Global Soul Limited Company News

In recent years, the development of artificial intelligence has advanced by leaps and bounds, and with the continuous progress of technology and the continuous expansion of application scenarios, it has gradually penetrated into the field of industrial visual inspection; The deep learning AI algorithm with higher computing efficiency and higher detection rate came into being, which makes up for the shortcomings of traditional algorithms that cannot detect complex features, and realizes the quality and intelligence of enterprise production to a greater extent. What is AI deep Learning Algorithm Deep Learning is an important branch of machine learning. It mainly imitates the way human brain analyzes and processes information, trains machines to extract common patterns among these instances in case learning, draws a deep learning model containing features and expressions in data, and automatically learns the mapping relationship from input to output from data. It helps to quickly classify the acquired information in the future.   Intelligent upgrade AI technology enables AOI visual inspection Based on the deep learning algorithm, the company independently developed a new visual AOI detection equipment. On the basis of the traditional detection method, the AI deep learning algorithm realized the auxiliary programming of AOI, omitting the steps of the traditional manual frame debugging, which greatly simplified the programming process; At the same time, it has a more intelligent detection ability, which can accurately locate and classify different forms of solder joints and various types of welding problems, and can also detect characters on the components, eliminate the interference caused by blur or light, and accurately identify characters.   Jingtuo AOI visual inspection equipment diagram Now it has been widely used in SMT, THT, and other process production lines.   SMT production line THT production line Auxiliary programming With the help of deep learning algorithm, the AI model is generated by importing different forms of picture data for training, and the location of the measured object is accurately located in each detection, and the measured object can be automatically classified according to the training data.     Automatic solder joint identification Intelligent detection Through the AI deep learning algorithm, the characteristic information of the defect is identified and the problem type of the detected object is correctly judged.     Intelligent identification of welding problems OCR(Optical Character Recognition) Character detection is a form of detection that utilizes deep learning, and in the industrial world, character recognition is a machine vision task that involves extracting text from images. Jintuo AOI visual inspection equipment with pre-training font library, quickly identify picture information.     OCR character recognition In the review process, the deep learning system can perform a second review of the AOI test results, effectively avoid errors in the manual review and lead to quality instability, reduce the manual review workload, and increase the straight-through rate of the production line by 5%-10%.       Intelligent review diagram Since the introduction of deep learning algorithm in AOI vision inspection equipment, production efficiency and inspection flexibility have been effectively improved; The innovative development of visual inspection has promoted the development of lithium batteries, consumer electronics, automobiles, aerospace and other fields to intelligent manufacturing. In the future, Jingtuo will continue to focus on cutting-edge technologies, launch products that meet market trends and needs, and help the automation and intelligent upgrading of the manufacturing industry. Relevant recommendation

With the increasing influence of PCBA components on the external environment such as physical damage, chemical corrosion, wet oxidation, electrical short circuit and dust, this makes the performance requirements of PCB in electronic products further improved, the three anti-paint coating process is an important process in the production of electronic products, by coating a thin layer of insulating protective layer on the surface of PCB board. Isolate electronic components from the external environment. At present, PCB board coating three anti-paint has become a general trend, in communications, automotive, military electronics, aerospace, medical electronics and other industries are widely used; It can greatly reduce the repair situation, improve the quality of circuit boards and components, and effectively improve the safety, durability and reliability of electronic products. Veneer coating line: high efficiency production, high quality technology Most of the traditional veneer coating lines on the market use tunnel horizontal furnaces, which generally have problems such as large footprint, high energy consumption, low performance, and unstable quality, and can not meet the needs of the new era of factory heating and curing equipment in production and operation. In view of the drawbacks of the horizontal furnace, the company has devoted itself to designing a new coating line process plan, replacing the horizontal furnace with the vertical curing furnace, which has the characteristics of high automation, high production efficiency, low energy consumption, and saving labor costs     The process diagram of veneer coating wire body Compared with the traditional line body, it saves 40% of the floor space, improves the production efficiency by 50%, and is more suitable for the production capacity of the factory.   Precise temperature control The curing furnace has 6 groups of independent heating modules, each module has independent temperature control, and the temperature in the furnace is stable, which makes the baking and curing performance better and ensures nearly perfect quality.   Temperature test diagram Run smoothly The single-layer load inside the furnace chamber can reach 30kg, and the imported optical fiber sensor is used to accurately locate the product position and ensure the smooth operation to the maximum extent. Internal ascent operation indication Jintuo shares: hand in hand, to the future Through the effective management of each link, to achieve independent research and development, independent production. Vertical curing furnace has also gained the unanimous praise and support of the head communication technology company, which reflects the customer's affirmation of the product strength, and also represents the recognition of the market and customers for the comprehensive strength of Jingtuo in the field of electronic thermal engineering.

