Ada’s hair is dazzling.

Ada’s eyes are charming

Ada is sexy and mysterious.

Ada career line is half covered and half exposed.

Ada is lazy.

Ada has a sweet smile.

1905 movie network news On May 15th, Ada released a set of black and white beautiful pictures in Weibo. A low-necked sleeveless vest sets off Ada’s graceful figure, and her dazzling hair makes people feel lazy and full of mystery and sexy. Her charming eyes are mature and elegant, and her career line is half covered and half exposed, which has a hazy beauty of "still hiding half her face from us behind her guitar".

Netizens have commented that "Ada is a sexy goddess and won’t accept refutation", "I can’t describe my sister’s beauty, so I can only praise Brother Bin’s photography skills" and "It feels like a Hollywood star photo in the 1960s, which is so beautiful".

Wisdom things (WeChat official account: zhidxcom)
Wen | Xinyuan

In 2019, the new cloud AI chip battlefield is surging.

In the past few years, artificial intelligence (AI) has suddenly exploded from a neglected academic unpopular research to the forefront of commercialization in running all the way, which has set off a hurricane of intelligent upgrading and Internet of Everything in various fields closely related to people’s lives, such as security, finance, education, manufacturing, home and entertainment.

The direct promoters of this unprecedented technological revolution are foreign Internet giants such as Google, Microsoft, Facebook and domestic BAT, as well as a number of new AI start-ups, and the soul pillar of these companies to quickly break ground in the AI field is to provide a steady stream of AI hardware providers with high-density computing power.

AI hardware application scenarios are usually divided into cloud and terminal. Cloud mainly refers to large-scale data centers and servers, and terminals include rich scenarios such as mobile phones, vehicles, security cameras and robots.

Whether it is online translation, voice assistant, personalized recommendation or various AI development platforms that lower the threshold for developers to use, wherever AI technology is needed, cloud AI chips are needed to provide strong computing support for data centers around the clock.

According to the data revealed by NVIDIA in 2017, by 2020, the global market size of cloud AI chips will exceed 20 billion US dollars, and this huge market has become a place where chip giants are eyeing.

NVIDIA General Graphics Processing Unit (GPGPU) is soaring on the east wind of deep learning. Its share price was still $20 in 2015, and soared to $292 in October 2018. Its market value surpassed KFC and McDonald’s, and it became the first share in the AI field, with a market value of billions of dollars, enjoying unlimited scenery.

Its rocket-like rise awakened a number of potential competitors, and the storm appeared on the horizon. Semiconductor giants such as Intel and AMD are catching up. Google, Amazon, Baidu, and Huawei have made cross-border self-research, and dozens of new chip startups have sprung up, with the intention of breaking through the ceiling of cloud AI chip performance and reshaping this market through self-research architecture.

This paper will take a panoramic view of the battle of cloud AI chips, take stock of the five semiconductor giants, seven Chinese and American technology giants and 20 domestic and foreign chip companies that have joined the battle, and see if NVIDIA, which once created myths, can maintain its legendary empire? Can the new computing architecture that has appeared or is being developed now adapt to the future algorithms? Which companies are more likely to survive in a competitive environment with strong hands?

Whoever can dominate this cloud AI chip war will win more say in the battle of cloud computing and AI market in the future.

It all started with an accident, and it was by no means an accident.

More than a decade ago, NVIDIA and AMD became the two dominant players in the field of graphics cards after fierce fighting with dozens of rivals. At that time, most NVIDIA employees did not know what artificial intelligence (AI) was.

At that time, NVIDIA’s total revenue was about $3 billion, and its founder and CEO Huang Renxun made a risky decision-spending $500 million on CUDA projects every year, and transforming GPU into a more general computing tool through a series of changes and software development, with a total amount of nearly $10 billion.

This is a very forward-looking decision. In 2006, CUDA, the world’s first general computing solution on GPU, came into existence. This technology brought more and more convenient entry experience to programmers, and gradually accumulated a strong and stable developer ecology for NVIDIA GPU.

Until 2012, NVIDIA encountered the enthusiasm of deep learning.

This year, Geoffrey Hinton, a professor at the University of Toronto, Canada, a master in the field of machine learning and the father of neural networks, led the research group to train CNN)AlexNet, a convolutional neural network (CNN), and won the ImageNet image recognition competition in one fell swoop, pushing AI to the historical turning point of academic focus.

GPU is not born for deep learning, and its parallel computing ability coincides with the logic of deep learning algorithm. Each GPU has thousands of cores in parallel, and these cores usually perform many low-level and complicated mathematical operations, which is very suitable for running deep learning algorithms.

After that, the increasingly strong "CUDA+GPU" combination, with its invincible processing speed and multitasking ability, quickly captured the hearts of a large number of researchers and soon became an essential component of major data centers and cloud service infrastructures around the world.

The battle of the giants’ cloud AI chips quietly kicked off.

With an early start and ecological stability, NVIDIA soon became the leader in the cloud AI chip market.

NVIDIA is marching forward on the road to stronger, showing amazing technologies such as Tensor Core and NVSwitch one after another, and constantly creating new performance benchmarks. In addition, it also builds a GPU cloud, which enables developers to download a new version of the deep learning optimization software stack container at any time, greatly lowering the threshold for AI R&D and application.

In this way, NVIDIA built an indestructible wall by accumulating time, talents and technology. Anyone who wants a city needs to follow the rules specified by NVIDIA. As of today, NVIDIA has more than 10,000 engineers, and its GPU+CUDA computing platform is by far the most mature AI training program, which devours the cakes in most training markets.

From the functional point of view, the cloud AI chip is mainly doing two things: Training and Inference.

Training is to cram massive data into the machine and make it learn to master specific functions by repeatedly adjusting the AI algorithm. This process requires extremely high computational performance, accuracy and universality.

Reasoning is to apply the trained model, its parameters have been solidified, and it does not need massive data, so the requirements for performance, accuracy and universality are not as high as those of training.

GPU is a difficult mountain to climb in the training market, but its advantages are relatively less obvious in the reasoning market which requires higher power consumption.

And here, it is also the direction where the semiconductor giants who entered the game late gathered.

▲ Incomplete statistics of major cloud AI chip products of chip giants

Chips are a winner-take-all market, and cloud AI chips are no exception. NVIDIA’s high, medium and low-end general-purpose GPU for accelerating data center applications has always been a performance benchmark for all players.

NVIDIA invested billions of dollars and thousands of engineers in a short time, and launched the first Pascal GPU optimized for deep learning in 2016. In 2017, it launched Volta, a new GPU architecture with five times higher performance than Pascal, and TensorRT 3, a neural network reasoning accelerator, also appeared at the same time.

In the latest quarterly financial report, NVIDIA’s data center revenue increased by 58% year-on-year to $792 million, accounting for nearly 25% of the company’s total revenue, reaching a total of $2.86 billion in the past four quarters. If it can maintain this growth, it is estimated that the data center will reach about $4.5 billion in 2019.

AMD, which has long competed with NVIDIA in the GPU field, is also actively promoting the research and development of AI accelerated computing. In December 2016, AMD announced ——Radeon Instinct, an accelerator card program focusing on AI and deep learning.

Speaking of it, AMD’s start in the field of deep learning is inseparable from the support of China. Baidu was the first China company to adopt AMD Radeon Instinct GPU in its data center, and later Alibaba signed a contract with AMD.

At present, AMD’s GPU is still at least behind NVIDIA’s Tesla V100. However, when NVIDIA’s new move was not issued, AMD took the lead in announcing the launch of the world’s first 7nm GPU at its Next Horizon conference, named Radeon Instinct MI60, with a memory bandwidth of 1 TB/s. It also claims that its 7nm GPU has become the fastest double-precision accelerator in the world through AMD Infinity Fabric Link and other technologies, which can provide floating-point performance as high as 7.4 TFLOPS.

In addition to providing GPU chips, AMD is also building a more powerful open source machine learning ecosystem by launching ROCm open software platform.

Although GPU can’t resist NVIDIA for the time being, AMD has its own unique advantages. AMD has both GPU and CPU, and it can connect seamlessly between GPU and CPU with Infinity Fabric, but it is difficult for Intel Xeon processor +NVIDIA GPU to achieve such a perfect connection.

Imagination Technologies is also camped in GPU market, but it has been deeply involved in mobile GPU for a long time. From 2017 to 2018, Imagination announced three new PowerVR graphics processing units (GPUs), focusing on the AI terminal market.

At the end of last year, Imagination executives revealed in an interview that Imagination may announce the launch of GPU for AI training.

In the application of AI reasoning, FPGA has the advantages of flexibility and programmability compared with ASIC, which can be reconfigured in real time for specific tasks and has lower power consumption than GPU.

▲ Flexibility and performance difference of processors

The eldest and second children in the field of FPGA are Xilinx and Intel Altera all the year round. Facing the emerging AI market, the innovative genes in the body are also eager to try.

Xilinx’s killer is called Versal, which is the first adaptive computing acceleration platform (ACAP) in the industry. It adopts TSMC’s 7nm process and integrates AI and DSP engines. Its software and hardware can be programmed and optimized by developers.

This killer took four years to polish, and it is said that the AI inference performance of Versal AI Core is expected to be 8 times higher than that of the industry-leading GPU. According to the news released by Xilinx, Versal will deliver the goods this year.

Some insiders believe that Versal series may change the AI reasoning market.

If NVIDIA opens the door to AI by natural genes, then Intel quickly ranks among the front rows of cloud AI chips by the shortcut of "buy in buy buy". As a semiconductor overlord for decades, Intel’s first goal is to become a "generalist".

