What was your first introduction to AI?
For many it was a robot in a movie.
In 1968 the movie “2001: Space Odyssey” by Stanley Kubrick was released. A Robot called “HAL” was in control of a spaceship that quickly became dysfunctional and revealed a potential dystopian future for robots and AI.
In 1977 I saw Star Wars for the first time and was taken to a new world inhabited by physical robots and other alien creatures.
Our ideas about AI and how it would reveal itself to the world was often an imagined physical computer, robot or humanoid that did our bidding (if it was well behaved).
An old television series called the Jetsons (released in 1962) depicted what a world would look like in 2062.
It showed a futuristic world of video calls and conferencing, robotics and automation, smart homes, wearable technology, even drones and aerial transportation.
The Star Wars robot “R2-D2” was a “droid” that looked like a small, swiveling, talking garbage can. But now we want a more human looking form.
What we got instead looked a lot like a boring prompt box.
ChatGPT gave us simple way to ask questions (a bit like a Google search). Except now you type in a prompt and receive a piece of writing, an image or even a video.
AI today is a tad boring and underwhelming. You thought you were going on a date with a supermodel and you ended up with a nerd in a suit that answered questions.
But when you fire it up the magic of its superpowers is revealed. It performs tasks that might have taken you days, weeks or even months to complete.
The black magic box of AI
We live in a world of magic. But we often take it for granted.
We fly in planes at 40,000 feet sipping champagne at a cozy 75 degrees where the outside temperature averages minus 70. We can get to the other side of the world in less than 24 hours. The Mongols took months just to travel over a few countries and maybe invade Europe.
If you have a question about anything you can pull out your smartphone and the answer is provided in seconds. Pub fights avoided.
We want to drive to an unknown destination in a foreign country and our GPS powered smartphone shows us the way. My old paper map resource was often turned upside down and thrown out the window in frustration when I ended up in the ghetto instead of the hotel.
We want to transfer money to the other side of the planet and it is sent with a few clicks. A visit to a physical bank is now a distant memory.
We order something on Amazon and it arrives that afternoon. Who wants to visit a physical shop and find that what you want is out of stock while the shopping assistant chats up their cute colleague and quietly ignores you.
Now we have a boss that wants an article or a business plan written and ChatGPT does it with a few quick prompts and the answer arrives in minutes.
Welcome to the age of the “AI Oracle”. The machines do our bidding.
How does it work?
Behind the AI curtain (you can refer to it as Artificial Intelligence when it is wearing formal dinner attire) are three pillars that power the machines behind the scenes.
Pillar 1: Software
The first of our gallant digital era heroes, is the brainchild of the programming languages. It is the language of geeks (who might as well be speaking in tongues).
Software.
It consumes 1.7 trillion parameters with the intelligence and brute force of the Large Language Models (LLMs).
The more parameters a model has, the more complex and expressive it can be, and the more data it can handle. The more data it has the smarter it gets.
This is where the raw logic of AI is forged, from algorithms that learn like a toddler on a sugar rush to models that predict the future with the confidence of a seasoned fortune teller.
The question that begs our attention is…
Who was the first to unleash the horseman of the AI apocalypse on the world?
It wasn’t perfect but it beat Google to the starting line. The search giant was afraid of releasing something it already had in its tool box but had too much reputation to lose by releasing it into the world.
But maybe by not innovating and releasing AI into the wild it has already lost.
The major player
ChatGPT was launched by OpenAI in November 2022 and reached 100 million users in less than 8 weeks.
It created a simple user interface that made AI available to the world. A hidden world of algorithms and complexity was reduced to a simple prompt box.
OpenAI made $200 million in 2022. In 2023 it reached $2 billion in revenue. A growth of 1000% in just one year. Its current captital value is $86 billion.
Pillar 2: Hardware
Next we have hardware, the physical engine of AI’s needs. These aren’t just any run-of-the-mill circuits and silicon; no, these are the supercomputers, the GPUs (Graphics Processing Units) that crunch numbers faster than a bored accountant during tax season, and the neural network chips that dream of electric sheep and never sleep.
Without these Herculean beasts, our software would be like a racing driver without a car—dressed for the occasion but going absolutely nowhere.
Some hardware questions
Who is the major player here and who is after their crown?
The designer of high end graphics processing units (GPUs) were first designed for gaming computers.
The major player
This is without a doubt Nvidia. Its rising dominance is apparent with a look at its sales growth since 2020.
More Nividia numbers:
- The revenue of Nvidia is up 262% on the year before at just over $60 billion per annum
- It is now the 3rd most valuable stock in the world with a capital value of $2.38 trillion just behind Apple by $238 billion and Microsoft at a market value of just over $3 trillion.
Pillar 3: Data
And lastly, “Data”, the lifeblood of AI.
The new oil of the AI world.
This is the fodder on which our digital behemoth feeds, grows, and learns. Data is the experience of AI, each byte a lesson, each terabyte a tome of knowledge.
It’s the world through the eyes of our digital companion, and without it, AI would be as lost as a tourist without Google Maps.
The big question here?
Who has the data?
And the answer is? Nations and international corporations with access to the data of billions of our planets population.
International Corporations – Techno states
The social media, software giants, ecommerce providers and data center companies are the global players that have more data than many countries and more capital value than 95% of the world’s countries GDP.
In essence these companies are bigger than countries in wealth. This has changed since 2021 with Microsoft now over $3 billion in capital value in 2024.
Who are they?
- Meta – 4 Billion global users and counting
- Amazon – 40% of the ecommerce transactions in the USA
- Apple – App store and iPhone data
- Microsoft – Web hosting and software sales
How many data points do the top techno states collect?
These companies maybe know more about you than your friends or family. And that makes me a little uncomfortable.
- Google collects the most data points about its customers at 39 per person
- Twitter has 24 pieces of information
- Amazon has 23 Data points
- Facebook collects 14
Nations – Political states
Nations have access to huge amounts of data and the surveillance state is alive and well. China has maybe the largest gold mine of data as it has become a surveillance state and is also the second largest population on the planet.
Data can be captured in many ways including financial data, social media data and visual data. One of the visual technologies is CCTV.
Population size allows you to collect more information and data but you need to have the technology in place. And some countries do that better than others.
- China – Population 1.3 billion. China has 200 million CCTV cameras. That means they have 14 CCTV cameras for every 100 individuals.
- USA – Population 400 million. With 50 million CCTV cameras they top the CCTV list at 15 cameras per 100 people.
- UK – The UK has over 7 million CCTV cameras. They come in at a miserly 7.5 cameras per 100 people.
Last words
Software brings the brains, hardware brings the brawn, and data brings the lessons of a billion lives lived, all to be revealed on the open web.
Human data waiting to be harvested.
This data cuts two ways. Firstly, it can help by crunching data for the good.
This means things like better health and medical breakthroughs that will save millions of lives and allow us to live longer.
On the other hand, it can also be a weapon used against us for government surveillance, misinformation and digital device addiction.
We need to be putting in place guard rails.
We all have a choice in how we want to play. Awareness is everything.
Over to you.