Since AlphaGo defeated Go world champion Lee Sedol in 2016, the artificial intelligence track has entered a six-year stage of rapid development, and a large number of artificial intelligence companies have appeared, grown, and even successfully IPOed.
Fueled by the influx of capital and a large number of talents, these artificial intelligence companies continue to explore the path and possibility of commercialization, including the application of AI in security, retail, education, finance, logistics, automotive and other industries.
In fact, AI has become a necessity in many fields, and investors, consumers, and corporate customers have seen its value.
On the other side of the coin, we have not yet witnessed the explosive growth of AI like the wave of Internet entrepreneurship such as smartphones, group buying, and social networking, and even for a period of time in the future.
Where is the future? This is the question that all AI companies face, and it is also the answer that investors and people in the industry want to seek.
Survive on the B-side, and erupt on the C-end
AI to B or to C? A few years ago, there was no shortage of discussions about this issue in the industry; today, time has given the most correct answer: AI has landed deeper and more thoroughly on the B side.
For example, in the field of security, in the past information age, the camera was only a terminal that recorded video content, and managers needed to view video content frame by frame and seek relevant information. The camera just collects information and makes little progress in productivity.
Today, cameras with AI capabilities can identify and make decisions in seconds from shooting, computing, and intelligent analysis, bringing an order of magnitude jump to the effectiveness of managers.
Another example is manufacturing, in recent years, the industrial machine brain has become more and more intelligent, and the visual and voice exchange has become more and more accurate, which has replaced most of the repetitive work, replaced the manpower, and brought direct cost reduction and efficiency. Musk's Tesla factory is a typical example, its production and manufacturing lines are almost invisible, it is not only a factory, but a giant "industrial mother machine".
In addition, there are transportation, finance, education, logistics... AI has effectively brought about an improvement in efficiency at the B-side, and has gradually become one of the indispensable core technologies in many industries.
Relying on the B-end market is enough to keep the company alive and live well. From the data of the head AI company's revenue, we can also gain insights, and at the B end, it can already bring hundreds of millions or even billions of revenue, opening up the value closed loop.
AI application scenarios are very extensive, not only giving birth to some head companies, but also feeding many small and medium-sized enterprises. The B-end market has strong differentiation and regionality, as long as it can deeply cultivate a segment, it is not difficult for the company to live.
For example, the face gate subdivision scenario, if you can open up local resources and hold stable customers, you can live well. And small companies will not face too much pressure on the technical level, because more and more open source platforms promote the gradual reduction of development costs, and the overall level of algorithm accuracy in the industry is improving, which is enough to meet the general needs of the industry.
The core problem is that the growth rate of the B-end market has been relatively slow, and there has been no exponential explosive growth.
From the underlying logic analysis of market supply and demand, AI to B customer decisions consider whether it is useful or not, while C-end users consider more whether it is good or not. In other words, the B side needs to improve efficiency and cost performance, while the C side pays more attention to user experience.
More importantly, the C-end is easier to standardize, conducive to large-scale expansion, and easy to form a chain reaction.
At present, the global economic downturn requires a strong and grounded C-end product model to cater to the needs of users, while also helping AI companies better obtain upstream and downstream resource support such as capital and policies, forming a virtuous circle of value closed-loop and butterfly effect. The market urgently needs a disruptive C-end product that detonates the industry.
What form will AI to C explosives take?
Before answering this question, let's take a look at the ranking of the world's most valuable companies in the past 20 years.
The chart above shows the top ten companies in the world by market capitalization from 2000 to 2020. In the past 20 years, technology companies have gradually led the global economic growth, and 7 of the top 10 in 2020 are technology companies.
It is worth noting that most of these technology companies are To C companies, or have C-end explosives. For example, Microsoft Surface computer, Apple iPhone, Mac, Google search engine, Tencent social software... Either a soft and hard product, or a pure soft product.
What is the next generation of these C-end products? After adding AI intelligence, in the next decade, the butterfly will become an AI robot.
They will appear in people's daily lives in a variety of colorful forms, such as tangible family robots, chess companion robots, invisible digital people, humanoid robots... Self-driving cars are essentially robots with four wheels.
