327 karma · joined May 13, 2019
Remote: Only
Willing to relocate: Most probably not
Education: Pure mathematics BSc. and CS MSc.
Technologies: Haskell, Scala, Python, C, C++, J, Linux, more
CV: https://drive.google.com/file/d/1bCv2SzEe_ZZXkzRNqSoHLDqDGut...
Email: paston.cooper@gmail.com
Stuff I've been interested in recently: Built with some tips from HN an automated system for playing Betfair's Exchange Hi Lo card game based on an exact odds calculation algorithm I discovered. Only to find that there was no liquidity at the calculated odds.
Did some free Betfair sports betting data analysis in various markets.
Currently looking into crypto.
Looking for: Anything fun you want to work on together that isn't crypto that will potentially make money, with a minimal number of people involved. I am open to ideas.
I am not fixed to one specific technology. Anything that works. After years of Haskell I have found myself mainly coding in Python recently. Get prototype running, then optimise where needed.
What more general systems of computation are there than Turing? Are any in use? Are they really more general?
The claims of the generality of Actors seem to rely on continuous time and non-determinism. Actors, determinism, non-determinism, concurrency and the completeness axiom are models which we can use to express computation and our surroundings, and nothing more.
One man says lambda, another says actor. Given our models of physics; given Planck and Heisenberg, are they really different? If so, how? Measure theory rests on the completeness axiom, but it is just a very useful axiom.
Am I missing something?
In it, he claims that Godel's Incompleteness Theorem is not true, and that the actor model is more general than the Turing machine. I am open to entertaining the idea.
I've seen that his ideas have been discredited elsewhere on HN. I would be interested to know people's opinions on this, as a lot of the paper went over my head.
I chose to figure out how to do this in Python instead of my usual Haskell because I wanted to see how productive I would be compared to how I did similar things in Haskell. I wanted to get away from what I call type-wankery, which the author seems to be complaining about as well.
I’ve been using the Python asyncio library and have been thinking that Python could certainly do with monads in this context. Then I remembered what a ball-ache stacking monads is. In any case, I can’t help seeing programmes in an algebraic context after using Haskell.
The author, and many people who complain about types, seem to forget that types and interfaces exist whether or not they are explicitly defined.
Is the problem with such an attractive type system that they lead to people defining interfaces before they are fully explored? In that case, maybe it could be argued that a less attractive type system would keep people away from so much type-wankery.
It’s hard to know where the best balance is. I am considering F# now. It also seems to have working IDEs, which is nice.
I wonder how the multiple graph ‘levels’ (which could interact with each other) would come into play. EXCHANGES, BROKERS, HEDGE_FUNDS, INTERNET_PIPES, PEOPLE.
What existing tools are there for analysing information propagation like in the paper?