A strange game. The only winning move is not to play.
1,425 karma · joined December 4, 2020
“Why don’t you just make the minimum 37 pieces of flAIr?”
The inference response to the prompt is not deterministic. In fact, it’s probably chaotic since small changes to the prompt can produce large changes to the inference.
This doesn’t seem like a good example. People who engineer systems that rely on integrals still know what an integral is. They might not be doing it manually, but it’s still part of the tower of knowledge that supports whatever work they are doing now. Say you are modeling some physical system in Matlab - you know what an integral is, how it connects with the higher level work that you’re doing, etc.
An example from programming: you know what process isolation is, and how memory is allocated, etc. You’re not explicitly working with that when you create a new python list that ends up on the heap, but it’s part of your tower of knowledge. If there’s a need, you can shake off the cobwebs and climb back down the tower a bit to figure something out.
So here’s my contention: LLMs make it optional to have the tower of knowledge that is required today. Some people seem to be very productive with agentic coding tools today - because they already have the tower. We are in a liminal state that allows for this, since we all came up in the before time, struggling to get things to compile, scratching our heads at core dumps, etc.
What happens when you no longer need to have a mental model of what you’re doing? The hard problems in comp sci and software engineering are no less hard after the advent of LLMs.
The internet famously doubled in connectivity every 100 days during its expansion era. Its usefulness was blindingly obvious - there was no need for management to send out emails warning that they were monitoring internet usage, and you'd better make sure that you were using it enough. Can you imagine!
We are at a remarkable point in tech. The least-informed people in an organization (execs) are pushing a technology onto their organizations. A jaw-droppingly enormous amount of capital is being deployed in essentially a "pushing on a rope" scenario.
The terminal never left.
It’s not a “joke” in the sense of being lighthearted or unserious: there was a press conference at the White House. Official US maps have been updated. Google Maps has been updated.
Think of all the jobs that do not involve putting your hands on something that is crucial to the delivery of a service (a keyboard, phone, money, etc does not count). All of those jobs are amenable to this technology. It is probably at least 30% of the economy in a first pass, if not more.
The industrial revolution started in the early 1800's. It was a migration from hard physical labor outdoors, around the home and in small workshops to hard physical labor in factories.
My main concern about AI is not any kind of extinction scenario but just the basic fact that we are not prepared to address the likely externalities that result from it because we're just historically terrible at addressing externalities.
I find it hard to accept your claim because at the start of the industrial revolution there were far fewer women in the formal labor market than there are today.
It would not even necessarily result in a human-like robot - just some device that can move the water heater around and assist with the process of disconnecting the old one and installing the new one.
The Luddites were skilled artisans in the textile industry. They often worked from home, owning spinning and weaving equipment and acting as what we’d call independent contractors today.
The mechanization of the textile industry resulted in work that required less skill and had to be performed in a dangerous factory for suppressed wages that were determined by a cartel of factory owners rather than a robust market of small makers.
Sitting here 200 years on from the Industrial Revolution it seems to be an obvious good. But it sure did not sound like an appealing thing to live through if you weren’t one of the few owners of the means of production.
Others who attend church presumably assume that you share the stated beliefs?
In desktop GUI apps, the delineation is much crisper: the model is the data that the application manages (the CAD geometry, the document, etc). The view is one or more renderings of the data to screen, and the controller is the input and command processor that updates both the model and the view.
Storage is not central to this architecture - it exists, of course, but it’s not really described as part of these core relationships.
With LLMs you have no such guarantee or expectation.
This is highly rewarded in many (most?) corporate environments, so that’s not surprising.
When’s the last time you heard “when will it be done?”
When’s the last time you heard “can you demonstrate that it’s right|robust|reliable|fast enough|etc?”