AI Business Review believes that ten years later, standing at the top of the global market value, it must be a company that can create world-class C-end software/soft and hardware integrated robots.
Tesla founder Elon Musk has long been known for his forward-looking vision, believing that robots will be the next generation of disruptive technology products, and Tesla's humanoid robot Optimus business will far exceed the market value of Tesla vehicles.
Recently, at the Cyber Rodeo event in Texas, Musk discussed the future of Optimus and humanoid robots in society with Chris Anderson at TED.
"Tesla tends to build a robot that's meant to be dangerous, boring, repetitive, and things people don't want to do. When the robotics business took off, the automotive business, which generated $18 billion in revenue last year, looked like a mini-game. "I'm surprised that people don't realize the potential of Optimus Prime's robotics program, and its importance will become apparent in the coming years." Those with insight will understand that Optimus Prime will ultimately be more valuable than the automotive business, more valuable than fully autonomous driving, and this is my firm belief. ”
He also said Tesla will be showcasing a "prototype" of optimus robots sometime this year, that by 2023 "there may be something useful" coming out, and by around 2025, Optimus's utility will grow rapidly and become a reality.
In fact, robots are not a new track, in the past decade, this field has experienced several waves of entrepreneurial small waves, but it has always been tepid. At the heart of the market's concerns lie in the technology and market redlines. At the root cause, it is still a problem of technological breakthroughs.
Looking for answers from the evolution of AI-related technologies, here's the Hype Cycle for Artificial Intelligence, 2021, a global information technology research and consultancy Gartner:
As shown in the figure, many core technology modules of artificial intelligence are already in the embryonic stage and expectation period, and the next 5-10 years will usher in a blowout outbreak. In particular, chatbots, self-driving cars, computer vision and semantic search have passed the trough of bubble bursting and gradually moved towards a recovery period of steady climbing, and the large-scale application of robots is coming.
Shubhangi Vashisth, senior principal research analyst at Gartner, said: "Ai Is innovating at a rapid pace, with more than half of the technology maturity curve going mainstream within two to five years. Innovations such as EDGE AI, computer vision, decision intelligence, and machine learning will all have a revolutionary impact on the market in the coming years. ”
As a robot with four wheels, the smart car is already on the eve of the outbreak. Tesla, "Wei Xiaoli" and other new energy vehicle companies striding forward, traditional car manufacturers have also begun to take the initiative to adjust the direction, and vigorously accelerate the investment in new energy vehicle tracks. At present, BMW, Mercedes-Benz, Honda and other world-renowned automobile companies have released new energy vehicles. Moreover, traditional car manufacturers have announced that in the next 5-10 years, they will completely stop production of fuel vehicles.
Under the wave of smart cars sweeping the world, smart cars will become the entrance to lead the next generation of industry changes.
In the past, the essence of the automobile was a means of transportation, relying on suppliers to develop new functions to prioritize costs and squeeze supply chain profits. Innovation in the car revolves around power, including the engine, transmission and chassis.
Now, the essence of the car is intelligent mobile space, direct contact with users, user experience design and user value creation first, car innovation has become a battery, motor and electronic control, software, data and services will become the core competitiveness of automotive product differentiation.
In addition to cars, there are service robots, elderly companion robots, virtual digital people, customer service robots... In a few years, robots will become an integral part of humanity.
Write at the end
The commercialization of To B+To C two-wheel drive AI is the best business model for artificial intelligence companies.
The To B market is more rigid, with the characteristics of large demand and high degree of intensification, and the commercial landing gives priority to the To B market for "landing". B-end orders are large, and revenue can be continuously generated through follow-up services, which can enable enterprises to quickly return costs and achieve stable marginal cost goals.
To C products, which directly connect with consumers, will certainly create greater value if they can occupy user time through a great experience. Once the C-end products rise, they will usher in a full-scale explosive growth in the short term.
Catherine Wood, founder of the ARK Fund, said the market capitalization created by deep learning will be 2.5 times larger than that of the Internet. In the next 5-10 years, the first echelon of global enterprise market capitalization will give birth to new world-class technology giants, no matter who spends it, it must be inseparable from artificial intelligence.
There is a high probability that there are also Chinese technology companies among them, and we look forward to it together!