I remember
back in my college days at Purdue, I was absolutely terrified of
computers. I never wanted to take a class
that them as part of the curriculum. But
being an Ag Econ major, I had no choice but to face my fears of computers, because
while I loved the subject matter, technology was a big part of the major. My first
major test of computers occurred when I took a class called “CS 110”. This was simply an introductory class in
computers, but there was a lot of work involved.
Probably the
most terrifying part of the class for me was sitting through the actual lab
final, where we only had something like two hours to complete it. But somehow, I managed to get a “B” in the
class, and boy, I was happy with that.
My next experiences
with computers took place in my graduate school days at both SIUC and BGSU. For the former, I had to learn (the very hard
way) how to do mainframe SAS programming.
With the latter, I actually ended becoming an MIS major, and even worked
full time as a computer consultant for the university. Back then, I was dealing with the Mac
Classics.
But fast
forward to today, and look where we are at.
We can spin up a Virtual Machine in just a matter of minutes, at just a
fraction of the cost it would have been back in the late 90s and early
2000s. Probably the best example I give
of this is setting up an Oracle Enterprise Database.
Back in the day,
it would have cost at least $30,000 to set up an On Prem Server (most of this was
in the licensing costs). Now, you can create
the exact same thing in Microsoft Azure for as little as $80.00 per month.
So, what does
the future now hold? It is an area known
as “Quantum Computing”. Wondering what
it is? Well, here is a technical
definition of it:
“Quantum
computing is an emergent field of cutting-edge computer science harnessing the
unique qualities of quantum mechanics to solve problems beyond the ability of
even the most powerful classical computers.”
(SOURCE: https://www.ibm.com/topics/quantum-computing)
Given its sheer
power and speed, Quantum Computing has a number of key use cases, which are as
follows:
*Analyzing
financial portfolios of all kinds of clients, no matter how small or large they
may be.
*Improving
and optimizing the lifespan of Electrical Vehicle (EV) batteries.
*Further enhancing
the drug research and discovery process (for example, Generative AI has already
propelled this, but Quantum Computing is expected to take it beyond leaps and
bounds).
*Creating new
GPU and NPU chips for Generative AI based applications.
Capgemini
just published a report on the state of Quantum Computing, and you can access
it at this link:
http://cyberresources.solutions/blogs/Quantum_Computing.pdf
But another
area where Quantum Computing will make a huge mark as well is in Generative
AI. Technically, this is a field of Artificial
Intelligence which is known as “Quantum AI”, or also commonly referred to as “QAI”. Right now, we marvel at how quick the GPT4
algorithms can deliver an output in just a matter of a few minutes by using ChatGPT. But, the algorithms that will derived from
QAI will deliver that very same output in just a matter of seconds. The reason for this is that Quantum Computing
relies heavily on massive parallel processing.
This simply
means that many processes are run at the same time in order to compute very
complex calculations in just a fraction of the time it would take the computers
of today to do. The other bit of good news
here is that since the QAI algorithms will be far more efficient, it will
demand less energy from the data centers in which they are hosted in. Right now, cooling and using fresh water for
that is a huge issue in this kind of environment.
But, now come
the downsides of QAI. Probably the
biggest one here is that of the Cyberattacker manipulating the algorithms in
order to break the strong levels of Encryption that exist today.
To paint how
bleak this picture is, it is even expected that with the next five years or so,
the Cyberattacker will have the ability to break all of these Encryption
Protocols. More details on this can be
seen at the link below:
People in
fact have given serious thought to this, especially by our own Federal
Government. For instance, back in 2022,
Congress passed what is known as the “Quantum Computing Cybersecurity
Preparedness Act.”
This ensures
that all of the related agencies have developed and are testing their Incident Response/Disaster
Recovery/Business Continuity plans should a breach actually occur. More details about this can be seen at the link
below:
https://www.congress.gov/bill/117th-congress/house-bill/7535
Also, the National
Security Agency (NSA), Cybersecurity and Infrastructure Security Agency (CISA),
and National Institute of Standards and Technology (NIST) have created a
document known as the “Quantum Readiness: Migration to Post-Quantum
Cryptography.” This was a joint effort
in order to address the Cybersecurity risks that are associated with QAI. It can be downloaded from this link:
http://cyberresources.solutions/blogs/CSI-QUANTUM-READINESS.pdf
My Thoughts
On This
Whether we like
it or not, QAI will make its grand
entrance into our society in a way that ChatGPT did a few years ago. But, this time, there is a lot more at stake,
given just how powerful Quantum Computing is.
It will impact every walk of life all over the world.
But we have
one key advantage here: At the present
time, we are more or less learning about the risks that Generative AI poses
(and those that are evolving, but have not been discovered yet), and we can
apply those lessons learned to QAI.
But the key
thing here is that we all mut be proactive about this. QAI will be here a lot quicker than we
realize. For more details on what this means
to you, Capgemini also published a supplemental report, and it can be
downloaded here:
http://cyberresources.solutions/blogs/Quantum_Computing_Supplement.pdf
Also, CISOs
and their IT Security teams must address at what levels they use
Encryption. They will of course need to
be trained in QAI, and many of the Encryption Infrastructures (most notably
that of the Public Key Infrastructure) will have to be redesigned and even redeployed
in order to keep up with Cybersecurity risks that QAI will bring to the table.
In the end,
this will be known as “Crypto Resiliency”, just like what Cyber Resiliency
means to us today.
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