Template:M intro technology pattern matching: Difference between revisions
Amwelladmin (talk | contribs) No edit summary Tags: Mobile edit Mobile web edit |
Amwelladmin (talk | contribs) No edit summary |
||
| Line 1: | Line 1: | ||
{{quote| | {{quote| | ||
{{sbf on bayesian priors}} | |||
}} | |||
Pattern matching is checking a given set of data for the presence of the constituents of a given pattern. This is the principle behind large language models that drive generative AI. [[Pattern matching]] involves doing a huge number of not especially sophisticated operations as quickly as possible over as much data as possible. The reason Nvidia graphics chips are so successful is that they are set up for many simple parallel operations, where CPU chips are geared to make complicated sophisticated calculations ''in series''. | Pattern matching is checking a given set of data for the presence of the constituents of a given pattern. This is the principle behind large language models that drive generative AI. [[Pattern matching]] involves doing a huge number of not especially sophisticated operations as quickly as possible over as much data as possible. The reason Nvidia graphics chips are so successful is that they are set up for many simple parallel operations, where CPU chips are geared to make complicated sophisticated calculations ''in series''. | ||
A characteristic of either is the one-way interaction | A characteristic of either is the one-way interaction | ||
Latest revision as of 19:58, 18 October 2023
I could go on and on about the failings of Shakespeare ... but really I shouldn’t need to: the Bayesian priors are pretty damning. About half of the people born since 1600 have been born in the past 100 years, but it gets much worse than that. When Shakespeare wrote, almost all of Europeans were busy farming, and very few people attended university; few people were even literate—probably as low as about ten million people. By contrast, there are now upwards of a billion literate people in the Western sphere. What are the odds that the greatest writer would have been born in 1564?
- —Chauncey Gardiner’s “sophomore college blog”, quoted in Michael Lewis’ Going Infinite
Pattern matching is checking a given set of data for the presence of the constituents of a given pattern. This is the principle behind large language models that drive generative AI. Pattern matching involves doing a huge number of not especially sophisticated operations as quickly as possible over as much data as possible. The reason Nvidia graphics chips are so successful is that they are set up for many simple parallel operations, where CPU chips are geared to make complicated sophisticated calculations in series.
A characteristic of either is the one-way interaction