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We are in the era of another gold rush, the AI ​​gold rush. AI startups in various fields have attracted tens of billions of dollars in investment. In 2016, the four major technology giants: Google, Amazon, Microsoft and IBM, invested more than 20 billion US dollars in AI. Companies are scrambling to invest in AI, and they want to use AI to increase productivity earlier than their competitors, but at the same time they are keeping a close eye on startups and are always wary of the threats to startups.
AI and machine learning will be everywhere in society. Just like any gold rush, we will ask who will find gold? Is it a minority, a brave, or a strong? Can a fast-growing startup find a gold nugget? Will companies that offer shovel and shovel get the most out of it? Who will pay the price to become cannon fodder? Where is the value created by AI?
When I started thinking about who would benefit from AI, I thought of seven questions. Who will benefit from:
1. Chip manufacturer 2. Platform and infrastructure provider 3. Pattern and algorithm provider 4. Enterprise solution provider 5. Vertical industry solution provider 6. Company using AI 7. Country
Although the cost of computing power has been greatly reduced, the demand is increasing. Both AI and machine learning need to collect a huge amount of data sets and perform tera-scale matrix calculations, and a large demand for chips will follow.
NVIDIA's share price has grown 15 times in the past two years thanks to its GPU (graphics processor) chip has historically been used to create high-definition, high-speed, high-end gaming graphics, which is perfect for this chip. In machine learning. Google recently released a second-generation TPU (tensor processor) (a tensor processor is a dedicated chip designed by Google for machine learning). Microsoft is also developing its own Brainwave AI machine learning chip. At the same time, startups are also preparing to enter the market, such as Graphcore has raised $110 million.
Today's chip suppliers such as IBM, Intel, Qualcomm, AMD (AMD) have not stayed where they are. It is even said that Facebook (Facebook) is also creating its own team to design its own chips. Chinese companies are also paying more and more attention to chip technology. Cambrian Technology just launched the first generation of cloud AI chips last week (May 3, 2018).
Clearly, the cost of designing and manufacturing chips and the cost of maintaining a global chip leader position is very high. This requires very strong financial support and requires world-class chips and software engineers. There won't be a lot of winners. Like the gold rush at the time, whoever sells shovel and shovel is the cheapest and can be used by most people, who is the winner.
The cloud is another venue for the AI ​​competition. Amazon realized early on that startups needed to lease rather than buy computers and software. In 2006, Amazon launched AWS (Amazon Web Services). Today, AI has a very high computing power, and more and more companies are turning to hardware for IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) vendors.
The figure above illustrates the market share of cloud infrastructure services. Amazon is the leader in cloud services, but Microsoft, IBM, Google, and Alibaba are also close behind.
Competition is taking place among tech giants. Microsoft's Azure cloud service can serve both public and private customers, and Azure is said to have one million computers. In the past few weeks (March 26, 2018), Microsoft announced that Brainwave's hardware solutions have increased Bing's search engine speed by more than 10 times, greatly improving machine learning performance. Google is also catching up, their product is called GoogleCloud. China's Alibaba has also begun to occupy a place in the international market.
Large cloud service providers are taking the lead in the big demand of AI drivers.
Amazon – Microsoft – Google and IBM will continue to lead in this area, and China's cloud service providers are already strong. In this AI battle, merchants selling shovel and shovel will benefit again.
Google is now the world's largest AI company, attracting the best AI talent, spending AI research and development on a small country's GDP, and tens of billions of users provide them with the best data sets. AI has improved many of Google's features and products, such as search, autopilot, speech recognition, intelligent reasoning, large-scale search, and even finding drugs and diagnosing diseases.
What drives Google AI is its powerful AI machine learning software and algorithm tool - TensorFlow. Now TensorFlow is an open source software that is free to use for everyone. Yes, free! Why is Google going to open TensorFlow for everyone? Jeff Dean, head of Google Brain, recently said that 20 million companies or organizations around the world will benefit from it. If millions of companies use this world-class free AI software, they will most likely need a lot of computing power.
