Throughout the 1990s, I figured that if we want to resist this unsettling trend in the government to outlaw cryptography, one measure we can apply is to use cryptography as much as we can now while it's still legal. When use of strong cryptography becomes popular, it's harder for the government to criminalize it. Therefore, using PGP is good for preserving democracy. If privacy is outlawed, only outlaws will have privacy.
There are a lot of interesting reasons but for the purpose of this article the one I would like to highlight is the baggage of X86 backwards compatibility. For the first time power efficiency became more important to the success of a CPU than speed. All of the transistors and all of the millions of lines of x86 code that Intel and Microsoft had invested in the PC became an obstacle to power efficiency. The most important aspect of Microsoft and Intel’s market hegemony became a liability over night.
Police initially told a different story, and the Cook County grand jury indictment alleges that three officers — David March, Joseph Walsh and Thomas Gaffney — were at the scene of the killing and worked together to conceal crucial facts in the initial police report.
InterPlanetary File System (IPFS) is a protocol designed to create a permanent and decentralized method of storing and sharing files. It is a content-addressable, peer-to-peer hypermedia distribution protocol. Nodes in the IPFS network form a distributed file system. IPFS is an open-source project developed since 2014 by Protocol Labs with help from the open-source community. It was initially designed by Juan Benet.
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between them is based on the likeness of their meaning or semantic content as opposed to similarity which can be estimated regarding their syntactical representation (e.g. their string format). These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving".
Computationally, semantic similarity can be estimated by defining a topological similarity, by using ontologies to define the distance between terms/concepts. For example, a naive metric for the comparison of concepts ordered in a partially ordered set and represented as nodes of a directed acyclic graph (e.g., a taxonomy), would be the shortest-path linking the two concept nodes. Based on text analyses, semantic relatedness between units of language (e.g., words, sentences) can also be estimated using statistical means such as a vector space model to correlate words and textual contexts from a suitable text corpus.
I’ve tried to read a number of AI texts and tutorials. I understand the concepts intuitively. They make perfect sense to me. It’s just that when I see a string of symbols my brain glazes over and I have no idea what I’m reading.
Get the price of any cryptocurrency in any other currency that you need at a given timestamp. The price comes from the daily info - so it would be the price at the end of the day GMT based on the requested TS.
President Obama, in one of his final acts in office in January, commuted her sentence after deciding that she had been punished enough for handing a trove of military and diplomatic reports to the anti-secrecy website WikiLeaks.