September 29, 2025 • 14 mins
A credit card typed at midnight feels routine—until you realize someone may already be saving that encrypted transaction, waiting for a future machine to read it like plain text. We unpack the quantum shift from distant speculation to near‑term reality, explain why “harvest now, decrypt later” is the live threat, and map the urgent path to post‑quantum cryptography. Along the way, we separate myth from mechanics: quantum isn’t a faster laptop, it’s a specialized tool that exposes hidden structure in problems classical computers can’t touch.
We take you inside the promise that actually matters: simulating molecules to accelerate drug discovery, unlocking catalysts like the FeMoCo pathway that could slash the Haber–Bosch energy bill, and optimizing complex systems—global supply chains, urban traffic, and renewable‑heavy grids. In finance, we explore how quantum could sharpen Monte Carlo simulations for real‑time risk, edging closer to portfolios that protect ordinary savers in volatile markets. Then we turn to the physics: decoherence, two‑level system defects, and quasiparticles, and why counterintuitive design choices—like physically larger qubit pads—can extend coherence and push performance forward.
Power without guardrails invites trouble, so we tackle ethics and governance head‑on. Quantum AI can magnify bias and erode privacy by re‑identifying “anonymous” data at speed, shifting the surveillance calculus and forcing a rethink of data minimization, retention, and transparency. Sustainability sits alongside security: these systems demand energy and rare materials, so responsible sourcing, recycling, and low‑carbon operations must be built in from the start. We close with practical steps: inventory your crypto, prioritize long‑lived secrets for PQC, pilot hybrid algorithms, and invest in the convergence skills where quantum meets your industry. Subscribe, share with a colleague who handles security or data strategy, and leave a review with the one upgrade you think can’t wait.
Leave your thoughts in the comments and subscribe for more tech updates and reviews.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Ida (00:00):
Have you ever been, you know, just sitting there, maybe
late at night, buying somethingsimple online?
Allan (00:05):
Happens all the time.
Ida (00:06):
Right.
Like maybe you use Smart Gadgetor, I don't know, socks even,
and you type in your credit carddetails, hit buy.
Allan (00:13):
And you just assume it's safe.
Yeah.
Completely secure.
Ida (00:16):
Aaron Powell Exactly.
You just assume that encryptionwell, it's basically
unbreakable, right?
Allan (00:20):
That assumption, that implicit trust.
Ida (00:23):
Yeah.
Allan (00:24):
That's precisely what's on shaky ground now because of
quantum computing.
Ida (00:28):
Aaron Powell Shaky Ground is putting it mildly, maybe.
Allan (00:31):
Well, yeah.
Some experts are genuinelycalling this an extinction level
event for today's standardencryption.
Ida (00:37):
Aaron Powell Okay, extinction level event.
We need to unpack that.
Because I think most peoplehear quantum computing and they
think, you know, maybe decadesaway, science fiction.
Allan (00:46):
Aaron Powell That used to be the thinking, yes.
But the reason we're talkingabout this now in late 2025 is
that the timeline has uhdramatically shrunk.
Ida (00:55):
How much?
Allan (00:56):
Significantly.
Look at the recent hardwarenews Google's Willow,
Microsoft's Major INA One, evenAmazon's Ocelot.
These aren't just small steps.
Ida (01:04):
They're big leaps.
Allan (01:05):
Huge leaps.
They signal a real inflectionpoint.
Microsoft's own CEO saidrecently that a meaningful
quantum computer is coming inyears, not decades.
Ida (01:15):
Aaron Powell Wait, years, not decades.
So this future problem is well,it's practically knocking at
the door.
It really is.
And just to give you, thelistener, a sense of the scale
here, Google's Willowchip.
It did a calculation in underfive minutes.
Okay.
A calculation that would takethe fastest supercomputer we
have today.
Get this 10 septillion years.
Allan (01:37):
Aaron Powell 10 septillion.
That's a 10 with what, 25 zerosafter it?
Ida (01:41):
25 zeros.
It's a number bigger than theage of the universe.
Allan (01:45):
Right.
And that is the kind ofcomputational power we're
suddenly dealing with.
That's the threat to, well,basically all the security we
rely on online.
Banking, messages, secrets.
Ida (01:54):
Everything.
Okay.
So let's tackle the immediateworry.
People might think, fine,quantum is coming, I'll just
upgrade my security later.
But that's not the real dangerright now, is it?
Allan (02:03):
No.
The immediate threat issomething else.
It's happening today.
It's called data harvesting.
Or maybe a better name is HNDL.
Harvest now, decrypt later.
