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recent bookmarks from jmGeoffrey Hinton/Oppenheimer comparison2023-07-31T17:39:59+00:00
https://twitter.com/blairasaservice/status/1653196500317491200
jm
The keynote speaker at the Royal Society was another Google employee: Geoffrey Hinton, who for decades has been a central figure in developing deep learning. As the conference wound down, I spotted him chatting with Bostrom in the middle of a scrum of researchers. Hinton was saying that he did not expect A.I. to be achieved for decades. “No sooner than 2070,” he said. “I am in the camp that is hopeless.”
“In that you think it will not be a cause for good?” Bostrom asked.
“I think political systems will use it to terrorize people,” Hinton said. Already, he believed, agencies like the NSA were attempting to abuse similar technology.
“Then why are you doing the research?” Bostrom asked.
“I could give you the usual arguments,” Hinton said. “But the truth is that the prospect of discovery is too sweet.” He smiled awkwardly, the word hanging in the air — an echo of Oppenheimer, who famously said of the bomb, “When you see something that is technically sweet, you go ahead and do it, and you argue about what to do about it only after you have had your technical success.”
]]>research science discovery oppenheimer geoffrey-hinton ethics aihttps://pinboard.in/https://pinboard.in/u:jm/b:97822316e794/newrelic/sidecar: Gossip-based service discovery. Docker native, but supports static discovery, too.2017-11-03T13:14:06+00:00
https://github.com/newrelic/sidecar
jmServices communicate to each other through an HAproxy instance on each host that is itself managed and configured by Sidecar. It is inspired by Airbnb's SmartStack. But, we believe it has a few advantages over SmartStack:
Native support for Docker (works without Docker, too!);
No dependence on Zookeeper or other centralized services;
Peer-to-peer, so it works on your laptop or on a large cluster;
Static binary means it's easy to deploy, and there is no interpreter needed;
Tiny memory usage (under 20MB) and few execution threads means its very light weight
]]>clustering docker go service-discovery ap sidecar haproxy discovery architecturehttps://pinboard.in/https://pinboard.in/u:jm/b:03ce2764a357/Rendezvous hashing - Wikipedia, the free encyclopedia2016-04-13T14:01:11+00:00
https://en.m.wikipedia.org/wiki/Rendezvous_hashing
jm
Rendezvous or Highest Random Weight (HRW) hashing[1][2] is an algorithm that allows clients to achieve distributed agreement on a set of k options out of a possible set of n options. A typical application is when clients need to agree on which sites (or proxies) objects are to assigned to. When k is 1, it subsumes the goals of consistent hashing, using an entirely different method.
]]>hrw hashing hashes consistent-hashing rendezvous-hashing algorithms discovery distributed-computinghttps://pinboard.in/https://pinboard.in/u:jm/b:8be4d585c6d4/VividCortex uses K-Means Clustering to discover related metrics2015-03-05T21:50:41+00:00
https://vividcortex.com/blog/2015/03/05/analyzing-related-metrics-with-vividcortex/
jmmetrics k-means-clustering clustering algorithms discovery similarity vividcortex analysis datahttps://pinboard.in/https://pinboard.in/u:jm/b:71d69a91d3df/