Development of nitrogen applications   In the early 1970s, nitrogen was found to be able to create an inert environment, effectively preventing the reaction with oxygen, and it was gradually used in the field of electronics manufacturing; With the rise of surface mount technology (SMT) in the 1990s, welding quality and reliability were inseparable from low-oxygen environments, and manufacturers began to standardize the use of nitrogen in reflux processes. Today, the trend of miniaturization and precision of electronic components continues to drive the demand for nitrogen applications, and nitrogen reflow has long been the preferred configuration in high-quality electronics manufacturing.   How to achieve accurate nitrogen flow control   The nitrogen closed loop system is an automated control system used to control the oxygen concentration range within the required PPM value during the welding process, ensuring a low or no oxygen environment in the welding.   ▲ Write the PPM value to be controlled in the nitrogen setting interface The control value is then written into the oxygen separator     ▲ Proportional valve closed-loop system controls the nitrogen flowmeter The nitrogen input can be adjusted without manual operation     The nitrogen closed-loop system effectively avoids nitrogen consumption and cost increase due to inaccurate nitrogen control flow rate. And frequent adjustment of welding parameters caused by rework, thereby reducing production efficiency.       ▲ PPM change curve: When the input set value is 500 The control accuracy of the full closed-loop control sampling oxygen separator is effectively controlled within the range of ±50ppm     The actual process improvement brought about by low oxygen environment   In practical applications and tests, the following welding processes can be improved by using a nitrogen closed-loop system.   Finer crystal structure   The solder joint surface is bright   Reduce fine-pitch bridging   Reduce oxidizing spot welding   Cavity rate reduction     At present, the KT series reflow welding has realized the quantitative control of nitrogen in the whole process, and the independent closed-loop control of each temperature zone, so that the oxygen concentration range is controlled in 50-200ppm     ▲KT full series nitrogen consumption diagram   The nitrogen closed-loop system significantly improves the stability and reliability of the welding process. We firmly believe that with continuous technological progress and process optimization, we can continue to maintain advantages in the fierce competition and provide customers with higher quality products and solutions.

In the production process of the electronic manufacturing industry, the uncleaned residue on the pcb will indirectly affect its short-term and long-term functional reliability, ‌ residue will gradually harden and form metal halate and other corrosion with time, ensuring the cleanliness and cleaning timelessness of the pcb is a link that cannot be ignored in quality improvement.   ▲ There are tin beads between the solder joints of each small board   01 Tin bead cleaning machine details - functions and characteristics   In order to meet the requirements of automatic cleaning after welding, Jingtuo launched a tin bead cleaning machine, the general standard configuration is composed of two modules: transmission and cleaning. By connecting and selecting the welding equipment programming device, each welding spot can be programmed in turn, and the cleaning module can complete the cleaning of each welding spot.   X/Y/Z axis movement, separate cleaning parameters Tin bead cleaning machine: integrated with selective welding   Brush head diameter 10mm-30mm optional, flexible, to meet the cleaning needs of different scenarios The large brush head has a wide coverage, can carry out a comprehensive cleaning work, easily reach and clean up a large area, accelerate the cleaning process, and its design can effectively prevent tin beads splash, protect the surrounding environment from pollution.   The small brush head focuses on high-precision cleaning, removing hard-to-reach stains and residues in subtle places, especially when cleaning small gaps in precision instruments, leaving no dead corners.   The combination of the two not only improves cleaning efficiency, but also ensures a high standard of cleanliness, helps the production process proceed smoothly, and ensures product quality and safety.   02 Selective wave soldering - the complete process from operation to cleaning   Selective wave welding is modular design, flexible configuration, can be freely expanded, connected with tin bead automatic cleaning machine as a cleaning module in the selection of welding, to achieve spray, preheating, welding, cleaning integration.     Spray module system       Used for flux spraying to prevent oxidation of liquid solder and heated metal in contact with oxygen in the air; Precision spray flux system with rosin spray detection function and rosin flow monitoring can be configured with two independent spray modules, spray width up to 2~8mm, programmable spot spray and line spray. Preheating module system       After the PCB board is sprayed with flux, it will reach the preheating zone to heat and activate the flux. The preheating module is mainly equipped with the top hot air and the bottom infrared heater, and the power heating mode is also configured for the PTH complex process PCB. To ensure efficient, safe and uniform heating.   