Showing posts with label artificial intelligence. Show all posts
Showing posts with label artificial intelligence. Show all posts

Thursday, June 17, 2021

The brains are wide open, and the scientist Nature issued an article: After artificial intelligence, the rise of "smart matter" computing?

 Artificial intelligence (AI) is not a new concept anymore. We know that it is inspired by the human brain and neural networks. The human brain is particularly good at computationally intensive cognitive tasks, such as pattern recognition and classification.

Regarding AI, a long-term development goal is decentralized neuromorphic computing, that is, relying on a distributed core network to simulate the large-scale parallel computing of the brain, so as to realize a super information processing method inspired by nature. By gradually transforming interconnected computing blocks into continuous computing organizations, it is possible to conceive advanced material forms with basic characteristics of intelligence. This "smart material" can learn and process information in a non-localized manner, and can receive and Respond to the interaction of external stimuli and the environment, and at the same time can adjust the structure autonomously in order to be able to distribute and store information reasonably. Does this kind of thinking broaden your cognitive boundaries of the word "intelligence" again?

On June 17, a team of scientists from the University of Münster, Germany and the University of Twente, the Netherlands, published an article in the "Nature" magazine to give an overview of "smart substances". They reviewed and analyzed the current industry's use of molecular systems, soft materials or solid-state materials. The progress of intelligent materials realized by materials, as well as the practical applications in soft robots, adaptive artificial skin and distributed neuromorphic computing.

Although the intelligent substances in the thesis do not show the kind of intelligence (such as recognition ability or language ability) that the public is familiar with, their functions have far exceeded the characteristics of static substances, and their potential applications are inspiring.

How to understand smart matter?

Under normal circumstances, we can understand intelligence as the ability to perceive information and use it as a knowledge reserve in order to complete adaptive behavior in a constantly changing environment. Although there is no exact definition of intelligent matter, researchers believe that when it comes to the concept of "intelligence", at least two main characteristics must be included: first, the ability to learn; second, the ability to adapt to the environment. So far, most of these two abilities exist in organisms.

With the popularity of AI technology, people are stepping up efforts to realize the machine learning and adaptation skills in an increasingly complex systems, these systems will be integrated in various functional components together . In addition to these functional architectures, it is worth noting that artificial synthetic substances themselves also show many intelligent characteristics, which may constitute a brand-new concept of AI.

Because advanced AI applications generally need to process a large amount of data, it is very challenging to regulate the behavior of intelligent substances in a centralized manner, especially when using traditional computers based on the von Neumann architecture for centralized information processing. The limit is quickly reached, moving data from the memory to the processor and back, not only greatly reduces the calculation speed, but also requires a lot of power consumption.

Therefore, new methods and computational paradigms need to be implemented directly at the material level, so that smart matter itself can interact with the environment, self-regulate its behavior, and even learn from the input data it accepts.

For the development and design of smart materials, inspiration from nature is very useful. The macroscopic functions of natural substances come from the complex internal structure and the interaction of molecular, nano-scale and macro-scale building blocks. In artificial substances, the combination of bottom-up and top-down methods can make the architecture have various novel characteristics and functions.

Researchers believe that the intelligence of artificial materials can be defined in a hierarchical manner. For example, smart substances are realized by combining four key functional elements: (1) the sensor interacts with the environment and receives input and feedback; (2) the actuator responds to the input signal and adjusts the performance of the material; (3) for long-term use A memory for storing information; (4) A communication network for processing feedback.

Ideally, these elements can form a functional processing continuum, which does not require a centralized processing unit, but provides local and distributed information processing capabilities.

Figure|Structural substances are static and cannot change their properties after synthesis, such as pure silicon; octopus tentacles, with embedded sensors, actuators and nervous system, represent smart substances (source: Nature)

The most basic structural substance, it may contain a highly complex but static structure. Although it has a wide range of applications, its properties cannot be changed after synthesis. At an advanced level, reactive substances can change their characteristics (shape, color, hardness, etc.) in response to external stimuli, such as light, current, or force.

