latest:
latest:
Embedded Files
5, learning in the age of abundance
5, learning in the age of abundance
8 February 2026
“It strikes me as we’re talking that it’s only going to get increasingly easier for the ambitious to act as superpowered autodidacts, right? We’ve already seen this. Certainly YouTube has a nice track record now. You can either entertain yourself to death and avoid doing things that help with self-growth and development or you can supercharge it”. - Tim Ferriss
Tim’s recent interview with Fei-Fei Li, a computer scientist often referred to as the “Godmother of AI”, was both endearing (immigrant stories of perseverance are timeless) and a reminder that the way we learn is profoundly changing (1).
The convergence of open education and internet technologies unlocked new possibilities for the self-taught. Once a day in the burrows of the local university library, self-teaching has evolved into on-demand courses and collaborative learning platforms. As someone who has always loved learning new things, I can’t help but get excited by the new tools and resources available to us. That said, I still enjoy the occasional jaunt through the library aisles. There’s something mildly thrilling about searching the catalogue, scanning the shelf numbers and plucking a book from its perch. The prize at the end of the hunt.
The democratisation of education is something to be celebrated, and students of all ages have benefitted enormously from widespread access to free learning resources. In 2006 Sal Khan started posting tutoring videos on YouTube for his cousins and family members. Today, Khan Academy is a registered nonprofit with over 104 million yearly active learners (2). Once supplemental to tertiary study, informal education is an increasingly viable pathway for those seeking both personal and professional growth.
As a result, education institutions are being challenged to provide more flexible options for students. The introduction of microcredentials and remote courses is a start, but the barrier of credentialism still persists, particularly in regulated professions where the parchment continues to hold power. It’s worth noting that traditional schooling and university still have an important place in society. For one, the social skills and networks one develops are irreplaceable. And education standards need to be upheld through certified programs, providers and teachers. But the way education is delivered, evaluated and recognised is undoubtedly changing.
With the emergence of large language models the pace of change is only accelerating (3). Personalised learning has arrived, and budding students are now supported by virtual tutors capable of explaining any concept in every way possible. In only a few years, we’ve witnessed the transformation from AI chatbots being an amusing novelty to a technology that’s upending almost every industry. And it’s enabling people to do extraordinary things, such as building a nuclear fusor in your kitchen (4).
The process of learning is a cycle of breakthroughs and bottlenecks. Despite the wealth of resources within reach, sometimes imposing constraints can spur progress in unexpected ways. A painter with only a few colours at their disposal learns to visualise a scene differently. Li herself turned to crowdsourcing (an unconventional approach at the time) to build the enormous dataset which eventually became ImageNet. Would da Vinci have been more prolific today with the overwhelming volume of information at his fingertips? It’s entirely possible he becomes perpetually sidetracked by an endless stream of curiosities demanding his attention.
Herein lies the challenge we all face today. In a swirling sea of information, it’s easy to drown in your own dopamine. A little motivation keeps us afloat, but it doesn’t stop us from drifting off course. In the age of abundance, sorting fact from fiction and signal from noise is half the battle. Personally, I’ve found it helpful to adopt some principles and frameworks to guide my learning. Scott H. Young’s ‘Ultralearning’ is a great reference for those looking for structured approaches (5). Ultimately, we all learn in different ways, and it falls upon each of us to discover how we learn best.
The interview concludes with Li’s message that finding your north star is key to one’s journey of education. We are in the midst of a learning revolution, and the possibilities are limited only by our imagination. Li invites us to ask audacious questions, know who we are and what we want to chase after. There’s never been a better time to learn something new. And if knowledge is power, the superheroes of tomorrow are likely to be self-taught.
Footnotes:
Large Language Models, or LLMs, are language models trained on vast datasets of text, and are designed to understand and generate human language. They now serve as the backbone of conversational programs known as ‘chatbots’.
Report abuse