Welding module system     After entering the welding zone from the preheating zone, the machine will position the pcb and start welding. The welding module is driven by electromagnetic pump. It can be configured with double tin cylinder to meet the production demand. At the same time, it has nitrogen protection to ensure durable and reliable welding.   Tin bead cleaning module system     After the welding is completed, the cleaning module will clean the residual tin beads on the welding plate. The roller brush was used to clean the solder bead of PCB solder pad. Through software control, components are positioned and cleaning parameters are controlled. The cleaning parameters of each solder joint can be set independently to achieve point-by-point cleaning of each solder joint, and can be repeated cleaning, repeated positioning accuracy up to ±0.15mm.   03 Customer case: Welding quality display -- practical application and results   Selected welding spray, preheating, welding, cleaning modules work together to achieve a high-quality production process, in practical application cases, after welding products in appearance or performance, can meet customer expectations. Application scope is not limited to: military electronics, aerospace ship electronics, automotive electronics, digital products and other high welding requirements and complex process of multi-layer PCB through hole welding.   PCB cleanliness high PTH solder joint dialysis 100%   By introducing automatic cleaning technology for tin beads, we not only take into account the cleanliness of the production line, but also ensure the enhancement of welding quality and product reliability. Looking forward to the future, Jintuo will continue to uphold the spirit of innovation, constantly broaden the horizon, in-depth exploration of diversified application scenarios and emerging market opportunities, and is committed to transforming cutting-edge technology into an inexhaustible driving force for the vigorous development of the electronics manufacturing industry.

SPI: Software and hardware collaborative upgrade, suitable for silver pulp printing detection! Intelligent vision leads the future of detection 01 Using DLP digital raster projectors - high precision imaging, diverse algorithms The traditional mechanical grating projectors have limited accuracy and insufficient flexibility in detection. In practical applications, SPI using DLP optical structure projectors has the ability of high speed, high resolution and high contrast detection. Range optimization: When the solder paste height is greater than the range range, there will be a situation where the imaging does not match the actual height.       After the upgrade, the measuring range is upgraded from 0-600um to 0-1100um, with a large measuring height range and high imaging restoration degree. Beautiful image   After image beautification, 3D point cloud has no obvious sawtooth and has better sinusoidal property   02 One person multi-machine remote review - saving labor costs   Solder paste test will be checked by statistical Process Control (SPC) tool to predict the solder paste printing process trend. This SPI model upgrade rewritten SPC software to realize one person control multiple machines, save labor costs, make the production process smoother and improve the overall production efficiency. Before the upgrade: Each device on the production line is separately equipped with a computer, and a corresponding number of operators are required to conduct real-time data monitoring, recording and exception processing.   After the upgrade: The "one-to-one" monitoring method has been changed, and only one person can centrally monitor and manage data.   03 Optimize the zero plane calculation method -- adapt to complex application scenarios   The calculation method of zero plane is very important to ensure the accuracy of detection. The traditional SPI system may face the problem of zero plane misjudgment caused by complex scenes such as impurities around the solder paste, background color, reflectivity and geometry, which will affect the precision of solder paste detection.       04 Customer case: Detection imaging display -- silver pulp printing detection   The application of SPI technology to the detection of silver paste printing is also a highlight of this innovative application. Silver paste is a key material connecting substrate and chip. The upgraded SPI height detection accuracy (correction module) is 1um, and repeatability (volume/area/height) is

Production standard 1. Appearance quality standard Joint smoothness: The joint should be flat, without obvious bumps, wrinkles or warping. No air bubbles or impurities: There should be no air bubbles, foreign objects or glue residue in the joint. Edge alignment: The edges of the two sections of tape should be aligned, the width is the same, and the deviation is usually not more than ±0.1mm. Uniform tape coverage: If the receiving tape is used, the tape should completely cover the joint, and there is no offset or leakage. 