I've always heard this, and so when I went for my first smart thermometer I went straight to Ecobee (which I'm very happy with btw).

So I gotta ask HN...what the heck was so popular about Nests?! It's one thing to be go after shiny lures like new iPhone apps or luxury items...but a Thermostat?!

Mind boggling...

It looks good on the wall, has a bright large display that lights up when you approach and intuitive enough for non-techies to operate. Also it can be installed without a common wire.

And you can control it from your phone, or with your voice by talking to Google assistant.

The industrial design of the thing is really nice. I wish someone could/would copy them. I don't use any of the smart features nor do I connect it to the app, but it's still the nicest looking thermostat out there.

The problem I think with all of these ML functions is that there is never enough of an in between full manual and full auto magic. The Nest could simply ask you a few times a day how you feel about how its doing (too hot ? too cold? too expensive?) or you could opt in somewhere and to give feedback. And then it could keep doing its behind the scenes mumbo jumbo.

How I feel is at least psychosomatically related to how the system is operating, but also how things are outside of the controlled environment.

Generally this is an algorithm that might work for one person:

* Is it equal or higher than the upper temperature outside? Run COOLing function (if it exists) until the LOWER inside temperature bound is reached.

* ELSE Is it equal or lower than the lower temperature outside? Run HEATing function (if it exists) until the UPPER inside temperature bound is reached.

In both cases DO NOT continue to run the circulation fans, at least above a whisper quite slow circulation, past the thermal shift operation. Luke-warm airflow makes the system perceptibly anemic and the results dis-satisfactory.

This is more of a product problem than a technological one. I don't think the issue is lack of imagination, but hostility from consumers.

There are a million and one cases where a pdocut could be 10x better with 10% more effort from me,and where that tradeoff is more than worth it (hell, it's why I use Linux). But the average consumer is aggressively turned off by having to do any "work", and the type of person hanging out on Hacker News is very high-percentile for wanting to put a nonzero amount of work into optimizing this type of thing.

I have already a solution where I can put zero amount of work for optimizing it, it's called a button. Why would I bother with something as needy as this "smart" thing?

I don't understand your comment or how it's remotely relevant to the thread. Is this just a non sequitur Luddite rant about the very existence of new tech?

Surely each time I change the temperature manually that's a signal it's been wrong for the past half hour or so

Same story. We moved into a house that had a Nest preinstalled. Got everything set up, and noticed after a couple of days we would always wake up freezing in the early morning. Nest was all over the place and I just turned off the automation.

>And then after a few instances, I just turn off all the automation and set up a schedule like normal.

If you have a fairly regular life I would think a schedule would outdo ML pretty much all the time, because you know exactly what that schedule should be. ML might be useful for a secret agent whose life is so erratic that a schedule would be useless.

That is to say ML is maybe better than falling back to nothing.

If your schedule is so irregular/erratic, how is a ML algorithm supposed to be able to learn it?

Sounds like in that case it's better to just control things manually.

ML can learn patterns that humans might not be aware of, so you there might be certain things that happen that show you will be on a mission to East Asia for a couple days.

Only when data is supplied to it to match the trained pattern,

ML is pattern recognition. Anything outside of that is still AI, but it isn't ML. I can think of very few feature sets we could supply to help predict someone will be deployed to East Asia for a few days other than scraping calendars and mail for religious and military organizations.

From a design perspective, Nest and others are either additively learning in situ to enhance a base model or they are working from a base model that doesn't directly learn, just classifies workflow to categorize observations on a base model. I doubt heavy training is occurring where the Nest and similar is treated as the central compute node.

One niche that ML seems to be growing into is /assisting/ humans, but not doing the whole task. ML might give you an image that is 90 percent what you want but needs a few tweaks.

If the task is clear enough, ML can take it on by itself, but this requires clear rules and an absolutely unambiguous definition of what winning means. For example, the best chess players in the world are machines, and are FAR better than the best human players. Same for Go (the game, not the programming language).

I bought one back before Google bought the company, because it seemed like a well-designed product with a good UI. In addition to the problems you mentioned, it was constantly updating its firmware. That sometimes bricked the device temporarily and sometimes it changed the UI so I had to relearn how to use the device. One update removed the ability to manually set "away" mode. I finally wised up and reset the thing so it couldn't attach to my wifi any more. Which made the app useless of course.

Then it became clear the thermostat wasn't getting enough power from my 2-wire thermostat transformer and that made it even flakier. I finally threw it away and replaced it with a $20 dumb thermostat, which will still be working fine after the zombie apocalypse. No more Nest products for me.

> Same with the "away from home" which seems to randomly think I'm away and I have no idea why.

Away from home should be an easy problem to solve assuming Nest can talk to your phone(which is almost 100% true in real life). IN my experience there are several easy heuristics that can achieve ~ 90% precision and recall in home detection, like are you connected to a wifi or even combining it with some IMU data to be more confident.

Everything should be an easy problem to solve yet it somehow stays a problem. For me it's quite binary: the problem is solved yes/no. And if the easy problem is still not solved, it's still not solved, period.

The ability to remotely activate it is useful in the case of erratic short term rentals. Other than that, I'm not sure of the point

Which is something that a cheaper, more basic Honeywell model with way less surveillance potential can also do...

Indeed. I wouldn't buy a Nest. But there is a use case for an IoT thermostat.

Maybe it considers environmental impact of air conditioning in its models and tries to nudge users into tolerating higher temps.

Which is not respecting your users. In fact, in my previous house the Nest was provided by the utility company and they used it /exactly/ for this purpose (although were legally mandated to notify us and allow us to opt out on a daily basis) where they'd intentionally raise your temperature during the hottest part of the day to reduce energy usage. But the thing is, I work from home, and if I'm sweating out a liter of fluids while I'm trying to work, I am getting nothing done and look unpresentable on meetings to boot.

In the end because most of the house was empty, I let the Nest do its thing and installed a separate mini-split AC in my office I kept set at 72 year-round because that's a sane and reasonable temperature for an office. Don't try to "nudge me into tolerating higher temps", respect my agency and choice about what is a comfortable environment for me to work in.

As a side note, I will never again buy a Nest product.

If you have to guess why it's making decisions you don't want, it's a shitty product.