Zhou Zhifeng, the co-founder of Chinese venture capital firm Qiming Venture Partners, said that AI is a promising field for venture capital firms in the next three years. He made the comments at the 13th ChinaVenture Investment Conference LP/GP Summit in Beijing on October 22. The following are his views on the AI industry.
Since 2013, Qiming has invested in around 16 to 17 AI-enabled companies, including Megvii software company, UBTECH robots, AI-based risk management firm Tongdun Technology and AI-powered speech recognition provider Unisound. Qiming will continue to invest in AI companies and adjust its strategy. "We are confident about AI from the perspective of venture capital," Zhou said.
Zhou said that "AI is one of the most promising fields for venture capitals in the following three years." There are more than 100 AI-related papers every day on one academic paper archived website, which other segmentation fields-related research papers cannot compare with. AI does not lag behind in the research field.
With years of development, several leading AI companies have shown their great potential for commercialization. Only some leading AI companies have achieved it because AI companies have high requirements for technology which is the most important part of a company’s core competitive advantage. As long as being commercialized, the AI company could receive promising revenue.
There are three stages in the development of AI companies. The first stage is the Go-to-Product stage when one product is equipped with the technology; the second is the Go-to-Market phase which is to upgrade the product and find its customers, which can be built as a business model; the third is the Go-to-Scale that is the scale of revenue. However, 80% of AI companies are struggling in the second phase which is the most important period in the development of AI companies.
Qiming has upgraded its investment strategy from AI 1.0 to AI 2.0. As for future investment plans in AI companies, Qiming has found three main directions.
The first one is to invest in the leading AI technology which is far from commercialization. The second is to invest in more mature AI tech such as speech recognition which has great potential for commercialization. The last one is to invest in the most fundamental technology that can help AI penetrate people’s life.