but the leader of fascist Italy was an atheist, which suggests the endorsement of the Catholic Church was not entirely sincere. Its possible that Mussolini was not entirely honest in his public behaviour.
The Chinese room metaphor is an argument about AI, or computation more generally, attempting to distinguish the difference between performance metrics and "understanding".
There is the role of the human within the metaphor, and the argument/position of the metaphor as a whole. I don't think it makes much sense to talk about the "point/argument/position of a single component of the metaphor. At least, that wasn't how it was originally structured.
The Chinese Room metaphor is yet another one of those arguments that fails to take into account that humans are a bag of functional proteins. There is no soul anywhere in the human body.
In other words: it's an argument that would work perfectly fine to defend the idea that humans have no consciousness.
Ergo it can only really prove that either humans have no consciousness/soul/... (whatever you name the magical human property) or that it doesn't exist at all.
That is a pretty simple grasp of the example. It doesn't claim that no system can have understanding or consciousness. It just demonstrates that performance alone is insufficient to conclude consciousness and understanding. A calculator or abacus can add 2 + 2 but instead self aware
The thought experiment doesn't give a limit to the amount of intelligence the Chinese Room can display though, and if the thesis is that you just need a big enough model, then the fact that it doesn't "understand" is not an impediment. It's not a decided matter, in any case, and is still controversial among philosophers of the mind (who are less biased than AI researchers in companies that they have stock options in).
Maybe Im reiterating the same point as you, but the experiment is an illustration of distinction between understanding and performance. Size of the model or perfect performance does not negate the distinction.
IMO, the line of thinking in the metaphor is contingent on unanswered questions about self-awareness, which seems to be a definitional prerequisite for semantic understanding.
If we hypothesis perfect performance, the philosophical question is if that's a distinction without (or with) a difference. Perfect performance would simulate semantic understanding, no? More relevant to the real world though, how do we rate imperfect performance? If a Chinese Room that I have access to can make some logical leaps but not others, how do we rate this artificial intelligence? We have words to describe humans with insufficient semantic understanding but they are not usually able to write/generate cromulent essays on basically every topic.
>Perfect performance would simulate semantic understanding, no?
The thought experiment argues the exact opposite. The idea is you can have perfect Chinese but not understand a single word of what you are saying. The argument is that syntax (procedure based operation) and semantics (understanding) are distinct and separable.
As you extend the scope of the Chinese room from a single task (e.g. Chinese conversation) to human behavior in general, it converges with the question of if philosophical zombies can exist.
In terms of the Chinese room, the distinction IS the difference.
That's what Searle's argument is, but it's a thought experiment and there's no consensus among professional philosophers as to whether or not to believe it is true.
I kinda interpreted it as: "Here's an example of something which we would not call intelligence if you knew how it worked, therefore our definition of intelligence must somehow involve process or understanding, not just results."
This seems like a good thing if front-end fragmentation is not an issue, ie. if it's hosted on a server and kept in sync with the backend through deployment.
As a mobile app? Maybe not.
I'm honestly a bit puzzled which scenario the original article is envisioning when arguing this, because it mentions mobile, but then also argues for monorepos, which are kind of at odds with each other, unless you somehow force your mobile users to always be using the version that matches your back-end.
Oh, I see. Yeah, you'd definitely need to be very careful in this case.
To be fair though, this is a general problem when clients and servers might not agree on data formats. You can still safely do what the author is describing since type checking occurs at compile-time and not runtime.
You would, of course, need to be sure your app handles whatever the API/db returns at runtime though. But, again, this is a general problem.
> Generally the field declaration/migrations system in Django feels to me designed to lead people down a garden path towards bad and dangerous behavior. If I had my druthers I'd enforce a policy in our Django app of "never run makemigrations, all migrations must be manually written SQL".
`makemigrations --dry-run` is helpful to see if your manual migrations are complete but besides that I agree
I believe `makemigrations` builds up its conception of "what the schema is" from the `CreateModel`, `AddField`, `AlterField`, etc. ops in the migrations files. But it doesn't incorporate `RunSQL` ops into building that model of the schema. If my migrations were just a bunch of `RunSQL` ops, I think `makemigrations --dry-run` would basically just see everything from models.py as always needing to be added.
