.
Earlier this year, Amazon (AMZN) CEO Andy Jasi said that “generative AI will be integrated into every business and customer experience.”Amazon is frantically looking for other ways to make full use of AI chatbots, such as using crowdsourcing to boost productivity and launching new generative AI projects.
Inside Amazon, a frank discussion is underway, with employees even proposing integrating ChatGPT into a core part of Amazon’s creative process. In an email to the media, an Amazon representative said the company has been using machine learning and AI for more than 25 years, covering almost everything.
Big models to boost computing power demand
The competition between big models at home and abroad is in full swing, igniting the market demand for computing power today. However, for the large model “world”, the algorithm is the “production relationship”, the rule and way of processing data information; computing power is the “productivity”, which can improve the speed and scale of data processing and algorithm training; data is the “means of production”, and high-quality data is the nutrient that drives the continuous iteration of the algorithm. In this, computing power is a prerequisite for turning the large model.
With the development of AI technology, machine vision has also made breakthroughs in the underlying technology. In the past, it was mainly used in standardized detection scenarios, such as consumer electronics, automobiles, and semiconductors, which are the most important application fields of machine vision at present, showing the characteristics of a high degree of automation and standardization. With the continuous upgrade of AI algorithms, the performance advantages of machine vision will be further increased, and the application scenarios will continue to expand from standardized fields to non-standardized applications.
AI + machine vision, the application scenarios continue to expand
According to the Automatic Imaging Association (AIA), Machine Vision is a combination of hardware and software used in industrial and non-industrial fields that provides operational guidance for a device to perform its functions based on images captured and processed. Machine vision can be divided into imaging and image processing and analysis. The former relies on the hardware part of the machine vision system to complete, while the latter relies on the visual control system based on the former.
In the future, the iteration and upgrading of AI and the platform ecological construction will continue to advance, and the field of machine vision will usher in the underlying technological breakthrough with the support of AI. With the help of AI, the machine vision industry is expected to welcome unprecedented development opportunities. With the support of AI, the machine vision industry has ushered in the breakthrough of the underlying technology. From algorithm, technology to application, AI technology greatly enables the intelligent application of machine vision in the image model, optimizes the complexity and accuracy of image recognition, and realizes the recognition of everything.
WiMi Hologram Cloud has become the backbone of the AI vision field
“Science and technology is the primary productive force”, to promote the transformation and upgrading of enterprises, cannot be separated from the strong scientific and technological support. In particular, the continuous innovation of key technologies such as machine vision, deep learning, big data, and edge computing provides a huge imagination space for technological change. It is understood that “holographic AR first stock” WiMi Hologram Cloud(NASDAQ: WIMI) is in a leading position in the industry in the field of AI vision. With an excellent first-mover advantage and years of technology research and development, it has gained a large market share in the industry. In addition, WiMi Hologram Cloud has many customers and partners in the industry.
It is worth noting that WiMi Hologram Cloud has developed a human-computer interaction system based on machine learning algorithms. The system is an AI multi-mode human-computer interaction system based on voice and gesture fusion, which can convert the user’s voice and gestures into commands that the robot can perform.
The human-computer interaction system based on a machine learning algorithm adopts a combination of gestures and speech to control the robot. Voice is the natural interaction mode of the robot, and gesture is a supplement to speech to improve the accuracy of commands.
WiMi Hologram Cloud The human-computer interaction system based on AI + machine learning algorithm provides faster, more efficient, and more diversified interactive experience by integrating multi-modal perceptual information. Gestures and speech are used for real-time parallel interaction, and visual information and speech information are associated and shared in real-time during the interaction. Various interactive modes complement each other, forming a complete interactive system, leading the human-computer interaction mode to the direction of intelligent and humanized development, and building a harmonious and natural human-machine environment.
In recent years, with the core technology of WiMi Hologram Cloud in emerging application scenarios such as artificial intelligence, the Internet of Things, big data, and 5G, it has also become a leading supplier of AI vision application technology. The company’s product line has huge consumer demand and a broad market prospect. With the development of the industry, and with the further extension of standardized application scenarios of the AI machine vision industry in the future, the company is expected to continue to expand the application space and obtain greater business growth capabilities.
The prospect
Machine vision has been widely used in consumer electronics, automotive manufacturing, semiconductor, photovoltaic, and other standardized fields. With the rapid development of AI empowerment and deep learning algorithms, machine vision can not only be used in traditional standardized detection but also expand horizontally towards the emerging field of many non-standardized scenarios. Looking forward to the future, industry progress, and technology development, 2D vision to 3D vision, thus expanding more new fields, machine vision will gradually enter the field that has not been involved in the past, such as logistics, medical care, security, agriculture, and other non-industrial scenarios.