But who has a good product to meet this demand? Of course, Google Cloud, it is best for TensorFlow and its related AI services. Once you rely on Google's software and cloud services, you will be a long-term sticky customer. It's no wonder that winning the top spot in the global AI algorithm competition will be a brutal game. In addition to Google, Amazon, Microsoft and IBM are also offering cheap or even free AI software services.
In addition, fierce competition is not only in the field of machine learning algorithms, but also in the field of intelligent algorithms, including dialogue robots, conversational languages, natural language processing (NLP), semantics, vision, and enhanced core algorithms. One startup is growing rapidly in this highly competitive field -- Clarifai provides companies with advanced image recognition systems to search and identify almost identical images. The company has raised $40 million in the past three years. The market for image-related algorithms and services is estimated to reach $8 billion between 2016 and 2025.
The competition between deep learning and cognitive algorithms will facilitate the development of application-based AI solutions.
Technology giants will not stop. For example, the Watson cognitive products and services provided by IBM have about 20 APIs (APIs: ApplicaTIon Programming Interface), which can be widely used in various fields such as dialogue robots, vision, conversational languages, languages, knowledge management and Empathy area. If a company needs to create its own AI-driven application, it only needs to embed IBM's API into the company's software. Cognitive APIs are everywhere. KDnuggests lists a list of the top 50 cognitive services, with technology giants and start-ups. These cognitive services can be provided in the cloud, namely AIaaS: AI as a Service, so that more people can use these services.
Microsoft's recent CEO said that 1 million programmers are using their AI application programming interfaces (APIs), services, and tools to build AI applications, and nearly 300,000 programmers use their tools to develop session bots. If I am a startup, I don't want to compete with these giants.
The winners in this field are likely to be those heavyweights. They can hire the best R&D team, have strong financial support, and the largest data set. For start-ups to develop, they must have strong economic backing, world-class research experts, intellectual property and research results, deep expertise, and high-quality data sets. Startups must have superb navigation skills to sail faster than the tech giants; or open up new routes that have evaded direct competition with the giants.
There are many startups that will die, but those startups that can grow bigger will become international companies, or they will soon be acquired by technology giants. Even if some startups don't find a suitable commercialization method, if their AI algorithm team has strong research capabilities, they will be acquired because of their technological capabilities. DeepMind is a two-year London company that was acquired by Google for $400 million in 2014 because of its unique enhanced machine learning algorithm.
Technology giants have been occupying enterprise software such as Salesforce, IBM, Oracle, and SAP in Germany. They all realize that their products need to have AI elements. At the same time, many startups are fiercely competing in areas that large companies are not currently involved in, in the hope of providing next-generation solutions for businesses.
We analyzed more than 200 cases in the enterprise solution space, involving customer management, market development, network security, information management, human resource management, and the current hot cognitive robotic process automation (RPA: CogniTIve RoboTIc Process AutomaTIon). The enterprise solution space is more open than the previous ones, with a variety of startups offering a single point of solution for specific user needs. There are now more than 200 AI-driven companies in the recruitment field, many of which are startups.
UiPath, the leader in network security and the leader of RPA (Cognitive Robot Process Automation), has a readout fund of 100 million yuan. Big companies also want to ensure that their product ecosystems are always at the forefront of technology, and that investing in startups has improved their product performance. Salesforce invested in a customer management services company, Digital Genius, and also invested in a corporate translation services company, Unbable. Some big companies have more urgent problems. For example, the German SAP company is trying to catch up with cloud services, let alone catching up with the development of AI.
Some companies also offer AI-related tools that simplify the creation, application, or management of enterprise AI services. For example, machine learning training is confusing, and 80% of the time is spent combing data. It took too much time to test and debug hyperparameters. Pettum, a company in Pittsburgh, USA, has raised $100 million and its products are applications that accelerate and optimize machine learning models.
Enterprise AI solutions will drive customer service levels and productivity.
