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Oldest comments (123)
Blockchain!!!!
It's like almost no one really understood that you don't need blockchain if you have a trusted network, which most companies do. So they are basically implementing distributed databases which they probably are already using in some form once we ditched mainframes.
Yeah, Blockchain is only useful when decentralization is of utmost importance. It's great for that though.
Yet, tech like blockchain has amazing potential to reduce corruption and improve governance for countries and municipalities. It's too bad the hype is overshadowing this amazing ability.
I've always wondered why governments don't use it in an online voting system. You could register your IP address up with something that identifies you in the gov database and use it for online voting.
That rings true, but also there is the simple fact that online voting solves a non-existing problem.
Paper based voting is much simpler and works.
If it doesn't work in the US, do it like in the countries where it works, problem solved.
I don't know if I'm interpreting "movement" correctly, but I remember when NoSQL was super-hyped, then we realized that good ol' relational databases were still the best for most of the tasks.
I wasted a lot of time fretting about databases at that point.
8 years of MongoDB development here and I can confidently say that I will never recommend NoSQL for another professional project.
Nowadays, we are putting our JSON into relational databases :D
SCNR
Oh I'm with you. If I ever need to save unstructured data, I would just use JSONB inside of PostGres. Now I'm a type-safety kind of guy, so I'm not sure I ever would do that. But if I found a good use case, PostGres' JSONB is the tech I would use instead of MongoDb.
If you tell nobody, I am using postgres too π
How is the name of that product supposed to be pronounced? Why is there only one S if it is both Postgres and SQL? FWIW I call it Post-GRE-SQL because somehow it seems "graduate level."
Originally the product was called "Postgres" (as Post Ingres, a DB at the time), then they joined the word SQL to make it clear it was a relational DB.
I think "POST-GRES-QL" is the correct one, like if it was "Postgres query language"
After two years of using dynamodb I would gladly slap the team that came up with it. Especially the throttling mechanism
Is it bad?
Depends your traffic profile and pockets. If your traffic follows a nice and constant increase/decrease pattern it's fine. If you have huge sudden spikes like we do...the only option is to turn it to on demand charging ...which is slightly more expensive but you don't have all the problems that come with bursting capacity, throttling and scaling.
It's hard to pick just one! Candidates...
I'd say that Neural Networks and AI/ML have made a huge impact in the large companies that have the expertise to implement them correctly, i.e. Google, Facebook, Amazon. But for the general purpose programmers they haven't at all.
"...Scroll-wheel hijacking on Javascript websites..."
One of those things we should have asked 'just because we can, should we?'
Apropos to the last twenty years of web development, I might add.
And people mock me for creating content-oriented sites without all the bells and whistles. "You should make it modern-looking."
criticism >> /dev/nullBLOCKCHAIN!
These ones I would say:
They all have the potential to be great but I fell like they are all really early in their development and a lot of people are just throwing it at problems where they really don't fit.
Also Scrum...
Scrum is one of them things that works amazingly... but only if done really well.
Which means it's a terrible idea for a team organisation process.
You can't base your organisation on everyone performing the process to perfection all the time, you have to account for the fact that humans are performing it.
The best process is one that always produces the desired result regardless of the proficiency with which you execute it.
But do you think such a process exists? I feel that as soon as you add the human factor you also need to have a more human approach to team organization.
That's why it's best to focus on the Agile values instead of the processes.
Agree. I just feel that management tend to just throw it in to a project as the silver bullet and then wonder why all of these sprint planning meeting haven't gotten us to write more code.
Blockchain, sure. Scrum... arguably, I guess, though I still use it. I disagree about IoT; afaik it's still huge, and more and more smart home devices are being produced every year and seem to be doing well (though I haven't done market research or anything).
But seriously, machine learning? The biggest, most successful field of AI research and development of the last like 50 years? I can't agree there. ML is powering every major search engine, it's used for photo and video analysis for all sorts of applications from social media to law enforcement and government intelligence, it's used for every sort of mass data analysis from advertising to stock markets to demographics research, and it's invaluable to the hard sciences where quickly identifying trends in huge datasets (think about trying to manually examine astronomical datasets, the output from Large Hadron Collider experiements, or even animal migration patterns with hundreds of thousands of data points).
I'm really not trying to be a jerk and go all "someone is wrong on the internet" or anything, I'm honestly very curious: what do you see as the failures of machine learning? Sure, there have been misfires and misapplications, just like any tech, but my god, it's been absolutely exploding as a field of both CS research and practical application for literally half a century
I thought scrum was an agile thing. Is it a software?
It's sort of a movement in, but not exclusive to, the software industry
I might interpreting over-hyped in a different way than you are then. By over-hyped I don't really mean that something is bad. Machine Learning is awesome and has solved a lot of problems that were previously, dare i say, unsolvable.
