Believe in smart people
Editor’s note: This article comes from the WeChat public account “outside the stack” ( WeChat ID: zhanwai_) by Jim Breyer.
Someone often asks me if I can post some insights into artificial intelligence (AI) investments.
The fact is that the field is too complicated and the dogmatic theory does not apply. In this sense, my answer is no.
However, after more than a decade of thinking about AI investment, I came to some conclusions. Some of them are business insights that I learned after working with a particular company, and others are my natural insights after seeing the industry mature. I hope this article will help readers better understand my views on AI investments and how I have gained these insights from industry experience.
Insight 1: A successful AI opportunity is a combination of technology and business acumen
I came to the board of Facebook when I came to this conclusion. At the time, Zuckerberg and his team were thinking about using AI technology to equip the team with top AI personnel. They are far ahead in this regard. Today, most technology companies understand that if they want a good future, they must start using it, or at least start exploring AI technology.
Facebook recognized this as early as 2010, and even was willing to invest a lot of time and money in the AI strategy. Zuckerberg and his team did not focus on research and bold planning, but pursued practical goals. Facebook believes that AI projects that are value for money must be closely related to business goals. But this does not prevent the team from making long-term investments.
In contrast, in many cases, business-oriented thinking makes them more willing to make long-term investments. If an AI project is commercially meaningful and meets all appeals, Facebook is happy to implement it. Other companies continue to lose their way in this regard, they are mainly concerned with technology, thinking that the use case scenario will eventually be realized.
Facebook cares a lot about technology, but it also pays attention to feasibility. It’s no wonder that they have such an enviable performance in the AI field and continue to be at the forefront.
Insight 2: The best team form is an interdisciplinary team
I found this especially true in the AI field, thanks to Daniel Nadler for pointing me in the right direction.
When Daniel Nadler founded the financial data analysis company Kensho, he was still reading at Harvard University.Shi. In addition to having a clever technical mind, Nadler is a poet and filmmaker. The rich background experience made him understand that if he wanted to overcome a multi-faceted problem, his team must also come from different academic backgrounds.
Illustration: Kensho Headquarters.
Today, Kensho has created a new generation of AI analysis platforms for professional investors using massively parallel statistical calculations, user-friendly visual interfaces, breakthrough unstructured data engineering and predictive analytics. Building such a complex platform requires outstanding team members from different disciplines. There are economists, statisticians and developers in Daniel’s Kensho team. He has built a strong business by hiring top user experience designers to expand their products and build a first-class sales culture.
In 2018, Kensho acquired financial analyst firm S&P Global for $550 million, making it the most valuable privatized artificial intelligence company in history. Breyer Capital and other early investors had a unique vision. When Daniel asked me to support Edo, his next forecasting and analysis company, I readily agreed.
Insight 3: Believe in smart people
I first saw Thomas Reardon in the 1990s, but he was admired for his wisdom, energy and courage. Later, when I was working at Microsoft and Internet streaming service provider Real Networks, I learned more about him. I found that Thomas is also very good.
He cares a lot about his work and his impact on the world. Every time we meet, Thomas teaches me something new. I knew then that I would support him if there was an opportunity. My chances are coming in 2016, thanks to the founder of Real Networks, Rob Glaser, who reconnected with Thomas. Thomas has just graduated from Columbia University and is eager to establish a neuroscience company. His vision of the company (Thomas later founded CTRL-labs, a brain-computer interface development) is clear and convincing.
I know that what he is trying to do is very difficult, but he also knows that he is one of the few people in the world who has the ability and tenacity to do it. I am very happy to be an A-round investor, to ensure that the company has a bright future,