As we all know, Intel’s invincible trump card is Xeon processor. Xeon processor is like a brilliant strategist, strategizing and able to handle all kinds of tasks, but if you let him forge weapons, his efficiency is completely inferior to that of a warrior with a simple mind but a brute force.

Therefore, in the face of AI with a large number of repetitive and simple operations, it is both overqualified and inefficient for Xeon processors to handle such tasks. Intel’s approach is to match the Xeon processor with an accelerator.

What if I don’t have the technical background to be an AI accelerator? With a stroke of Intel’s pen, buy it directly!

In December 2015, Intel spent $16.7 billion to buy Altera, the second child of the programmable logic device (FPGA) at that time. Now Intel has accelerated some tasks in the data center by more than ten times with the "Xeon+Altera FPGA" heterogeneous chip.

Especially in the past year, Intel’s overweight on FPGA is visible to the naked eye. Two years ago, Intel successively launched Stratix 10 series, which is known as the fastest FPGA chip in history, and this series won the favor of Microsoft.

Microsoft launched Project Brainwave, a cloud solution based on Intel Stratix 10 FPGA, claiming that it runs at a speed of 39.5 TFLOPS with a delay of less than 1 ms.

In addition to Stratix 10 FPGA chip, Intel first settled in Chongqing in December last year, and then in April this year, it unveiled a new weapon that has been quietly polished for several years-FPGA Agilex with a new architecture, which integrated Intel’s most advanced 10nm process, 3D packaging, the second generation HyperFlex and other innovative technologies.

Intel’s FPGA has gained a foothold in the server market, while another important transaction is still in the dormant period.

In August 2016, Intel spent 300-400 million dollars to buy Nervana, a California startup dedicated to building deep learning hardware. Shortly after the acquisition, the former CEO of Nervana was promoted to the general manager of Intel AI business unit, and the first deep learning special chip Lake Crest using TSMC’s 28nm process was mass-produced in 2018, and claimed that its performance was 10 times that of the fastest GPU at that time.

In May 2018, Intel’s new cloud AI chip Nervana Neural Network Processors (NNP)-Spring Crest was officially unveiled. It is said that its power consumption is less than 210 watts, and its training performance is 3-4 times higher than that of Lake Crest, which will be open to users in the second half of 2019.

For cloud AI chip reasoning, Intel revealed at CES in Las Vegas that it is working closely with Facebook on the reasoning version of Nervana neural network processor NNP-I. NNP-I will be a system-on-a-chip (SoC) with built-in Intel 10nm transistors, and will include the IceLake x86 core.

Compared with Google’s TPU, Carey Kloss, vice president of Intel Artificial Intelligence Group (AIPG) and core member of Nervana team, thinks that TPU 2.0 is similar to Lake Crest and TPU 3.0 is similar to Spring Crest.

Qualcomm, which is flourishing in the field of mobile chips, has just raised a stepping stone to enter the field of cloud computing and supercomputing.

In April this year, Qualcomm announced the launch of the Cloud AI 100 accelerator, which will expand Qualcomm’s technology to data centers, and it is expected that samples will be delivered to customers in the second half of 2019.

It is reported that this accelerator is based on Qualcomm’s technology accumulation in signal processing and efficacy, and is specially designed to meet the rapidly increasing demand of AI reasoning processing in the cloud, so that distributed intelligence can spread from the cloud to the user’s edge terminal and all nodes between the cloud and the edge terminal.

Keith Kressin, senior vice president of product management in Qualcomm, said: "Qualcomm CloudAI 100 accelerator will set a new benchmark for AI inference processors in data centers in today’s industry-no matter which combination of CPU, GPU and/or FPGA is adopted to realize AI inference processors."

In addition, he also said that Qualcomm is currently in an advantageous position to support complete AI solutions from the cloud to the edge, and all AI solutions can be connected with 5G with the advantages of high speed and low latency.

Compared with the ambitious chip giants facing the cloud and data center market, the minds of the following cross-border players are relatively "simple".

The goal of these Chinese and American Internet giants is not to directly compete with NVIDIA, Intel or AMD, but to provide their own cloud customers with powerful computing power and reduce their dependence on traditional chip manufacturers.

Their choice of self-developed chips is also different. Google, Amazon and others choose the route of ASIC, while Microsoft and others are committed to using field programmable gate array (FPGA).

▲ Incomplete statistics of major cloud AI chip products of cross-border technology giants

As one of the earliest technology companies to start AI-related research and development, Google is also a pioneer in testing special AI chips, and it was the first to verify that ASIC can replace GPU in the field of deep learning.

In 2016, Google launched its own AI chip Tensor Processing Unit(TPU), which has now entered the third generation, providing computing support for various AI applications such as Google’s voice assistant, Google Maps and Google Translation. The TPU originally designed is used in the reasoning stage of deep learning, and the new version can already be used for AI training.

Google claims that it takes one day to train a machine translation system using 32 best commercial GPUs, and the same workload takes six hours on eight connected TPU.

Google currently only operates this device in its own data center and does not sell it to the outside world. Recently, however, Google said it would allow other companies to purchase its TPU chips through its cloud computing service.

Google TPU is limited in Google’s external service market. TPU can only be used and run with Google TensorFlow AI framework. Users cannot use them to train or run AI built with Apache MxNet or Facebook’s PyTorch, nor can they be used in non-AI HPC applications where GPU occupies the supreme position.

But Google is satisfied with this because it regards TPU and TensorFlow as its comprehensive AI leadership strategy. Software optimized for its software is optimized for its software, which can build a powerful and durable platform.

The new news this year is that Google set up a new chip team gChips in Bangalore, and recruited at least 16 technical veterans from traditional chip companies such as Intel, Qualcomm, Broadcom and NVIDIA.

In May last year, the Microsoft AI chip Brainwave opened the cloud beta, saying that the FPGA chip used in the Project Brainwave computing platform was designed for real-time AI, which was five times faster than the TPU chip used by Google (the Microsoft AI chip Brainwave open cloud beta was five times faster than TPU). Jason Zander, executive vice president of Microsoft Azure, also said that Microsoft Azure actually designed many self-developed chips for data centers.

I have to admit that the domestic technology giants named the chip, and the cultural Level was higher than that of foreign countries by more than one level.

The "Kunlun" named by Baidu for the cloud AI chip is the first mountain in China. According to legend, the ancestor of this mountain was honored as "the ancestor of thousands of mountains" and "the ancestor of Long Mai" by the ancients, and well-known myths and legends such as the Goddess Chang’e flying to the moon, Journey to the West and Legend of the White Snake are all related to this mountain.
The "rise" of Huawei’s cloud AI chip takes the meaning of transcending the world, rising and imposing, and is quite popular among literati.

Both Baidu and Huawei are domestic technology companies that have made cross-border cores early. As early as August 2017, Baidu released a 256-core FPGA-based cloud computing acceleration chip at the Hot Chips conference in California, and its partner was Xilinx. Huawei made chips earlier. In 2004, HiSilicon, a semiconductor company, was established, but it used to be a chip solution for terminals.

In the second half of 2018, a new round of core-making forces represented by them blew the horn of China cloud AI chip charge.

Baidu is an early technology giant in China. As early as 2010, it began to use FPGA to do research and development of AI architecture. In 2011, it launched small-scale deployment. In 2015, it broke the deployment scale of thousands of chips. In 2017, it deployed more than 10,000 FPGAs. Baidu’s internal data center and autonomous driving system were all used on a large scale.

In August 2017, Baidu released a 256-core XPU chip based on FPGA, which is in cooperation with Xilinx. The core is small, there is no cache or operating system, and the efficiency is equivalent to that of CPU.

Then at the Baidu AI Developers Conference held in July 2018, Baidu announced Kunlun, the most powerful AI chip in the industry at that time.

In terms of parameters, Kunlun chips are manufactured by Samsung, using 14nm technology, with a memory bandwidth of 512GB/s and tens of thousands of cores, which can provide computing power of 260 TOPS at a power consumption of over 100W W..

Compared with NVIDIA’s latest Turing architecture T4 GPU, T4′ s maximum power consumption is 70W, and the highest computing power it can provide is 260 TOPS. However, this GPU was released two months later than Kunlun Chip, and it was not sold in China at the beginning. Ouyang Jian, chief architect of Baidu, revealed at this year’s AI chip innovation summit that this year’s "Kunlun" will be used on a large scale within Baidu.

Huawei’s cloud AI chip Ascension 910 is directly at the release site and the front PK of NVIDIA and Google. Ascent 910 directly uses the most advanced 7nm technology, adopts the Leonardo da Vinci architecture developed by Huawei, and the maximum power consumption is 350W. Huawei’s banner is "the chip with the highest computing density on a single chip" as of the release date, and its semi-precision (FP16) computing power reaches 256 TFLOPS, which is twice as high as the 125 TFLOPS of NVIDIA V100.

Xu Zhijun even said that if 1024 Ascending 910s are collected, there will be "the largest AI computing cluster in the world so far, with a performance of 256P, and no matter how complicated the model is, it can be easily trained." This large-scale distributed training system is called "Ascend Cluster".

In terms of landing, Baidu said that its Kunlun will be widely used in Baidu data center this year. Huawei’s Ascent 910 was originally planned to be listed in Q2 this year. Now, under the background of trade war, I don’t know if it will be delayed.

As the leaders of the cloud computing market in China and the United States, Alibaba and Amazon are a little late, but they will never be absent.

The research and development purposes of the two companies are very clear, which are to solve the AI reasoning operation problems of commercial scenes such as image, video recognition and cloud computing, improve the operation efficiency and reduce the cost.

