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Comment by adamnemecek | Hacker News Reader

"Their vision is that by 2060, a one petaflop computer that would fill half a football field today, will fit on your desktop."

Will it be able to run Crysis?

But seriously, I'd be even more interested in how these computers will be programmed. Any wild speculations?

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Abstraction will be the answer. We will need very, very high level domain specific "programming languages".

Problem is: I feel like we are abstracting software slower than computers are getting faster. Is Javascript really that much more abstract than machine code (assembly)? I think not. In the long run, what we do now are baby steps.

We are still telling computers exactly what to do. Every step needs to be spelled out. And we're doing it by text files...

Think about the huge amount of computing power currently used to run gmail on millions of web browsers, servers, and apps. It could be viewed as one big computer program that just happens to run different parts on different devices. The benefit of separating it into parts is that it gives the program close proximity to different data. A massively parallel system would have to divide data into chunks that are separated by latency and bandwidth limitations in a similar way. The language abstractions are less important than the unavoidable physical limitations. Surely the event driven approach of Javascript is a good solution to this latency problem?

And yet, there are so many layers of abstraction under everything that it all still feels no faster than it all di in the late 90's...

We don't need to develop extremely high abstractions yet. Not until all the layers below are optimised.

While domain specific languages are important , i believe most abstraction today happens at the library/tool level. Yes, some of them use text files and exact instruction, but are still high level.

And with machine learning , we don't even spell every step.

Most people will use some hacked-on C extensions. They'll waste most of the performance, but the inner loops will be fast, and this approach will do better on benchmarks (which involve a small amount of heavily-optimized code).

A few will use Haskell/Erlang/etc. and make better use of the performance.

I loved this comment.

I'm pretty sure it's a (half) joke...

Simple answer. Star Trek like. NLP + AI + Data-Flow-Based Programming.

☛ "Computer make a sandwich, with extra cheese!"

• 1:Computer analyses the command, reverse-engineers the receipe on an atomar/molecular level.

• Femto-lasers a nanostructure to the replicator using computer models

• 3D Prints synthetic biomimetic chemical protein and nano-textured (for color) carbohydrates

☛ "Computer make a new sandwich, this time more piquant!"

• Computer this time tries to optimize the taste based on personal data and global taste data

• GOTO: 1

Most of this can be done today already

Brain-machine interface, obvi. That or strong AIs. :)

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