According to a report from Titanium Media on September 5, although large models have sparked a new round of global AI boom in the past 9 months, many technology giants are racing to generate AI technology. However, in frontier technology fields with long cycles, such as the research and development of new AI drugs, it is difficult for companies to make quick profits in the short term. Coupled with poor performance in the secondary market, investment enthusiasm has gradually cooled down, and major technology companies have reduced pure AI technology research. CB Insights data shows that in the second quarter of this year, the total investment in the global AI field plummeted by 38% from the previous quarter. Qu Jiarun, vice president of Baitu Biotechnology, said that now is no longer the era of "burning" investors' money and then going public for 5 years. Comprehensive capabilities such as resources, technology, data algorithms, and business implementation are becoming important factors for the long-term development of AI companies. . "Now we have actually reached the first inflection point of Gartner's emerging technology development curve, and bottoming out requires the opportunities and capabilities of enterprises."

According to the "Kechuangban Daily" report on May 30, according to data from the American research institute CB Insights, there are currently 13 generative AI companies that have become unicorns (referring to start-up companies with a corporate valuation of more than US$1 billion), and by 2023 So far this year, 5 companies, including Cohere in Canada and Runway in the United States, have become unicorns. The average time spent by these 13 companies from starting a business to becoming a unicorn is 3.6 years, which is halved compared with the overall average time of 7 years. The revenue of these generative AI companies varies greatly, and most of them are not high, but the staff expansion speed is fast.