Think about it.
Bad actors, governments, maybecriminals, corporate spies, they
are right now vacuuming up hugeamounts of today's encrypted
data.
(02:23):
Your emails, financialtransactions, health records,
everything.
Ida (02:27):
But they can't read it yet, right?
Because of current encryption.
Allan (02:29):
Exactly.
They can't read it today, butthey're storing it.
Petabytes of it.
They're making a bet.
Ida (02:35):
Betting that future quantum computers will just slice
through today's encryption.
Allan (02:39):
Precisely.
Once those powerful quantummachines arrive, all that stored
data becomes an open book,instantly decrypted.
Ida (02:46):
Okay, that's genuinely chilling.
It makes my online sockpurchase feel a bit more
serious.
So remind us quickly, how doestoday's encryption work?
The stuff they're harvesting.
Allan (02:54):
Well, the most common kind, like RSA, relies on math
being hard, specificallyfactoring large numbers.
Ida (03:02):
Factoring.
Allan (03:02):
Yeah.
It's super easy for a computerto multiply two massive prime
numbers together.
You know, primes are numbersonly divisible by one in
themselves.
But trying to take that hugeresult and figure out the two
original primes that made it,that's incredibly difficult for
our current computers.
It would take them billions ofyears for the numbers used in
encryption.
That difficulty is the lock.
Ida (03:24):
A mathematical lock.
And quantum computing has thekey.
Allan (03:28):
It does.
It's a famous algorithm calledShore's algorithm, developed
back in the 90s, actually.
Ida (03:33):
So we've known about this key for a while.
Allan (03:35):
We've known the theory.
Shore's algorithm uses quantummechanics stuff like
interference and superpositionin a really clever way.
It can essentially find thehidden mathematical rhythm, the
period, in the factoringproblem.
Ida (03:47):
Okay, finding a rhythm, how does that help?
Allan (03:49):
Imagine looking for a needle in a ginormous haystack.
A classical computer checks onestraw at a time.
Shore's algorithm lets aquantum computer somehow sense
the entire haystack at once andpoints directly to the needle.
Wow.
It turns that billions of yearsproblem into something that
takes maybe seconds or minuteson a capable quantum computer.
Ida (04:10):
So the lock isn't just picked, it's fundamentally
broken.
Okay, so what's the defense?
There must be one.
Allan (04:15):
There is.
It's called post-quantumcryptography, or PQC.
New types of encryption basedon different mathematical
problems that we think evenquantum computers can't solve
easily.
Ida (04:26):
And this is happening now.
Allan (04:27):
Oh yes.
MIST, the U.S.
National Institute of Standardsand Technology, has been
working on this seriously since2016.
They've already finalized thefirst few PQC standards.
The algorithms exist.
Ida (04:39):
So if the new locks are ready, why the panic?
Why the HNDL threat?
Is it just about cost?
Allan (04:46):
Aaron Powell Cost is a factor, sure, but the real
nightmare is deployment.
Getting these new PQC standardsrolled out everywhere.
Ida (04:52):
The last mile problem.
Allan (04:54):
Exactly.
But on a global scale.
Think about every website,every server, every phone, every
piece of software that usesencryption.
They all need to be updated.
Ida (05:02):
Aaron Powell That sounds huge.
Years of work.
Allan (05:04):
Aaron Powell Years and years potentially.
And any delay creates a windowof vulnerability.
That's why you're seeingcompanies like Google, Apple,
Microsoft pushing to shorten thelifespan of current security
certificates, those TLScertificates that make websites
secure.
How short?
They're aiming for just 47 daysin some cases.
Ida (05:20):
Aaron Powell 47 days.
Wow.
They're basically trying toforce everyone to update
constantly because they knowthis quantum threat is coming
fast and the HDL data is pilingup.
Allan (05:30):
That's the urgency.
It's a race to replace thelocks before the quantum key
gets mass-produced.
Aaron Powell Okay.
Ida (05:36):
So the security threat is real and immediate, but let's
pivot slightly.
This incredible quantum power.
It's not just for breakingthings, right?
We need it.
Allan (05:47):
Absolutely.
But maybe not for the reasonspeople assume.
Let's bust a big myth rightnow.
Ida (05:52):
Please do.
Allan (05:52):
Quantum computers are not going to be your next super
fast gaming laptop.
They won't run Windows fasteror load websites quicker.
Ida (06:00):
Aaron Powell So not a turbo boost for my current tech.
Allan (06:02):
Not at all.
It's a fundamentally differentkind of computing.
