The third one.
As we conclude Q1, numerous companies have shared their stances and predictions on AI, anticipating developments before mid-year. Below, I'll link to some of the most informative content, but first, I want to highlight one source in particular. This past week, influential venture capital firm Sequoia Capital hosted an AI Summit and shared the videos on YouTube. The opening remarks video had some surprising data in it and the implications are massive. Here is the video link - I highly recommend that people watch the entirety of the video for themselves. Please note, I'll be summarizing the statements of Sequoia employees below. They are the originators of the content, and I'm drawing some conclusions based on their insights.
Surprising Data
Technology in each decade can be summarized by the dominant spaces and themes.
For example, let's focus on mobile technology. In the 2010’s we saw multi-billion dollar companies arise whose main medium was through a phone. This was made possible by the introduction of smartphones, notably the iPhone, and the creation of the app store. Typically, with each of these phases in the industry, you see the greatest value creation (money) going to the things we interact with. You’ll notice most of the apps above are names we’re well acquainted with, Facebook, Amazon, Adobe. You don’t necessarily hear about the funding into the server farms that Facebook runs off of or the real estate developments companies that Amazon works with to locate new build sites and construct their warehouses. This is the infrastructure that makes those companies tick. However, if you look at where funding has gone from investment companies - it’s at the this infrastructural level and not at the app level…yet.
Currently, the majority of investments are directed towards infrastructure, significantly outweighing application-level funding—$16.9B versus $4.9B. To me personally, this is incredibly exciting. I believe this signifies two major implications:
Number 1: We’re just getting started.
Before the real world applications of AI can be built, the infrastructure must exist. Going back to the iPhone example, there was understandably a delay in when we saw value created at the app level. The apps needed the iPhone to exist (2007) and the App Store to exist (2008) before they could live in our pockets and travel with us everywhere we go. Imagine 2024 as akin to the 2008-2009 period; the logos that will soon shape our daily lives remain unseen.
Number 2: The winners are far from being announced.
The AI race, with players like OpenAI, Anthropic, and Google, doesn't guarantee these names will become or remain the household terms synonymous with AI. The iconic names of this era are likely still emerging. The value goldrush is just beginning. Those who quickly discern how AI applies to their specific use cases and scale it efficiently stand to reap substantial benefits.
Summary
History is in the process of being written. Just as the first banks, social media platforms, and airlines that successfully transitioned to mobile gained a significant advantage over their competitors, the early adopters of AI will similarly outpace theirs. And the entrepreneurs and tinkerers who are developing the tools to allow companies to do this will make massive impact. This is why I’d encourage every company out there to investigate what AI means for them. If you are lacking insight into AI's implications, it's wise to collaborate with experts who can unveil its possibilities, challenging them with your most significant problems and committing resources to test and prototype solutions. If you are able to make the move before your competition, the possibilities of positive outcomes are truly without limit.
Other interesting resources:
Stripe’s annual letter (lots of information about volume in AI startup ecosystem)
A video went viral on X where a company has developed incredibly realistic ad videos
