Is intelligence a resource you "download", or do you need to be intelligent in order to learn? For a long time we believed the latter. But today knowledge behaves like free software: it gets copied, translated, adapted and improved as a community. I call that way of learning Opensource Knowledge — and it completely changes who can learn what.
From "being intelligent" to having access
We call almost everything smart: artificial intelligence, smartphones, smart homes, intelligence services. We use the word because they all share the same idea: processing information to carry out actions or solve problems. And if intelligence largely depends on obtaining and processing information, then the interesting question is no longer who is intelligent, but who has access.
That is the shift of an era. Never before could the same information be represented, transformed and distributed in so many formats and with so little friction. That flexibility is exactly what turns knowledge into something open source: available, adaptable and improvable by anyone.
Access to information stopped being the bottleneck. Today learning is, above all, a matter of method and motivation.
Knowledge, in four formats
Before the pillars, it helps to see how many ways a single idea can travel today. Each format opens a different entry point into learning:
| Format | What it is | Examples |
|---|---|---|
| Visual | Graphic representations | Text, images, infographics, animations |
| Audiovisual | Sound-based representations | Voice, podcast, video |
| Interactive | Human-machine and human-human communication | Social interfaces, IoT, digital tools |
| Immersive | Simulations that respond to the body | Extended Reality (XR), 3D environments |
The same idea can reach you as a paragraph, a video, a conversation with an AI or a simulation you walk through with your body. Choosing the right format for each thing you want to learn is, in itself, a skill.
The four pillars of Opensource Knowledge
Recognizing that information is now abundant and flexible is the first step. The second is knowing how to exploit the traits that make it "open". I group them into four pillars.
1. Accessibility
Many technologies were born for people with specific needs and ended up being universal. Vibrate mode on your phone was created for people who are hard of hearing, and today we all use it to silence the device. Voice dictation was designed with visual impairment in mind, and today it captions half the internet.
That very technology is now your learning tool. Speech-to-Text, Text-to-Speech and Computer Vision let you capture, convert and analyze information in the format that works best for you: listening to a long text while you walk, transcribing a lecture, or extracting the text from an image to search for it later.
In practice
What was designed as accessibility is, really, format flexibility for everyone. Learn to move the same information between text, voice and image and you'll have doubled your entry points.
2. Distribution
Globalization connects, in seconds, information that lives at opposite ends of the planet. But that connection runs into two barriers, and for each one there's technology that tears it down:
- The language gap. Knowledge is spread across dozens of languages and English doesn't always reach far enough. Machine translation and simultaneous interpretation —now in real time and with voice— let you research sources that used to be out of your reach.
- The spatial-perception gap. Some things can't be understood by reading: they're understood by being there. Virtual, Augmented and Mixed Reality and 360 video let you explore objects and places with three-dimensional perception without leaving home.
3. Updating
Technology changes so fast that specific tools age within months. That's why what's really worth developing isn't tools, but skills that don't expire: judgment, creativity, logic, self-learning and teamwork.
To keep from getting lost in the change, there's a group of technologies that exist precisely to observe it: data visualization, Big Data and Artificial Intelligence make visible the connections you can't deduce at a glance, or that would take you weeks to find by hand.
4. Collaboration
The most powerful way to extract knowledge is to build collective intelligence: groups focused on different areas who share what they know and test it against each other. Social networks, blogs, messaging and live communication are an ideal environment to remove biases —if used with your head— broaden your perspective and learn on your own.
The key isn't to consume more, but to cross-check more: find the original source, compare versions and tell the real from the fake as a community.
So then, "what about intelligent people"?
Every new technology awakens the same suspicion: that we're building an environment that dulls human intelligence. It usually shows up as an ironic question: "and what about intelligent people?".
It's a poorly framed question. Access to information in order to become capable was never the real problem; in a hyperconnected world, almost everything comes down to motivation. Intelligence is a valuable tool, but it isn't only about having access to information: it's about knowing how to use it well and making the most of our own human capacity.
Modern tools —and today, above all, language models like ChatGPT, Claude or Perplexity— don't diminish your intelligence: they let you develop it in new ways. But none of them thinks for you. Opensource Knowledge hands you the access; the judgment to turn that access into real learning still is, and always will be, yours.
And the how?
This is the why. If you want the concrete method —how to collect, filter and analyze information to research on your own— I cover it in Learning and effective documentation techniques.
An early version of these ideas was published in 2023 under the name "Open Source Intelligence". This is a 2026 rewrite, now under the concept I use today: Opensource Knowledge.