It's a highly specialized tool,brilliant for certain types of
problems where quantum effectslike interference can find
hidden structures.
Ida (06:13):
Problems that our regular computers just choke on.
Allan (06:16):
Exactly.
Problems they can't solveefficiently, or maybe ever.
Think complex simulations andoptimization.
Ida (06:21):
Aaron Powell Okay, so if it's not making my phone faster,
what are the bigsociety-changing applications we
should be excited about?
Allan (06:27):
Drug discovery and material science are huge ones.
Simulating molecules accuratelyis incredibly hard for
classical computers.
The complexity explodes.
Ida (06:37):
But quantum computers can handle it.
Allan (06:39):
They're naturally suited for it.
They operate on quantumprinciples themselves.
So designing new medicines,discovering new catalysts for
cleaner energy, creating betterbatteries, stronger lightweight
materials, QC could accelerateall of that dramatically.
Ida (06:53):
You mentioned catalysts.
There's that amazing exampleabout fertilizer.
Allan (06:57):
Right, the FOMOCO catalyst.
Nature uses this molecule andbacteria to make ammonia for
fertilizer at room temperature.
Ida (07:05):
And how do we make fertilizer now?
Allan (07:06):
We use the Haberbosch process.
It works, but it's incrediblyenergy intensive.
It consumes something like 2%of the entire world's energy
production.
Ida (07:15):
2% just for fertilizer.
Allan (07:17):
Just for fertilizer.
If QC can help us fullyunderstand and replicate how
FOMOCO works, we couldpotentially create an industrial
process that saves a massivechunk of global energy and
reduces emissions.
That's a game changer.
Ida (07:30):
Okay, that's huge.
What about optimization?
Things like logistics orfinance.
Allan (07:35):
Another sweet spot for QC.
Think about optimizing complexsystems with tons of variables.
Global shipping routes,managing city traffic flow in
real time, making supply chainsway more efficient.
Ida (07:47):
Less waste, lower costs, fewer emissions.
Allan (07:50):
Exactly.
And in finance, think aboutmodeling risk.
Monte Carlo simulations areused everywhere, but they're
computationally heavy.
Ida (07:57):
PC could make them faster and more accurate.
Allan (07:59):
Much faster, potentially allowing for things like truly
hyper-personalized financialplanning.
Imagine a 401k that constantlyadjusts based on incredibly
complex real-time marketanalysis.
That could offer much betterprotection against risk.
Ida (08:14):
And you also mentioned energy grids.
Allan (08:16):
Yes, vital.
Our grids are gettingincredibly complex with
renewable energy sources likewind and solar coming online,
plus the demands of electricvehicles and data centers.
Ida (08:24):
It's balancing act.
Allan (08:25):
A very complex one.
QC could be essential formodeling, predicting, and
managing these future smartgrids to keep energy reliable
and affordable.
Ida (08:34):
So amazing potential.
But if it's so great, why don'twe have these powerful machines
everywhere yet?
What's the holdup?
Allan (08:40):
It boils down to incredibly difficult physics and
engineering.
The main enemy is somethingcalled decoherence.
Ida (08:47):
Decoherence sounds bad.
Allan (08:48):
It is.
It's basically the quantumstate kind of dissolving, losing
its quantumness because ofnoise from the environment.
Ida (08:55):
Noise, like sound.
Allan (08:56):
Not sound, but more like tiny disturbances.
Imagine trying to build areally delicate house of cards
on a vibrating table, theslightest bump, and it
collapses.
Quibbits, the building blocksof quantum computers, are
unbelievably fragile.
Ida (09:10):
And what causes these bumps, this noise in the main
type of quibbits people arebuilding, the superconducting
ones?
Allan (09:16):
Aaron Powell Two main culprits.
Yeah.
First, tiny defects in thematerials themselves, literally
at the atomic level.
They call them two-levelsystems or TLSs.
Little imperfections.
Okay.
Second, stray energy particlescalled quasiparticles or QPs.
They're like little bits ofenergy bouncing around where
they shouldn't be messing withthe qubit state.
Ida (09:34):
Aaron Powell, so they're fighting noise just to keep the
quantum calculation running fors how long?
Allan (09:40):
We're often talking microseconds or milliseconds.
It's an intense battle againstphysics.
Ida (09:44):
Aaron Powell And the research shows something
interesting about the physicaldesign of the qubits matters a
lot here, right?
Something counterintuitive.
Allan (09:50):
Yes, this is fascinating.
You'd think in computingsmaller is always better, right?
Ida (09:54):
Yeah.
Allan (09:55):
Pack more in.
