Exponentially, We try to map human race advance through maths (eg Neumann-Einstein-Tiring) and win-win engineering visions.
Amongst good engineers it is now agreed that those linking in around Intel's Gordon Moore (law) from 1965 compounded million times more tech (silicon chips) capactity by1995; in itself an unprecdented time of chsange but then two more million fold multipliers linked human intelligence and AI can be every millennial brain's best friend or worst ( biographers of von neumann fad been told to expect 3 million fold waves by 20245 -see eg our 1984 rehearsal of this www.economistdiary.com/1984
LIVING WITH QUiNTiLLION 10**18 Change - HOW/s ThaT?
Today most engineers would vote for Partner Nvidia Jensen Huang as centre of gravity of million fold more deep learning: Intelligences computuing codes and engineering architecture; Many would now rename silicon valley Deep Learning Space
the orther million fold multiplier insed satellites and smart things to mobilise data on natire especially how real people communities networked to data clouds- we hypothesise steve jobs was most influential person on this though technically this inveolved communications stanrd such as 1G to 5G mediated by UN telecoms branch in Geneva. (Please note this is primarily a western rendering; eg 95%of humans live oitside N America something that jobs saw as a deep responsibility in integrating kocal & global)
Neumann Eistetin Turing all died about a decade before Moore's Law started up. However it is these mathematicians and their peers who worked from 1905 on Einstein's discovery E=mcsquared that natures' physic, chemistry, biology etc is not governed by Newton's science which man's science had previously assumed as gospel.. Unfortunately because of workld wars etc you could say 40 years of these maths genii time was wasted on projevts that led to the atom bomb or they saved humanity by making sure allies got nuclear first. All wanted to be providers of brainworkers machines and space-coms delivering a posotive gift to humanity- neumann was their main connector of engineers of this hinal decade though tiring representung the younger generation would have advanced much more if he had not committed suicide.
On foressing the design of brain tools; they advised celebratung win-win trades beyond history's empires and borders; they asked that energy and enginerring genii like they NOT be popularised by national media as most hated and wanted people (as they tjemselves had been); and they expected humanity would advance or risk disappearing depending how you all naviagted quintillino times more tech by 2025 to benefit the millennial generation
Among several pevculiar contexts of moores engineers is even as silicon valley emerged most of the first 1000 fold tech multpliers were primarily usded by japan korea taiwan- these countries developed microelectronics, applied borlaug quality superbly, developed models accelearaing customer benefits, civil enginered supercities linked through sme value networks conneeted by container ships, and bullet trains and advanced underground systems; it was effectively only the second half of moores law that app;ied to what were called personal computers and their networking
From my viewpoint as a diapora scot (but whose ddauhter was born nearly 30 years ago in washingtin DC) one of two miraculos economic advances in my lifetime can be linked to about 20 million people living in taiwan. Over and over they bet their freedom on the manufacturing cinsequences of serving dest engineering designers of chips. Doxcomm was a comany that pioneered this smart manufactiring and From 1987 Maurice Chang freed humanity by launching a chip foundry out of Taiwan.Instead of intel chips appearing in relatively few upgrades, a fooundry designs chips to hubderds of customer specifications. It was thsi freedom which jensen huang conneted when he and his peers inclyding hundreds of engineers who have now soent over 20 years on their lifes work around him, decided that it was possible to improve computing design from ibm 1963 linear central computing to all sorts of asynchronousd analyses and real time inputs
Of course there are many more exciting stories of who engineered what good usually with open source paradigms von neumann had recomended and who tried to capture markets with systems closed (failing) to accelerating greater human capabi,ities at speed o deep learning -
welcome to delectuing what humanly well engineered/artificial intel now demands
Chris AI Macrae MA DAMTP CantabAuthor