AFAIK, the relinking requirement only applies if you distribute the software to someone.
If you’re running Sidequest entirely on your own infrastructure to orchestrate jobs across your backend, you’re not distributing the software at all, you’re providing a service. The tight coupling does not itself trigger extra obligations. What matters legally is distribution, not architecture.
Edgecase is if you give your software to a customer to run on their own servers (self‑hosted deployment/docker image shipped to customer). In those cases, you would need to allow them to replace Sidequest.js (ie, not obfuscating it away).
Someone more knowledgeable can correct me, if I'm wrong
It appears from initial reading that it must be possible to support pure NLP tasks with this, but there weren't examples for these in the documentation, so I'm not sure. Does it support NLP models?
Ex: Could I have a store of articles and run NLP tasks against it?
Do you have a pdf-only variant for the 12-pack? I looked around and didn't find it, I might have missed it. Hence asking. I don't really need printed version, so don't really want to waste paper.
I have been following your blogs and zines for years now. Keep up the good work and vibes. Peace.
A channel worth subscribing. Matt (and team?) manages successfully to walk the fine line between managing the complexity of the topics they discuss (which are sometimes extremely dense), making it consumable for the population that's interested in science and physics, but doesn't pursue it on a daily basis. At the same time, they don't fall for the trap of dumbing it down to the point where the audience develops misconceptions and starts believing in pseudo scientific claims.
There are some series they sometimes do, which are entertaining to follow. I also enjoy things like Journal club, where they pick a paper and deep dive into it. The audience also participates, in a way, where they pick the questions/comments from the previous video and answer them.
However, it's not all academic either. There are some running jokes etc, which keep the content entertaining, while being informative, a format that I see common in some of the best Youtube channels.
I've loved Sublime for years, and it's always the first software I install on a new machine. I even voted with my pocket by buying a license.
However, since we started using Yarn workspaces (for JS), I've needed to switch to VSCode because its auto-import is just so much better, and it's one of those things that's hard to go back from, once you're used to it. Sublime text already indexes my code for search, which can probably be used for path suggestions / automatic imports without affecting performance too much maybe? I dunno.
I wouldn't mind it being a plugin either (before Yarn workspaces, I'd use FuzzyFilePath plugin which worked pretty well). But native support would mean the performance would be on par with what I've come to expect from Sublime Text :)
I don't know why you were downvoted. I'm the same; I still wear the clothes I got as swags when I was in college a decade ago. I've maybe bought a pair jeans since then, when my older ones didn't fit anymore.
I was able to enjoy TNG from the get go. It's one of the few shows where the stories have any depth. Although I did start watching it when I was in my twenties, so that could have been a factor in being able to pick up on the subtler themes
3. Target to achieve (in your case, it would mean a language that is frequently used in distributed system/data engineering)
Regarding "I find myself going through the crazy articles comparing languages and lose focus and give up.", I hear you. I've been there. Pick two and run with them. Once you start learning a language, stop reading articles on what other languages you can be learning. There is always something better down the corner. That doesn't mean you lose focus and drop whatever you're doing midway. Persevere, and you will prevail.
Finally, my recommendation, based on your requirements would be
1. Python (for data engineering - numpy, scipy, tensorflow, pandas and whatnot)
They most likely have some ML/AI algos in prototype stage (which is all the rage these days) that is processing all the messages, apart from informing their internal analytics as well as weekly analytics emails they send. They have less to gain from sharing message-data with third parties - this would be giving up control of their most precious component.
A marketing-speak filtered out version of this announcement: You will be able to assemble your own docker engine by stripping out components you don't need (that have until now been shipped in a single docker binary) and keeping the ones you do. This is like assembling PCs, for docker.
I think this was mainly intended as an answer to the criticism docker has been receiving (by kubernetes maintainers and others) ever since they decided to ship swarm with docker. I think this move is great as it goes a step further and allows you to swap out build systems, volume mgmnt too. Even though I did not mind docker shipping with swarm, others in the community were, and this shows docker listened, which is great.
I don't know if it's one of the best, but it teaches Docker concepts with a single project, and as you progress through chapters, you will find different ways you can deploy applications using Docker containers.