If AI companies that offer enterprise solutions can quickly prove that they are solving real-world problems and can scale their applications to meet the broad needs of their customers, such companies will have good prospects. As happened in the past, in the software gold rush, there are several winners in each industry category. These winners, and their world-class products, if they appear to be threatened, will most likely be acquired by technology giants.
AI is driving the creation of the best vertical industry solutions. Many new AI companies provide solutions for businesses such as health, finance, agriculture, automotive, legal, and industrial. Many startups provide services directly to customers and bravely challenge large companies in the field.
New industry AI solutions will be consolidated and may also challenge the leadership of existing large companies.
Clearly, many startups offer valuable point solutions for their specific needs. If they meet the following 4 conditions, they will succeed:
â— A large number of training data sets, and have their ownership â— Professional knowledge: a deep understanding of the industry â— Application AI talent pool â— Strong capital can support its rapid growth.
These startups are able to communicate well with customers in the client's business language, with good business efficiency and return on investment (ROI: Return on Investment), as well as good market entry strategies.
While many companies will look for new AI service providers in their industry to increase their revenues and profits, they will not negatively allow startups to snatch their customers. At the same time, they will not sit back and watch rival companies gain first-mover advantage through AI. Now that companies are innovating in competition, they will accelerate their development or set up their own startups to ensure they are leaders in AI innovation.
The advantages of large companies are obvious, they will benefit from the development of AI, such as providing services that make customers more satisfied, higher productivity, and better products and services.
Big companies have data assets that are more advantageous than start-ups or small companies. For AI and machine learning, data is fuel. Insurance companies have a large historical data on underwriting claims; financial services companies are well aware of financial products and customer buying behavior; search engine companies know the most about users' search information. These companies, who will take the lead in the AI ​​war?
Regardless of size, all companies want to benefit from AI. The business value of Gartner Consulting's research on AI drives is estimated to be as high as $3.9 trillion in 2022. The value of AI can be reflected in all walks of life. Even if there are not thousands of such user cases, there are at least hundreds. AI can help companies improve customer experience, save costs, lower prices, increase revenue, and sell better products and services. AI will make big companies stronger, and of course the price is small companies. To this end, big companies as leaders must have vision, extraordinary execution, and can tolerate failure, because the project is likely to fail when first trying new technologies (like the first person to eat crabs).
Many countries are also taking the lead in AI. The Chinese government has strongly advocated the development of AI, and has invested heavily in cultivating AI talents and supporting start-up companies. A more relaxed environment, especially in terms of data privacy, will make China a leader in certain areas of AI such as security and face recognition. It has recently been reported that the Chinese police can identify the face of a suspect from 50,000 faces at a music concert.
Shangtang Technology Co., Ltd. is an AI company that analyzes a large number of faces and images. According to reports, Shangtang Technology has raised $600 million and will become the most valuable AI startup. China says its mobile market is three times that of the US, and mobile payments are already more than 50 times that of the US – these are huge data advantages. Europe focuses on data privacy regulation, and the EU is said to invest $22 billion in AI, but data privacy regulation will likely put Europe at a disadvantage in certain areas of AI.
Will the above countries be the winners of the AI ​​battle? China? United States? Japan? Germany? United Kingdom? France?
Britain, Germany, France, and Japan have recently announced that the AI ​​strategy will be a national policy. For example, French President Mark Long said the French government will invest $1.85 billion over the next five years to develop the AI ​​ecosystem, including the establishment of large public data sets. Google's DeepMind and South Korea's Samsung will open new labs in Paris; Fujitsu will expand its Paris R&D center. The UK has just announced an investment of $1.4 billion for AI to fund 1,000 AI doctors.
Although countries are vigorously developing AI talent and AI ecosystems, the question is who will ultimately benefit? Will Dr. AI, funded by France and the UK, eventually become a Google employee? Machine learning experts hold a reasonable six-figure salary and pay a reasonable income tax (a lot of income), but most of the economic value they create is left to US companies, shareholders of these companies, and the US finances unit.
