The 2018 State of JavaScript survey is out. They got 20,000 responses and have some delicious, delicious data. I'mma thread in some highlights:
React 65% (vs. 60%)
Vue 29% (vs. 24%)
Ember 5% (vs 4%, I was expecting a bigger rise)
But there's a shocker in here: Angular.
- 58% (if you include those who don't want to use it again)
- 24% (if you count only those who like it)
Since npm's question didn't ask if they intend to *continue* using it I think that might explain this.
Maybe: lots of people in 2017 wanted to try Angular, tried it, and almost none of them liked it.
Or maybe: new users are still liking it but old users are churning out?
- Next.js has an enormous "want to learn" pool, great sign for them
- 62% of Meteor users and 72% of Sails users would not use them again, ouch
We need to stop calling Express a framework, it's too big. It's bedrock.
More from Tech
On Wednesday, The New York Times published a blockbuster report on the failures of Facebook’s management team during the past three years. It's.... not flattering, to say the least. Here are six follow-up questions that merit more investigation. 1/
1) During the past year, most of the anger at Facebook has been directed at Mark Zuckerberg. The question now is whether Sheryl Sandberg, the executive charged with solving Facebook’s hardest problems, has caused a few too many of her own. 2/ https://t.co/DTsc3g0hQf
2) One of the juiciest sentences in @nytimes’ piece involves a research group called Definers Public Affairs, which Facebook hired to look into the funding of the company’s opposition. What other tech company was paying Definers to smear Apple? 3/ https://t.co/DTsc3g0hQf
3) The leadership of the Democratic Party has, generally, supported Facebook over the years. But as public opinion turns against the company, prominent Democrats have started to turn, too. What will that relationship look like now? 4/
4) According to the @nytimes, Facebook worked to paint its critics as anti-Semitic, while simultaneously working to spread the idea that George Soros was supporting its critics—a classic tactic of anti-Semitic conspiracy theorists. What exactly were they trying to do there? 5/
1) During the past year, most of the anger at Facebook has been directed at Mark Zuckerberg. The question now is whether Sheryl Sandberg, the executive charged with solving Facebook’s hardest problems, has caused a few too many of her own. 2/ https://t.co/DTsc3g0hQf
2) One of the juiciest sentences in @nytimes’ piece involves a research group called Definers Public Affairs, which Facebook hired to look into the funding of the company’s opposition. What other tech company was paying Definers to smear Apple? 3/ https://t.co/DTsc3g0hQf
3) The leadership of the Democratic Party has, generally, supported Facebook over the years. But as public opinion turns against the company, prominent Democrats have started to turn, too. What will that relationship look like now? 4/
4) According to the @nytimes, Facebook worked to paint its critics as anti-Semitic, while simultaneously working to spread the idea that George Soros was supporting its critics—a classic tactic of anti-Semitic conspiracy theorists. What exactly were they trying to do there? 5/
Machine translation can be a wonderful translation tool, but its uses are widely misunderstood.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.