Ida (09:56):
Moore's law, yeah.
Allan (09:57):
But with these superconducting quibits,
research is showing that thephysical size of the qubit
components, the pads, actuallymakes a huge difference to
noise.
Ida (10:07):
And bigger is better.
That seems weird.
Allan (10:09):
It does, but the physics bears it out.
Quibits with a smaller physicalfootprint, smaller surface
area, are actually moresensitive to noise from both
those TLS defects and thequasi-particles.
Ida (10:21):
Why would that be?
Allan (10:22):
It's complex, but it relates to the density of these
noise sources and somethingcalled the effective volume.
Basically, the noise gets moreconcentrated in smaller spaces.
Research suggests the densityof those unwanted
quasi-particles is about 2.5times higher in quibits with
small pads.
So making the pads physicallylarger gives the quibbit more
(10:42):
stability, a longer coherencetime.
It shows how much the physicaldesign, down to the micro level,
matters.
Ida (10:48):
So it's not just about having more quibbits, it's about
having good, stable quibits.
Allan (10:52):
Quality over quantity, at least for now.
Building stable quibbits is thereal engineering hurdle.
Ida (10:57):
Okay, this power is immense.
The challenges are huge.
Which brings us to ethics.
When do we start thinking aboutthe ethical implications of
something this powerful?
Allan (11:06):
Right now.
Absolutely now.
While it's still being designedand built, we can't wait until
it's fully mature.
Ida (11:12):
Because once you combine this quantum power with AI, you
get quantum AI.
And that could amplify existingproblems.
Allan (11:19):
Dramatically.
All the concerns we alreadyhave about AI bias, fairness,
privacy, quantum computing couldput them on steroids.
Ida (11:26):
So with fairness, we know AI can be biased if trained on
bad data.
Allan (11:31):
Aaron Powell Right.
Now imagine a quantum systemtrained on flawed data.
Its speed and power could leadto discriminatory outcomes much
faster and potentially on a muchwider scale.
A small bias could become ahuge problem very quickly.
Ida (11:44):
Aaron Powell And privacy.
You mentioned HNDL brakingencryption, but what about
analyzing data that's supposedlyanonymous?
Allan (11:50):
Aaron Powell That's a huge concern.
Quantum AI could potentiallyre-identify individuals or infer
sensitive information fromlarge data sets with incredible
speed and efficiency, even dataprotected by current regulations
like GDPR.
Ida (12:05):
So the speed itself changes what's possible in terms of
surveillance or pattern finding.
Allan (12:11):
Absolutely.
It changes the whole calculus.
We need to rethink dataprotection entirely in the
quantum era.
How do we ensure data integrityand control when machines can
process it this fast?
Ida (12:22):
And then there's sustainability.
We talked about QC potentiallysaving energy with things like
FOMOCO.
Allan (12:27):
Yes, the potential upside is there.
Ida (12:29):
But building and running these things and the whole tech
ecosystem around them mustconsume a lot of energy and
resources, too, right?
Allan (12:36):
It's a critical trade-off.
Quantum computers, especiallyearly ones, are power hungry.
Data centers are already a hugeenergy drain.
Plus, manufacturing thespecialized components involves
rare materials and createse-waste.
Ida (12:48):
So we need to build sustainability in from the
start.
Allan (12:50):
We have to.
Corporate responsibility hereis key.
We need eco-friendly designs,responsible sourcing, plans for
recycling.
We can't solve one problem bycreating another massive
environmental one.
Ida (13:03):
Okay, so wrapping this up, it feels like we're standing at
a really pivotal moment.
Allan (13:08):
We absolutely are.
Ida (13:09):
We're in this incredible race.
Quantum computing is this giantleap that, yes, threatens our
current digital security blanketthrough things like H and DL.
Allan (13:19):
A very real threat.
Ida (13:20):
But it's also the same power that might be our best
hope for solving some trulymassive global challenges in
energy, medicine, materials.
Allan (13:29):
That's the paradox.
Huge risk, huge reward.
Ida (13:32):
And the key myth we busted today
just faster laptops.
Don't expect one on your deskrunning spreadsheets anytime
soon.
Allan (13:39):
Definitely not.
They're specialized machinesfor specialized, incredibly hard
problems that classicalcomputers just can't handle.
Think different tool, notfaster tool.
Ida (13:48):
So for you listening, what's one thing you can do now?
It feels like specific techskills might become outdated
fast.
Allan (13:54):
Adaptability is key.
And understanding where thistechnology intersects with
existing fields.
Look at the convergence points.
