The most important technological event of December 1968 may not have been the Earthrise photo, but the first demo of hypertext, the essence of plug-and-play AI

Fifteen days before the 1968 Earthrise photo by William Anders, the Mother of all Demos started the tech revolution that led to the AI movement we have now. Our Earth appears so small and far away in Anders’s photo, but at that very moment, momentous things were happening at Stanford Labs, where the first mouse and hypertext were being demonstrated in the weeks before Anders's iconographic photo of planet Earth. 

While a photo of Earth from the moon was clearly a stunning moment of acknowledgment about Earth’s place in the universe, the impact of the mouse and hypertext may not have been so obvious then. Point-and-click technology and text and image tagging sit at the very heart of AI. But their arrival on the tech scene was not nearly as celebrated as man’s arrival on the moon, perhaps because you cannot see AI from space. In fact, you really can’t “see” AI on Earth, when it is all around us. 

The idea of AI is driving a different sense of collective worth today, the same way Anders’s Earthrise photo did more than 50 years ago.  

AI creates three new Fortune companies a year

AI is creating $1BN of new GDP every single day. That’s like creating three new Fortune 100 companies from scratch to be on the list in a year. The volume of data needed to create these AI models is truly staggering (one hundred times more than historical applications).

Globally, AI consumes what would be nearly one third of US energy

Up to 5% of the whole earth’s energy supply is being consumed by the experimentation and deployment of these data-heavy AI applications. That is just under one third of the total energy consumed in the US, the world’s largest economy.

Right now, critical workloads are having AI operationalized in them

Given the economic and energy impact of AI, creating deep and meaningful value is essential for this groundbreaking technology. At EDB, we recently did a study on the aspirations of executive leaders in some of the largest enterprises in the US, to get a better understanding of their views on AI as it relates to the driving data force of their business: transactional, analytic, big data, data warehouse applications. 

Upwards of 30% of HTAP, OLTP, Big Data and other workloads are in the process of operationalizing these AI investments. Imagine tens of thousands of databases working with AI in near real-time. AI is going to be the common component of these workloads very quickly, whether it's analytical, transactional, or data lakes. The AI generation is a world in which Postgres should thrive. Legacy solutions can’t compete with the flexibility and scalability of open source Postgres, making it the most elegant and important platform for AI workloads.

Universal optimism abounds for nearly all classes of leaders, especially those with a blueprint for it

Generally, executives expect a substantial and near-immediate lift in performance from their operationalization of AI, (sometimes up to 25% lifts in a range of areas). The optimism is palpable in major industries including BFSI, healthcare, IoT/manufacturing, and transportation. If you add a blueprint for how to operationalize AI into each of these workloads the uplift is 50% more.

Ask a C Suite leader how they plan to get value from AI. Their aspirations might surprise you (in a good way)

The DNA of AI in these workloads is creating a whole new value moment. The C suite leaders we interviewed told EDB that the moment for value is going to be created in five near-equal dimensions.  These leaders get the power of AI being infused to deliver new insights and value, either to respond or to create new opportunities. The simple idea of building better margins comes at the bottom of the five.  

1. Agility in market                          
2. Competitive advantage
3. Enhance skill sets
4. Open the capacity to innovate
5. Create better margins

Observability across the whole data estate is like seeing the Earth from the other side of the moon

A universal truth: to get ahead of the crowd you usually have to do things different from the norm. Leaders operationalizing their AI in critical workloads are 45% more focused on delivering observability across all their data estates than the rest of us. They get the power of seeing it all (like the Anders Earthrise photo) to change their perspective. 

Postgres is the world's most loved and used database and is uniquely positioned to thrive in the new AI landscape. Out of organizations that consider Postgres to support their next transactional, analytical or AI workloads, 84% of them see the power of observability across that whole data estate; more than twice the industry average.

It’s crazy to think that Anders’s Earthrise portrait of the world was seen on TV and in print and talked about on the radio. There was no internet; ARPAnet (the first internet) was not even publicly tested until 1969. How far we’ve come in the past 50 years. In fact, it is estimated that 90% of the world's data was generated in the last two years alone.

We are far past the “mother of all demos” moment with AI in 2024. The levels of organizational commits moving AI from testing and demos to full production is increasing every day.  The possibilities are also frankly larger and more nuanced than before. It’s about innovation, agility, competitive advantage, re-skilling people and then margins. That is a lot of positive potential.

Now imagine being able to see your data worlds (maybe 10,000 databases) through a single pane of glass. AI unlocks the potential to create new value by being able to see all your data simultaneously. Maybe it’s not the earthrise moment of Bill Anders, but it has the potential to be an equally revolutionary moment.

I think the famous Earthrise photo is still as beautiful and impressive as when it was taken in 1968, but in case you want a fresh perspective, NASA can show you a constantly updated picture of the earth every day on its website.