AI, ML, Data Collection and Use, and the Underlying Ethics with Balázs Kis, Co-CEO at memoQ memoQ talks

We talk about both the upsides and downsides of AI, particularly when it comes to its tangible impact on the environment and argue that if a job can be done using less compute-intensive (and environmentally unfriendly) resources, we should use them, providing several examples of how memoQ approaches this issue. We talk about the history of translation memories, machine translation, some hidden (and not so hidden) gems in memoQ, favorite movies and impactful books.

Timecode:

00:00:20 - Intro
00:02:47 - What makes memoQ special (how did memoQ come to be)
00:06:49 - Balazs and his background in book publication
00:08:25 - Atlas of AI, book by Kate Crawford
00:09:38 - Computational intensity of AI, its impact on the environment
00:13:00 - The ALPAC Report and machine translation
00:17:03 - Are we using more resources than we need
00:20:47 - The four components of AI
00:24:22 - Summa Technologiae
00:27:52 - Where is memoQ using AI and ML
00:33:33 - The big difference between statistical machine translation and neural machine translation
00:35:21 - The environmental impact of data centers
00:40:30 - Why do we refer to neural networks as a black box
00:43:59 - The Match Patch feature and the history of the translation memory technology
00:49:30 - The new kind of translation memory: TM+
00:53:22 - The technology that translators do not like talking about
00:59:05 - Do you see the future where machine translation is the only translation we use
01:03:10 - Privacy
01:04:23 - The main rule of GDPR in one sentence
01:06:40 - The challenges regarding data security when you are a cloud provider
01:11:24 - Do you have a favorite Sci-Fi movie

Links:

Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence: https://www.amazon.com/Atlas-AI-Kate-Crawford/dp/0300209576
The ALPAC Report: https://en.wikipedia.org/wiki/ALPAC
https://nap.nationalacademies.org/resource/alpac_lm/ARC000005.pdf
Balazs' first computer, ZX81: https://en.wikipedia.org/wiki/ZX81
Datasheets for Datasets: https://www.microsoft.com/en-us/research/uploads/prod/2019/01/1803.09010.pdf
Summa Technologiae: https://en.wikipedia.org/wiki/Summa_Technologiae
Neural networks: https://www.ibm.com/cloud/learn/neural-networks

Movies and TV series:

The Andromeda Strain: https://en.wikipedia.org/wiki/The_Andromeda_Strain_(film)
Annihilation: https://en.wikipedia.org/wiki/Annihilation_(film)
Alien: https://en.wikipedia.org/wiki/Alien_(film)
Dark: https://en.wikipedia.org/wiki/Dark_(TV_series)

Useful blog posts or ebooks by memoQ:

Machine Translation: The Complete Guide: https://blog.memoq.com/machine-translation-the-complete-guide
Post-editing Machine Translation (PEMT): Four Things to Know: https://blog.memoq.com/post-editing-machine-translation-pemt-four-things-to-know
Machine Translation vs. Machine Translation Post-editing: Which One to Use and When?: https://blog.memoq.com/machine-translation-vs.-machine-translation-post-editing-which-one-to-use-and-when
The Future of Machine Translation: Where are we Headed?: https://blog.memoq.com/the-future-of-machine-translation-where-are-we-headed
How to Choose a Machine Translation Engine: https://blog.memoq.com/how-to-choose-a-machine-translation-engine