one_electron

genuine question (asking because i have a biased perspective): why dont you consider advances in ai to be a major shift? in the past decade, there has been a rapid increase in capabilities in computer vision, language understanding, robotics, etc.

a complementary reading piece should be sutton's "the bitter lesson", which more or less argues that ai methods/techniques that "leverage computation are ultimately the most effective, and by a large margin."

[0] http://www.incompleteideas.net/IncIdeas/BitterLesson.html

i suspect the same. we saw the same exact behavior last year from amazon around minimum wages (https://techcrunch.com/2019/04/11/amazon-ceo-jeff-bezos-chal...)

i dont have any inside insight but id be surprised if thats the case. goodfellow's line of research has been adversarial learning [1].

[1] https://scholar.google.ca/citations?hl=en&user=iYN86KEAAAAJ&...

"easy to copy" isn't really a factor here tbh, seeing how tiktok (along with vine, snap, facebook, etc) is a classic example of network effects.

another one!

berkeley rise lab is such a powerhouse - spark, mesos, etc. just in the past few years. it really puts some of these big tech companies to shame.

it did! an entire generation of MBAs learned from jack welch, who popularized be #1 in anything you compete in (and if not, exit).

for those interested in management fads, https://www.investors.com/news/management/leaders-and-succes...

in my experience, most people dismiss cyc as a failed science experiment. this shouldnt be! after all, many important deep learning concepts have their roots in the 80s, and it is possible that cyc could be revived too.

same here, although i know unity has been staffing up their ml team eg arthur juliani doing good work at unity. more generally speaking, i think there is a clear need for reliable, robust simulators in ml. (openai released a few interesting environments a few years back but adoption seems to have plateaued, from my perspective.)