2. Dimensional accuracy standard Width consistency: the width of the material belt at the seam should be consistent with the raw material belt, and the deviation should not exceed ±0.1mm. Thickness consistency: The thickness of the joint should be consistent with the raw material belt, avoid being too thick or too thin, usually the deviation does not exceed ±0.05mm. Length error: the total length after feeding should meet the requirements, and the error is controlled within ±1mm. 3. Mechanical performance standards Tensile strength: The tensile strength at the joint should reach more than 90% of the raw material belt to ensure that it will not break during the production process. Flexibility: The joint should have a certain degree of flexibility and be able to withstand a certain amount of bending and stretching without cracking. Peel strength: If the tape is used to connect, the peel strength between the tape and the material should meet the requirements, usually not less than 2N/mm. 4. Electrical performance standards (if applicable) Electrical conductivity: If the tape is used for electronic components, the resistance at the joint should be consistent with the raw material tape, with a deviation of not more than ±5%. Insulation: If the tape needs insulation, there should be no leakage or short circuit at the joint. 5. Environmental adaptability standards Temperature resistance: The joint should be able to withstand temperature changes in the production environment, usually requiring no failure within a certain temperature range (such as -20 ° C to 80 ° C). Moisture resistance: The joint should have a certain moisture resistance to avoid opening or failure in a high humidity environment. Chemical resistance: If the tape comes into contact with chemicals, the joints should be resistant to chemical corrosion. 6. Process consistency standard Connection position: The connection position should meet the process requirements and avoid connection in key areas (such as the location of precision components). Receiving length: the length of the receiving belt should meet the production requirements to avoid too long or too short affecting the production efficiency. Frequency of connection: minimize the number of connection times to avoid frequent connection affecting the overall quality of the material belt. 7. Reliability test standards Tensile test: Tensile test is performed on the joint to ensure that it can withstand the tension during the production process. Bending test: Perform multiple bending tests on the joint to ensure that it does not crack or fail. Burn-in test: Simulate a long time use environment to test the durability of joints. 8. Record and traceability standards Receiving records: record receiving time, operator, materials and tools used for easy traceability. Quality inspection record: record the quality inspection results of each receiving material, including appearance, size, strength and other data. 9. Safety and environmental standards Material environmental protection: Bonding tape and glue should meet environmental requirements and do not contain harmful substances (such as RoHS standards). Operation safety: Tools and materials used in the feeding process should meet safety standards to avoid injury to operators.

1. Prepare Material inspection: Ensure that the material of the material belt and the material receiving belt is consistent, and the parameters such as thickness and width meet the requirements. Tools: Prepare the tools required for the material connecting belt, such as scissors, adhesive tape, pliers, and hot press. Clean working area: Ensure that the working area is clean to avoid dust or impurities affecting the quality of the material. 2. Cut material belt Cutting Angle: The material belt is usually cut at a 45 degree Angle to increase the contact area and improve the connection strength. Cutting accuracy: Ensure that the cutting edge is smooth to avoid burrs or unevenness. 3. Butt tape Align the strips: Align the two strips precisely to ensure the same width and thickness. Fixed material belt: Use receiving pliers or jigs to fix the material belt to prevent movement. 4. Connection mode Adhesive tape connection: Use special adhesive tape to bond the two sections of material tape. Make sure the tape covers the entire joint and apply appropriate pressure to ensure a strong bond. Hot pressing connections: For connections requiring higher strength, a hot press can be used for hot pressing. Make sure the temperature and time are set properly to avoid overheating or underheating. Ultrasonic welding: suitable for some special materials, through ultrasonic vibration to generate heat, so that the material is welded together. 5. Check and test Appearance inspection: Check whether the joint is smooth and there are no bubbles, wrinkles or unbonded parts. Strength test: Tensile test is performed to ensure that the joints can withstand the tension during production. Electrical testing (if applicable) : If the tape is used for electronic components, perform an electrical connectivity test to ensure that the joint conducts electricity well. 6. Record and mark Record receiving information: record receiving time, operator, materials and tools used for easy traceability. Mark the joint position: clearly mark the joint to facilitate subsequent process identification and processing. 7. Safety precautions Operation safety: Pay attention to safety when using tools to avoid cuts or burns. Environmental safety: Ensure that the working area is well ventilated, especially when using glue or hot pressing, to avoid inhaling harmful gases. 8. Follow-up Procedure Storage conditions: The connected material belt should be stored in a dry, dust-free environment to avoid moisture or pollution. Pre-use inspection: Before using the connected material belt, check the joint again to ensure that there are no quality problems. Through the above steps, you can ensure the quality and reliability of the material and tape joint to meet the production needs.

