These concrete descriptions at a granular level reflect how one might think about solving problems with edge computing and how it reflects large scale data analytics. Could also get the sense of the research behind it with the examples which included a mention of probability distributions involved with hashing the data.
@quonxinquonyi8570 Жыл бұрын
There is a Cornell professor video lectures series on KZbin about this edge computing and analytics of tiny ml problem...mit Hana lab also have that course on youtube...for architecture part of these edge devices,plz type” computer architecture for ai “ or CA4AI on search bar...hope these three will be enough for fundamental building for tiny machine learning
@olaoye93973 жыл бұрын
intelligent concepts on data fabric
@MM-lo9jy Жыл бұрын
There are just 30+ years old...
@MM-lo9jy Жыл бұрын
Absolutely stupid! This guy decided to call Data Warehouse and Data Lakes as Data Fabric and made a presentation about DW/DL replacing the term by Data Fabric... IT is pathetic!
@quonxinquonyi8570 Жыл бұрын
Second that...every one nowadays is coining hipsters marketing term, creating fake value on redundant Stuff...absolutely bore off being a capitalist...dao, decentralized finance, data mesh,data fabric blah blah blah...blockchain is a real deal which is based on that hard long encryption, so is machine learning and deep learning which must bring revolution in user experience but rest are just plain stupid redundancies that created a bubble of three trillion which is now on the way of bursting up
@fe007002 жыл бұрын
Guys, how is the silent data corruption handled on the end nodes? How is the data consistency maintained during data transfers across data centers?
@MM-lo9jy Жыл бұрын
Same way as in any DW... data integrity rules + reconciliation routines..