INSUBCONTINENT EXCLUSIVE:
Google and NASA have demonstrated that quantum computing isn&t just a fancy trick, but almost certainly something actually useful — and
they&re already working on commercial applications
What does that mean for existing startups and businesses? Simply put: nothing
But that doesn&t mean you can ignore it forever.
There are three main points that anyone concerned with the possibility of quantum computing
affecting their work should understand.
1
It&ll be a long time before anything really practical comes out of quantum computing.
Google showed that quantum computers are not only
functional, but apparently scalable
But that doesn&t mean they&re scaling right now
And if they were, it doesn&t mean there anything useful you can do with them.
What makes quantum computing effective is that it completely
different from classical computing — and that also makes creating the software and algorithms that run on it essentially a completely
unexplored space.
Quantum computing ‘Hello World& moment
There are theories, of course, and some elementary work on how to use these
things to accomplish practical goals
But we are only just now arriving at the time when such theories can be tested at the most basic levels
The work that needs to happen isn&t so much &bringing to market& as &fundamental understanding.&
Although it tempting to equate the
beginning of quantum computing to the beginning of digital computing, in reality they are very different
Classical computing, with its 1s and 0s and symbolic logic, actually maps readily on to human thought processes and ways of thinking about
information — with a little abstraction, of course.
Quantum computing, on the other hand, is very different from how humans think about
It doesn&t make intuitive sense, and not only because we haven&t developed the language for it
Our minds really just don&t work that way!
So although even I can now claim to have operated a quantum computer (technically true), there
are remarkably few people in the world who can say they can do so deliberately in pursuit of a specific problem
That means progress will be slow (by tech industry standards) and very limited for years to come as the basics of this science are
established and the ideas of code and data that we have held for decades are loosened.
2
Early applications will be incredibly domain-specific and not generalizable.
A common misunderstanding of quantum computing is that it
amounts to extremely fast parallel processing
Now, if someone had invented a device that performed supercomputer-like operations faster than any actual supercomputer, that would be an
entirely different development and, frankly, a much more useful one
But that isn&t the case.
As an engineer explained to me at Google lab, not only are quantum computers good at completely different things,
they&re incredibly bad at the things classical computers do well
If you wanted to do arithmetical logic like addition and multiplication, it would be much better and faster to use an abacus.
Part of the
excitement around quantum computing is learning which tasks a qubit-based system is actually good at
There are theories, but as mentioned before, they&re untested
It remains to be seen whether a given optimization problem or probability space navigation is really suitable for this type of computer at
all.
What they are pretty sure about so far is that there are certain very specific tasks that quantum computers will trivialize — but it
isn&t something general like &compression and decompression& or &sorting databases.& It things like evaluating a galaxy of molecules in all
possible configurations and conformations to isolate high-probability interactions.
As you can imagine, that isn&t very useful for an
enterprise security company
On the other hand, it could be utterly transformative for a pharmacology or materials company
Do you run one of those? Then in all likelihood, you are already investing in this kind of research and are well aware of the possibilities
quantum brings to the table.
But the point is these applications will not only be very few in number, but difficult to conceptualize, prove,
Unlike something like a machine learning agent, this isn&t a new approach that can easily be tested and iterated — it an entirely new
discipline which people can only now truly begin to learn.
