Topic: Machine learning
Inside Facebook’s AI Machine – Backchannel (Feb 23, 2017)
Backchannel (and Steven Levy in particular) seems to be becoming the default outlet (I was going to say channel) for these access-y pieces on AI and machine learning. Levy previously did something very similar for Apple last August, Amazon in November, and Google in October. And there continues to be a perceived need for this kind of thing because AI continues to be something that’s mostly talked about rather than seen by consumers. That’s not to say that it’s not in products – it clearly is, and the money quote from this article is that “Facebook today cannot exist without AI” – but that it’s not intuitively obvious to consumers that AI is behind a lot of what they use. Companies still need to tell their AI stories, particularly because narratives have emerged about Google being ahead or Apple being behind, and those narratives need to be countered. There are several interesting things in this particular article, but as that quote indicates the biggest thing that comes out of it for me is how central AI and machine learning are becoming to almost everything at Facebook. Secondarily, it’s interesting to see Facebook in some cases do complex processing on the phone itself, something Apple has pioneered but which others have largely eschewed in favor of cloud processing.
via Backchannel
Google RAISR Intelligently Makes Low-Res Images High Quality – PCMag.com (Jan 13, 2017)
This is a great example of the practical benefits of machine learning, which is where the focus should be as companies tout their AI/ML credentials. On-stage demos of new capability at the research level are impressive but ultimately meaningless unless they lead to real-world benefits for end users such as this image processing technique which can reduce file sizes by 75%.
via Google RAISR Intelligently Makes Low-Res Images High Quality – PCMag.com
Snapchat Is Beginning to Use Machine Learning to Improve Ad Targeting | Adweek (Dec 30, 2016)
One of the big goals for Snap in the coming months is driving faster revenue growth, which means making the tough transition from a niche spending category to a mainstream one for advertisers. That, in turn, means better tools for selling and measuring the performance of ads. It seems some basic machine learning is at play here, which is an interesting advance from Snap too.
via Snapchat Is Beginning to Use Machine Learning to Improve Ad Targeting | Adweek