After getting good feedback on yesterday's thread on #routemobile I think it is logical to do a bit in-depth technical study. Place #twilio at center, keep #routemobile & #tanla at the periphery & see who is each placed.
So I have been studying this entire communication layer as its relevance is ever growing with more devices coming online, staying connected, and relying on real-time communication. Not that this domain under penetrated, but there is a change underway.
— Ameya (@Finstor85) February 10, 2021
#routemobile too offer APIs for SMS & Voice for global platforms (https://t.co/XP9ImVWWlf)
#tanla on other hand offer it via Karix & only does for SMS. Nothing more
More from Ameya
20% more and this position will be 3x. Selan & CPCL hedging the core beautifully. Spot in advance! Covid accelerated IT, EU Energy crisis accelerating Selan/CPCL.
Almost every 6 year, Chennai Petro falls to 80 odd level, rises to 460-480 and falls again to touch same level. It happened in 2009, happened in 2015, 2020 it just reversed from 80 and result also to assist!! Can we see cycle playing out again?
— Ameya (@Finstor85) July 25, 2020
More from Tech
Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
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.