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Later in the game, sure. Who's going to build the early toolset? Who's going to own it? Will their be a FOSS API, or will we be locked in? All of that design i

by s_q_b 10y ago

Later in the game, sure. Who's going to build the early toolset? Who's going to own it? Will their be a FOSS API, or will we be locked in? All of that design infrastructure needs to be built by somebody, and that somebody stands to make a forunate. The tasks you listed are a decent summary of the likely eventual outcome. But: • Who will do the work to create this beautiful API? • Who will create this coprocessor architecture? • Will this theoretical stack be built by Microsoft, Amazon, Google, etcetera, or be FOSS? These questions are completely unanswered, and will affect my users of whatever quantum. When analyzing data, one cannot usually just gloss over the underlying math. All abstractions, by definition, are incomplete. But that's the exciting thing about right now. Most inventions occur when science outruns engineering. When engineering and cutting edge science just about to finally converge, that's when market opportunities are most prevalent.

eslaught 10y ago
How many people/companies did it take to build GPUs? A lot of people, to be sure, but as a fraction of all software engineers, that number is incredibly tiny. The vast majority of software engineers---even if we filter to just the set who have actually used GPUs for a project---only know the high-level APIs (OpenGL for graphics, CuDNN for AI, etc.). Fewer engineers are familiar with the more general-purpose APIs (CUDA, OpenCL, etc.), and even fewer still know any of what goes on underneath those layers. Bottom line: it takes a relatively small community of people to build tools for everyone else to use. People will need to know how to use the highest level of APIs, but most need not understand what goes on underneath that.
- yeukhon 10y ago
  Or a better way to put it in my own opinion: in the early days of any emerging technology, most of the founding members have little clue what to do except the concepts and ideas, so implementing toolsets which can be used on both quantum computers and non-quantum computers will be a learn-on-job work for most people, leaving a very very very small pools of experts who devoted his/her life to this area.
reikonomusha 10y ago
These questions are not completely unanswered. These dry problems are what Rigetti Quantum Computing [1] is working on. [1] http://rigetti.com/about http://rigetti.com/about

by s_q_b 10y ago

eslaught 10y ago

How many people/companies did it take to build GPUs? A lot of people, to be sure, but as a fraction of all software engineers, that number is incredibly tiny. The vast majority of software engineers---even if we filter to just the set who have actually used GPUs for a project---only know the high-level APIs (OpenGL for graphics, CuDNN for AI, etc.). Fewer engineers are familiar with the more general-purpose APIs (CUDA, OpenCL, etc.), and even fewer still know any of what goes on underneath those layers. Bottom line: it takes a relatively small community of people to build tools for everyone else to use. People will need to know how to use the highest level of APIs, but most need not understand what goes on underneath that.

yeukhon 10y ago
Or a better way to put it in my own opinion: in the early days of any emerging technology, most of the founding members have little clue what to do except the concepts and ideas, so implementing toolsets which can be used on both quantum computers and non-quantum computers will be a learn-on-job work for most people, leaving a very very very small pools of experts who devoted his/her life to this area.

reikonomusha 10y ago

These questions are not completely unanswered. These dry problems are what Rigetti Quantum Computing [1] is working on. [1] http://rigetti.com/about http://rigetti.com/about