In 2017, Andrew Ng (Industry AI leader, Adjunct Stanford Professor, founder of Google Brain and former Chief Scientist at Baidu) said, “Artificial Intelligence is the new electricity. Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years.”
The technological and financial opportunity AI presents should have been clear to investors - according to IDC, worldwide spending on AI-Centric Systems Will Pass $300 Billion by 2026. With its seemingly limitless applicability, many fields are rapidly embracing Machine Learning and AI, from education, to finance, to healthcare, to ecommerce and so much more.
Oft quoted English science-fiction writer, futurist and inventor, Arthur C. Clarke (most recently by Packy Mckomick of Not Boring) wrote that "any sufficiently advanced technology is indistinguishable from magic". One of the best examples of magic tech in recent memory is undoubtedly generative AI - the ability to create images and articles from short text prompts was the stuff of science fiction a few years ago.
With the release of GPT-3 and Dall-E 2 by Open AI and a flood of exciting rival tech, a sudden wave of optimism reminiscent of 2021 is surging through the VC capital markets as investors pour funding into generative AI. Recent news of multi-million dollar raises for companies such as Jasper and Stability AI reflect the dramatic way this technology has captured the imagination and excitement of not only the general public, but also venture capitalists in the otherwise dreary markets of 2022.
General Partner at Unusual Ventures Sandhya Hegde writes that we are now witnessing “the third wave of Applied AI in SaaS: generative software…scaling unique human-like work output across modalities, including text, image, voice, code, music, 3D models."
While access to generative AI via open APIs is exciting and has already spurred many new ventures, companies built on open APIs accessing models trained on publicly available data (image and text especially) will struggle to remain differentiated.
If data is publicly available then anyone can access it, and over time software models tend to become commoditized as new entrants join the market, meaning that generative AI companies pose significant mid-term risks to investors.
So what are savvy investors looking for in an AI investment in 2023?
Data IP and true data network effects.
What does that look like? Differentiated, proprietary data sets and unique access to scalable, real-time data allows a company to build a long-term competitive moat around its technology.
That’s a lot to break down.
Before we do that, let’s quickly explain AI, Machine Learning, and the role of data.