THE BIG REGRESSION
My folks are in town visiting us for a couple months so we rented them a house nearby.
Itās new construction. No one has lived in it yet. Itās amped up with state of the art systems. The ones with touchscreens of various sizes, IoT appliances, and interfaces that try too hard.
And itās terrible. What a regression.
The lights are powered by Control4. And require a demo to understand how to use the switches, understand which ones control what, and to be sure not to hit THAT ONE because itāll turn off all the lights in the house when you didnāt mean to. Worse.
The TV is the latest Samsung which has a baffling UI just to watch CNN. My parents arenāt idiots, but definitely feel like theyāre missing something obvious. They arenāt ā TVs have simply gotten worse. You donāt turn them on anymore, you boot them up.
The Miele dishwasher is hidden flush with the counters. That part is fine, but hereās what isnāt: It wouldnāt even operate the first time without connecting it to an app. This meant another call to the house manager to have them install an app they didnāt know they needed either. An app to clean some peanut butter off a plate? For serious? Worse.
Thermostats... Nest would have been an upgrade, but these other propriety ones from some other company trying to be nest-like are baffling. Round touchscreens that take you into a dark labyrinth of options just to be sure itās set at 68. Or is it 68 now? Or is that what we want it at, but itās at 72? Wait... What? Which number is this? Worse.
The alarm system is essentially a 10ā iPad bolted to the wall that has the fucking weather forecast on it. And itās bright! Iām sure thereās a way to turn that off, but then the screen would be so barren that it would be filled with the news instead. Why canāt the alarm panel just be an alarm panel? Worse.
And the lag. Lag everywhere. Everything feels a beat or two behind. Everything. Lag is the giveaway that the system is working too hard for too little. Real-time must be the hardest problem.
Now look... Iām no luddite. But this experience is close to conversion therapy. Tech can make things better, but I simply canāt see in these cases. Iāve heard the pitches too ā you can set up scenes and one button can change EVERYTHING. Not buying it. It actually feels primitive, like we havenāt figured out how to make things easy yet. That some breakthrough will eventually come when you can simply knock a switch up or down and itāll all makes sense. But that's at least 20 years down the road.
Itās really the contrast that makes it alarming. We just got back from a vacation in Montana. Rented a house there. They did have a fancy TV ā seems those canāt be avoided these days ā but everything else was old school and clear. Physical up/down light switches in the right places. Appliances without the internet. Buttons with depth and physically-confirmed state change rather than surfaces that donāt obviously register your choice. More traditional round rotating Honeywell thermostats that are just clear and obvious. No tours, no instructions, no questions, no fearing youāre going to do something wrong, no wondering how something works. Useful and universally clear. Thatās human, thatās modern.
Sharing an interesting recent conversation on AI's impact on the economy.
AI has been compared to various historical precedents: electricity, industrial revolution, etc., I think the strongest analogy is that of AI as a new computing paradigm (Software 2.0) because both are fundamentally about the automation of digital information processing.
If you were to forecast the impact of computing on the job market in ~1980s, the most predictive feature of a task/job you'd look at is to what extent the algorithm of it is fixed, i.e. are you just mechanically transforming information according to rote, easy to specify rules (e.g. typing, bookkeeping, human calculators, etc.)? Back then, this was the class of programs that the computing capability of that era allowed us to write (by hand, manually).
With AI now, we are able to write new programs that we could never hope to write by hand before. We do it by specifying objectives (e.g. classification accuracy, reward functions), and we search the program space via gradient descent to find neural networks that work well against that objective. This is my Software 2.0 blog post from a while ago. In this new programming paradigm then, the new most predictive feature to look at is verifiability. If a task/job is verifiable, then it is optimizable directly or via reinforcement learning, and a neural net can be trained to work extremely well. It's about to what extent an AI can "practice" something. The environment has to be resettable (you can start a new attempt), efficient (a lot attempts can be made), and rewardable (there is some automated process to reward any specific attempt that was made).
The more a task/job is verifiable, the more amenable it is to automation in the new programming paradigm. If it is not verifiable, it has to fall out from neural net magic of generalization fingers crossed, or via weaker means like imitation. This is what's driving the "jagged" frontier of progress in LLMs. Tasks that are verifiable progress rapidly, including possibly beyond the ability of top experts (e.g. math, code, amount of time spent watching videos, anything that looks like puzzles with correct answers), while many others lag by comparison (creative, strategic, tasks that combine real-world knowledge, state, context and common sense).
Software 1.0 easily automates what you can specify.
Software 2.0 easily automates what you can verify.
@champtgram It is a trend in South America as well. But there the reason used to be that most mobile subscriptions came with SMS/MMS limits and they were expensive. This lead to a strong preference for mobile-data based channels, like WhatsApp.
A big challenge in this age of āthereās an AI tool for everythingā is managing the expectations of the managers who donāt really understand it.
They want everything done at 1/100th of the current cost, with no overhead.
But we are simply NOT there yet, and every AI tool still needs LOTS of babysitting and fine tuning.
@shl Yes! It is the best path to professional growth: you are done automating your tasks? Great! Now you have to find other ways to create value. Rinse and repeat.
You need to look at it this way: Your pay is what is left after the government has taken its cut. Should there be no taxes, your income would only be your current pay after taxes. The market would not pay you more unnecessarily. Itās pricing, and taxes are just a part of the cost equation. Remove them for everybody and prices (income) will fall across the whole economy to keep relative prices balanced.
So how to cope? Be content and/or earn more.