Alibaba Dharma Institute announced in April last year that the performance of Ali-NPU will be 10 times that of mainstream CPU and GPU architecture AI chips on the market, with manufacturing cost and power consumption only half, and cost performance exceeding 40 times. In the same month, Ali wholly acquired Zhongtianwei, the only independent embedded CPU IP core company in mainland China.

The new progress occurred in September, when Ali merged Zhongtianwei and Dharma Institute’s self-developed chip business into a chip company, Pingtou Ge. The important task of developing Ali-NPU is taken over by Pingtou Ge. The first batch of AI chips are expected to be available in the second half of 2019 and will be applied in cloud data scenarios such as Ali data center, urban brain and autonomous driving. It will be opened to the outside world through Alibaba Cloud in the future.

In the simulation verification test, the prototype of this chip saved 35% of the hardware cost of laying Ali city brain. But since then, Ali has hardly made any sound of relevant progress.

Amazon’s cloud AI chip Inferentia was announced at the Re: Invent conference held in Las Vegas last November.

The technical source of this chip can be traced back to Annapurna Labs, an Israeli chip company acquired by Amazon for $350 million in early 2015. According to the official introduction, each Infirentia chip provides hundreds of TOPS, and multiple AWS Inferentia chips can form thousands of TOPS. The chip is still under development. According to the forecast, the chip will be listed at the end of 2019.

Facebook’s core-building plan surfaced very early, but it is the player with the least information exposure.

In addition to buying relatively mature chip companies, recruiting is also a standing choice. Facebook’s core-building plan first appeared in April last year, and official website posted an advertisement for ASIC&FPGA design engineers to form a chip team. Three months later, the US media Bloomberg reported that Facebook poached Shahriar Rabii, Google’s senior engineer, as vice president and chip leader.

Yann LeCun, the chief artificial intelligence scientist of Facebook and the winner of the latest Turing Award, revealed in an interview that its core-building is mainly to meet the needs of real-time video surveillance of the website in the future.

By January of this year, Intel said at the Global Consumer Electronics Show (CES) that it was working with Facebook to develop a new AI chip to speed up reasoning and strive to complete it in the second half of this year.

But so far, the outside world knows nothing about the performance information of Facebook AI chip.

The revival of AI has subverted the stable situation of the whole industry of carry, a top chip company such as Intel, AMD and Qualcomm, and created opportunities for a new group of chip entrepreneurs.

Some startups want to create a new platform from scratch, all the way to the hardware, which is optimized for AI operation. It is hoped that by doing so, it can surpass GPU in speed, power consumption and even the actual size of the chip.

▲ Incomplete statistics of major cloud AI chip products of domestic start-ups.

Let’s talk about the domestic cloud AI chip creation enterprises, the most dazzling of which are Bitland and Zhongke Cambrian.

Bitcontinent is famous as the leader of mining chip industry, but in the past year’s bitcoin ebb tide, Bitcontinent was the first to fall into the whirlpool of public opinion, and the listing plan failed to be realized as scheduled.

This company, established in 2013, started the AI chip business in 2015. Following the launch of the first generation of 28nm cloud AI chip product BM1680 in 2017, it released the second generation BM1682 in the first quarter of 2018, with an iteration time of only 9 months.

According to the core-making plan announced by Bitcontinent last year, the 12nm cloud chip BM1684 should be launched at the end of 2018, and BM1686 will be launched in 2019, probably using the 7nm process, but both chips are late.

Like Bitland, there are also AI chiplet unicorns, such as the Cambrian.

In CAMBRIAN, the neural network processor (NPU) embedded in Kirin 970, Huawei’s first mobile phone AI chip, became a popular fried chicken in AI chip enterprises at home and abroad. After two rounds of financing, the overall valuation was about 2.5 billion US dollars (about 17 billion yuan).

In May 2018, the CAMBRIAN officially released the first generation cloud AI chip MLU100, which is said to provide better performance than NVIDIA V100 with lower power. Iflytek, its customer, once disclosed the test results, saying that the energy consumption efficiency of MLU100 chip in voice intelligent processing is more than five times ahead of the cloud GPU solution of international competitors.

A year later, Siyuan 270, the second-generation cloud AI chip, did not get hot first, and some of its performance was exposed by netizens in Zhihu. The peak performance and power consumption were basically the same as NVIDIA Tesla T4. It is rumored in the industry that the Cambrian may make a breakthrough in the field of low-precision training. The chip will be released in the near future if nothing unexpected happens.

The startups that want to benchmark NVIDIA and Google don’t stop there.

A slightly surprising player is Etu Technology, one of the four little dragons of domestic computer vision (CV). In May of this year, Yitu released questcore, the first cloud AI chip jointly developed with ThinkForce, an AI chip maker.

Yizhi Electronics is a low-key but not to be underestimated AI chip startup in Shanghai. In 2017, it received a series A financing of 450 million yuan from Eto Technology, Yunfeng Fund, Sequoia Capital and Gaochun Capital. Its core members come from semiconductor giants such as IBM, AMD, Intel, Broadcom, Cadence, etc., and all have more than ten years of experience in the chip industry.

This customized SoC chip for cloud deep learning reasoning adopts 16nm process and ManyCore architecture with independent intellectual property rights. It is said that it can provide visual reasoning performance of up to 15 TOPS per second, and only accelerates for INT 8 data (8-bit integer data type). The maximum power consumption is only 20W, which is smaller than an ordinary light bulb.

According to the figure, the development of this chip is not to pursue the computing power of hundreds of T like NVIDIA, but to value high computing density.

Like the aforementioned cross-border technology giants, the first step of commercialization of Yitu chip is to package and sell it with its own software and hardware and solutions, and it will not be sold separately. The second and third generation products are also in preparation.

Shanghai’s hot new core-making force is Suiyuan Technology. It can be said that it is the youngest AI chip maker in China. It was established in March 2018 and received 340 million yuan of Pre-A financing from Tencent, focusing on R&D investment in cloud AI acceleration chips and related software ecology. This is the first time Tencent has invested in a domestic AI chip venture.

The founding team of Suiyuan Technology mainly came from AMD, and its founder Zhao Lidong previously worked in AMD China, and then went to Rideco (now merged with Spreadtrum to become Ziguang Zhanrui) as the president.

On June 6, 2019, Suiyuan Technology announced a new round of financing of RMB 300 million, which was led by Red Dot Venture Capital China Fund and invested by Haisong Capital and Tencent. The mystery of its deep learning high-end chip has not yet been unveiled.

Different from the previous players, Tianzhixin and Denglin Technology chose a general-purpose GPU that directly matched NVIDIA.

In China, there is no GPGPU company that can compete with NVIDIA, which is an opportunity worth cutting into for entrepreneurs.
The core-making lineups of the two companies are very mature. The hardware team of Tianzhixin is based on AMD’s GPU teams in Shanghai and Silicon Valley, and the founding team of Denglin Technology is also a veteran in the GPU industry for many years.

At present, the high, medium and low-end GPGPU products of Tianzhixin are under development, and its high-end chip Big Island will support cloud reasoning and training at the same time. The GPGPU processor of Denglin Technology has also passed FPGA verification, and the design of the first generation product Goldwasser has been completed, and it is planned to be available for customer testing before the end of this year.

There is also a startup named Longjiazhi, which was founded in July 2017 and led by Zhixin Capital and Yiling Capital, and is committed to the research and development of TPU chips.

In order to meet the requirements of low latency, high reliability and data security, Long Jiazhi introduced a new chip type, Mission-Critical AI Processor. The first generation chip was named Dino-TPU, which was first applied in cloud data centers. Its computing power exceeded all GPUs except the latest Nvidia Volta, with a delay of only 1/10 of that of Volta V100, power consumption of 75W, and unique redundancy backup and data security.

According to Long Jiazhi’s development plan, the company plans to complete the streaming of the first chip by the end of 2018.

On the other side of the ocean, many AI chip startups in the United States have also targeted the cloud and computing center market.

A company with a strong presence last year was Wave Computing. This startup acquired MIPS, an old chip IP supplier, last year, and also launched the MIPS open plan. Its accumulated financing reached $117 million.

Its core product is called Data Stream Processor Unit (DPU), which adopts CGRA (Coarsegrain Reconfigurable Array/Accelerator) technology, and is suitable for large-scale asynchronous parallel computing problems.

Its main advantage is to make hardware more flexible to adapt to software, achieve a good comprehensive balance in programmability (or universality) and performance, lower the threshold of AI chip development, and will not be affected by memory bottlenecks in accelerators such as GPU.

Wave’s first generation DPU adopts 16nm process technology and runs at a speed above 6 GHz, which has been put into commercial use. According CTO Chris Nicol, its senior vice president and CTO, the new generation of 7nm DPU will introduce MIPS technology and adopt HBM(High Band Memory), which is expected to be released next year.

There is also a very mysterious startup, Cerebras System, which was founded in California in 2016. Even if it hasn’t released any products yet, it doesn’t prevent it from being often compared with chip giants.

Cerebras’s founding team mostly comes from chip giant AMD. Andrew Feldman, its co-founder and CEO, previously founded SeaMicro, a low-power server manufacturer, which was acquired by AMD for $334 million in 2012. Since then, Feldman spent two and a half years climbing to the position of vice president of AMD.

Cerebras raised $112 million in three rounds of financing, and its valuation has soared to as high as $860 million. Today, Cerebras is still in secret mode. According to relevant sources, its hardware will be tailored for "training" deep learning algorithms.

▲Cerebras uses deep learning accelerator for neural network training and reasoning patent.

The Groq founding team established in April 2017 is even more eye-catching, with 8 people from the core team of Google TPU. This startup is ambitious as soon as it comes out, and the computing power of official website display chip will reach 400 TOPS.

