Facebook has open sourced their PyTorch based Natural Language Processing modeling framework. According to them it: πŸ‘‡

blurs the boundaries between experimentation and large-scale deployment.

Looking forward to trying this out. πŸ€“

Src: Facebook

DeepFakes Get More Realistic πŸ˜–

Remember back when I said I was terrified about deepfakes? Well, it’s not getting any better. 😟

Apparently researchers at Carnegie Mellon and Facebook’s Reality Lab decided there is nothing to worry about and the method for making them needed to be better. So they give us Recycle-GAN. ♻️

We introduce a data-driven approach for unsupervised video retargeting that translates content from one domain to another while preserving the style native to a domain, i.e., if contents of John Oliver’s speech were to be transferred to Stephen Colbert, then the generated content/speech should be in Stephen Colbert’s style.

Fantastic. Just what we need. A system that transfers content while maintaining stylistic integrity all while not needing a great deal of tweaking/input to make it happen. 😡

Also, why is Facebook helping to make fake content easier to create? Don’t they have enough problems on this front already? πŸ€”

Src: Carnegie Mellon

Facebook Can Read Photos πŸ–ΌοΈ

Big Blue has rolled out a tool called Rosetta that can scan photos for text, extract the text it finds, and then “understand” that text. πŸ‘οΈβ€πŸ—¨οΈ

This is huge as it means the platform can now increase accessibility by reading photos, it can pull out information from photos of menus and street signs, and it can monitor memes and images for destructive written content. And those are just a few examples I’m sure. ♾️

Personally, I’m interested to see how this impacts Facebook’s text content in ad image guidelines. It used to reject any ad that contained more than 20% text based on image size (but used a weird grid-based measuring system). Then it moved to an approach where the more text your image contain the narrower it’s delivery/reach. Facebook’s reason was always that “users preferred images with little to no text”, but I always figured it was more about their inability to automate filtering for content. Users don’t appear to have any issues with text overlays when it comes to organic content. πŸ–ΌοΈ

Their post has a bunch of technical details if you want to nerd out. πŸ€“

Src: Facebook

Facebook Spreads the Chips Around πŸ’«

It appears that Facebook is forgoing developing their own chips in favor of partnering with multiple top chip makers to add in their Glow machine learning accelerator. 🏎

It’ll be interesting to compare this approach to the other tech players looking to make their own. But this play makes sense. It follows Big Blue’s approach with prior software, doesn’t split their focus, and they also don’t have public-facing hardware offerings like Google (cloud) or Apple (duh). βš–οΈ

Also, Facebook showed off a new AI tool that uncovers bugs in code. That could be pretty nifty. 🐞

Src: TechCrunch

The Big 4 vs. The World 🌎

I mentioned in yesterday’s post that there is a much higher demand for AI talent than there is supply. No surprise, but the answer for a lot of firms appears to be buying AI startups to help infuse talent. πŸ’Έ

Even less of a surprise, Google, Apple, Facebook, and Amazon are leading the way when it comes to quantity of acquisitions. The mind blowing part is that there were 115 acquisitions last year! 😱

AI acquisition graph from CB Insights

Src: CB Insights

Facebook Chips in on Live Video

I’m starting to get obsessed with watching who is making a chip for what AI purpose these days.

Facebook has announced they’re designing a chip to help with analysis and filtering of live-streaming video. Why? Two reasons:

  1. To minimize reliance on outside suppliers (here’s looking at you Intel)
  2. To avoid the embarrassing mistake of letting someone livestream their suicide or orgy (or something else equally against their TOS or that generally harshes their chill)

Microsoft made the tech world all about that software back in the day with Windows. Now it seems like the pendulum is swinging back towards hardware. And the cycle continues.

Src: Bloomberg