This behavior is why `SeparateDatabaseAndState` is a necessary hack in Django: sometimes you need to do an `AlterField` where the SQL Django would generate is really bad, so you need to write your own `RunSQL` to do the right thing, but you also need Django to see the `AlterField` as applied or you'll have problems with future migrations.
I suppose I could modify my preference to "run makemigrations and then wrap every single op in SeparateDatabaseAndState", but that does not sound fun :).
Garmin estimates it using heart rate, body weight and power output. It also adjusts for temperature and altitude if possible. In my experience it still varies a lot depending on which conditions I exercise in but it's a decent tool to see your progress if you're able to test it under similar conditions every time.
The user you replied to has convinced me to get a smart watch as 1. I've had awful stamina since age 10 or birth 2. Stupid "number going up" gimmick generally works well at motivating me. But I'm not about to switch to iPhone, so getting an Apple watch isn't going to work.
Not OP but I’ve used Garmin’s for about 15 years and over 10k running miles. I don’t like or use non-fitness related smart watch features, so I can’t speak to those or recommend a good "smart watch that also does fitness". If you want top of the line with more data than you’ll know what to do with and a ton of fitness activity tracking beyond running, the Epix2, Fenix 7, or Forerunner 965 (I have the Epix2).
A step down but still great is the Forerunner 265. The feature they all have and I think has been the most useful is the Training Readiness. It looks at a bunch of different metrics, both current (your HRV, last workout performance, sleep, stress) and chronic (your weekly and monthly total exercise amount, types of running, etc) and advises you on how hard you should train and suggests a running activity for the day. It is basically a digital running coach/personal trainer that makes sure you are getting a good mix between tempo runs, long runs, easy runs, etc. and makes sure you aren’t overtraining or if a bad day means to switch to a light workout. I normally use it loosely to inform my choices but I’ve tried using its daily training plans exclusively and it was very good at keeping me progressing.
Super helpful, going to look into those! I too only care about the fitness part, in an even narrower scope - literally only the usecase mentioned here, giving some VO2max-ish or other "stamina level" number (even if of questionable accuracy) that I can slowly see improve over time to help with motivation.
In some sense less data might be better to make it clearer which number to focus on, so sounds like the Forerunner may be the right fit. The Training Readiness does sound a bit intidimating for someone who's starting from zero (or really, minus), but I can always strategically ignore that ;)
>The Training Readiness does sound a bit intidimating for someone who's starting from zero
I totally understand, however, I would say that is exactly where it is most useful. You don't need to actually know or understand any data, since Garmin crunches all those things in the background for you and distills it down to concrete advice on where you are and what to do next. You can really do well with just two metrics (the daily suggested workout and Training Status). You could just follow the workout of the day "Easy run, heart rate range x-y, 31 mins" or "Tempo run, warm up 10 mins, run 15 mins heart rate range x-y, cool down 10 mins" etc. And look at what your Training status is currently, which is things like “Productive”, “Overreaching”, “Maintaining”, etc.
You don’t need to understand about lactic threshold and what types of runs improve it or how high aerobic, low aerobic, and anaerobic runs affect different aspects of improving your fitness or how many rest days are enough. You don’t need to have the experience to know how to balance recovery and training and which factors to even look at. Was your status “Productive” most of the week? Awesome, you know you are improving. What is the next workout? Done.
I hope it works out for you and you enjoy running as a healthy hobby.
> Was your status “Productive” most of the week? Awesome, you know you are improving. What is the next workout? Done.
Right, but to us monkey-brained seeing a boolean "productive" isn't a great motivator, we need to see a number that can go up, making it much more addictive. That's why I was so convinced by the Apple Watch user giving that one number that they look at - that will definitely work for me as it's super effective on the reward-related parts of my brain. A boolean, or having a hundred numbers - not as much. If you're someone who doesn't need that, I'm sure the training readiness is much more actually useful for improving, but we're not necessarily looking for that - our hope is to one day get to a point where we may start looking for that :)
I've noticed it myself even when doing projects. So much easier to stay motivated when you have this one number, e.g. page views or active users that updates every day (not "enterprise contracts" which may change once every month), to focus on, purely for monkey-brain reasons.
A better example would be the chinese cultural revolution and their campaign against the Four Olds.