SambaNova Systems was founded seven months later than Groq, and headquartered in Palo Alto, California. Its founders include two Stanford professors, Kunle Olukotun and ChrisRé, and an old chip company (Sun’s former senior vice president of development).

Its A round of financing was led by Google Venture(GV), the venture capital department of Google’s parent company Alphabet. This is the first time that GV has invested in an artificial intelligence chip company. In April this year, intel capital announced a total of $117 million in new investment in 14 technology startups, and SambaNova Systems was also on the list.

In addition to China and the United States, AI chip startups in other regions are also gaining momentum.

The most optimistic is a well-funded British unicorn Graphcore, which was established in 2016 with a valuation of US$ 1.7 billion and accumulated financing of US$ 312 million. This startup can be called a giant harvester with a strong investment lineup, including Sequoia Capital, BMW, Microsoft, Bosch and Dell Technology.

This company has built an intelligent processing unit (IPU) specially designed for machine intelligent workload, which supports on-chip interconnection and on-chip storage, and extends from edge devices to "Colossus" dual-chip package for data center training and reasoning.
Graphcore wrote in official website: Our IPU system aims to reduce the cost of accelerating AI applications in cloud and enterprise data centers, and improve the performance of training and reasoning by as much as 100 times compared with the fastest system at present.

At the event of NeurIPS at the end of last year, Graphcore showed an example configuration RackScale IPU-Pod, including 32 1U IPU-Machines, each consisting of four Colossus GC2 IPU processors, providing mixed precision calculation of 500 TFLOPS, more than 1.2GB of processor memory and more than 200TB/s memory bandwidth.

▲Graphcore IPU-Pod racksale system

Habana Labs, another Israeli startup founded in 2016, announced at the AI Hardware Summit last September that it was ready to launch its first AI chip Goya for reasoning. It showed the throughput of classifying 15,000 images per second in the Resnet50 image classification database, which was about 50% higher than NVIDIA’s T4 device, with a delay time of 1.3ms and a power consumption of only 100 W.

Its latest $75 million Series B financing (December 2018) was led by Intel Venture Capital, and part of the funds will be used to develop the second chip Gaudi, which will be oriented to the training market. It is said that the training performance can be linearly extended to more than 1,000 processors.

AlphaICs of India was also established in 2016, and is designing AI chips and working on AI 2.0, hoping to realize the next generation of AI through this series of products.

One of the co-founders of AlphaICs is Vinod Dham, who has the title of "Father of Pentium Chip". He cooperated with some young chip designers to create an executable agent-based AI co-processing chip-RAP chip.

Dham said that AlphaICs chips have an advantage over competitors in processing speed, and that most of what we see now belongs to weak AI, and they can be called "strong AI".

According to Dham, the RAP chip is expected to be launched in mid-2019, "hoping to create a big bang for the real AI".

Tenstorrent is a startup located in Toronto, Canada. It was founded by two former AMD engineers, Ljubisa Bajic and Milos Trajkovic. Most of the core teams came from NVIDIA and AMD to develop high-performance processors designed for deep learning and intelligent hardware.

Earlier last year, the company received a seed round investment from Real Ventures, but it is still in a secret mode.

Among the hardware forces in the field of cloud and data center, a special team is favored by domestic and foreign technology giants, which is photonic AI chip.

Different from conventional chips, these chips use photonic circuits instead of electronic transmission signals. They have higher transmission speed, lower delay and higher throughput than electronic circuits.

In 2016, the MIT research team built the first optical computing system, which was published in the top journal Nature Photonics in 2017 as a cover article. It is this paper that inspires more people around the world to invest in the research and development of photonic AI chips.

Only this MIT team hatched two American companies, Lightelligence and LightMatter, in 2017.

In February 2018, Lightelligence received a $10 million seed round financing from Baidu Venture Capital and American semiconductor industry executives. In February 2019, LightMatter received a $22 million B round financing led by Google Ventures, a venture capital department of Google’s parent company Alphabet.

Lightelligence claims that Photonic Circuits can not only be used as a coprocessor of CPU to accelerate deep learning training and reasoning in the field of cloud computing, but also be used for network edge devices that require high efficiency and low energy consumption.

In April this year, Lightelligence announced the successful development of the world’s first photonic chip Prototype board (prototype), and its photonic chips have been in contact with customers at Google, Facebook, AWS and BAT levels.

LightMatter also focuses on large cloud computing data centers and high-performance computing clusters. They have built two early chips, one of which contains more than eleven transistors.

Inspired by the MIT paper, in 2017, the first photonic AI chip enterprise in China was founded by doctoral students from 10 universities including Tsinghua University, Peking University and Beijing Jiaotong University.

The company received angel round financing in September 2018. It is said that the performance of its photonic chip is 1000 times that of electronic chip, and the power consumption is only 1% of that of electronic chip.

Just this month, Bill Gates also began to invest in AI chips, and invested in Luminous, which also developed silicon light technology. Other investors include the 10100 fund of Uber co-founder Travis Kalanick and the current Uber CEO Dara Khosrowshahi.

Luminous currently has only seven members, but its appetite is not small. Its goal is to create a substitute for 3,000 circuit boards containing Google’s latest Tensor Processing Unit AI chip. Their methods draw lessons from the early work of their co-founder Mitchell Nahmias in neuroporphology photonics at Princeton University.

Now the common problem of these startups is that it is not clear how long it will take to release the first mass-produced photonic AI chips, and whether the practical application effect of these chips can really replace the position of electronic chips.

Nowadays, there are dozens of players who have cut into the cloud AI chip market. However, the general pattern of the software, hardware and service market, which is dominated by NVIDIA and divided by many semiconductor giants, is still relatively stable, and it is not an easy task to produce new pattern changes.

For the chip industry, sufficient production capacity is crucial.

Semiconductor giants can achieve 10 times or 100 times the production capacity, but it is difficult for a startup to do this at the early stage of its business. Today’s startups are mostly IC design manufacturers. If they want to become "self-sufficient" companies like Intel and Samsung, they may need to spend billions of dollars.

After the wave of semiconductor industry integration in 2015-2016, the wave of semiconductor mergers and acquisitions in the past two years is gradually "cooling down", and large companies will be more cautious in their investment or acquisition of chip startups.

The core competitiveness of cloud AI chips lies in talents.

Judging from the more concerned cloud AI chip companies in the current market, their research teams are mostly industry veterans with more than ten years of experience in chip giants, and often have the experience of taking the lead in developing relevant successful products.

Both semiconductor giants and cross-border core-building technology giants are basically taking two paths. One is to invest in and acquire mature chip companies, and the other is to poach chip executives from other big companies.

Song Jiqiang, president of Intel Research Institute, once told Zhizhi that the future of AI chips must be diversified. Different kinds of products meet the requirements of different power consumption, size and price. AI is a marathon, and now this game has just begun.

At this stage, the vast majority of giants and entrepreneurs in the field of incoming cloud AI chips are playing innovative signs, including innovative architecture, storage technology and silicon light technology.

Due to the surge in demand for new computing resources to promote deep learning, many people think that this is a rare opportunity for start-ups to win funds from giants and investment institutions.

Although the number of players is increasing and the flags played tend to be diversified, at present, the innovative hardware that is really mass-produced is still limited. There are still many difficulties faced by cloud AI chips, such as Moore’s Law, which is common in computer architecture, and bottlenecks in semiconductor devices.

The process of developing chips may take several years, and most of the hardware is still under development or in the early test plan. Therefore, it is difficult to predict which enterprises will achieve the promised performance.

Generally speaking, the cloud AI chip market is gradually divided into three forces: semiconductor giants represented by NVIDIA and Intel, Chinese and American technology giants represented by Google and Huawei, and chip entrepreneurs represented by Cambrian and Groq. Among them, semiconductor giants and chip-creating enterprises focus on general-purpose chips, while cross-border core-making technology giants and AI-creating enterprises will not sell directly to the outside world for the time being.

From the application field, although the high energy consumption of GPU has been more and more criticized by the industry, due to its unparalleled parallel computing ability, there is no player who can compete with NVIDIA GPU in the field of cloud AI training. Players who challenge this field are mainly traditional chip giants and startups. Cross-border technology giants include Google, Baidu and Huawei, and the main architectures adopted are general GPU and ASIC.

In the field of cloud AI reasoning, which pays more attention to energy consumption, delay, cost and cost performance, there are relatively more players entering the game, and the advantages of FPGA and ASIC are relatively higher than GPU. Intel, which has a comprehensive AI chip layout, is gaining momentum, and other players are not far behind. Several major Internet giants in China and the United States have basically joined the battle, but the progress of chip research and development of some giants is still unknown.

With regard to improving the core-building strength, most semiconductor giants and technology giants have chosen the shortcut of investment, M&A and chip-digging, so as to be directly assisted by mature chip teams and quickly fill the vacancy of talents and business. For start-ups, there are basically two factors that are favored by the investment community-an experienced founding team and products with innovative technologies. From the perspective of the landing process, the pace of chip start-ups in China can rank among the top in the world.

At present, the vast majority of AI applications still rely on training and reasoning in the cloud. In the field of training, NVIDIA’s solid ecosystem is still an unshakable mountain, and in the field of reasoning, it is even more competitive. As AI is more widely spread to all walks of life, the cloud AI chip market will gain more room for growth, but this market may not accommodate so many players. Capital, device bottlenecks, architectural innovation, adapting to rapidly changing AI algorithms and building an ecosystem are all difficult problems facing these enterprises. What is the AI chip form that is completely suitable for cloud training and reasoning has not yet reached a unified conclusion.

When you ask a young man why he doesn’t like sports and what his pain points are, he will probably get the answer: he can’t find a partner.

