Jocelyn Goldfein (LinkedIn, Twitter)  is a true IT Visionary. She worked at VMware and Facebook when they were both in their early days, and now serves as Managing Director at Zetta Venture Partners. Jocelyn was on the ground-floor with many technological movers and shakers during formative years. She worked closely with IT heavy-hitters – including Mark Zuckerberg and Diane Greene – and learned many lessons during her time with them. 

In part one of their interview, Jocelyn and host Ian Faison discuss a wide-range of topics: from the rise of the computer sciences industry, to investing in start-ups, to the role artificial intelligence will play in businesses moving forward – and, finally – how the rise of cloud technology could be a precursor to the rise of A.I. Plus, Jocelyn dives into her years of experience at Facebook –years spent working closely with Mark Zuckerberg – as well as what it was like riding the VMware rocketship right as it caught fire. 

Here are some of the key takeaways from part one of this wide-ranging conversation:

Why Zetta is investing in start-ups that are harnessing the power of big data, A.I. and machine learning:

At Zetta, Jocelyn and her partners are investing in companies that are attempting to change the world through the use of artificial intelligence. But their investments come with a caveat: “We only invest in companies solving business problems,” Jocelyn says. 

A.I. is going to become more essential in several key areas of business. Start-ups that learn to use A.I. effectively to collect and use data will be the ones that last and create change.

Lessons from the early days of Facebook and VM Ware:

Jocelyn joined Facebook in 2010, and the amount of data being brought in during those massive growth years was unprecedented. “Facebook is where I cut my teeth with modern techniques in machine learning and A.I,” Jocelyn says.

The arrival of cloud infrastructure made it fast enough, cheap enough, and practical enough to amass enough data to train the machine learning models. Primarily, Facebook was using A.I. to optimize ads, ensure optimal search functions, and to organize newsfeeds. “The nature of machine learning is that it compounds,” she explains. “With every click, with every like, with every comment, you’re sending more training data back to the model to make it more and more accurate.”

Prior to joining Facebook, Jocelyn worked at VMware. She joined in 2003, right when the company was taking off. It was a lesson in how having great success doesn’t mean you work less. On the contrary – it means you work more, just with more people and a bigger budget. 

How CIOs and CTOs should think about A.I. and machine learning: 

When you are a CIO or a CTO, you have a lot of responsibility on your shoulders, and a lot of your job is achieving business goals and making business-based decisions. As such, their focus needs to be on the things that truly matter to their businesses. It’s also important for executives – and those in the general public – to remember that A.I. is an attempt to optimize something. Therefore, it usually ties very directly to business goals and directives.

 “A lot of people think A.I. is synonymous with automation and job loss,” Jocelyn says. “But what I have seen from our customers – and people who are adopting it – is that it is hardly ever because they’re saying, ‘I want to fire these people,’ or, ‘These people are too expensive for me.’ That is not a motivation for people. Usually, it’s because they have a critical problem to solve they can’t otherwise solve.”

For that reason, CIOs and CTOs would be smart to pay attention to the A.I. space and find ways to implement the technology in a way that is helpful – and unobtrusive – so it doesn’t scare away the people who work for them.

The current state of cloud technology and how it could be predictive of the future of A.I.:  

“It’s trite at this point to say, ‘cloud is the future.’ I think cloud is the present,” Jocelyn says. Everyone today is using the cloud, because it offers freedom to CIOs and CTOs. They no longer have to worry about building the same kind of infrastructure in-house, which frees them up to focus on other areas of business. A.I. could work in a similar way, in that it can free up other resources and decentralize pieces enough so that human resources can be put to work on more valuable problems. 

To listen to the entire interview, click here. And to find part two, click here.