At present, scientists are working hard to explore adaptive substances, which have the inherent ability to deal with internal and external feedback. Therefore, it can respond to different environments and stimuli. This definition is similar to "life-like materials", that is, synthetic materials inspired by living things and living substances.

Researchers believe that transcending adaptive substances will ultimately promote the development of smart substances. Smart substances will include four major functional elements (sensors, actuators, networks, and long-term memory), and can show the highest level of complexity and functionality.

What are the things that tend to be smart?

Researchers outlined in the paper traces the development of smart materials, has given no isozyme example of a complex system level of energy, thereby showing the development of intelligent material may trend.

The first type is cluster-based self-organizing materials (such as nanoparticle assemblies, molecular materials).

A prominent form of complex behavior is to rely on the collective interaction of a group or a large number of individuals in a group. In such a system, multiple individually responding entities will organize and communicate in a special way, thereby realizing large-scale adaptive phenomena and forming a collective protection model. In nature, this behavior is usually observed in insect communities, fish schools, birds and even mammal populations.

When using this concept to implement building blocks on a microscopic scale, this concept of basic intelligence is particularly interesting for the realization of intelligent matter. For example, cluster robots interact with a large group of small robots. Each small robot is about one centimeter high and has limited capabilities, but they can be arranged in complex, predefined shapes.

When considering group behavior on the nanoscale, similar logic is still available, such as nanoparticle assemblies. In self-assembled material systems, the local communication between weakly coupled and highly dynamic components takes place in the form of particle interactions. .

Based on chain formation, repulsive fluid and attractive magnetic interactions between structural nanoparticles, and according to the initial shape, micro-groups can perform reversible anisotropic deformation, controlled splitting and merging with high modal stability, and navigational motions, but these Shape adaptation relies on external programmer input, magnetic field control, etc., so the particles themselves do not show intelligent behavior.

Figure|Adaptive group behavior and colloidal clusters (Source: Nature)

Interesting adaptive behaviors are also found in synthetic molecular systems, and feedback comes from the interaction between the reaction network and coupling molecules. In addition, the transmission of information about the size of self-replicating molecules can be observed. From ancestors to offspring replicons, this behavior is somewhat similar to the norm in biology.

However, the lack of memory in this type of material prevents the material's ability to learn from past events.

The second is the realization of soft matter (such as reactive soft matter, soft matter embedded in memory, and adaptive soft matter).

In biological systems, softness, elasticity, and flexibility are notable features. Molluscs can achieve continuous deformation in a crowded environment, thereby achieving smooth motion. Natural skin also exhibits the remarkable characteristics of basic intelligence, including the tactile sensation of force, pressure, shape, texture and temperature, tactile memory and even self-healing ability.

The goal of the field of soft robotics is to transform these characteristics into soft matter. The soft robot can simulate biological movement by adjusting its shape, grip and touch. Compared with rigid materials, due to the conformity of the materials, when they come into contact with humans or other fragile objects, the risk of injury is greatly reduced.

Figure|Responsive soft matter and soft matter with embedded memory function (Source: Nature)

Soft matter contains reactive soft matter, and the most common drive is the change of shape and softness with input.

A typical example is a self-contained artificial muscle composed of a silicone rubber matrix. Its driving relies on the vapor phase transition when the liquid is embedded in ethanol microbubbles and heated. This sensitive artificial muscle can repeatedly lift more than 6 kilograms of weight.

Another case is based on the double cross-linked responsive hydrogel induced by DNA hybridization. With the help of an external DNA trigger, the volume contraction of the material is locally controlled to imitate human hand gestures. There is also an artificial skin developed by using the triboelectric effect, which can actively sense the proximity, contact, pressure and humidity of the touched object without the need for an external power source, and the skin can autonomously generate an electrical response.

There are also scientists who use the ion gradient between the micro-polyacrylamide hydrogel compartments of the cation and anion selective hydrogel membranes to create an "artificial eel" that uses a retractable stacking or folding geometry to activate thousands at the same time. A voltage of 110 V is generated after a series of gel chambers. Unlike typical batteries, these systems are soft, flexible, transparent and potentially biocompatible.

