In short, most of the language-centric conferences I’ve been to in the past were about “hey look at what I did with this library or weird corner of the language”, though the most recent Ruby/Rails conference are more varied than this. By comparison, Strange Loop was more about “I did this thing that I’m excited about and its a little brainy but not intimidating and also I’m really excited about it.”
Elm Conf 2017
I started the weekend off checking out the Elm community. I already think pretty highly of the language. I would certainly use it for a green-field project.
Size, excitement, and employment-wise, Elm is about where Ruby was when I joined the community in 2005. Lots of excited folks, a smattering of employed folks, and a good technical/social setup for growth.
It’s also exciting that Elm is already more diverse than Ruby was at the same point in its growth/inflection curve. Fewer dudes, more beginners, and none of the “pure Ruby” sort of condescension towards Rails and web development.
- “Teaching Elm to Beginners” (no talk video), Richard Feldman. Using Elm at work requires teaching Elm to beginners. Teaching is a totally different skill set, disjoint from programming. When answering a question, introduce as few new concepts as possible. Find the most direct path to helping someone understand. It’s unimportant to be precise, include lots of details, or being entertaining when teaching. You can avoid types and still help students build a substantial Elm program.
- If Coco Chanel Reviewed Elm, Tereza Sokol: Elm as seen through the lens of high and low fashion. Elm is a carefully curated, slow releasing collection of parts ala Coco Chanel. It is not the hectic variety of an H&M store.
- Accessibility with Elm, Tessa Kelly: Make accessible applications by enforcing view/DOM helpers with functional encapsulation and types. Your program won’t compile if you forget an accessibility annotation. A pretty good idea!
- Mogee, or how we fit Elm in a 64×64 grid”, Andrew Kuzmin: A postmortem on building games with Elm. Key insight: work on the game, not on the code or engine. Don’t frivolously polish code. Use entity-component-system modeling. Build sprite/bitmap graphics in WebGL by making one pixel out of two triangles.
The majority of the talks referenced Elm creator Evan Czaplicki’s approach to designing APIs. He is humble enough that I don’t think this will backlash like it did with DHH’s opinions did with Rails.
By far the biggest corporate footprint in the community and talks was NoRedInk. Nearly half of the talks were by someone at the company.
Most practical talks from StrangeLoop
Types for Ruby: it seems like they’ve implemented a full-blown type system for Ruby. It’s got all the gizmos and gadgets you might expect: unions, generics, gradual typing. It applies all its checks at runtime though, and they didn’t say if it does exhaustive checking, so I’m not sure how handy it would be in the way that e.g. Elm or Flow are. On my list of things to check out later.
Level up your concurrency skills with Rust. Learning Rust’s concepts for memory and concurrency safety, i.e. resources, ownerships, and lifetimes, can help you program in any language. Putting concurrency into a system is refactoring for out-of-orderness and most likely a retrofit of the underlying structure. Rust models memory like a resource, ala file handles or network sockets are modeled by the operating system. Rust resource borrowing in summary: if you can read it, no one else can write it; if you can write it, no one else can read or write it; borrows are checked at compile time so there is no runtime overhead/cost.
GPGPU programming with Metal. Your processor core has a medium sized arithmetic logic unit and a giant control unit (plus as much memory/cache as they can spare). A GPU is thousands of arithmetic logic units. Besides drawing amazing pictures, you can use all those arithmetic logic units to train/implement a neural network, do machine vision or image processing, run machine learning algorithms, and any kind of linear algebra or vector calculus. Work is sent to the GPU by loading data/state into buffers, converting math instructions to GPU code and load that into GPU buffers, and then let the GPU go wild executing it.
Seeking a better culture and organization of open source maintainership (no talk video). Projects are getting smaller, more fragmented, and attracting no community (ed. the unintended consequence of extreme modularity?) Bitcoin and Ethereum have very little backing despite the astronomical amounts of money in the ecosystem. We need a new perspective on funding open source work. Consumption of open source has won, but production of open source is still in a pretty bad place.
How to be a compiler. Knitting is programming; you can even compile between knitting description pseudo-languages. Implemented Design by Numbers, a Processing predecessor, as transpiler to SVG.
Random cool things people are really doing
Measuring and optimizing tail latency. Activating instrumentation and “slow-path” techniques on live web requests that run so long they will fall into the 99th percentile. Switch processor voltage to “power up” a processor that’s running a slow request so it will finish faster, e.g. switch a core from low power/500MHz mode to high power/2GHz mode.
Facebook stopped using datacenter routers and started building their own servers that program the networking chips a router would use from CentOS, basically giving them programmable routers that deploy like you would update infrastructure like Nginx or memcached. I wonder when/if treating network devices as software will scale down to your typical large company?
Strange Loop takeaways
- a conference of diverse backgrounds and experiences is a better one
- my favorite talks told a hero’s journey story through illustrations
- folks in this sphere of technology are taking privacy and security very seriously, but the politics of code, e.g. user safety and information war, were not particularly up there in the talks I went to (probably by self-selection)
- way more people are doing machine learning applications than I’d realized; someone said off-hand that we’d “emerged from the AI winter in 2012” and that struck me as pretty accurate
- everyone gets the impostor syndrome, even conference speakers and wildly successful special effects and TV personalities like Adam Savage
If you get the chance, you should go to Strange Loop!