The AI Boom: Why We’re Investing in the Future of Intelligence

By Jéssica Leão

I — like many others — have been spellbound by OpenAI’s latest release, ChatGPT, and have spent the past days since its launch ferociously contributing towards the occasional “system is far too busy” message. It is simply addictive. There are numerous examples shared by the community around it acting as a code debugger, haiku writer, and inspirational eulogy deliverer. The potential applications are truly limitless and I’ve already seen many try to tinker and build apps on top of the release — in less than 2 days!

For anyone following AI — whether new to the space or steadily tracking its progress — the past couple of months have been more than exciting. Think: GPT-3’s upgrade with Davinci 003 & ChatGPT showing what creative AI looks like, BLOOM’s massive contribution to open source, PaLM’s breakthrough performance, DALL-E 2 & Stability Diffusion’s jaw-dropping image generation capabilities, and really so much more. We are seeing transformational changes to the field and are starting to glimpse at how industries as we know them will be reoriented by AI.

As a venture investor, I look forward to seeing AI adopted by my portfolio companies, and anxiously await the companies that will be created in an AI-native world. Among the many potential areas where AI can come in handy (such as data analysis and insights across sectors, automation of tasks and processes, personalized CX), perhaps the one I am most excited about is around innovation in product development. We’re seeing a glimpse of that power today with ChatGPT’s capabilities with code. I can see AI being leveraged to create new and optimize existing algorithms… or even to develop new applications using itself:

Admittedly the above example does not alone create a chatbot — but you get the idea. I look forward to seeing what talented entrepreneurs will come up with as adoption of these models continue to proliferate. I am similarly enthusiastic about where AI can add leverage to legacy industries. Some of the top of mind examples for me include:

• Legal: My very first job out of college was at a law firm, and as I remember my painful hours spent combing through Bluebook to make sure my citations were accurate, or as I recall drafting the 342th version of the same boiler plate filing document, I know how easily AI algorithms can be leveraged to automatically analyze, extract, and write key information from briefs, contracts, clauses, and more.
• Healthcare: How often do we consult Dr. Google only to leave feeling hypochondriac? Something better can be built that is just as easy to access by consumers. I think a great company will be created in the AI healthcare space — assist doctors in making diagnoses, predicting patient outcomes, and identifying potential treatments. AI algorithms can and will be able to analyze large amounts of medical data to identify patterns and potential risk factors for diseases, and can even assist in the development of new drugs.
• Finance: This one almost goes without saying but AI’s magic is the ability to process so much data at once. We will see a lot of impact in the financial services world — improve the efficiency and accuracy of financial processes, such as fraud detection and risk assessment. Algorithms can analyze large amounts of data to identify potential fraudulent transactions, and can also help banks and other financial institutions to make more informed decisions about lending and investing.
• Retail: Fresh off Black Friday shopping, I know I could use better CX. AI can dramatically improve the customer experience in the retail industry by analyzing customer data and purchase history to make ever-more-personalized product recommendations. AI can also be used on the backend to improve supply chain management and optimize inventory levels.
• Manufacturing: We all remember what it was like to wait 7+ months for a coffee table to ship because of supply chain issues. AI can help there: optimize production schedules, identify inefficiencies in the production process, and even assist with tasks such as quality control and maintenance.

Lastly — and this will merit its own blog post at a later time — one has to always be thinking of “picks and shovels.” If I believe in the future of an AI world — and I do! — then what are the necessary conditions for this world to flourish? I predict a lot will happen in the AI stack. We’ll see an explosion of companies around compute optimization, MLOps (more ML models being used means more training, observability, and deployment loops), cybersecurity, and much, much more.

I had a hard time coming up with a sign off here, so I went back to ChatGPT to help. Here goes: “Thanks for reading my blog post about AI! I hope you learned something new and exciting, and that you’re now eager to start building your own AI applications. Remember: with AI, the sky’s the limit (or at least the ceiling of your data center). Until next time, keep learning and keep AI-ing!”

The views expressed herein are solely the views of the author(s) and are not necessarily the views of Maverick Capital, Ltd. or any of its affiliates. They are not intended to provide, and should not be relied upon for, investment advice.