Running, skipping and swimming can be done by one person, but there is always a lack of fun. Sports in which two or more people must travel in a row are always full of uncertainty. Either no one can be invited, or several people with different technical levels reluctantly accommodate each other.

There are always endless excuses, but when young people see that the cholesterol value in the physical examination report is increasing year by year, they have to take action and look around for sports games that can be played by themselves without being too boring.

(Source/"My Savage Girlfriend")

Squash is simply tailor-made for them, the most cost-effective choice.

Squash is similar to tennis, but the court usually only needs a semi-closed indoor rectangular space with a length of 9.75 meters and a width of 6.4 meters, and it takes only a few steps to run the whole court.

Other ball games need to practice all kinds of footwork, grip and hitting posture for a long time, but even zero-based squash students can perfectly explore all the abilities of entertaining themselves within 2 hours;

Squash courts give players a sense of privacy. (Source/vision china)

In the era when everyone claimed to be I, as long as he spent tens of dollars, he could confidently enjoy an entire air-conditioned space alone. Those scenes where the ball next door flies over and needs to be picked up and asked if it is possible to make up the field have never belonged to squash.

The unique advantages of venue and game mechanism have cleared away all the excuses of young people for not exercising. At the moment when the squash door is closed, the young people who have been sitting in the office for a long time finally have the opportunity to release themselves without scruple, draw the opposite wall full of black spots, and then leave smartly.

For ordinary people, it is often in TVB dramas and Korean dramas that they first come into contact with the concept of squash.

In the play, the executives go straight to the squash court after work, change their sportswear, swing against the wall and play ball. During the break, several people talk to each other, and maybe some cooperation has been reached.

TVB gold collar standard: playing squash. (Source/"Forensic Pioneer")

Now, while the executives are talking in Kan Kan in the squash court, almost all the venues next to them have become the best places for young white collars who have just entered the workplace to start sports.

After graduating from college and returning to work in her hometown, Sally can find few friends to go out with. Colleagues either have families or work overtime. Looking at each other’s tired eyes, Sally was even embarrassed to send out an invitation to play ball together.

When searching on social media how to solve her sedentary "pear shape", Sally accidentally discovered this new gadget of squash.

Hammamy v Sherbini 2023 Qatar Classic Final. (Source /@5#Squash)

The rules of squash are not very similar to what we understand as "duet": in a semi-closed room, two players hit the ball against the wall in front of them, and the opponent needs to catch the ball that bounces off the wall and hit it again.

When there is no opponent, the addition of the wall allows the player to control the rhythm of hitting the ball by himself, and it is most comfortable and relaxed without accommodating other people’s movements.

Social terrorists are most afraid of the sudden "guidance" of strangers during sports, but squash requires a closed space, and the court must be closed when using it. As long as the door is closed, no one can tell whether judge’s own actions are standard.

"It doesn’t matter even if he says it. Anyway, in the glass room, I can only hear my own panting."

Nowadays, when searching for "squash", the key word is often "social fear". (Source/@ 么么么么么么么)

Coach Mo, who has more than 20 years’ experience in squash teaching, often meets golfers who play alone when waiting at the squash court. Although they are familiar faces who have played in the same venue for many years, they will still avoid the crowd. "Some people don’t even want to have normal language communication with us at all."

However, coach Mo understands this very well. After all, when he started playing squash, he took a fancy to its "at any time, one person can play" characteristics.

"You can go to the squash court at 3 o’clock in the morning to enjoy 7 pieces of land, or you can take turns to play in a field with five or six friends. Squash, that’s it,’ I can e’. "

Free from social leisure, although a person’s squash can relax his mood, the black ball with irregular high-speed beating in such a large venue can still touch the players’ nerves at all times. After several rounds, people who "mess up" at ordinary times will sweat profusely and their hearts will accelerate.

Squash can fly at a speed of 150 kilometers per hour. (Source/WeChat official account @ Hangzhou 19th Asian Games)

After the first solo squash experience, Sally rested for a whole week, but she still made an appointment for a squash experience class two weeks later happily rubbing her sore thigh muscles, hoping to try the "complete form" of the sport.

Unfortunately, Sally lost interest after playing a few rounds with strangers. Although everyone is a beginner, when she can’t catch the ball sent by the other side and is forced to run all over the court to pick it up, she will still be numb with embarrassment.

"I still have the pleasure of hitting the wall when I play. When I play with others, I only feel that the wall is hitting me."

Unlike Sally, a beginner, Dee, who has been playing squash for 22 years, thinks that squash is more like a social and brain-burning game.

Dee fell in love with squash when he was accidentally brought into contact with his classmates in high school 20 years ago.

Beginners who play ball once a week spend half a week to relieve sore muscles, but for squash fanatics, it’s easy to make appointments twice a week, and even spare time to participate in competitions all over the country.

(Source/"My Savage Girlfriend")

Nowadays, Dee has less and less entertainment time with friends, but more and more social clubs, and the golfers have basically become "middle class" and "executives" in the relative sense, such as foreign consuls and brand owners.

In business, another popular social sport is golf, but the effect of this relatively static and non-sweating sport is not so direct.

It is impossible for decent executives to rush to play basketball together. Holding a golf club with a sense of distance, taking into account safety and antagonism, squash seems to be the best choice for sports and social interaction.

"Although they won’t take care of my business, playing ball is indeed the lowest cost way to get closer."

There are few conflicts on the squash court, and everyone is polite. (source/worm idea)

Sally thinks that every time she waves a racquet, it’s like slapping a face on the wall with a small ball, which is a great pleasure to vent her anger.

For old players, every stroke means constant calculation and thinking from footwork to ball speed and trajectory, which not only does not decompress, but also burns the brain abnormally.

But this does not mean that old players can’t get emotional value by "smashing the wall". In the process of playing squash, Dee’s most fulfilling moment is the moment when the ball is "smashed".

The ball used in squash is a hollow rubber ball filled with inert gas. Whenever the ball is hit, the inert gas in the ball expands due to friction and the speed of the ball becomes faster and faster.

Double yellow rubber balls used in squash. (source/worm idea)

When the speed reaches the limit of the surface rubber, the squash will burst open at the moment when it hits the wall, and the inert gas inside will "hiss" and the rubber will cross a short parabola in the air and slide to the ground like a breath.

Like collecting medals, Dee will collect the smashed balls: "It’s like a friend who has been with me for a long time suddenly left, and I want to cherish its company."

The pursuit of technology has always been the ideal of hardcore sports players, and "decompression" is the ultimate reason why many sports can be persisted by most people for a long time.

Different from other sports, most students who seek a coach to learn squash do not want to hone their skills, but hope to entertain themselves and relieve their pressure after learning the basic movements.

"After all, this kind of sport, which is difficult to break the ball, wall and racket, is most suitable for venting negative emotions." Coach Mo said.

One-to-many squash experience class is a popular entry method at present. (Source/Respondent for the picture)

On the court, coach Mo has met students from 4 to 80 years old, but the main consumer group of squash is still young people. Among them, foreign trade, media, accounting, construction, finance, public relations, lawyers and other occupations accounted for the majority.

Young people engaged in these industries have a relatively long work cycle, and there may be complications at any time in the process. Therefore, there is always a string in their minds, and they dare not relax completely.

On the squash court, the ball path is unpredictable, and all attention needs to be mobilized in starting, hitting and dodging. High-intensity exercise is enough to make nervous young people forget the pressure of work for a short time and concentrate on the audio-visual enjoyment of the 360-degree all-round beating sound in the field.

From the muffled sound of hitting the ball at the beginning, to the blasting sound produced by learning to use physical strength to the rhythmic sound of hitting the ball continuously … The subtle change of the sound of the ball hitting the wall every time is the most beautiful decompression music for them.

After playing ball and getting high, skills seem to be less important. (Source/Shepherd photo)

What’s more, the amount of exercise in squash can be regarded as rich and frugal. Punching the wall for 15 minutes is enough to cover the consumption of a sedentary office for a week, and slowly hitting the wall can just reach the critical point of fat consumption in aerobic exercise.

I’m already very tired at work. If you want to vent your pressure after work, you’d better choose a way to make yourself more comfortable.

Dee has never regarded squash as an "aristocratic sport". On the contrary, this kind of sport, which is sun-free, air-conditioned, unaffected by the weather and has a low entry threshold, has a wide mass base.

After all, compared with the expenses of old-fashioned "middle-class sports" in the public impression, such as golf, fencing and equestrian, squash that can be played for tens of dollars is simply cabbage price.

More and more teenagers are playing squash. (Source/Respondent for the picture)

Coach Mo, who has worked for many years, believes that the biggest reason why squash is still a niche in the world is the space limitation.

A standard squash court has requirements for lighting, floor and air conditioning, and each court can only accommodate two people at a time, which is not a common sports basic configuration.

Nowadays, when more and more players value the sociality and entertainment of squash, the old players are both happy and tangled. Where there is demand, there will be supply. It is foreseeable that there will be more and more squash venues in the future.

Perhaps, as Sally said, "Before squash courts really become popular, whether you can continue to play ball may not depend on whether you have time, but whether you have hand speed."

Every week, coach Mo organizes a "novice game" with his golfers. (Source/Respondent for the picture)

Ending：

Around 1830, the aristocratic students of Harrow College, a famous British aristocratic school, were tired of the boring living on campus and invented an indoor sport of hitting the ball against the wall, which was the origin of squash.

Up to now, squash is still inseparable from the labels such as "elite sports", "middle class" and "minority", which seem to be far from the lives of ordinary people.

In fact, "tolerance" is the key word of squash. Beginners can entertain themselves, and hardcore players also have fierce play. On the squash court, everyone can find their own comfort zone.