"During the Spring Festival alone, nearly 100 investment institutions asked people to introduce them to see if there was an opportunity to invest in DeepSeek." In the face of the phenomenon of DeepSeek, a large model released by domestic AI companies, an angel investor admitted to the Surging news reporter, "We need to think about why projects like DeepSeek were previously missed by us." DeepSeek technology boom triggered a global shock, the stock prices of many technology giants on the other side of the ocean plunged, and artificial intelligence leader Nvidia fell 4.3 trillion yuan in market value overnight. "DeepSeek does not have a promotional budget, nor does it have an annual salary of 10 million people, it is a clear goal to invest in research and launch products." The above investor comments. Another large model unicorn told reporters that "DeepSeek founder Liang Wenfeng is a person with AI beliefs, and the technical romanticism he insists on is very well-known in the industry." "Don't miss the next DeepSeek because you follow DeepSeek, what we need is not a rush to pursue and imitate, the era of artificial intelligence will force humans to return to the source of value." Fudan University School of Computer Science and technology professor, Shanghai Key Laboratory of data science director Xiao Yanghua told reporters. In his view, behind the rise of DeepSeek is the epitome of China's AI power, and a group of artificial intelligence startups similar to DeepSeek are standing on the world stage. Why DeepSeek broke through "DeepSeek was out of my reach last year. Now it's out of my reach." Tao Ru, an algorithm engineer at an AI company in Shanghai, told Surging news reporters with a smile that as an algorithm graduate of a top domestic university, he had received an olive branch from DeepSeek last year, but finally gave up because he was worried that the company was not well-known enough and would not focus on AI. On social media, many fresh graduates have shown DeepSeek's job invitation, and the words are quite regrettable. Also "missing" DeepSeek there is a circle of investment institutions, "DeepSeek company executives are clearly not interested in commercialization, just want to do technical research." Investment institutions need to commercialize the company, have revenue profit and capitalization requirements for the company, and also need the founder to surrender a certain degree of equity and freedom." An investor admitted that, in fact, no practitioner of AI investment does not know DeepSeek, and some people extended an olive branch before the explosion. But the end result is that no VC (venture capital firm) has successfully invested in the company. Some people who know DeepSeek told reporters that they had interviewed some talents in the field of AI, and finally rejected their own company and went to DeepSeek, on the grounds that they had a good scientific research atmosphere and were a team that really did things. "In terms of salary package, DeepSeek is only in the middle of the industry, not the highest." He admitted, "The density of talent may not be as good as the head of the big factory, not that the people in the big factory are not smart, but the smart people in the big factory spend too much energy outside of technology." "Big companies pay well, but their internal struggles are fierce, and the desire to focus on technology is not as pure as a technology company like DeepSeek." "DeepSeek's popularity was due to chance, but more to necessity." Xiao Yanghua told reporters. "The parent company behind it, Magic Capital, has strong technical strength and computing power foundation in the field of quantitative trading and intelligent finance. At the end of 2022, when OpenAI just launched ChatGPT, there were few domestic clusters of Wanka, except magic Square. In addition, the convergence of a large number of AI-related talents in the financial field also gives DeepSeek a deep talent advantage." "It's more about the change in mindset." Xiao Yanghua admitted that most AI companies in the past were eager to achieve success, busy with brush list, publicity, realization and capital accounting, while DeepSeek was calm and focused on technical exploration, allowing the team to drive research and development based on curiosity, and was not eager to commercial realization. In terms of environmental factors, Hangzhou, where DeepSeek is located, has an advanced innovation environment. The government has created an atmosphere of tolerance, trial and error and exploration, and only built platforms without interfering with the innovation direction of enterprises, which is very conducive to the development of enterprises. Tan Jian, associate professor of intelligent interaction design at Beijing University of Posts and Telecommunications, believes that the key changes brought by DeepSeek mean that, as the cost of the model decreases, in the future, high-level AI applications will be promoted by small and medium-sized enterprises, and form a "hundred flowers" situation, and in the short and medium term, cloud computing, edge computing, and server three types of manufacturers. "At present, the three major operators and many Internet computing service platforms have connected to DeepSeek and provided Internet access, and it can be predicted that the revenue of these traditional cloud services and computing platforms will rise steadily as the entire population registers AI services." DeepSeek is not the only Chinese