hi there - i'm a full stack (primarily backend) eng. who is available for part time work. you can email me at jayceekay at gmail. ex spotify if it matters. best to you!
you always have that option though and i assumed it was a fairly common debug thing to have to do if you use docker enough. not just for the times it works (ie you find a bug between the layers) but for all the times it isn't the culprit.
the other post mentioned setup, so i thought he meant they imposed presetup containers for developers to use?
If you do go through with this, you can get quite a bit of competent volunteer work, especially from potential beneficiaries and retired programmers.
Post to HN if this moves forward and you want volunteers / low paid staff - currently I dn't know how you find thsiad volunteers when you are finally ready.
I'll preface this by saying that my time working with it was while I was working at IBM, so feel free to take this with a grain of salt. In my time since I've worked in a few Data/ML and Security positions, so I do have a basis for comparison with other systems.
From what I saw, the actual language-processing part of it was top-tier. It's just it's a hard problem to come up with a demo for that people will actually respond positively to, hence the Jeopardy stint. It has limited real applications. It's really good at what it does but what it does isn't really widely useful.
Nobody wants to see "We're going to replace all our online help / support chat stuff with Watson" because people find those systems frustrating already, even if it would make things vastly better than some of the alternatives.
So you end up with weird stuff like Chef Watson, Doctor Watson, and so on -- things in areas where an ML model isn't going to replace a human anytime soon.
Then Marketing gets involved and suddenly anything that uses any kind of ML needs to have Watson slapped on it, even if it's not doing any language processing.
Welp, you're downplaying IBM too much. IBM got the product direction right earlier than anyone. Watson is a querying system w/ advanced NLP/IR/KRR capability running on dedicated compute chips, and large corps are more or less following this path. It's just that IBM did it too early and used rather old approaches, which doesn't grow well (thus "spaghetti").
Still, Watson is pretty much the only one in its class. There are good alternatives out there that worked well for many people, but they offer only a subset of Watson's feature set. If an organization need some real bang, Watson is the only option.
"What if you simply arrive at the perfect time to every flight, neither too early nor too late?"
Nobody can ever do that, so it's pointless to ask.
(I suppose that if you built your own editor this might be true, but if you have your own plane then you're never early or late to your flight either.)
how to build your knowledge? assuming this is a project for recreation, just build it, it doesn't really matter what you use. both are viable for low traffic sites. the valuable thing is that you're gonna learn the ins and outs of one or the other, especially if/when it starts to get some decent traffic. without knowing the specifics of the forum it's tough to recommend one vs the other, but honestly you should optimize for just getting it done.