AI will increase the productivity and wealth of companies and countries. But if 30-40% of our jobs are replaced by machines, how will these new wealth be distributed? Economists can learn from the problems brought about by technology automation over the centuries. Will AI bring about an increase or decrease in pure job opportunities? The machine learning godfather, Geoffrey Hinton, predicted that a large number of radiologists would be unemployed because the machine would use medical imaging to diagnose the disease.
But at the same time, we also saw that with the aid of AI, Chinese radiologists can check the CT map of 1.4 billion lung cancer patients every year. This workload, if there is no AI, is impossible. This result is not a lost job, but a larger potential market and a more efficient and accurate diagnosis. However, for a certain period of time, because a small number of companies and countries control AI technology and data, the value brought by AI will be monopolized by these companies and countries. This will bring some conflicts to the world. Some countries have more low-end technologies and a lot of work will be replaced by AI automation, and these countries will be at a disadvantage. Large companies and powerful countries with advanced technology will benefit from AI.
When we studied this AI map carefully, we clearly saw that we were in the golden age of AI. Where the economic value will flow, the answer is obvious:
◠The global technology giants will be the shovel and shovel of the AI ​​gold rush - providing tools for AI gold digger.
Google – Amazon – Microsoft and IBM will compete for leadership in the AI ​​space. They will compete to provide the best chips, cloud and AI algorithms and services. China's Alibaba and Baidu are close behind. A few start-ups will come to the fore, their products may be cheaper than Microsoft's cloud computing products, or they may produce better AI chips than Google's Tensor Processing Unit, or develop more than Amazon. Good object recognition cognitive algorithm.
â— AI startups offer a variety of cognitive algorithms, enterprise solutions, and deep industry vertical solutions.
To be successful, start-ups need a unique data set, deep industry understanding, strong financial backing, the ability to absorb and retain AI talent, and the demand for these talents will grow. This is not an app that can be invented in the garage and change the world with it. The AI ​​startup company will solve important problems in the real world, quickly scale the market strategy, and establish a moat to protect itself. Start-ups should focus on the resolution of companies and industries because there are some high-value users in these areas.
However, in the next few years, in order to compete for talent, more and more algorithmic startups will be merged. Just like in the gold rush, many startups will become cannon fodder, and only a few survive in every field. These winners will see technology companies looking to merge them with attractive checks.
â— The company will gain a lot from AI, and it is estimated that the revenue will be trillions.
By automating business processes and increasing the competitiveness of products and services, AI will continue to enhance the customer experience, increase productivity, and reduce costs. The benefit will be the most economies of scale, with the best and largest data sets, the largest customer base, and the largest distribution chain.
Big companies will grow bigger and bigger. But big companies must have strong leadership and execution, and there must be agility that big companies don't usually have. Currently leading the AI ​​field are still the major technology companies - Google, Facebook, Apple, and Amazon, which have a variety of AI products and services, with billions of users worldwide. Some companies in the retail, health and media industries are deeply impressed by the AI ​​products of these big technology companies.
â— AI competitions are also being carried out between countries. China has claimed to be the global leader of AI by 2030.
China believes that it has a structural advantage. Many European countries also claim to have increased their investment in AI, but the risk is that they only fund AI talent, and these talents will eventually become employees of the global AI company, promoting the development of AI in other countries. Will strict data privacy regulation hinder AI innovation in Europe? AI's wealth is likely to flow to countries and companies that control and leverage AI's leading technologies and data, such as the US and China.
Companies and countries that do not have AI-leading technology and data are likely to be threatened because automation will gradually replace those of low-tech, low-income jobs.
Overall, companies and countries with the best AI technology, tools, data, technology talent, the most customers and the strongest financial strength will benefit from the AI ​​Gold Rush. Companies and countries with the most economies of scale can get the biggest chunk of AI. In a way, the more things change, the more they stay the same (in other words, the strong one). But a few brave start-ups still have the opportunity to find big bullion. Unfortunately, most startups will become cannon fodder, and many individuals and societies may not feel the benefits of AI gold mining, they may be eliminated by AI.
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