‘Early gravity mapping efforts in the 1960s revealed that the Hudson Bay area in particular exerts a weaker gravitational force. Since less mass equals less gravity, there must be less mass underneath these areas.’ informed!
Interesting product line — I didn’t know this existed, but it makes good sense as a “network flight recorder”. Big in finance.
SolarCapture is powerful packet capture product family that can transform every server into a precision network monitoring device, increasing network visibility, network instrumentation, and performance analysis. SolarCapture products optimize network monitoring and security, while eliminating the need for specialized appliances, expensive adapters relying on exotic protocols, proprietary hardware, and dedicated networking equipment.See also Corvil (based in Dublin!): ‘I’m using a Corvil at the moment and it’s awesome- nanosecond precision latency measurements on the wire.’ (via mechanical sympathy list)
This is a phenomenally useful ML/data-mining resource post — ‘the top 10 most influential data mining algorithms as voted on by 3 separate panels in [ICDM ’06’s] survey paper’, but with a nice clear intro and description for each one. Here’s the algorithms covered:
1. C4.5 2. k-means 3. Support vector machines 4. Apriori 5. EM 6. PageRank 7. AdaBoost 8. kNN 9. Naive Bayes 10. CART
g’wan the Colm!
a fuzzy matching library. Given a byte stream with a minimum length of 512 bytes, TLSH generates a hash value which can be used for similarity comparisons. Similar objects will have similar hash values which allows for the detection of similar objects by comparing their hash values. Note that the byte stream should have a sufficient amount of complexity. For example, a byte stream of identical bytes will not generate a hash value.Paper here: https://drive.google.com/file/d/0B6FS3SVQ1i0GTXk5eDl3Y29QWlk/edit via adulau
What is the relationship between Kubernetes, Borg and Omega (the two internal resource-orchestration systems Google has built)? I would say, kind of by definition, there’s no shared code but there are shared people. You can think of Kubernetes?—?especially some of the elements around pods and labels?—?as being lessons learned from Borg and Omega that are, frankly, significantly better in Kubernetes. There are things that are going to end up being the same as Borg?—?like the way we use IP addresses is very similar?—?but other things, like labels, are actually much better than what we did internally. I would say that’s a lesson we learned the hard way.