Soft matter embedded in memory, this type of functional soft matter combines material memory and perception capabilities. Some scientists have verified this concept in a mechanical hybrid material, in which a resistance switching device is used as a storage element on an island of rigid polymer photoresist (SU-8), which is embedded with stretchable polydimethylsiloxane In (PDMS), the microcracks in the gold film evaporated on polydimethylsiloxane act as electrodes and stress sensors at the same time. This kind of motion memory device allows the detection of humans based on changes in stress and subsequent information storage Movement of the limbs.

In addition, self-healing is also an important property of soft materials, allowing materials to quickly restore their original properties after being disturbed/bent, and is a way to eliminate past traumatic memories. A scientific team has reported an organic thin film transistor. This kind of transistor is made of stretchable semiconducting polymer, which can work normally even when folded, twisted and stretched on the moving human limbs, and this kind of polymer can repair itself after special solvent and heat treatment, almost completely The field effect mobility is restored.

Information processing usually involves counting, which requires a perception ability and a storage unit that stores the latest value. A scientific research team has proposed a design concept based on subsequent biochemical reactions to calculate substances, which can release specific light pulses based on the number of detected light pulses. The output molecules or enzymes to achieve the actual counting process.

In addition to sensing and driving, the adaptive soft matter also includes a precisely customized chemical-mechanical feedback loop. One way to realize adaptive soft matter is the autonomous particle motion model system proposed by scientists. It contains an elegant combination of sensing and driving, coupled through a reaction network, for example, there is a material that can regulate the growth and contraction of oxygen bubbles in the capsule. , Which leads to the antagonistic adjustment of effective buoyancy, and realizes the oscillating vertical movement of the colloid in the water driven by the enzyme.

The third type is the realization of solid materials (such as neuromorphic materials, distributed neuromorphic systems).

At present, the information processing technology of solid materials is much more advanced. For example, the traditional computer core is constructed by physical devices (such as chip transistors). Non-traditional computing surpasses standard computing models, especially biology, which can be considered as non-traditional computing systems.

Programmable and highly interconnected networks are particularly suitable for performing computational tasks, while brain-inspired or neuromorphic hardware is designed to provide physical implementation. Although in the top-down manufacturing of the semiconductor industry, mature semiconductor materials are used to enable neuromorphic hardware (such as Google’s tensor processing unit) to be realized, the bottom-up approach using nanomaterials may be unconventional and Efficient calculations provide new ways.

Researchers believe that combining the above-mentioned various material realizations, the hybrid method may eventually lead to the realization of smart materials.

For example, the use of phase change materials to simulate neuromorphic computing systems has become a key enabling factor for brain-inspired or neuromorphic hardware, allowing artificial neurons and synapses to be implemented in artificial neural networks, using them to be heated in an amorphous or crystalline state by Joule heating Under the programmability to achieve fast, accessible room temperature non-volatile memory function.

The memory behavior of phase change materials further makes them suitable for brain-inspired calculations, where they usually embody synaptic weights or nonlinear activation functions. In addition, two-dimensional (2D) materials, such as graphene , molybdenum disulfide, tungsten diselenide, or hexagonal boron nitride, have also appeared in experiments with neuromorphic devices, allowing the design of compact artificial neural networks.

A recent study showed that it is possible to perform nonlinear classification and feature extraction on disordered networks of boron-doped atoms in silicon at a temperature of 77K. Many other research results show that the deep neural network model of nanoelectronic devices can be used to effectively adjust the device through the gradient descent method to complete various classification tasks instead of achieving functions through artificial evolution.

These works reveal the potential for efficient calculations at the nanometer scale using the inherent physical properties of matter.

Figure|Neuromorphic materials and systems (Source: Nature)

It is worth noting that in the neuromorphic system, information processing and memory are co-localized, which is strictly different from the traditional von Neumann structure. One promising study is the optical neural network model, because light itself can be calculated by interacting with matter or interfering with itself without pre-defined paths. In addition, this model allows data to be processed at the speed of light (in the medium). Processing, and the power consumption is extremely low compared with electronic equipment.