DeepSeek's explosion also lets the outside world see that China has formed a number of powerful and influential companies in the large model industry, including ByteDance, Ali, Tencent and other large factories, and there are start-ups such as Moon's dark side, Wisdom spectrum and MiniMax. On the first day of the New Year after DeepSeek hit the whole network, Ali Yuntongyi team released its flagship model "Qwen2.5-Max", becoming the second Chinese large language model that can match the o1 series of OpenAI company in the United States, which once again caused a shock. According to the ranking of the third-party platform, "Qwen2.5-Max" ranked 7th in the overall list with 1332 points, surpassing the deep search "DeepSeek-V3" and OpenAI's "o1-mini". In math and programming, "Qwen2.5-Max" ranked first and second in Hard prompts. The AI unicorn "Dark Side of the Moon" was established in April 2023, and its legal representative Yang Zhilin graduated from Tsinghua University. He earned a doctorate from Carnegie Mellon University in the United States and started his own business in Beijing. According to third-party data, as of January, the company valuation on the dark side of the month has reached $3.3 billion. MiniMax, a Shanghai-based AI unicorn, was founded in December 2021 with large multi-modal models of text, voice, music, images and video. A highlight worth noting is that MiniMax is at the forefront of the country in terms of AI going to sea. The latest data show that MiniMax's Conch AI overseas version topped the global AI video list in December last year, with more than 27 million monthly visits. Liu Hua previously told surging news reporters that the United States is in a leading position in AI large model technology as a whole, and in voice, video and other segments, China's large model catch-up speed is fast, such as conch AI and Kuaishou's large model are widely used in the United States, and at present in these fields, the technical level of the two countries has reached a stage of equal. "In fact, the rate of iteration and evolution of large model technologies in the United States today is actually slower than before." Liu Hua said, "At present, the leading enterprises in the United States have or are building 100,000 card clusters. There are even plans to build million-card clusters to train more advanced models. However, the realization of the million-card cluster faces many challenges, among which whether the local large-scale power facilities support is one of the key factors." Against this backdrop, Chinese companies are rapidly catching up with their American rivals. DeepSeek is like a "catfish", once again stimulating the vitality of AI competition. "The large model field has not yet formed an absolute moat, the industry is still in the early stage of development, and there is still a long way to go from the mature stage." Chen Cheng, a veteran observer of the AI industry, told Surging news reporters that he guessed that competition and internal volume in the large model industry would be further intensified after DeepSeek exploded. "The fierce competition between manufacturers, the most benefit is undoubtedly the user of the large model, that is, the ordinary user, they will enjoy the continuous evolution of the large model capability, the continuous improvement of the cost of the dividend." A well-known AI company told reporters that DeepSeek is not perfect, v3 model mainly in mathematics and code and other capabilities are more prominent, other general class text generation, understanding and other effects have room to improve, on its particularly low training costs, does not include all costs. (Editor's note: v3's published training cost is about $5.576 million. A third party report points out that the $5.576 million figure mainly refers to the cost of the GPU for model pre-training, and does not include other important costs such as R&D, data collection, and cleaning.) "After the explosion of DeepSeek, it will undoubtedly stimulate all parties in the industry to further invest in benign technology competition, which is extremely beneficial to the development of the entire industry." At present, in the large model circuit, companies are working hard to achieve better performance, and this dynamic competitive atmosphere is very rare." Another AI startup insider admitted to reporters that "at this stage, who will fall behind and who can stand out are still unknown." In order to survive and develop in the competition, we will definitely invest more resources, and the whole industry is full of vitality and development potential." How does the DeepSeek effect work Hu Yanping, chief expert of FutureLabs FutureLab, said that DeepSeek has become an effect, including four aspects, namely, the cost effect of computing power, the user detonating effect, the confidence boosting effect and the open source ecological effect: "Next, there will be a new phenomenon, many slightly strong related enterprises will be based on the base of the large model to do a variety of post-training, distillation fine-tuning, combined with knowledge base, etc., and then to face thousands of industries, forming a large model industry in the AI 2.0 era of the back of the market." Based on this observation, Hu Yanping believes that the AI industry has three potential directions next: the first direction is the end of the first cycle of AI 2.0 represented by the large language model, and the second cycle represented by multi-modal, embodied