Dee describes the feeling of being in a squash court with the feeling of being wrapped. (Source/vision china)

Most importantly, after closing the door, the player can immediately immerse himself into another world from the senses. Compared with the real life where hard work may not necessarily lead to results, the world of squash is so disciplined.

There, as long as you pay close attention to the direction of the ball and try to hit it on the wall, the sense of coolness will certainly accumulate.

Only then can the young people who are tired of life really find the pure happiness that belongs to sports without any label.

Acknowledgement: Coach Mo of Guangzhou Squash Club

Writing and herding sheep

Original title: "It’s hard for a young man who smells like a class not to like playing squash"

Read the original text

Please indicate "Shanghai Education" on the WeChat of Shanghai Municipal Education Commission.

Say goodbye to the familiar campus and classroom, and meet the students in the "cloud" every day. How to make the students at home on the other side of the screen study actively and with peace of mind? The primary and secondary school teachers in Shanghai incarnate "Avalokitesvara" to show their magical powers, attract children to study efficiently with ingenious online class skills, and care for them through various channels after class, so that children can feel the warm love of teachers through the screen.

After careful design, teachers’ online teaching blackboard books are not only as neat and beautiful as offline classes, but also innovate and practice according to the characteristics of online teaching to help students better master the knowledge system. Let’s take a look at these "most beautiful online blackboard books" with Xiaoyu!

Songjiang Sijing experimental school affiliated to Shanghai University of Engineering Science

Small blackboard design plays a big role

Online teaching, with the help of the network platform, has turned some "impossible" of offline teaching into reality. Teacher Mao Kaijie of Songjiang Sijing Experimental School affiliated to Shanghai University of Engineering Science discovered the "evolution of blackboard" in online teaching.

At ordinary times, one blackboard in the classroom has become 50, and at the same time, the blackboard that can only write offline has become a multifunctional blackboard that can write and call a lot of mathematical tools.

Of course, there are more blackboards, which does not mean that teachers can write on the blackboard at will, especially in math class, because its subject characteristics, in addition to being refined, also need to have more rigorous logic. In the online teaching platform, using the following three forms to write on the blackboard can make online teaching more "memorable".

1. Add color to the text, and the focus will naturally come. Multi-color writing is not only for beauty, but more importantly, it plays a role in highlighting key points, breaking through difficulties and correcting error-prone points. Adding arrows can make the meaning more concise and intuitive.

2. Words with pictures make sense. Daily teaching needs time-consuming and laborious stickers and forms, and online teaching can be done with a picture. You can take a screenshot of the video or upload the picture to the cloud disk in advance and call it.

3. Ruler plus material, graphics come at will. The influence of teacher’s demonstration is self-evident, especially the beauty and standardization in writing and drawing. In the column calculation, we ask students to draw the equal sign straight, and the teacher must do it first. You can easily get standardized symbols and lines by calling ruler tools or inserting text for input. Of course, there are also some plane graphics and three-dimensional graphics, which can be easily drawn by teachers simply by directly transferring them from teaching materials.

Changning district yuyuan rd 1 ST primary school

"By combing pictures and texts and connecting symbols, we can clarify the logical relationship between knowledge and summarize the learning focus of this lesson", "To solve problems, build a class blackboard with logical thinking context", "Make clever use of classroom resources in the air, optimize and reorganize by means of symbols and pictures, and design and construct a structured blackboard" … Teacher Dai Yanbin from Xianghong Branch, Yuyi Primary School, Changning District, Shanghai, in the online teaching practice of natural science in the fourth grade, based on students’ learning situation and unit learning content, Carefully designed electronic blackboard books with various forms, scientific contents and convenient for students to read, which are displayed in the online discussion area of each "cloud" class, to build a scaffold for students’ thinking, consolidate scientific concepts, guide them to analyze and solve problems by using the methods they have learned on the basis of understanding knowledge, and improve students’ scientific practical ability and scientific literacy.

In the lesson "How to Make Sinking Objects Float", Mr. Dai extracted relevant materials from the classroom resources in the air, and presented the contents of electronic blackboard books in two columns with brief explanations at the top of the pictures, so as to guide students to consolidate their scientific knowledge and learn the scientific methods to solve problems, and realize the extensive application of buoyancy in production and life.

In the teaching of "Buoyancy of Air", Mr. Dai’s electronic blackboard book revolves around the core content of this lesson, "Buoyancy of Air and its Application", which is organized in an illustrated way and presented in a question-and-answer way, listing "What is buoyancy of air?" "What is the relationship between the buoyancy of air on an object and it?" "What is the relationship between the ups and downs of objects in the air?" "What are the applications of air buoyancy in production and life?" These four key issues. Problem-oriented, leading students to think and solve doubts in the process of reading electronic blackboard books, cultivating students’ problem-solving consciousness and stimulating students’ interest in scientific inquiry.

Shiba junior high school

Writing on the blackboard in class: teachers’ operation show

"I can’t let my students see clearly" is a problem that teachers often pay attention to and care about. No, the teachers of the eighth junior high school in the city give full play to their majors and use tools to try their best to provide students with a good class experience.

Li Songjia, a math teacher who was suddenly isolated at home, was a little disappointed at first. The community is suddenly closed, and the handwriting board is too late to prepare. Writing on the blackboard with the mouse can easily become messy. The same challenge is very common in science teaching. Teacher Li immediately "asked for help" in the teaching and research group of the school mathematics group. It turned out that many seniors in the group grafted the micro-lesson treasure with the auxiliary camera function of the teaching platform and put the blackboard on paper! The clear and complete answering process is presented on the screen. There are also some teachers who set up mobile devices directly and use the rear camera to shoot blackboard books, just to present the best teaching state to students! In order to make students have a better learning effect, the teachers of all teaching and research groups and preparation groups have used their brains and tried their best.

Nanyang junior high school

"The classroom is complete with blackboard writing"

Teachers of Nanyang junior high school are equipped with black (white) boards at home. The combination of "computer+handwriting board" is also favored by teachers. It is both chalk and red pen, which makes teachers play freely in online teaching guidance.

Yangpu junior high school

How can teachers and students interact effectively in the classroom through the screen? This is a practical problem that has been puzzling teachers and students. In order to solve this difficulty, the teaching team of Yangpu Junior High School in Shanghai carefully designed blackboard writing with pictures and texts in teaching practice:

The blackboard writing of teachers in mathematics teaching and research group

The teachers of the mathematics teaching and research group appeared in formal attire and explained "the area problem of a linear function" in the form of a special course of thinking expansion. In the design of blackboard writing, teachers consider using multi-equipment to teach, computer screen to monitor students’ class situation, tablet writing problem-solving process, and sometimes use the interactive annotation function of online conference platform to enhance classroom interaction. The teacher then marked it with different colors to make the blackboard key.

The blackboard writing of English teaching and research group teachers

In order to empower the classroom with information technology and enhance the effectiveness of the classroom. Teachers of the English Teaching and Research Group re-edited the high-quality resources in the air classroom for our use, guided the students’ thinking through the flow chart in the blackboard, let the students understand the truth that time is precious, and skillfully integrated the content of Lide Shuren into the subject teaching to achieve the effect of moistening things and being silent.

Anting high school

The "capacitance pen" and "mouse" in the hands of online teaching teachers still seem to be less handy than the "chalk head" in the classroom. No matter whether it is in regular script or song style, all of them become "earthworms", and the effect of online blackboard writing is always a little worse. However, the electronic blackboard written by teacher Chen Yi from Anting High School makes people shine at the moment, and suddenly reminds them of the long-lost blackboard in the classroom. She wrote the blackboard in advance with related apps on the tablet computer, which is convenient for students to use as a reference when reviewing and sorting out knowledge points.

Baoshan district 2 nd central primary school

Since the online teaching was launched, the teachers of the Second Central Primary School in Baoshan District of Shanghai have used the online teaching platform to make children feel at home. Teachers also show their magical powers:

Teacher Xia Tian’s practical class is guided by core literacy, starting with simple mathematical problems in daily life, so that students can understand the methods of list enumeration and feel the value of orderly thinking and the application of mathematics in life in the process of solving problems.

There is also teacher Nancy who combines subject resources to cultivate children’s thinking ability and add color to online teaching.

Teacher Nancy teaches the blackboard writing in the third class of Parallel online.

shanghaipudong foreign languages school

In order to help students adapt to modern education, and at the same time to cope with the sudden online teaching at any time, the teaching team of the international course class of Pudong Foreign Language School affiliated to Shanghai International Studies University has adopted electronic means with distinctive subject characteristics and strong interactive experience in advance in teaching materials, blackboard writing, homework and other aspects to ensure the effectiveness of online teaching.

In science teaching, teachers pay the most attention to clear logical deduction and detailed answers. Jiang Lili, a math teacher, uses a digital handwriting board to show the deduction process in real time, with brief drawings to show unimaginable three-dimensional thinking.

Electronic blackboard writing in mathematics classroom

Feng Yanying, a physics teacher, made her own electronic school-based notes, marking the key points and standardized answers of each class in detail, so that students can quickly locate notes and master knowledge points.

Physical electronic school-based notes

Although it is an online teaching mode, students can still interact face to face with teachers and students, see the familiar handwriting of teachers and receive professional and meticulous guidance. The teachers’ team used various and sufficient electronic means, which not only kept their own teaching characteristics, but also improved the teaching effect and learning enthusiasm, and tried their best to help every student grow sturdily!

Jinshan primary school

Ge Jiayi, a first-grade math teacher in Jinshan Primary School, used mind maps to sort out knowledge, pay attention to the correspondence between algorithms and arithmetic, and improve students’ understanding of the diversity of algorithms in the teaching of Unit 4 "Two Numbers Plus One Number".