When light propagates through different diffractive layers, the information is processed at the same time, similar to the preprocessing of data in human skin before it is transmitted to the brain through the nervous system.

In addition, the researchers also believe that each material reservoir has its own physical problems, and material learning can be used to make the reservoir emerge from the system instead of designing the material matrix into a good reservoir.

Looking forward to the future development path

So, what are the challenges in the future?

Researchers believe that the difficulty lies in the development of effective methods for manufacturing, amplifying and controlling smart substances.

Smart substances must contain dynamic materials with considerable degrees of confocal freedom, mobility, and nano-level component exchange. This means that the interaction between nanoscale components must be weak enough to be manipulated by external stimuli. In addition, such substances must exhibit a certain degree of internal organization of nano-level components, so that feedback and long-term memory elements can be embedded, and in order to fully receive and transmit external input, addressability with spatial and temporal accuracy is required. These requirements may be contradictory to a large extent, and may not be compatible.

Obviously, the key elements of smart materials are easier to implement in different material types, but researchers hope that hybrid solutions can solve the incompatibility problem.

So, what will the road map to smart matter look like? They have an idea.

First, a demonstrator and design rules are needed to develop an adaptive substance with an inherent feedback path. By integrating nano-scale building blocks, the self-assembly and top-down manufacturing of nanostructures can be reconfigurable and adaptable;

Then, it must start with adaptive substances that can handle feedback and develop into substances with learning capabilities ("learning substances"). These materials will be enhanced by embedded memory functions, material-based learning algorithms and sensor interfaces;

In addition, it is also necessary to develop from learning materials to truly intelligent materials, receive input from the environment through sensory interfaces, display the required response through embedded memory and artificial networks, and respond to external stimuli through embedded sensors.

Therefore, the development of smart materials will require coordinated, interdisciplinary and long-term research efforts.

Ultimately, considering that overall performance is the collective response of components and connections, a complete system-level demonstration is necessary to accelerate the use of smart materials. Various technological applications of smart materials are foreseeable, and the collaborative integration with existing AI and neuromorphic hardware will be particularly attractive. In this regard, applications in life sciences and biological cybernetic organisms also require biological Compatible realization.


Tuesday, March 9, 2021

Accurate AI investment for health insurance, "Shu Ming Technology" completed a round of financing of more than 100 million yuan

 "Quickly become the top traffic portal in the insurance industry through algorithms"

It is reported that "Shu Ming Technology" has recently completed a round of financing of more than 100 million yuan. This round of financing was jointly led by Weilai Capital and Zeyue Capital. The funds raised will be used to invest in the research and development of artificial intelligence algorithms and SaaS service platforms, and to expand the technical operation team. "Suming Technology" said that through this round of financing, the company will achieve significant improvements in algorithm optimization, launch scale, and market development, which will bring significant revenue and profit growth to the existing promotion and customer acquisition business. It is predicted to be in the first half of the year. The implementation-level trial operation of the first batch of customer SaaS service platforms was completed.

"Suming Technology" was established in Shanghai in 2017. It is an artificial intelligence algorithm company with insurance and big health user behavior prediction and commercialization as its core business. Its core technology lies in the use of artificial intelligence algorithms to predict and analyze user consumption behavior based on the fusion of multiple data sources. The two major business lines of the company are: First, through the unique "Federal Modeling" technology platform, redesign the best insurance process and user matching model to help C-end customers find the best medical care that suits their specific needs. Insurance plans/products; second, provide traditional insurance companies and innovative Internet insurance platforms with labeling and structuring capabilities for insurance company’s existing user data, and assist insurance companies to increase the secondary conversion rate of existing users and LTV (user lifetime value) ), and work with insurance companies to optimize and customize insurance products.