Ida (14:02):
Convergence points.
Allan (14:03):
Yeah, where quantum computing meets healthcare or
finance or logistics or energy.
That's where the realtransformation will happen, and
where the valuable skills andopportunities will be
understanding both the quantumpotential and the specific
industry's needs.
Ida (14:17):
Be the bridge between the quantum world and the real
world.
Allan (14:20):
Exactly.
That's going to be incrediblyvaluable.
Ida (14:22):
And maybe a final thought to leave people with.
It comes back to control,doesn't it?
Allan (14:26):
It does.
The really deep question isabout autonomy.
As these machines get smarterand faster, thanks to quantum
and AI, how much decision makingdo we hand over?
Ida (14:37):
How do we ensure they align with human values?
Allan (14:39):
How do we maintain trust?
We need to decide, consciously,how much power we give these
incredibly potent new tools.
That's maybe the most profoundchallenge of the quantum era
ahead.
Have you ever been, you know, just sitting there, maybe
late at night, buying somethingsimple online?
Allan (00:05):
Happens all the time.
Ida (00:06):
Right.
Like maybe you use Smart Gadgetor, I don't know, socks even,
and you type in your credit carddetails, hit buy.
Allan (00:13):
And you just assume it's safe.
Yeah.
Completely secure.
Ida (00:16):
Aaron Powell Exactly.
You just assume that encryptionwell, it's basically
unbreakable, right?
Allan (00:20):
That assumption, that implicit trust.
Ida (00:23):
Yeah.
Allan (00:24):
That's precisely what's on shaky ground now because of
quantum computing.
Ida (00:28):
Aaron Powell Shaky Ground is putting it mildly, maybe.
Allan (00:31):
Well, yeah.
Some experts are genuinelycalling this an extinction level
event for today's standardencryption.
Ida (00:37):
Aaron Powell Okay, extinction level event.
We need to unpack that.
Because I think most peoplehear quantum computing and they
think, you know, maybe decadesaway, science fiction.
Allan (00:46):
Aaron Powell That used to be the thinking, yes.
But the reason we're talkingabout this now in late 2025 is
that the timeline has uhdramatically shrunk.
Ida (00:55):
How much?
Allan (00:56):
Significantly.
Look at the recent hardwarenews Google's Willow,
Microsoft's Major INA One, evenAmazon's Ocelot.
These aren't just small steps.
Ida (01:04):
They're big leaps.
Allan (01:05):
Huge leaps.
They signal a real inflectionpoint.
Microsoft's own CEO saidrecently that a meaningful
quantum computer is coming inyears, not decades.
Ida (01:15):
Aaron Powell Wait, years, not decades.
So this future problem is well,it's practically knocking at
the door.
It really is.
And just to give you, thelistener, a sense of the scale
here, Google's Willowchip.
It did a calculation in underfive minutes.
Okay.
A calculation that would takethe fastest supercomputer we
have today.
Get this 10 septillion years.
Allan (01:37):
Aaron Powell 10 septillion.
That's a 10 with what, 25 zerosafter it?
Ida (01:41):
25 zeros.
It's a number bigger than theage of the universe.
Allan (01:45):
Right.
And that is the kind ofcomputational power we're
suddenly dealing with.
That's the threat to, well,basically all the security we
rely on online.
Banking, messages, secrets.
Ida (01:54):
Everything.
Okay.
So let's tackle the immediateworry.
People might think, fine,quantum is coming, I'll just
upgrade my security later.
But that's not the real dangerright now, is it?
Allan (02:03):
No.
The immediate threat issomething else.
It's happening today.
It's called data harvesting.
Or maybe a better name is HNDL.
Harvest now, decrypt later.
Think about it.
Bad actors, governments, maybecriminals, corporate spies, they
are right now vacuuming up hugeamounts of today's encrypted
data.
(02:23):
Your emails, financialtransactions, health records,
everything.
Ida (02:27):
But they can't read it yet, right?
Because of current encryption.
Allan (02:29):
Exactly.
They can't read it today, butthey're storing it.
Petabytes of it.
They're making a bet.
Ida (02:35):
Betting that future quantum computers will just slice
through today's encryption.
Allan (02:39):
Precisely.
Once those powerful quantummachines arrive, all that stored
data becomes an open book,instantly decrypted.
Ida (02:46):
Okay, that's genuinely chilling.
It makes my online sockpurchase feel a bit more
serious.
So remind us quickly, how doestoday's encryption work?
The stuff they're harvesting.
Allan (02:54):
Well, the most common kind, like RSA, relies on math
being hard, specificallyfactoring large numbers.
