6 min Read
History has shown that it’s impossible to scale up anything significantly & sustainably – without an underlying structure or framework. So who built this new AI framework?
Here are the two unconnected, major technology developments which were initiated around the year 2000:
NVIDIA unknowingly laid the foundation of the hardware AI stack, when it launched GeForce256 – a single-chip Graphics Processing Unit (GPU) which targeted the PC gaming industry. This was the first chip of its GeForce series.
NVIDIA’s GPU was a new category of processors with
* Parallel architecture to concurrently process multiple tasks.
* Handle thousands of simultaneous mathematical calculations.
* Manage multiplication of multi-dimension matrices.
Perfect for AI.
But NVIDIA did not stop there. Seeing the future, it launched CUDA – its free programming platform for data scientists for complex mathematical simulations & processing large data sets using its super-powerful GPUs. (CUDA stands for Compute Unified Device Architecture.)
That’s why most modern AI software is practically hardwired to run best on Nvidia chips!
(Two decades prior, in 1978 we saw the launch of the Intel 8086 chip, which became the building block of the personal computing revolution that followed.)
(Some of you may still remember the DotCom crash & the overhyped Y2K bug!)
Vector & Graph Databases btw, are used today for large scale similar words search & for traversing today’s massive social network data!
IT Systems rely on an invisible backend, which is a part of the overall tech stack. This traditionally comprises of 2 major components:
So what is the backend on which the prolific AI Platforms rely?
The above is just a quick understanding of how conventional IT has been transformed for AI. For the classic IT enthusiast, it would be reassuring to note that the core concept of back end database management is still the underpinning layer, with new models which manage the more complex queries on the humongous sets of loosely-structured data with a huge number of primary keys.
Also, it should be amply clear that we the people should be ready to embrace AI as a part of our lives & businesses – just like we adapted to the software/PC boom in the 1980s & 1990s.
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