I’ve been obsessed with AI and its impact on our world for decades. This obsession led to several investments in the field, as I described four years ago in my blog posts on Applied AI: Beyond the Algorithm and The AI Paradox. So like many others, I have watched the evolution of generative AI and ChatGPT with keen interest.
At our Flybridge investment team meeting earlier this week, my colleagues asked how the explosion in the AI market compares to previous tech trends I have seen emerge over the last nearly 25+ years. Spoiler alert: I’ve been a VC for a looong time – see my reflections on 25+ years here).
While the move to the cloud (looking at you, MongoDB), mobility, and the rise of consumer social apps were all significant developments over the previous 15-20 years, they pale in comparison to the sudden change in the market over the last 12 months brought about, primarily by OpenAI and the launch of first GPT-3, more recently ChatGPT, and the rapid advances from other players such as Google.
In particular, I am struck by the speed of adoption and the incredible ubiquity and breadth of impact that the Large Language Models ( LLMs) and Generative AI already have. Today Groupthink is our always-on collaborative AI research assistant (picture a stateful marriage between ChatGPT, Google Search, and your favorite collaborative apps, and that’s Groupthink); we use the AI-powered no-code tool Blaze to build internal apps, Aiera provides me real-time transcriptions and AI-generated summaries of Wall Street events, Brighthire streamlines our hiring insights and processes with AI-powered interview summaries and transcripts, Proscia’s AI pathology platform will analyze my skin biopsy from the dermatologist, and my college-age son can use Teal to customize cover letters based on his resume and a potential job’s needs. And that is just an illustrative sample from our small Flybridge portfolio. Everything Everywhere All at Once, indeed.
(It should be noted that Everything Everywhere All at Once was an incredible movie and my clear Best Picture Winner winner from 2022.)
The closest analogy is the excitement I felt when I first opened the Mosaic browser to explore the worldwide web in early 1994. At the time, there was a rush to define companies as “web or dot com” companies, but that quickly became a meaningless distinction as every company leveraged the global connectivity and accessibility the web uniquely enabled to solve problems and create new markets. The same will hold for today’s new “dot AI” companies, as very quickly, there will be no such thing as an AI company, as the underlying technology will be leveraged across every new and existing application to drive unique value for customers and end-users. As with the first web applications, there will be value in being a first mover, but the real value will come from harnessing the underlying technical enablers in unique and new ways to solve real problems. For B2B founders, this will typically mean starting with a vertical focus, incorporating the AI into existing business processes and workflows, and in a way that is not AI for AI’s sake but rather with a laser focus on driving business value.
There is a lot of hand-wringing about whether this technical step function will change the nature of the economy, and perhaps not for the better. Similar concerns were raised with the rise of the internet in the mid to late 90s, but instead, it unleashed a creative explosion of new ideas, tools, and solutions. As my favorite movie of 2022 shows, there is an incredible opportunity to harness humankind’s unique creativity to build magical experiences and creative solutions to real-world problems. We could not be more excited to back this generation of founders harnessing the power of AI to build everything.
Great read, Chip. Thanks for sharing. Adding to your point, the definition of “intelligence” is an evolving topic, and not well understood.
An “AI company” is an even more ambiguous concept than a dot com company.