In terms of the current status of payers in the Chinese medical market, total non-government health expenditures in 2019 amounted to 4.7 trillion yuan, of which 1.85 trillion were personal expenditures and 2.09 trillion were basic medical insurance expenditures. As the aging trend of China's population structure becomes more obvious, the social security balance rate has also dropped rapidly from 18% in 2013 to 4% in 2019. Judging from the recent policy situation, the government is also starting to solve the problem of insufficient medical insurance funds by building a multi-level medical security system and increasing efforts to develop health insurance. In this context, the compound growth rate of health insurance premium income in China in the past five years has exceeded 30%, and the health insurance premium income in the first three quarters of 2020 will be nearly 700 million yuan.

In the field of health insurance, "Shu Ming Technology" applies machine learning technology to locate, evaluate and prioritize all user behavior data in real time, and obtain learning sample sets and real order feedback results based on user interaction, so as to continuously optimize algorithms to get closer Actual business needs. According to reports, as of the end of 2020, the annualized premium of "Shu Ming Technology" has exceeded 100 million yuan, with a compound growth rate of more than 100%.

The lead investor in this round, Weilai Capital’s partner Zhao Yang, believes that China’s medical industry is rapidly switching from the hospital’s in-hospital market to the out-of-hospital user market, and the underlying business logic is shifting from the traditional "enterprise user market" to the "individual user market". Users have a greater say in choosing appropriate medical and payment solutions. This has brought about a radical change in the growth model of the pharmaceutical industry, channels, and medical service scenarios. The forces driving this change are diverse, including the top-level design of the National Medical Insurance Bureau and the Banking and Insurance Regulatory Commission, as well as the cross-domain integration of new technology companies such as Shuming Technology. Zhao Yang believes that Shuming Technology has a great opportunity to replicate the successful cases of the insurance market in the pharmaceutical supply chain and medical service fields and cut into a new trillion market.

Monday, January 11, 2021

Consumerism is in full swing, and the Internet no longer has technological innovation

 In the past year, companies scrambled for IPOs, and some "bleeded" continuously and plunged all the way, and some IPOs were high light, which was enviable.

On November 20, Yixian E-commerce , the parent company of Perfect Diary , was listed on the New York Stock Exchange. On the first day of trading, its share price rose 75.24% to US$18.40, with a market value of US$12.2 billion; on December 11, Bubble Mart officially It was listed on the Hong Kong Stock Exchange with an issue price of HK$38.5 and an opening price of HK$77.1, which was a 100.26% increase from the issue price, and its market value exceeded HK$100 billion.

Perfect Diary and Bubble Mart broke out among a group of listed companies, attracting the attention of the outside world to new consumer brands. It is worth mentioning that in the tea industry, hi tea, vitality forest, tea Yan Yue Se and other websites Red brands have emerged one after another, driving wave after wave of consumer enthusiasm. In the game industry, the emergence of explosive models also quickly brought young companies such as Mihayou and Lilith to the center of the stage, damaging the face of major game companies. The interweaving and changes of the old and new forces will be particularly conspicuous in 2020.

In fact, this is also a reflection of the rise of a new generation of entrepreneurs, such as Perfect Diary, Bubble Mart, Hi Tea, Miha Tour... behind this are mostly the post-80s.

Post-80s entrepreneurs have become the core force of the current entrepreneurial world.

But not all post-80s entrepreneurs are so lucky. Technology-based startups represented by the "AI Four Little Dragons" all announced their impact on the listing this year, and it is still unclear who will get this AI "first share". In the context of doubts about the entire industry, the valuation given to them by the market is also unsatisfactory.

Flowers and applause on one side, cold water and doubts on the other.

Two Roads for Post-80s Entrepreneurs

In the early years, when the post-70s founders began to call the wind and rain and buy emerging companies everywhere, the post-80s entrepreneurs struggled to survive in the fierce competition between the giants, and when they were acquired as the reality, the post-90s had already begun to enter the entrepreneurial stage. Disturb the situation on the tuyere. As a result, the Internet entrepreneurs in the post-80s group once showed a "disruption" phenomenon, which also makes the post-80s entrepreneurs' sense of existence seem not as good as the post-90s.

Now this situation is changing. Zhang Yiming, Su Hua, Huang Zheng and other post-80s tycoons have already gained a foothold in front of the giants. In addition, a large number of post-80s entrepreneurs have gathered in front of the IPO this year. . They can be roughly divided into two distinct camps: technology companies emerging from the AI ​​entrepreneurial wave and new consumer brands born from consumerism.