Ida (03:02):
Factoring.
Allan (03:02):
Yeah.
It's super easy for a computerto multiply two massive prime
numbers together.
You know, primes are numbersonly divisible by one in
themselves.
But trying to take that hugeresult and figure out the two
original primes that made it,that's incredibly difficult for
our current computers.
It would take them billions ofyears for the numbers used in
encryption.
That difficulty is the lock.
Ida (03:24):
A mathematical lock.
And quantum computing has thekey.
Allan (03:28):
It does.
It's a famous algorithm calledShore's algorithm, developed
back in the 90s, actually.
Ida (03:33):
So we've known about this key for a while.
Allan (03:35):
We've known the theory.
Shore's algorithm uses quantummechanics stuff like
interference and superpositionin a really clever way.
It can essentially find thehidden mathematical rhythm, the
period, in the factoringproblem.
Ida (03:47):
Okay, finding a rhythm, how does that help?
Allan (03:49):
Imagine looking for a needle in a ginormous haystack.
A classical computer checks onestraw at a time.
Shore's algorithm lets aquantum computer somehow sense
the entire haystack at once andpoints directly to the needle.
Wow.
It turns that billions of yearsproblem into something that
takes maybe seconds or minuteson a capable quantum computer.
Ida (04:10):
So the lock isn't just picked, it's fundamentally
broken.
Okay, so what's the defense?
There must be one.
Allan (04:15):
There is.
It's called post-quantumcryptography, or PQC.
New types of encryption basedon different mathematical
problems that we think evenquantum computers can't solve
easily.
Ida (04:26):
And this is happening now.
Allan (04:27):
Oh yes.
MIST, the U.S.
National Institute of Standardsand Technology, has been
working on this seriously since2016.
They've already finalized thefirst few PQC standards.
The algorithms exist.
Ida (04:39):
So if the new locks are ready, why the panic?
Why the HNDL threat?
Is it just about cost?
Allan (04:46):
Aaron Powell Cost is a factor, sure, but the real
nightmare is deployment.
Getting these new PQC standardsrolled out everywhere.
Ida (04:52):
The last mile problem.
Allan (04:54):
Exactly.
But on a global scale.
Think about every website,every server, every phone, every
piece of software that usesencryption.
They all need to be updated.
Ida (05:02):
Aaron Powell That sounds huge.
Years of work.
Allan (05:04):
Aaron Powell Years and years potentially.
And any delay creates a windowof vulnerability.
That's why you're seeingcompanies like Google, Apple,
Microsoft pushing to shorten thelifespan of current security
certificates, those TLScertificates that make websites
secure.
How short?
They're aiming for just 47 daysin some cases.
Ida (05:20):
Aaron Powell 47 days.
Wow.
They're basically trying toforce everyone to update
constantly because they knowthis quantum threat is coming
fast and the HDL data is pilingup.
Allan (05:30):
That's the urgency.
It's a race to replace thelocks before the quantum key
gets mass-produced.
Aaron Powell Okay.
Ida (05:36):
So the security threat is real and immediate, but let's
pivot slightly.
This incredible quantum power.
It's not just for breakingthings, right?
We need it.
Allan (05:47):
Absolutely.
But maybe not for the reasonspeople assume.
Let's bust a big myth rightnow.
Ida (05:52):
Please do.
Allan (05:52):
Quantum computers are not going to be your next super
fast gaming laptop.
They won't run Windows fasteror load websites quicker.
Ida (06:00):
Aaron Powell So not a turbo boost for my current tech.
Allan (06:02):
Not at all.
It's a fundamentally differentkind of computing.
It's a highly specialized tool,brilliant for certain types of
problems where quantum effectslike interference can find
hidden structures.
Ida (06:13):
Problems that our regular computers just choke on.
Allan (06:16):
Exactly.
Problems they can't solveefficiently, or maybe ever.
Think complex simulations andoptimization.
Ida (06:21):
Aaron Powell Okay, so if it's not making my phone faster,
what are the bigsociety-changing applications we
should be excited about?
Allan (06:27):
Drug discovery and material science are huge ones.
Simulating molecules accuratelyis incredibly hard for
classical computers.
The complexity explodes.
Ida (06:37):
But quantum computers can handle it.
Allan (06:39):
They're naturally suited for it.
They operate on quantumprinciples themselves.
So designing new medicines,discovering new catalysts for
cleaner energy, creating betterbatteries, stronger lightweight
materials, QC could accelerateall of that dramatically.
Ida (06:53):
You mentioned catalysts.
