Why not corporations? They would be owned by the market and compete against each other to offer best quality machinery.
Of course you still have the leadership class of people that could be corrupt, but that can be solved e.g. by sortition https://en.wikipedia.org/wiki/Sortition
+ you need anti-monopoly laws and some solutions preventing competition-to-the-bottom (e.g. if marginal cost of service becomes 0, it may no longer make sense to compete for it, so it needs to enter some sort of maintenance mode to keep quality in check)
I've been thinking along similar lines on high level - this approach will likely be very general and can be used to create different kinds of media, as well as potentially behaviours in a later stage.
Hmm actually now i'm not certain which one of these I have.
I'm a software developer and I have kind of like two different "address spaces".
There is the normal visual + auditory address space.
And there is the "intuition space" which is similar to the first one (e.g. I can imagine a 3D object and rotate my viewpoint around it, simulate conversations, etc), but it's with limited detail, more like black and white unless I concentrate more. I can "hear" there but it's separate from normal hearing.
It's super-useful in programming, as i can imagine code in some kind of 3D space, where I can move in and out of different functions calling each other (I still imagine them mostly as text though), so I can remember them pretty well.
The issue to be reconciled is though that some of those ideas are talking about "keeping uncertainty in the sweet spot, not too high or low" while others about "minimising uncertainty/prediction error". I think the difference will turn out to be only in relation to how far of a future/prediction we are talking about. So optimising for long-term vs the short-term.
This is a similar view to the emerging theory of Bayesian Brain, which views the brain as a system that tries to minimise the prediction error (which might be the same thing as "free-energy" in some related publications) by comparing expectations with actual information coming from the senses.
So far it seems that it explains quite a lot of data, and many mind illnesses (e.g. many diseases can be thought as the brain under-correcting or over-correcting for the prediction error).
By under-correcting, the brain is not learning enough on its mistakes, which may lead to delusions of superiority (e.g. being stuck in usual habits, or inability to change one's world-view based on new information). On the other hand, when over-correcting, the world may seem unpredictable, frightening - leading to self-doubt, anxiety and negative thoughts.
Science has been sticking to that view since around Newton. But it's actually beginning to slowly change now, as time-independent physics might be a reason why our theories work very well in specific areas, but tend to break down in a more holistic approach.
Yes. You might find interesting some very rated ideas as this article - Bayesian Brain. In this view, the brain is a complex system that learns to adapt to and predict its environment, similar to other complex systems like even companies.
Theories are now emerging that Universe is running one large bayesian learning algorithm (bayesian inference itself is proven to be an optimal knowledge creation method)
There are many ways to do this, like meditation, or some substances.
You basically imagine yourself in the future, having achieved some goal, or being in a situation that you like. This image has to be rich and invoke many emotions, so it becomes engraved in your neural paths.
You then work backwards from there, imagining different roads and specific steps on how to achieve that.
It literally and physically changes your brain over time, as you repeat it.
I wonder how this relates to Cosmological Natural Selection theory - the idea is that the black hole 'bounces' into a child universe, which inherits some of the parent characteristics. Perhaps the information finds its way there.
This sounds quite in tune with some of Daniel Dennett's ideas also, especially from 'Consciousness Explained'.
The gist is that our consciousness is only, and all, that we can say, or in any other way act on the world. So if people really believe in the things they say, those things must be quite real to them.
And perhaps visual hallucination come from some incomplete separation of the 'inner' visual loop - thoughts, memories - from the outside visual information.
Even if we don't, the progress is not going to stop, for example on:
- lowering the price of each chip - you can get that by more automation.
- lowering the cost of energy used by a chip - you can have that by raise of renewable energy generation and its decentralisation (and again, more automation).
The point is that automation caused by AI will start a reinforcing feedback loop where more and more work can be done more cheaply, speeding up automation itself too.
> current equity compensation is far too low and tricky
Of course, we can imagine various ways in which the situation can be improved, like getting equity directly instead of options, increasing the amount of equity, etc.
But that's beyond the main point of stocks. The point of them is to align employees with founders more, get them excited and motivated about the future.
> workers, and especially new workers, should not be optimistic about the benefits.
But the same argument can be made about founders and starting new companies. Of course most startups do not succeed, but should that discourage people from creating them?
I think there is a bit of confusion in that generally it's believed that these aspects of startup industry are much different - one is a 'unavoidable state of the world' and the other is 'unwillingness of certain people to make the situation better'. But perhaps both of them are in fact state of the world... There are many variables that go into selecting the values for employee stock grants and could be just as much hard to change.
Maybe they ultimately end with 'smarter people are able to control those less smart', but that's another discussion.
Great to see you unveiled. Best of luck, i really look forward to having a real cloud-native way of developing software.
Do you guys plan to support smart diffs for code reviews? As you work on AST level, it should be possible to detect some more patterns, e.g. an re-arrangement of some pieces of code, refactorings of many identifiers, etc., categorise them and have a diff summary for the review.