SAN FRANCISCO — Digital payments provider Square is the most recent, vivid example of this trend: What private investors judge a hot tech company is worth can be miles apart from what public shareholders think.

On Wednesday, Square priced its IPO at $9 a share, less than what it had earlier indicated, valuing the company at $2.9 billion. That was just half of its most recent private valuation of $6 billion.

Shares surged as much as 64% on Thursday in Square’s debut, rekindling hope for private tech companies eyeing the public markets. Still, the IPO price of $9 a share was well below the expected range of $11 to $13.

It’s got company: Fidelity reportedly reduced the value of its investment in the fast-growing messaging service Snapchat by 25%. Dropbox’s $10 billion valuation seems hard to fathom when competitor Box’s public stock has sunk 43% since its IPO debut.

Ben Ling, who specializes in early-stage investments at Khosla Ventures, says this gap has a lot to do with demand from private investors, and the guesswork involved in valuing a company that may stay private for the better part of a decade.

“It’s more art than science,” he told USA TODAY in a podcast interview.

Ling, who previously held senior operating roles at Google, YouTube and Facebook, also talked about how this tech boom compares to past cycles; his investing style; his investment hits and misses (including his regret over turning down Brian Chesky when the Airbnb CEO invited him to invest early on), and the private companies he’s watching.

Khosla Ventures and Ling as an individual are investors in Square.

Here are excerpts of the interview, edited for brevity. The audio recording of the edited interview is below.

What’s going on with start-up valuations? 

Private valuations for the last couple of years have often followed the trend of a venture investor asking an entrepreneur: at what price will you take my money even though you don’t need my money today. You see a lot of high valuations based off of that dynamic. And so the investment is really predicated off the future growth of the company and realizing these gains in terms of product, or in terms of revenue and  engagement. It’s a venture investment, or a growth investment, and so it takes many many years to realize. There has been a mismatch recently between private valuations and public valuations but you’re starting to see them come closer to each other.

We hear that at the later stage, there’s a lot of investors piling in. Is that distorting the value of things?

There’s a lot of money chasing very few companies. Historically in the last couple of years there have not been that many asset classes performing well. Technology appeared to be a safe haven or a place or a good opportunity to invest.

In the latest round of Square investment, there was a thing called a ratchet. Could you explain what that is, is that a product of this new era, where these private companies stay private longer and investors want some safety net?

Ratchets aren’t a new thing and they’ve existed in a variety of investor term sheets for a long period of time. In the case of Square, what I will say is company fundamentals are really strong, company is growing nicely year over year. The company has a really strong management team with Jack (Dorsey) at the head and a variety of very strong senior members; we’re quite bullish on the company.

It seems to be one of chief concerns of investors, the dual role of Jack Dorsey as CEO of Twitter and Square. Can Jack really run two publicly traded companies at the same time?

If anyone can do it, Jack can. Jack is extremely talented, he’s extremely hard working. He’s developed a really, really deep bench at these companies of very talented operators who helped build the company with him. As we all know, it’s not a single person that builds the company, it’s a combination of the senior management team, the broader teams, and the individual contributors that make everything work. The bench strength you’re looking at in these companies is really important in terms of evaluating how these companies can operate as public companies.

Do you see any parallels between the last big booms and busts?

In the 2001 era, a lot of it was companies going public with really no real revenue. It was my company going public, your company going public, Jessica’s company going public, we all just traded revenue with each other.

2008 was not a Silicon Valley issue, it was a global issue, which hit Silicon Valley and everywhere pretty hard. (Silicon Valley) recovered pretty quickly from that. There were big companies that were very successful — Apple, Google, Facebook, to name a few. And there were a variety of other companies being built shortly thereafter — Pinterest, Uber, Airbnb, Dropbox.

If you look at today, there is a lot of money chasing technology, but the difference between today and 1999/2001, there are lot of companies generating real revenue based off real products. It’s hard to tell whether valuations are correct. You basically only need one investor to be willing to write a relatively large check to set a valuation in the private market.

What’s your personal investing philosophy?

First, a really good entrepreneur, we like to say, ‘a killer,’ someone who is emotionally and intellectually very intelligent, unrelenting, is going to run through walls to make something happen. This person usually has a vision of the future that is different from what everyone else says. They have a clear, articulate way of selling a vision. Second, it’s a large market; sometimes the markets don’t exist today, but it needs to be a large market in the future.

What about artificial intelligence? Is it becoming a big part of start-ups?

It’s definitely the future. The way that we think about AI, in for example the medical context, is that we think that the function of humans will largely be replaced in medicine. If you think about  the training of a  doctor, and many of my best friends are doctors, they go through years and years of schooling to learn certain patterns and learn certain rules, and observe certain behaviors from patients, and they also gather certain data from patients, and from that they make a diagnosis based upon the best engine they have in their head. There will be a time in the future, maybe in the next 5-10 years where this is done via machine, and the human can easily validate.

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