Q&A with Omega Venture Partners: What We Look For in AI Startups

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Q&A with Omega Venture Partners: What We Look For in AI Startups

Q. How do you define Artificial Intelligence?
A: We view Artificial Intelligence and Machine Learning (AI / ML or just AI) as a powerful enabler and source of unfair advantage, which has reached an inflection point.

Our focus is on backing high-growth business software companies that are leveraging AI to deliver superior solutions across large industry verticals and business functions.

The vast majority of advancements and applications of AI that you hear about refer to Machine Learning. In a nutshell, ML is the ability to find patterns in massive amounts of data. What changed over the last 2 years is that ML got supercharged with the advancements made in Deep Learning (DL is a subset of ML).

Deep Learning gives software an enhanced ability to find – and amplify – even the smallest patterns – and opens up a whole new world of game changing applications.

Q: We are seeing an absolute explosion when it comes to artificial intelligence startups. From an investment standpoint, what are you looking for?
We’re growth stage investors at Omega Venture Partners. Broadly we’re seeing two main groups of companies that are leveraging AI.

The first are companies that are AI-first companies or born into AI, so to speak. They have data science teams from day one, machine learning engineers, and they really understand the problem that they’re going to solve using artificial intelligence technologies. Companies such as Cylance and Braze are great examples of this category of companies.

The second type are companies that have amassed a really interesting data set, but may not necessarily be “AI-first.” These companies incorporate machine learning over time to gain an unfair advantage. Criteo and Square are good examples of companies in this category.

One of the ways that we engage with this second type of companies is to leverage our world-class subject matter experts and Industry Partner resources to help them figure out what are the right types of machine learning technologies that are appropriate for the data set that they have, as well as the problem that they’re trying to solve. Omega’s industry partners give our portfolio companies turnkey access to unmatched vertical and industry expertise.

Q: How does a company know when it has an AI opportunity?
The most interesting problems generally relate to complex business processes. One of our companies, called Recommind, is leveraging machine learning technologies to solve long complex processes for the back office, for financial institutions, and for specific functional use-cases such as e-discovery in the legal vertical.

They’ll look at a process that can’t necessarily be solved with traditional rules-based automation, and say, well if we apply machine learning technologies, which are much more flexible, much less rigid, we can actually solve this problem using an end-to-end automation approach. So those tend to be the kind of opportunities that are really interesting for AI where you have a lot of data and it’s a more complex and interesting process than what we’re traditionally seeing using a rules-based automation approach.

Q: When you’re investing in companies that are leveraging artificial intelligence, do you take into consideration the issue of bias?
That’s a problem that we explore with all of our companies that are leveraging machine learning technologies.  When we think about the way the world is moving and when we think about the kinds of decisions that are being made by algorithms, whether someone gets a loan, whether in some cases someone gets admitted to an institution, or gets a particular type of job, those are big decisions. And so, when we have a company that’s exploring machine learning, we always think about the opportunity for bias to creep in to the algorithms that they’re using and ways to mitigate that kind of potential outcome.



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