Ni Shengji, a Chinese teacher at Jinshan Primary School, designed the blackboard book "Spider Shop Opening" for the second grade, which helps students to sort out the process of spider shop opening three times in the form of schematic diagram and presents the key information of the text, paving the way for guiding students to grasp these key information to tell stories, aiming at cultivating students’ ability to tell stories.

Wang Ling, a science teacher at Jinshan Primary School, wrote on the blackboard in the last lesson of Fish and Snails in Grade One, mainly sorting out the knowledge points of the whole unit and explaining the key contents of the four lessons respectively.

The material is provided by the relevant district education bureau.

Editor: Zhao Xuhua

　　Since the 18th National Congress of the Communist Party of China, the CPC Central Committee with the Supreme Leader as the general secretary has put forward a series of new ideas, new ideas and new strategies for governing the country, led the industrial development with the strategy of innovation-driven development and the strategy of manufacturing a strong country, and promoted the industrial transformation and upgrading of China with the extraordinary determination of reform and perseverance. The industrial production maintained a medium-high growth, the production of emerging industries grew rapidly, and the traditional industries accelerated the transformation and upgrading, which played an important supporting role in realizing the medium-high growth of the national economy and moving towards the middle and high-end level.

　　First, the industry maintained medium and high-speed growth, and the results of improving quality and increasing efficiency were obvious.

　　(A) China’s industry has maintained a moderate and high-speed growth in the complex and severe economic environment. From 2013 to 2015, the added value of China’s industrial enterprises above designated size increased by 8% annually. In terms of categories, the manufacturing industry grew at an average annual rate of 9%, the mining industry at an average annual rate of 4.5%, and the electricity, heat, gas and water production and supply industries at an average annual rate of 3.8%. In terms of economic types, state-owned holding enterprises grew by 4.4% annually; Collective enterprises grew at an average annual rate of 2.4%, joint-stock enterprises grew at an average annual rate of 9.3%, and foreign-invested enterprises from Hong Kong, Macao and Taiwan grew at an average annual rate of 6.1%. Private enterprises grew at an average annual rate of 10.4%. In recent years, the recovery of the world economy is weak, the phenomenon of weak external demand has not changed significantly, the rebound of major developed economies is less than expected, and the growth rate of emerging economies has generally declined. According to the data of the United Nations Industrial Development Organization, during the period from 2013 to 2015, the annual growth rate of the world manufacturing industry was only in the range of 2% to 4%, and China’s industrial growth was still in the forefront among the world’s major economies. Under the background that the economic environment at home and abroad tends to be complicated and severe, it is especially difficult for China’s industry to achieve medium and high-speed growth.

　　(2) The overall efficiency level of enterprises is good, and the unit labor output has been significantly improved. From 2013 to 2015, the main business income of industrial enterprises above designated size increased by 6.3% annually and the total profit increased by 4.2% annually. Among them, the main business income of manufacturing industry increased by 7.3% annually, and the total profit increased by 8.6% annually, both higher than the overall level of industries above designated size. From the per capita income of main business, the increase of unit labor output reflects the progress of improving quality and efficiency of enterprises. In 2015, the per capita main business income of industrial enterprises above designated size reached 1.174 million yuan, an increase of 186,000 yuan or 18.9% in three years compared with the level of 988,000 yuan in 2012.

　　Second, innovation drives kinetic energy conversion, and emerging industries form new growth points.

　　Since the 18th National Congress of the Communist Party of China, high-tech industries have developed rapidly and improved their efficiency, becoming an advantageous industry leading the transformation of industrial economic kinetic energy. Emerging industries and products are constantly emerging, and new kinetic energy and power show their vitality and become new growth points in the industrial economy.

　　(A) the rapid growth of high-tech industries, leading role significantly enhanced. From 2013 to 2015, the added value of high-tech industries increased by 11.4% annually, which was 3.4 percentage points higher than that of all industries above designated size. The main business income and total profit increased by 9.9% and 14.4% annually, respectively, and the growth rate was 3.6 and 10.2 percentage points higher than that of all industries above designated size, which reflected that the driving role of high-tech industries was significantly enhanced under the innovation-driven development strategy.

　　(2) The development of new kinetic energy within the industry shows vitality, and technological progress has become an important source of power for industrial growth. From 2013 to 2015, some emerging industries developed rapidly. The added value of urban rail transit equipment manufacturing industry grew at an average annual rate of 32.2%, communication equipment manufacturing industry grew at an average annual rate of 20.3%, biopharmaceutical manufacturing industry grew at an average annual rate of 13%, electronics and electrical machinery special equipment manufacturing industry grew at an average annual rate of 12.4%, and electronic device manufacturing industry grew at an average annual rate of 12.3%.

　　(3) Emerging industrial products release growth potential, and intelligent manufacturing has become a new engine driven by leading innovation. In 2015, new, intelligent, automated equipment and high-end information and electronic products became new growth points. Compared with the previous year, the output of new energy vehicles increased by 161.2%, industrial robots increased by 21.7%, smart TVs increased by 14.9%, and smart phones increased by 11.3%. The output of vending machines and ticket vending machines increased exponentially, and solar cells (photovoltaic cells), optical fibers, optical cables, optoelectronic devices, emus and urban rails increased.

　　Third, the economic structure optimization has achieved remarkable results, and industrial transformation and upgrading have been steadily advanced.

　　Since the 18th National Congress of the Communist Party of China, the industrial economic structure has been continuously optimized, and the advantageous industries with the change of production structure and profit growth among industries reflect the characteristics of industrial upgrading. The transformation of the internal development mode of the industry is also going on. Traditional industries are transformed through optimal allocation. New energy, new materials and new technologies promote the upgrading of product structure, and the increase of production added value promotes the value of the industrial chain.

　　(1) The industrial production structure continued to show positive changes. Since the 18th National Congress of the Communist Party of China, the proportion of high-tech industries has increased year after year, and the increase rate is increasing year by year. From 2013 to 2015, the added value of high-tech industries accounted for 9.9%, 10.6% and 11.8% of all industries above designated size. The equipment manufacturing industry has become the industry with the largest proportion, accounting for 31.8% of all industries above designated size in 2015; The proportion of consumer goods manufacturing industry is rising, and the proportion of added value from 2013 to 2015 is 24.5%, 25.1% and 26.1% in turn; The proportion of high energy-consuming industries and upstream mining industry is decreasing year by year. From 2013 to 2015, the proportion of the six high energy-consuming industries is 28.9%, 28.4% and 27.8% respectively, and the proportion of mining industry is 12.4%, 11% and 8.6% respectively, which shows that the situation that industrial economic development relies too much on resources is improving.

　　(2) Industries with rapid profit growth show the characteristics of industrial upgrading. From 2013 to 2015, among the above-scale industries in China, the equipment manufacturing industry realized a total profit of 6,668.3 billion yuan, with an average annual growth rate of 10.8%, which was 6.6 percentage points higher than that of the above-scale industries; The total profit of the consumer goods manufacturing industry was 5,094.3 billion yuan, with an average annual growth rate of 8.8%, which was 4.6 percentage points higher than that of industries above designated size. With the gradual improvement of residents’ living standards and the continuous increase of family car consumption, automobile manufacturing industry has become the industry that creates the most profits among 41 industrial categories, with a total profit of 1,717 billion yuan in three years, with an average annual profit growth rate of 14.4%.

　　(3) Traditional industries have achieved transformation and development through upgrading the value of industrial chain and optimizing product structure. While the proportion of traditional industries in industry is generally declining, its structural adjustment is also deepening, and the transformation and upgrading of development mode are promoted through the optimal allocation of production share and product structure. Judging from the changes in the internal structure of traditional industries, the production share is more adjusted to the industrial chain links with high added value. For example, in iron and steel and non-ferrous industries, the production share of smelting industry with relatively low added value decreases and the growth rate decreases, while the production share of calendering industry with relatively high added value increases. From 2013 to 2015, steel calendering production achieved a relatively fast annual growth of 8.6%; The production of non-ferrous metal calendering increased by 13.5% and the profit increased by 8.8% annually. In addition, the average annual production growth rate of synthetic materials manufacturing, special chemical products manufacturing, glass fiber and glass fiber reinforced plastic products manufacturing in these three years is above 10%. The product structure is also being adjusted in the direction of better quality and higher technical content. For example, in the building materials industry, the output growth of traditional cement and flat glass is relatively slow, while the output of tempered glass, laminated glass and insulating glass with high technical content increased by 7.4%, 11.1% and 14.3% respectively from 2013 to 2015; From 2013 to 2015, the average annual profit growth of new building materials such as lightweight building materials, waterproof building materials, heat insulation and sound insulation materials all exceeded 10%. Such as in the chemical industry,The output of new materials such as carbon fiber reinforced composites and rare earth magnetic materials all achieved double-digit growth in 2015.

　　Four, industrial exports continued to grow, and the export of equipment manufacturing industry became the pillar.

　　(1) Industrial exports continued to grow. From 2013 to 2015, the export delivery value of industrial enterprises above designated size reached 35,298.6 billion yuan, with an average annual growth rate of 3.1%. Faced with the weak recovery of the world economy and the obvious weakening of external demand, industrial exports still maintain a certain speed, and it is very difficult for the annual export scale of industrial products to exceed 10 trillion yuan.

　　(2) The equipment manufacturing industry has become a pillar industry for the export of industrial products. From 2013 to 2015, the equipment manufacturing industry achieved a total of 22,804 billion yuan in export delivery value, accounting for 64.6% of all industrial export delivery value above designated size. Equipment and technology-intensive mechanical and electrical products have replaced labor-intensive textile industrial products as the main export force, which reflects that under the new round of high-level national strategy of opening to the outside world, the structure of China’s industrial exports has been optimized, and the comparative advantage of foreign trade has gradually shifted to the middle and high-end technology and capital competition fields.

