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And to the extent that it's not reliable, we can describe when we expect it to be unreliable and what the odds are. Someone might argue that this is equivalent to "understanding", but that's your point, I think -- the talk is so vague it can mean whatever you want.
He has this idea that composing simple components is the way to make robust systems and that abstractions over complexity are worthless.Sounds reasonable, but we manage to build reliable chips even though the underlying physical mechanics we abstract over are tremendously complexpic.twitter.com/ESbBbYQKgB
The big productivity boosts have been abstractions that hide but don't eliminate underlying complexity. Gate-level design instead of transistor-level design, RTL instead of schematic capture, synthesis instead of doing raw circuit design, etc.
Later, he says you should just use data structures because they're "simple". Imagining the same idea in EE: no gates, only do layout because it's simpler. Metal, poly, and n/p-wells are "simple", why complicate things with gates? We're EEs, it's all physical layout in the end.pic.twitter.com/uEiZ1CY7Zk
As for software, why have data structures? Memory is actually very simple. There are not a tremendous number of variations in the essential nature of memory. There are locations that contain addresses. There are locations that contain values. There are not a lot of other concep
Even worse, this sounds super reasonable...until you confront the reality that every single component of a system can work (to specification, even!), and the system can still fail! Focusing on "simple" and driving down granularity means more composition, means more system edges!
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