intelligence, space-time intelligence, etc.; The second direction is the aftermarket of AI large models, that is, the ecological emergence of the waist and long tail; The third direction is end-to-end AI agents, especially those that can be integrated with workflows and individual needs. In Xiao Yanghua's view, many AI startups have a good university background, and there is no shortage of talent and funds, but there is a general problem of mental anxiety, too eager, but not conducive to original innovation. "Companies need a more relaxed development atmosphere and develop steadily according to their own pace and strategic direction." He believes that, in fact, governments around the world are now very concerned about AI companies, but the lack of truly excellent, take out of hand enterprises, "the government's concern should be moderate, after building a good environment and platform, there will be no more intervention." "Caring too much can disrupt the pace of business. It's more important to be a smart carer." In addition, the emergence of DeepSeek, proved that AI enterprises rely on burning money volume "investment flow" "customer" path is not feasible, the past Chinese AI large model "volume" computing power, "volume" price, "volume" customer, "volume" liquidity ability, now people more recognize the original innovation of long-term, enterprises should think about structural innovation and low-cost research and development, Instead of burning money. "Big AI models are a very risky investment track with huge amounts of money, and only a few companies will survive, which means that many investments in companies will fail." The vice president of a large model enterprise told the Surging news reporter that in the current environment, the US dollar fund cannot achieve the traditional "investment and financial tube withdrawal" path because of the reason of fund-raising limitation, "the large model industry must accept a reality, and the government will guide the foundation to play a more important role." From a formal point of view, he suggested that you can refer to the current domestic and international computing power coupons. For example, now the state-owned enterprises can establish a computing power cluster to provide computing power for large model enterprises, and after the investment, most of the investment funds will be returned to the hands of state-owned enterprises in the form of computing power leasing fees. Xiao Yanghua believes that the wave of entrepreneurship set off by the large model industry means that private enterprises and small and micro enterprises play an important role in the national science and technology innovation system, and will drive more enterprises to flourish in the future. "Enterprises are often the most curious and creative in the start-up and small and micro stage. Curiosity is like a precious spark. It is so precious that the whole society should take good care of it so that the seeds of innovation can continue to take root and grow in the right soil."

At the end of January, Tesla CEO Elon Musk told investors that the company would launch a "profit-oriented driverless taxi service" in Austin, Texas, by June this year. Tesla has few regulatory restrictions in Texas, raising questions about the safety and legal risks it will take by deploying unproven driverless technology on public roads. Tesla has long blamed customers for accidents involving driver-assistance systems Autopilot and "full Autopilot" (FSD), and has reminded Tesla owners to be ready to take over the vehicle when the system is activated. Now Musk has promised to launch true driverless taxis, a move that legal experts say would make Tesla fully liable in the event of a traffic accident. For a decade, Musk has promised to launch a fully self-driving Tesla car, but has never been able to deliver. Those promises have become more frequent and the timeline tighter in recent months as Musk has shifted Tesla's focus from selling affordable electric cars to developing and deploying self-driving vehicles. However, Musk's vague rhetoric has left investors wondering when Tesla will actually launch fully autonomous driving technology, how big and what the business model will be. To date, Tesla has never demonstrated this technology on public roads. Tesla and Musk did not respond to requests for comment. Current Texas law does not prohibit Tesla from launching a driverless taxi service. The hands-off approach to regulation is in line with Musk's growing opposition to government intervention as an adviser to US President Donald Trump. Under Texas law, self-driving companies are free to operate on public roads as long as they are registered and insured like human-driven cars, but they must be equipped with technology that can record data on any potential accidents. There is no state agency that licenses or regulates driverless taxi services, and state law prohibits cities and counties from setting their own regulations for driverless cars. Texas Senator Kelly Hancock is the sponsor of the Texas Autonomous Driving Act of 2017. He said the Texas legislature wanted to promote the industry in a competitive market and avoid creating barriers with too many restrictions. "As a conservative, I want to minimize government intervention," he said. "We can't kill an industry by having different regulations in every place." In contrast, California has strict regulations on the operation of self-driving cars, and Musk moved Tesla's