bjr-
When Bitcoin miners consume electricity shouldn't that increased demand affect the market price and dis-incentivize mining? What other use of electricity has such a high price elasticity? People don't turn off their ACs in the middle of summer because electricity costs are high -- they value comfort, a lot. But miners, IIUC, shut down their ASICs when they're unprofitable. Bitcoin mining is extremely price sensitive.
If Bitcoin mining is driving up local electricity prices it seems worthy of local regulation. It also seems like an incentive for increased energy production -- and given today's prices would most likely be clean energy production.
The report states Bitcoin's consumption is 39% clean energy. That is considerably higher than the overall portion of global energy consumption from renewables. Does this not mean Bitcoin is a large source of demand for renewable energy? https://ourworldindata.org/grapher/share-electricity-renewab...
Increased demand increases prices in the short-run and incentivizes production -- decreasing prices, and further increasing usage in the long-run. Right? What am I missing?
Kanopi is...
- a tool that blurs the line between private note-taking and public linked data
- a part-time project from 2015 - Sept 2020, full-time since then
- my attempt to explicitly support more of the thinking/learning process (capture, collection, organization, synthesis, analysis, and maybe recall)
--- excluding functionality for presentation and real-time collaboration
- in private alpha - request an invite at kanopi.io!
The problems I'm trying to solve with Kanopi are:
- remove frictions from note-taking by using data on the web to suggest notes and links
- make notes useful across contexts/projects by adding outlines (Trees) and mind-maps/diagrams (Maps) on top of your notes
--- notes are not contained in these tools, they are referenced
- make notes more meaningful over time by encouraging smaller notes, with titles, that have labeled links to other notes (how is X related to Y?)
From user interviews I think academics and professional researchers experience these problems most acutely so they are my focus at this stage.
As some on this thread have discussed -- I don't expect to make this decision lightly, but if this sounds interesting and you feel it is a good fit then please reach out.
Typed and untyped code must (and will soon) be able to cooperate in providing compile-time and run-time type checking in Clojure.
Clojure, ClojureScript, Storm, Semantic Web (RDF/OWL/RDF*), Prolog, Datomic, Cassandra, Om
We are building a system that takes fuzzy human language financial regulations and transforms them into something computable: rules. Rules are then executed against billions to trillions of triples and all information (raw and inferred) is presented in a UI that gives the user tools to navigate, manipulate and analyze linked data.
The conceptual heart of the system is a set of semantic web standards that allows us to formally model data and rules.
The technical heart is Datomic, Storm, Clojure, ClojureScript and Om.
Clojure, ClojureScript, Storm, Semantic Web, Prolog, Datomic, Cassandra, Om
We are building a system that takes fuzzy human language financial regulations and transforms them into something computable: rules. Rules are then executed against billions to trillions of triples and all information (raw and inferred data) are presented in a UI that gives the user tools to navigate, manipulate and analyze linked data.
The conceptual heart of the system is a set of semantic web standards that allows us to formally model data and rules. The technical heart is Datomic, Storm, Clojure, ClojureScript and Om.
I feel most relaxed when that's split between 2 hours in the morning and 2 hours in the afternoon. Great days are 6 hours (i'll be in "the zone" from ~4:30 to ~6:30).
Another 3-6 hours can be spent reading (code or books) and exploring (fiddling around in a repl).
I am at the office for 8-10 hours per day, but the office is really only a center where most work hours occur. Often a good Saturday spent across libraries, cafes and parks can yield 6 hours of getting shit done.
Clojure, ClojureScript, Storm, Semantic Web, Prolog, Datomic, Cassandra, Om
We are building a system that takes fuzzy human language financial regulations and transforms them into something computable: rules. Rules are then executed against billions to trillions of triples and all information (raw and inferred data) are presented in a UI that gives the user tools to navigate, manipulate and analyze linked data.
The conceptual heart of the system is a set of semantic web standards that allows us to formally model data and rules. The technical heart is Datomic, Storm, Clojure, ClojureScript and Om.
2) ClojureScript, React, Datomic are my preferences. A well-designed language with JS as a compilation target, React Native, and a graph database with ACID guarantees and scalable reads are powerful tools.
My story:
I was fired 2 weeks after moving to a suburb ~90 min from nyc (employer had ok'd remote work, oh well). I came up with a good side project using all the technologies I was excited about and sprinted on that while I 1) signed up for unemployment, 2) updated resume, 3) updated linkedin, 4) started looking at freelancing marketplaces, 5) go to all the relevant meetups, etc. This worked really well because it gave me something fun to focus on while grinding through all these job channels.
3 weeks later I found a local job using some of the technologies I was excited about (Clojure, ClojureScript and Datomic!) and I'm working there now. The market is nuts.
Everything you do is magnified, good and bad.
Right now lots of people do this manually.
Maybe computers can do it better.
If computers can do it better, maybe people could focus on writing new laws and refactoring old ones instead of repeatedly interpreting old laws for each case.