TalkML Podcast TalkML

Hello Listeners :)

This is our second podcast where we take an interesting topic - in this case “Data sharing and privacy online” - and provide as many interesting technical and non-technical details to you - our audience.

Please find links below that we refer to in our podcast.

- Elon’s Interview: https://www.youtube.com/watch?v=Mwe2ABPkZLU
- Sign up / login with Apple ID : https://developer.apple.com/design/human-interface-guidelines/sign-in-with-apple/overview/introduction/
- AdGuard Pro Signup : https://aff.adguard.com/?ref=atpdxb (Works with iOS, Android, Mac OS and Windows. We’ve our DNS filters turned on + other local ad blockers
- AI miss identify African American Women 10 to 1: https://www.wired.com/story/best-algorithms-struggle-recognize-black-faces-equally/
- Google Map Traffic Data: https://medium.com/@imtechpros_87395/where-does-google-maps-get-its-traffic-data-from-2562f984d82f#:~:text=The%20Answer%20Is%20Very%20Simple,picture%20of%20live%20traffic%20conditions.
- How Yelp Works: https://computer.howstuffworks.com/internet/social-networking/networks/yelp.htm
- Check Google’s Privacy Setting: https://myaccount.google.com/privacycheckup
- Check Facebook’s Privacy Setting: https://www.facebook.com/privacy/checkup/?source=settings_and_privacy
- Read more about GDPR: https://www.csoonline.com/article/3202771/general-data-protection-regulation-gdpr-requirements-deadlines-and-facts.html
- You are the product:
GFI: https://techtalk.gfi.com/if-its-free-youre-probably-the-product/
Tim O’Reily: https://twitter.com/timoreilly/status/22823381903
YouTube TV Ads: https://www.youtube.com/watch?v=LvZYwaQlJsg

Hello Listeners :)

This is our first podcast where we take an interesting topic - in this case “Fake News” - and provide as many interesting technical and non-technical details to you - our audience.

In this podcast, we discuss Fake News and how it can be defined. The fundamentals of fake news and how it spreads like wildfire using the same infrastructure and rails as standard / normal news. It is important to understand these concepts from a ‘norm’, ‘biased feedback loop’ and ‘machine-learning’ perspective as these are foundations to how fake news perpetuates.

Aside from the physical infrastructure, we touch upon tech companies (such as the FANG) role to formulate different users into clusters. And a learning algorithm would take over and learn the user behavior in a supervised manner.

We also define Deep Fakes and its repercussions to our culture and society at large. Deep Fake, like all emerging technologies, has its flaws too. We can recognize / discern that a video is a deep fake by looking at some clues e.g. eye blinks, facial features contours etc.

Fake News Generation and Detection

https://github.com/rowanz/grover

Deep-Fake Links


https://arxiv.org/pdf/2005.05535v4.pdf
https://arxiv.org/pdf/1909.12962v4.pdf
https://arxiv.org/abs/1406.2661
https://github.com/deepfakes

Try it yourself:

shorturl.at/bBRT1

Acronyms and Abbreviations

FANG: Facebook, Amazon, Netflix, and Alphabet

Creators

Stefan: https://www.linkedin.com/in/stefan-juang-93b63998/

Abhishek: https://www.linkedin.com/in/aparyani/