There's that amazing exampleabout fertilizer.
Allan (06:57):
Right, the FOMOCO catalyst.
Nature uses this molecule andbacteria to make ammonia for
fertilizer at room temperature.
Ida (07:05):
And how do we make fertilizer now?
Allan (07:06):
We use the Haberbosch process.
It works, but it's incrediblyenergy intensive.
It consumes something like 2%of the entire world's energy
production.
Ida (07:15):
2% just for fertilizer.
Allan (07:17):
Just for fertilizer.
If QC can help us fullyunderstand and replicate how
FOMOCO works, we couldpotentially create an industrial
process that saves a massivechunk of global energy and
reduces emissions.
That's a game changer.
Ida (07:30):
Okay, that's huge.
What about optimization?
Things like logistics orfinance.
Allan (07:35):
Another sweet spot for QC.
Think about optimizing complexsystems with tons of variables.
Global shipping routes,managing city traffic flow in
real time, making supply chainsway more efficient.
Ida (07:47):
Less waste, lower costs, fewer emissions.
Allan (07:50):
Exactly.
And in finance, think aboutmodeling risk.
Monte Carlo simulations areused everywhere, but they're
computationally heavy.
Ida (07:57):
PC could make them faster and more accurate.
Allan (07:59):
Much faster, potentially allowing for things like truly
hyper-personalized financialplanning.
Imagine a 401k that constantlyadjusts based on incredibly
complex real-time marketanalysis.
That could offer much betterprotection against risk.
Ida (08:14):
And you also mentioned energy grids.
Allan (08:16):
Yes, vital.
Our grids are gettingincredibly complex with
renewable energy sources likewind and solar coming online,
plus the demands of electricvehicles and data centers.
Ida (08:24):
It's balancing act.
Allan (08:25):
A very complex one.
QC could be essential formodeling, predicting, and
managing these future smartgrids to keep energy reliable
and affordable.
Ida (08:34):
So amazing potential.
But if it's so great, why don'twe have these powerful machines
everywhere yet?
What's the holdup?
Allan (08:40):
It boils down to incredibly difficult physics and
engineering.
The main enemy is somethingcalled decoherence.
Ida (08:47):
Decoherence sounds bad.
Allan (08:48):
It is.
It's basically the quantumstate kind of dissolving, losing
its quantumness because ofnoise from the environment.
Ida (08:55):
Noise, like sound.
Allan (08:56):
Not sound, but more like tiny disturbances.
Imagine trying to build areally delicate house of cards
on a vibrating table, theslightest bump, and it
collapses.
Quibbits, the building blocksof quantum computers, are
unbelievably fragile.
Ida (09:10):
And what causes these bumps, this noise in the main
type of quibbits people arebuilding, the superconducting
ones?
Allan (09:16):
Aaron Powell Two main culprits.
Yeah.
First, tiny defects in thematerials themselves, literally
at the atomic level.
They call them two-levelsystems or TLSs.
Little imperfections.
Okay.
Second, stray energy particlescalled quasiparticles or QPs.
They're like little bits ofenergy bouncing around where
they shouldn't be messing withthe qubit state.
Ida (09:34):
Aaron Powell, so they're fighting noise just to keep the
quantum calculation running fors how long?
Allan (09:40):
We're often talking microseconds or milliseconds.
It's an intense battle againstphysics.
Ida (09:44):
Aaron Powell And the research shows something
interesting about the physicaldesign of the qubits matters a
lot here, right?
Something counterintuitive.
Allan (09:50):
Yes, this is fascinating.
You'd think in computingsmaller is always better, right?
Ida (09:54):
Yeah.
Allan (09:55):
Pack more in.
Ida (09:56):
Moore's law, yeah.
Allan (09:57):
But with these superconducting quibits,
research is showing that thephysical size of the qubit
components, the pads, actuallymakes a huge difference to
noise.
Ida (10:07):
And bigger is better.
That seems weird.
Allan (10:09):
It does, but the physics bears it out.
Quibits with a smaller physicalfootprint, smaller surface
area, are actually moresensitive to noise from both
those TLS defects and thequasi-particles.
Ida (10:21):
Why would that be?
Allan (10:22):
It's complex, but it relates to the density of these
noise sources and somethingcalled the effective volume.
Basically, the noise gets moreconcentrated in smaller spaces.
Research suggests the densityof those unwanted
quasi-particles is about 2.5times higher in quibits with
small pads.
So making the pads physicallylarger gives the quibbit more
(10:42):
stability, a longer coherencetime.
It shows how much the physicaldesign, down to the micro level,
matters.