　　(3) Exports of some industries maintained rapid growth. From 2013 to 2015, the communication equipment manufacturing industry in export delivery value grew at an average annual rate of 13.6%, the radio and television equipment manufacturing industry grew at an average annual rate of 11.1%, the electronic and electrical machinery special equipment manufacturing industry grew at an average annual rate of 10.5%, and the automobile parts and accessories manufacturing industry grew at an average annual rate of 10.2%. Facts have proved that the supply-side upgrade of exports is still promising in the overall downturn of external demand. It is a feasible way for industrial exports to develop to a higher level and a higher level by broadening the space for international development according to the quality improvement, aiming at market segments to achieve overseas competition breakthroughs, and achieving win-win industrial linkages through holding a group to the sea.

　　"Pinch" is becoming the new favorite of young people.

　　

　　A few days ago, the topic "Why are young people willing to spend thousands of dollars to buy a’ pinch’" rushed to Weibo hot search. In fact, "Pinch" is a kind of slow-rebound decompression toy, made of soft silicone materials, which highly restores the delicious and attractive food shape. It is loved by many young consumers because of its beauty and fun, and its price ranges from several yuan to thousands of yuan.

　　

　　According to the industry, "pinching" can release the pressure and anxiety accumulated by young people in their work, study or daily life. Among them, the limited edition or specially designed "pinching" is hyped due to scarcity, resulting in abnormally high prices. At the same time, the "pinching" industry standards and regulations urgently need the relevant departments to clearly specify the materials, safety performance and labeling requirements of the products, so as to avoid endangering the health of consumers.

　　

　　Pinch lets people release pressure and adjust their mood.

　　

　　"Pineapple bags, rice balls, doughnuts, strawberry cakes, fried dough sticks" … Li Jingwen, a white-collar worker in Beijing, showed his trophy about "pinching" to the reporter of China City News. These "pinching" shapes are so lifelike and lovely that people can’t help but want to pinch them. There are many young people like Li Jingwen who have been "pinched".

　　

　　In fact, in addition to the above-mentioned baked cakes and other food shapes, there are also "pinched" shapes of plants and animals on the market, most of which are made of silica gel, which will not melt or harden, and have strong plasticity, and can be roughly divided into three categories: water feeling, cement feeling and mud feeling. Among them, the water is the lightest and softest, it has no resistance when pinched, and it rebounds the fastest; The cement feels slightly with plasticine feel, and the rebound speed is moderate; Mud feels like squeezing plasticine, and its rebound is the slowest.

　　

　　According to the data of Tmall New Life Research Institute, in 2022, the overall growth rate of decompression toys in Taobao Tmall was nearly 40%; By 2023, "pinching" has become one of the fast-growing toy categories in Taobao 2023.

　　

　　"The first time I came into contact with’ Pinpinch’ was when I brushed relevant posts in Little Red Book at the beginning of this year. I found them cute and found them very interesting. Plus, I usually like small craft products, and I went to into the pit after I got to know them a little." Li Jingwen told reporters that when you pinch this kind of slow-rebound toy, you will feel very calm in your heart. While playing "pinching", you can also make it faster to think and reduce anxiety while working or studying, which can achieve the effect of venting emotions or relieving stress for her.

　　

　　There is also a saying circulating in the "pinching" circle: "When you pinch this toy, you will never forget the feel." As a decompression toy, "kneading" can make people feel relaxed and happy under the simple kneading or squeezing action. Zhang Yue, chairman of Aoyou International, said in an interview with China City News that in the fast-paced life, many people are facing the pressure of work and life, and "pinching" provides a convenient and brand-new entertainment way, so that people can release pressure and adjust their mood anytime and anywhere.

　　

　　Why are all kinds of "pinching" different in value?

　　

　　The strong purchasing demand of young people has also stimulated the "pinching" market. In addition to being able to buy "pinch" in Jiumu Sundry Club, The Green Party, famous products and other stores, online platforms such as Taobao, Xiaohongshu and Xianyu also have a wide variety of "pinch" on sale, most of which are priced between several yuan and hundreds of yuan.

　　

　　However, there are some exceptions, such as Zulala Pinch, which is very popular in the circle. In particular, a blogger in Xiaohongshu has exposed an out-of-box video of Zulala Pinch worth 15,000 yuan, of which two Zulala Pinch were filmed at a price of 2,900 yuan, so some netizens joked that Zulala Pinch is Hermes in Pinch Circle.

　　

　　Li Jingwen told reporters that her purchasing channels are generally small red book shops, Taobao shops and micro-shops, and occasionally from the live broadcast room, with unit prices ranging from 10 yuan to 60 yuan. Under normal circumstances, the larger the volume, the higher the customer unit price, and the pricing of different stores is also different. "At present, I have not bought a’ pinch’ with a unit price of more than 100 yuan." Li Jingwen said.

　　

　　In fact, most of the "pinching" of high-priced auctions on second-hand platforms come from hand-made shops in online celebrity. "This reflects the imbalance between supply and demand in the market and the drive of collecting and showing off." Yu Fenghui, a special researcher of China Financial Think Tank, analyzed in an interview with the reporter of China City News. On the one hand, some limited edition or specially designed "pinching" became popular due to scarcity, and the hype similar to tide play made their value surpass the toys themselves and become collectibles; On the other hand, some young consumers are willing to pay a high price for this, in addition to the actual decompression needs, but also because of its role as social capital, that is, by having a unique or expensive "pinch", they can show their personality and taste among their peers and meet the needs of self-expression and social comparison.

　　

　　Emotional value business is popular

　　

　　This young people are troubled by small emotions and pay for them.

　　

　　According to the data released by the survey results of China Modern Consumption Development Index in 2023, the proportion of consumers who think that "pleasing oneself" is more important has risen sharply, reaching 47.8%, an increase of 16.8% compared with 2022. According to the data of China Consumption Trend Survey in 2024, 64% of consumers pay more attention to spiritual consumption, and young consumers pay more attention to spiritual consumption. Consumers pay more attention to their own small world and pursue a sense of gain, value and significance. Rational consumption and emotional life will become the fundamentals of consumption.

　　

　　Behind the popularity of "pinching" the whole network and the price of thousands of yuan, many people have found that selling emotional value seems to be gradually becoming a business. For example, recently, a product named "hydroponic banana" continued to sell well on the e-commerce platform. In the past month, more than 10,000 people bought a number of similar products, most of which sold thousands. According to reports, this kind of hydroponic banana is different from the general foliage planting, and it has the characteristics of "viewing+eating", and it is easy to feed. Just put it in a vase full of water and wait for about a week to mature. For migrant workers who don’t have much energy to take care of it, the cost is extremely low and more worry-free.

　　

　　Besides hydroponic bananas, other "emotional" fruits are also favored by consumers. For example, on the shopping platform, 20 yuan can buy a "fresh-cut pineapple" and a pot of tomato seedlings for 30 yuan, while hydroponic strawberries, hydroponic bergamot and other categories range from 20 yuan to 100 yuan.

　　

　　Is the emotional value business really so "profitable"

　　

　　In Yu Fenghui’s view, the business of selling emotional value is profitable to a certain extent. He believes that with the growth of social psychological demand, people are more and more willing to pay for products and services that can bring psychological comfort and emotional satisfaction. The commercial logic of emotional value lies in that it captures the pain point of modern people’s lack of emotion, and creates an emotional resonance through product design, marketing strategy and brand story, thus transforming it into consumers’ purchase intention. However, this kind of market also has volatility and uncertainty, which requires continuous innovation and precise positioning to continuously attract consumers.

　　

　　In this regard, Zhang Yue holds different views. "Selling emotional value has indeed become a business, especially among young people, but it is not always easy to make money." Zhang Yue said that in addition to "pinching" such decompression toys, other emotional value products, such as psychological counseling services and emotional healing books, also need to be attractive enough to attract consumers. In addition, product quality, brand reputation and service quality are also important factors that affect whether this business can make money.

　　

　　Zhang Yue’s worry is not unreasonable. Some bloggers revealed: "I bought a bunch of’ pinching’, and the flavor was very strong. I simply measured it with a formaldehyde instrument and directly exceeded the standard. These two days are not only crazy acne, but also conjunctivitis. I don’t know if it is related to’ pinching’. "

　　

　　It is reported that Guangzhou Consumer Council has published the comparative test results of 37 decompression toys. The test results show that the product has some quality problems and potential safety hazards, such as excessive plasticizer, excessive release of volatile organic compounds and xylene, too many colonies and too loud noise.

　　

　　At present, there are many sales categories and channels of "pinching", but few well-known domestic manufacturers enter the market, and most of them are handmade by individuals. Therefore, many people in the industry call for the industry standards and regulations of slow-rebound decompression toys to be clearly defined by relevant departments in terms of material specifications, safety performance, labeling requirements, etc., so as to effectively and pertinently supervise and ensure that products meet human health standards, standardize market order, and safeguard the legitimate rights and interests of consumers.

　　

　　In addition, Yu Fenghui also suggested that excessive market speculation may cause a price bubble, which will lead consumers to blindly follow suit and eventually cause economic losses. At the same time, over-reliance on "emotional economy" may ignore the practicality and durability of the product itself, which is not conducive to the healthy development of the industry in the long run. Moreover, the best-selling of "pinching" may also aggravate the consumerism tendency of young people, and excessive consumption may have a negative impact on personal financial situation and mental health.

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