Chances are high that at some point – maybe on vacation, maybe with work – you have it. At the airport, as you hand in your luggage, it disappears into the hidden world of baggage handling. After that, in most cases, your luggage magically appears at your destination. Akuningi ukusho ngalokhu, empeleni.
But before You get to the service counter, you have to get your luggage There. Futhi izikhumulo zezindiza zinkulu. If you've ever traveled across a major hub like Dubai, Frankfurt, Heathrow, Istanbul, or Beijing while lugging bags, you know how that feels.
outside of trolley bag.
At some point, someone had the idea to put small wheels on a suitcase and add a handle. That's all; nothing fancy. No machine learning, no distributed systems, no “hardest problem of all” – Good Problems. Just wheels in a bag. However, this simple idea changed the way millions of people travel around the world, not just when flying.
We probably never thought of the Trolley bag as an “Innovation.” In our minds, new things always seem to change the world, going from zero to one instantly. Kepha trolley IS The establishment – and, like many others, important.
Ngabe i-trolley ihlangana ini nge-AI? Yes, right now, AI is often called the missing ingredient to solve humanity's biggest and biggest challenges.
IX (MoonShot Factory) and similar organizations advertise their focus on renewable energy, clean drinking water, reliable and healthy food. In many of these industries, AI is proving to be an important tool: preparing power grids, synchronizing plants, improving medical diagnosis. These are good intentions and I don't doubt the sincerity or technical depth behind these efforts *.
A large part of the narrative of AI resides in the realm of moonshots: Shocking, press-ready, “this could change everything” news. That is interesting, and we want to believe in these declarations. Just imagine .
However, the establishment that moved the peace forward is very common :
- Wheels on luggage
- A barrier
- A zipper
- Simple
- Plugs are standard
- Traffic signs
This is boring, of course, and no one sees them as such. But they are also great. They reduce the anger of millions of people every day.
Most AI projects today don't aim for this level, well, you're back to being boring. All:
- Prepare for experiences that you might not want to do well Some progress (“better” content content, faster ad prediction), or
- It aims at major global challenges where the impact is real but slowuncertain, or heavily constrained by non-technical factors.
Not on this list is the equivalent of ai-days on the trolley: simple, reliable, established on the same day, out of the day, but can be missed quickly if taken.
For many people, I wished that these fundamentals were still more relevant than the latest release of the AI Model (even if they are from 500 billion parameters):
A good relationship.
Good food.
Good health.
At the current stage, AI is not as incredibly advanced as the hype sometimes suggests. Not most people, not yet in the “Wheel-on-a-Bag” category.
These are good, but mostly bad and often require more human intervention. . After your theft, you (hopefully) won't think: “I wish I had better recommendations.”
Lokhu akusho ukuthi i-AI ayinamsebenzi. It's become very important in many careers, including my own (think code help, for example!). Kepha kufanele senze kabusha okulindelwe kwethu: The development of tools is not the same as the invention of civilization. And right now, the bulk of AI's attention is relegated to dramatic narratives, and away from quiet, systematic development.
When research, funding, and talent all converge on “the world's toughest problems”, three things can happen:
- Annoying paperwork procedures, hospital flows, municipal services, municipal issues, logistics quirks – areas where small, robust ai tools can remove daily pain – are paying little attention.
- We speak as if the impact of Transformative AI has already fully arrived, when most of it is still conditional: in policy, infrastructure **, economics, adoption.
- We overestimate how much AI matters for good health. We risk managing the enthusiasm of AI or AI more important than basic, human, offline things that actually drive well (like eating friendship or food).
The trolley bag metaphor can serve as a sanity check: If an AI system disappeared tomorrow, would humans hear Like losing the wheels on their luggage? Kwamanye amacala amancane ***: Yebo. Ezimweni eziningi: cha, hhayi nhlobo.
To incorporate this idea into your daily thinking, I suggest three ways:
When you see bold AI promises – featuring “Revoluse,” “Disrupt,” “SOLING X
- Does this improve something concrete in everyday life, or is it something much bigger?
- Is the bottleneck here really intelligence (which could be solved by an advanced AI system), or policy, incentives, logistics, or basic infrastructure?
- actually
2
Use the everyday implementation as a reference class:
- Does this AI system simplify life clearly as, for example, light matching, zippers vs buttons, trolley bags vs. pregnant?
- Is it strong, cheap, and potentially boring enough that people will rely on it without thinking?
If the answer is “not even close,” treat the announcement accordingly: It's interesting, maybe useful, but maybe not world-changing.
3. When choosing your AI projects, think about fighting the hype
- Look for existing problems : Programming, documentation, accessibility, internal tools, error mitigation, security checks, forms, billing, routing, maintenance.
- The purpose of the tools people stop seeing because they just work.
Ask yourself: Is this approaching a trolley bag or a trailer being delivered? If it's the first time, you're probably on the right track.
Closing thoughts
I am not arguing against emerging AI research. Lokho bekuzolimaza umsebenzi wami. We must definitely look at what is possible and apply it to difficult problems. Kepha kufanele futhi sibone igebe lapha:
Right now, most of the AI hype stays away from the quiet, structural improvements that make up everyday life.
As individuals – Researchers, developers, users – we can respond to the dubious onslaught of inflated promises, by allowing development in Mundane but with purpose, and with deliberate construction tools like a set of wheels in a bag.
Those kinds of changes that continue, over time, move the world forward.
* In fact, after this program, it is 10 years + until the development is improved, not to process the many shoulders that are built in these years. From what I remember, David Elver started researching reinforcement learning around 2000 – but it would take a decade and more until we heard about Alphago!
** If you have ever installed a model, you know that the infrastructure is actually a paint point. Or, consider the energy costs used to train these species. Money spent on training AI may have solved the problem without needing AI…
*** Sebenza kakhulu, ngicabanga. For everyday interactions with people, AI is not needed.