Ida (10:48):
So it's not just about having more quibbits, it's about
having good, stable quibits.
Allan (10:52):
Quality over quantity, at least for now.
Building stable quibbits is thereal engineering hurdle.
Ida (10:57):
Okay, this power is immense.
The challenges are huge.
Which brings us to ethics.
When do we start thinking aboutthe ethical implications of
something this powerful?
Allan (11:06):
Right now.
Absolutely now.
While it's still being designedand built, we can't wait until
it's fully mature.
Ida (11:12):
Because once you combine this quantum power with AI, you
get quantum AI.
And that could amplify existingproblems.
Allan (11:19):
Dramatically.
All the concerns we alreadyhave about AI bias, fairness,
privacy, quantum computing couldput them on steroids.
Ida (11:26):
So with fairness, we know AI can be biased if trained on
bad data.
Allan (11:31):
Aaron Powell Right.
Now imagine a quantum systemtrained on flawed data.
Its speed and power could leadto discriminatory outcomes much
faster and potentially on a muchwider scale.
A small bias could become ahuge problem very quickly.
Ida (11:44):
Aaron Powell And privacy.
You mentioned HNDL brakingencryption, but what about
analyzing data that's supposedlyanonymous?
Allan (11:50):
Aaron Powell That's a huge concern.
Quantum AI could potentiallyre-identify individuals or infer
sensitive information fromlarge data sets with incredible
speed and efficiency, even dataprotected by current regulations
like GDPR.
Ida (12:05):
So the speed itself changes what's possible in terms of
surveillance or pattern finding.
Allan (12:11):
Absolutely.
It changes the whole calculus.
We need to rethink dataprotection entirely in the
quantum era.
How do we ensure data integrityand control when machines can
process it this fast?
Ida (12:22):
And then there's sustainability.
We talked about QC potentiallysaving energy with things like
FOMOCO.
Allan (12:27):
Yes, the potential upside is there.
Ida (12:29):
But building and running these things and the whole tech
ecosystem around them mustconsume a lot of energy and
resources, too, right?
Allan (12:36):
It's a critical trade-off.
Quantum computers, especiallyearly ones, are power hungry.
Data centers are already a hugeenergy drain.
Plus, manufacturing thespecialized components involves
rare materials and createse-waste.
Ida (12:48):
So we need to build sustainability in from the
start.
Allan (12:50):
We have to.
Corporate responsibility hereis key.
We need eco-friendly designs,responsible sourcing, plans for
recycling.
We can't solve one problem bycreating another massive
environmental one.
Ida (13:03):
Okay, so wrapping this up, it feels like we're standing at
a really pivotal moment.
Allan (13:08):
We absolutely are.
Ida (13:09):
We're in this incredible race.
Quantum computing is this giantleap that, yes, threatens our
current digital security blanketthrough things like H and DL.
Allan (13:19):
A very real threat.
Ida (13:20):
But it's also the same power that might be our best
hope for solving some trulymassive global challenges in
energy, medicine, materials.
Allan (13:29):
That's the paradox.
Huge risk, huge reward.
Ida (13:32):
And the key myth we busted today
just faster laptops.
Don't expect one on your deskrunning spreadsheets anytime
soon.
Allan (13:39):
Definitely not.
They're specialized machinesfor specialized, incredibly hard
problems that classicalcomputers just can't handle.
Think different tool, notfaster tool.
Ida (13:48):
So for you listening, what's one thing you can do now?
It feels like specific techskills might become outdated
fast.
Allan (13:54):
Adaptability is key.
And understanding where thistechnology intersects with
existing fields.
Look at the convergence points.
Ida (14:02):
Convergence points.
Allan (14:03):
Yeah, where quantum computing meets healthcare or
finance or logistics or energy.
That's where the realtransformation will happen, and
where the valuable skills andopportunities will be
understanding both the quantumpotential and the specific
industry's needs.
Ida (14:17):
Be the bridge between the quantum world and the real
world.
Allan (14:20):
Exactly.
That's going to be incrediblyvaluable.
Ida (14:22):
And maybe a final thought to leave people with.
It comes back to control,doesn't it?
Allan (14:26):
It does.
The really deep question isabout autonomy.
As these machines get smarterand faster, thanks to quantum
and AI, how much decision makingdo we hand over?
Ida (14:37):
How do we ensure they align with human values?
Allan (14:39):
How do we maintain trust?
We need to decide, consciously,how much power we give these
incredibly potent new tools.
That's maybe the most profoundchallenge of the quantum era
ahead.
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