headquarters from California to Austin, Texas, in late 2021. So far, only two companies have been approved to operate paid driverless taxi services in California: General Motors' Cruise and Alphabet's Waymo. Both companies completed millions of miles of testing under strict supervision before they were allowed to carry passengers. Cruise has suspended its driverless taxis. In an earnings call held on January 29, Musk said he expected to release an "unsupervised" version of the FSD system in California this year. However, two California agencies that oversee the industry say Tesla has not applied for the permits required to operate driverless cars or carry passengers, and has not submitted test data to the state since 2019. California does not specify how much testing self-driving technology must undergo before it is approved, but other companies that have gone through the process have completed millions of miles of self-driving car testing under state supervision. State records show that since 2016, Tesla has submitted just 562 miles for testing. Musk's challenge Mr Musk announced his latest plans for driverless taxis on the same day that Tesla reported disappointing earnings that failed to meet analysts' expectations. This follows news that Tesla suffered its first sales decline in 2024. Still, Tesla shares rose 3% the next day. Musk has promised that Tesla will launch a "driverless taxi service" in Austin in June. Musk said he expects to roll out an "unsupervised" version of the FSD system later this year in California and "many areas across the United States." But he did not explain whether that meant a driverless taxi service, a feature that Tesla owners could buy, or some other service. Musk did say that the "unsupervised" version of the FSD system would be able to drive "without a human driver." Musk did not say how many cars would be deployed, how customers would use them or whether the service would be open to everyone. Brian Mulberry, client portfolio manager at Zacks Investment Management, a Tesla investor, said the rhetoric often leaves investors guessing about exactly what Tesla will launch and when it will be delivered. "That's the challenge for Musk: you're sort of playing divination with tea leaves, trying to figure out from a few words what's going to happen," he said. Musan also said he's not particularly worried about the promises and timelines Musk has made this year, as long as Tesla can show progress: "I think the blueprint is there." Bryant Walker Smith, a law professor at the University of South Carolina who studies autonomous driving, said Texas does not require "pre-approval" before Tesla can deploy driverless cars. However, after Tesla's Cybercab demonstration at a Los Angeles movie studio in October failed to live up to expectations, Smith expressed doubt that Tesla would deploy self-driving technology on a large scale in Texas or elsewhere. "Tesla is not going to make all its vehicles autonomous overnight in any environment," he said. According to Smith, Tesla is more likely to try a small scale test of the technology in an area of Austin, Texas, perhaps in good weather or through manual remote control to avoid crashes. "There should be many ways to operate," he said. "We have no power." Adam Hammons, a spokesman for the Texas Department of Transportation, said the state allows self-driving cars to be tested and operated on public roads "as long as they meet the same safety and insurance requirements as other vehicles." The proliferation of driverless cars on Austin's streets over the past two years has raised concerns among residents and authorities after a series of near-fatal accidents involving pedestrians, cyclists and other vehicles. In 2023, more than 20 Cruise driverless taxis caused a traffic jam near the University of Texas campus when the vehicles failed to meet and blocked an entire street. Gm declined to comment. Since July 2023, the city of Austin has received 78 formal complaints from law enforcement, first responders and residents. City officials said the complaints may not have fully documented all incidents involving the vehicles. A resident complaint in December said a Waymo vehicle blocked a lane for half an hour, causing "at least three incidents." "I cannot believe that you would allow potentially lethal technology to be tested on the citizens of this city," the complaint added. A Waymo spokesperson said the company has been working with local leaders and first responders to "earn the trust of the Austin community" and is constantly working to improve service. A spokesman for the Austin Department of Transportation and Public Works said police have also run into difficulties, with driverless cars unable to recognize traffic officers' command gestures and the city unable to issue tickets to the cars. Recently, the city proposed a way for police officers to file a complaint in municipal court when they spot a traffic violation. The spokeswoman said Tesla contacted Austin officials in May, and city officials provided information about local fire and police procedures, maps of areas around schools and school districts, and traffic rules during special events. Austin City Council member Zo Qadri is frustrated with the city government's inability to set rules against "private companies occupying public roads for testing," especially in downtown areas where driverless taxis are common. "The bottom line is we have no power.

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