The former takes the technical route and the latter takes the marketing route.

In 2016, AlphaGo defeated the world's top Go player Li Shishi with an overwhelming 4:1 advantage. This victory quickly blew up a massive artificial intelligence trend in China, and countless entrepreneurs devoted themselves to the AI ​​boom. Earlier, a large number of technical elites who had been dormant in the laboratory for many years also chose to walk out of the laboratory. They were looking for outlets, betting on them, and eager to change the world with technology.

The post-80s accounted for a large part, such as Yin Qi, who was born in 1988, graduated from Tsinghua University with a master's degree in computer science from Columbia University, and co-founded Megvii Technology with two classmates , and Lou Tiancheng, born in 1986— The recognized first person in computer programming for college students in China founded Xiaoma Zhixing.

In addition, the AI ​​"Four Little Dragons" and the Cambrian that just went public, these AI start-ups that have broken out of the siege, are behind the 80s entrepreneurs.

However, the upsurge of AI entrepreneurship did not continue after all. In 2020, entrepreneurs will target the new needs of young consumer groups and play new tricks in industries such as tea and entertainment . Different from the past entrepreneurs, the new batch of post-80s are good at stimulating consumer desires, creating products in a way that satisfies the curiosity of users, and shaping new “net celebrities” one after another.

The entrepreneurial wave represented by new consumer brands such as Perfect Diary and Bubble Mart is no longer a deep transformation of business models or the creation of new species based on technological breakthroughs, but the market's pursuit of them has surpassed AI companies. After being listed on the Science and Technology Innovation Board, Cambrian’s stock price fluctuated all the way. The current market value is only 64.8 billion yuan, while Bubble Mart’s listing broke through 100 billion Hong Kong dollars; the AI ​​"Four Little Dragons" went public on a bumpy road, and the perfect diary only took 4 years. Time has become the first stock of Chinese beauty.

The high expectations of the outside world for AI have fallen, and the business prospects of AI companies have been questioned. The road of technological entrepreneurship seems to have entered a cold winter, and consumerism is prevailing, trendy shoes, blind boxes, beauty... can meet the inner needs of young consumers The products are popular, attracting more entrepreneurs influx.

However, this trend hides the crisis.

2020, no new story in venture capital

In September of this year, Ali publicly predicted that "the next ten years are the 10 years for the Internet to create new brands." They believe that the rise of "new consumer brands" will become the most certain opportunity for China in the next 5-10 years.

Jiang Fan’s original intention is to emphasize that Tmall is still the core position of the new brand. From the perspective of the entire entrepreneurial environment, this judgment is surprisingly similar to the current entrepreneurial track focused on creating consumer brands. Perfect Diary, Bubble Mart , Hey Tea, Yuanqi Forest, Tea Yanyue... There seems to be no other new business stories besides those pouring into the center of the entrepreneurial stage in 2020.

Internet giants are busy reducing dimensionality and cracking down on vegetable vendors, and a new generation of entrepreneurs is staring at the pockets of young people.

This is inevitable. The Internet has left fewer and fewer opportunities for entrepreneurs born in the 1980s. Each track and each subdivision has almost been crowded with all-pervasive giants or entrepreneurs within the giant system, which does not include those who have fallen out. "Floating corpses" everywhere. If you take a closer look at the top 100 apps in Yuehuo, you will find that there are almost no new products born in 2020. Only when consumerism prevails, new brands can grow rapidly.

However, mainstream public opinion criticizes consumerism, and many people believe that consumerism deceives the younger generation to consume the symbolic meaning of goods rather than the actual use value. For example, blind boxes. Buying a blind box does not necessarily mean you really like the contents, but the act of opening the box itself brings an emotional experience similar to gambling.

The outside world is worried that young consumers will fall into the trap of consumerism, but it may be the entrepreneurial model that actually enters the trap.

