Comment by paulpauper
1 year ago
I think the mythos of the Bell labs and other thinktanks of the Cold War era is overstated to some extent. https://greyenlightenment.com/2024/07/19/the-decline-of-cold...
These organizations employed too many people of relatively mediocre ability relative to output, leading to waste and eventual disbandment. Today's private sector companies in FAMNG+ are making bigger breakthroughs in AI, apps, self-driving cars, etc. with fewer people relative to population and more profits. This is due to more selective hiring and performance metrics. Yeah those people form the 60s were smart, but today's STEM whiz kids are probably lapping them.
I’m hoping this is sarcasm deserving my heart-felt belly laugh. FANG (or whatever the backcronym is these days) “selective hiring” is just puzzle driven mediocrity with a ridiculous amount of elect self-praise at their own good fortune. And “performance metrics”, give me a break - product innovation is in the toilet and product quality even further down the drain. Unless you’re talking about advanced PR and market manipulation techniques to capture and retain ad revenue…definitely genius there.
I agree with the vibes of your comment, but I have to reply to this:
> Unless you’re talking about advanced PR and market manipulation techniques to capture and retain ad revenue
Those very much _are_ the goals at those enterprises.
Indeed they are, but my point is that _these_ goals are hardly admirable. At the same time, the claimed innovations aren’t real, at least in the sense that anything in any issue of the Bell Labs Technical Journal was. “Apps”, etc? This is like giving the Medellín cartel credit for their hippo culture while ignoring the basis of their real success.
Off the top of my head: Shannon, Nyquist, Hamming. Lapping them you say.
I think my reading of your comment is: that's just wrong. And I tend to agree. The current STEM and FAANG activity is second order work in the main. I wouldn't hold AI work up as a paragon, myself. It's diverting from progress across a field.
I have hopes of a resurgence of operations research and linear optimisation as goods in themselves: we could be plotting more nuanced courses in dark waters of competing pressure. Decision systems support across many fields would remove subjective, politicised pressures.
Do you think there is room for a resurgence in linear optimization?
Linear programming, and even integer linear programming are pretty well solved practically speaking.
2 replies →
> making bigger breakthroughs in AI, apps, self-driving cars
Those weren’t really the topics people were interested in at the time (depending on your definition of AI).
The shoulders of giants, as they say.