What I mean with over-hyped is that it, in many ways, have started to be used as a buzzword. It is a thing that startups instantly put in their sales pitch even though they might use it in the smallest and least significant part of their actual service. Even worse is when ML is crammed in to a project that doesn't really warrant for it. Working for an agency I have even had clients saying "We want to solve this using machine learning" when there are solutions that would have done the work better.
This of course does not mean that machine learning is bad or has failed. It just means that it is hyped and sometimes misunderstood by a lot of people working in the industry.
What I am saying is not
"over-hyped = Bad"
but rather
"over-hyped = People sometimes use it only because there is hype around it".
Oh I totally agree with the first impretation though. I think Machine Learning is absolutely terrible. Even if we solve the issues around climate change, AI research will inevitable bring the end of humanity and needs to be stopped.
Do you mean because of strong AI and the rise of the machines, or privacy concerns, or something else? I probably agree with all of your concerns at least somewhat, but even if we avoid the research heading in those directions, ML is still fundamentally important. ML is a very field that covers everything from data compression algorithms to cyber security to, as I mentioned, interpretation of scientific datasets. We would honestly never have progressed past the tech of the 70s without ML
Yeah scrum, the management at scale π
For web-dev it was Meteor. It was supposed to be the next Ruby on Rails.
Meteor was very productive however not having a Postgres Adaptor and only MongoDB I think hurt its adoption significantly.
MongoDB. Also, Coffeescript.
I second Coffeescript π€¦π½ββοΈ
Coffeescript gets a pass for being the transpile gateway drug.
What should a coffeescripter (like me?) graduate to? Clojure?
Typescript, probably. Like CoffeeScript, Typescript is pretty much just normal Javascript, with some extra goodies. Clojure is a completely new paradigm of programming (Lisp), and won't be as easy of a transition.
I liked Coffeescript :(
Blockchain: the world's least-efficient linked list!
React
True, React is great but not THAT great.
Can you expand? I feel like it's one of the greatest successes in the last decade of development.
I think it depends on how much you like HG and SVN.
Two that people still use to sell projects but aren't as shinny as the hype made them look:
Without starting a rant βthere's a lot of articles taking both sidesβ over agile, is one really over-turbo-hyped things.
And the case for big Data is that everyone started saying "we have a big data solution" and eventually all the big data solutions turned out to be simply dashboards reading simple databases, most of them with simple query generators
What is the difference between "big data" and "data mining"? Or is it just the same thing rebranded?
Big data is about handling lots of data, it's about volume. Data mining is about finding data, it's about source.
BLOCKCHAIN!
During my AI module at uni a while back, my lecturer (a leading AI researcher) basically said that the huge wave in AI/ML success is basically running AI/ML theories from the AI boom in the 60's and 70's. Now we have the easy access to data and processing power to actually get somewhere with it.
New approaches to AI/ML are rare and tools like TensorFlow basically slow actual innovation.
Can confirm.
AFAIK the new stuff is 'just' practical stuff about what structures work better for tasks, and way too expensive for most companies.
Most of the industry still neglects data bias, one of the first things I learned about AI, with urban legends about soviet tanks and sunshine going back to the early days of AI...
Front end frameworks! Angular, React, Vue. All of them work pretty same except few differences here and there. Still there's lot of hype around those and it's way too much I would say.
"Write once, run anywhere" for Java
XML as the universal interchange format (we're still dealing with CSV :D)
I'll take "Over-hyped Technologies From The 1990's" for $100, Alex. ;-)
+1 for XML. JSON ate it for breakfast.
But I don't understand: Java fulfilled that promise? Java has been the Top or 2nd Top Language for 15 years1
On top of that, the JVM allows programmers to target the JVM instead of worrying about Operating Systems.
"Write once, run anywhere" wasn't about popularity, it was about writing the code once and running it literally anywhere.
They created JVMs for basically anything (from personal computers to washing machines), but there was obviously a fault in that logic: virtual machines don't completely isolate you from the operating system.
Also remember not all JVM implementations were the same (I'm not sure about the current state).
See also what happened on the client side with Java applets or well... do you remember Java Mobile Edition?
That's why that slogan was "over promising and under delivering" :)
Java and JVM as you said reached immense popularity, but the title of the thread is about "over hyped software movement" and I think this one deserves to be here.
I wonder if WebAssembly will be the "write once, run anywhere" promise fulfilled of the 2020s or if in a few years it will be mentioned in another thread like this :D
Only if you're doing relatively simple stuff and don't need amazing performance. The VFS layer in particular still shows a lot of the underlying OS behaviors.
That's why Docker was created, we do not need Java anymore