From 2010 to 2020, there have been many climaxes in the wave of Internet entrepreneurship. Takeaway, O2O, online ride-hailing, short video, sharing economy, AI... these outlets are becoming more and more lively with more and more capital participation, but they are carried. The value of innovation has plummeted. From transforming traditional industries, upgrading consumption patterns to killing users' time, until now, only the satisfaction of consumer desires remains.

This is related to the starting point of the entrepreneurs. In the past, the original intention of entrepreneurs was to change, but now it has become catering. This leads to a key problem. Consumers’ consumer needs and psychology are constantly changing. Once you are not sure about this change, The life cycle of the company's products will be greatly reduced.

Moreover, the original commercial chain from user habit formation to user value mining is no longer established.

Another risk is that behind the new consumer brands such as Bubble Mart, Hey Tea, and Genki Forest are essentially consumer behaviors promoted by the insecurities of the current young people. When more and more people realize that this consumption behavior does not have much benefit in anxiety relief, it is obvious what choice they will make.

No more "breakers" on the Internet

Will the next BAT emerge among Internet startups in 2015?

This question was once asked by a netizen on Zhihu in September 2015. Among the few answers, the answer was surprisingly consistent: No.

However, the facts later hit the face. On January 6, even though it was caught in a storm of public opinion, Pinduoduo's stock price skyrocketed, and its market value reached its highest value ever-230 billion US dollars. Huang Zheng personal wealth also suffered over the horse of Ma Teng and become China's second richest. For entrepreneurs, Pinduoduo's success is more impactful than Meituan, which is not much different from its market value.

New forces such as Meituan and Didi have grown into industry giants, relying on model innovation to transform traditional industries. This is no different from the earlier BAT occupying the e-commerce, social, and search fields without strong opponents. Pinduoduo It was abruptly breaking through the cracks between Ali and This seems to prove that the entrepreneurs who have fallen behind have proved that in an industry environment with a set pattern, it is not necessarily impossible to beat the big with small ones.

However, if you want to ask if there will be the next "Pinduoduo" among Internet startups in 2021, the answer may still be pessimistic.

According to statistics from it oranges , there will be a total of 3886 new economy companies in China in 2020, with a total financing of 814.5 billion yuan. And in this big cake, 56% of the funds were taken by companies with a financing amount of more than 1 billion yuan, but such companies only accounted for 4% of the invested companies, and 89% of the companies had only Won 1 vote.

It is clear that future funding set the trend in the head a few companies will be more severe.

More specifically, where did most of this money go? On the one hand, medical care, online education, industrial Internet, and technology sectors represented by robots, chips, and smart hardware; on the other hand, new consumption investment in second-tier cities, that is, new consumption of tea, self-heating pot , hot and sour powder, etc. Brand.

In the former entrepreneurial track that has been in development for several years, in theory, technology companies have the greatest potential and are far more imaginative than Pinduoduo. However, technology-based companies have the characteristics of long R&D time and long commercial payback period. In the mid- and early stages, R&D is the main focus, with products as a supplement, and the business model is relatively backward. This has become the biggest flaw in the capital winter, because the market pays more attention to the profitability of the company itself.

Therefore, the way such companies could have been financing through venture capital is no longer possible, and they can only rely on the stock market to meet their growing capital needs.

As for the latter, new consumer brands such as Bubble Mart, Hi Tea, and Vitality Forest are also marketing success and failure marketing. Under the restriction of non-rigid demand, its products can cover only a small group of young people. Those who like it are willing to consume, and those who don't like it are hard to impress. What's more, there are many subdivisions in the new consumer field, and it will be difficult to give birth to a giant that unifies the tea or play market.

New entrepreneurs born in the 1980s still have a long way to go.

In 2020, the "lipstick effect" will begin to appear. Consumers avoid buying bulk commodities and prefer products that can satisfy strong consumer desires and bring psychological comfort. This is true for lipsticks, blind boxes, and online tea drinks, which will give birth to There are more new consumer brands. However, whether this is a good era or a bad era is uncertain.

But the pockets of consumers have long been targeted by countless entrepreneurs. Their methods have no technical content, but you still haven't seen the key.

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