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You probably have heard of quantum computing already, but to really understand its promise.
The founder and lead at Google Quantum AI, Hartman Nevin, took the Ted stage to break down how it works in practice.
After the break, better understand this revolution in computing by hearing it in action.
And now, our Ted Talk of the Day.
I'm Hartman. I lead Google Quantum AI.
I've been working on quantum computing since 2012 and let me tell you why it's so intriguing.
Today's computer is like a laptop or a server at the Google Data Center operate on the binary logic of zeros and ones.
A quantum computer replaces the binary logic with the laws of quantum physics that gives it more powerful operations, allowing it to perform certain computations with way fewer steps.
So where does this superpower come from?
Quantum computing is the first technology that takes the idea serious that we live in the multiverse.
It can be seen as farming out computations to parallel universes.
Let me explain. In quantum physics, the key mathematical object to describe many worlds is called superposition.
You just need three bits to describe it.
Each coin has a two-state system, heads or tails, zero or one.
We look at the start state.
If I were to know which forces act on the system, then I can predict its trajectory and future states.
This is how we reason in classical physics and also in everyday life.
But if we were to treat this as a quantum system, then it can branch into many configurations simultaneously.
And we have to keep track of all those trajectories, interfere them to make an accurate prediction of what states we are going to see in the future.
So the equations of quantum mechanics tell us that at any time, any object, myself or the world at large, exists in a superposition of many configurations.
Intriguingly, look around in this room.
We are forming a configuration too.
And the equations of quantum physics would suggest that we sit in different arrangements in different worlds.
This superpower can be applied to computation.
Also search task by envisioning a very tall closet with a million drawers.
I place an item in one of the drawers.
How many drawers do you have to open to find the item?
In average, it will be half a million.
But if you had access to a quantum algorithm, it would only be a thousand steps to find the item.
Hanselworld can this be?
Indeed, it cannot be in a single word.
So here you see a good example of how quantum computing can attain in the advantage by performing computations in parallel worlds.
So what can you do with quantum computers today?
We have prepared interesting quantum states and studied their properties.
This has led to dozens of publications in high impact journals like Nature or Science.
Actually, I like to think of it as creating little pieces of magic.
For example, one state we prepared can be sort of as spawning a tiny traversable wormhole.
We can use it to learn about the physics of wormholes.
We can throw a cube at in and see how it reappears on the other side.
We made time crystals. That's a cool word, isn't it?
Like, who doesn't want to have a time crystal as an earring?
These crystals have amazing physical properties.
They change periodically in time without ever exchanging energy with the environment.
There's the closest to a perpetual mobile that's lost a physics allow you to get.
Or a final example, non-abillion annules.
This is a mouseful. But these are systems that change their overall properties when exchanging two identical parts.
Some things humans have never seen before.
Because envision a little house made of Lego bricks and envision swapping two bricks that look identical.
In everyday life, you would not notice a difference.
But quantum physicists had predicted that systems can exist, that exchange or change their properties when you exchange two identical parts.
Today, nobody has performed a practical application that can only be done on a quantum computer.
Despite what you may have read in the press.
But today, I'm excited to tell you that we are completing the design of an algorithm that may lead to first commercial applications.
This quantum algorithm performs signal processing to enable new ways to detect and analyze molecules using nuclear electronic spin spectroscopy.
In times, this may lead to exciting consumer applications.
In vision, a device akin to an electronic nose near a phone or a smartwatch.
Wouldn't it be awesome if your phone could warn you that you step into a room with dangerous viruses?
Or if your smartwatch could detect free radicals in your bloodstream and tell you it's time to drink your assay juice or warn you of elegance and food or many other truly helpful use cases?
And now back to the episode.
To unlock more applications, we will need to build a large, error corrected quantum computer.
How to build a computer with a million physical qubits?
It consists of six milestones and we achieved already the first two.
Prior to 2019, nobody had shown a beyond classical computation on a quantum computer.
We were the first to demonstrate it.
Our chip could perform a computation that the Zen-Fast Supercomputer would have needed 10,000 years to do.
And recently we repeated this experiment and now frontier today's top supercomputer would need one billion years to perform this computation.
This dramatic growth in computer power corroborates Nevin's law, which says that the power of quantum computers will grow at a double exponential rate.
In 2023 we achieved the second milestone, we demonstrated again for the first time that quantum error correction is a scalable technology.
Error correction sounds boring, but it's crucial.
Today our two-cubid operations have an error rate of one in a thousand.
That means that in every thousand steps or so, the quantum computer will crash.
To improve this, we combine many physical qubits to a logical qubit to reduce the error rate to one in a billion or even less.
We are about halfway through our roadmap and we are optimistic that we will complete it before the end of this decade.
We have done analytical and numerical studies to predict which algorithms will be impactful on such a large quantum computer.
A class of applications we like and we call Feynman's Killer App is the simulation of systems where quantum effects are important.
This is relevant for designing more effective, more targeted medicines.
Specifically, we have worked with the pharmaceutical company on algorithms to describe cytochrome P450.
This group of enzymes metabolizes about 75 percent of the drugs we take.
For the design of lighter, faster charging batteries that can hold a larger charge for electric cars or even electric airplanes.
Or to hasten the design of fusion reactors to help with climate change, arguably humanity's most urgent challenge.
A recent result is a novel algorithm that delivers significant speed up for optimization.
It is a big deal because optimization problems are ubiquitous in engineering finance or machine learning.
The way to think about this result is in the future when an AI will play chess or go against the quantum AI, the quantum AI will win.
This result shows that quantum computers will become a must-have capability to serve foundational computational tasks.
I am also very interested in the intersection of physics and neurobiology.
Quantum information science may enable us to answer one of humanity's deepest questions.
What creates conscious experience?
An attractive conjecture is that consciousness is how we experience the emergence of a single classical world out of the many the multiverse is composed of.
These academic collaborators have started a program to experimentally test this conjecture using methods of quantum neurobiology.
If our conjecture is correct, this would allow us to expand human consciousness in space, time and complexity.
In conclusion, we are making steady progress towards building the world's first use for quantum computer and applying its enormous power to important challenges.
A quantum computer will be a gift to future generations, giving them the new tool to solve problems that today unsolvable.
Thank you. That was Hartman Nevin at TED 2024.
If you're curious about TED's curation, find out more at TED.com slash curation guidelines.
And that's it for today.
TED Talks Daily is part of the TED Audio Collective.
It was mixed by Christopher Faisy-Bogan, additional support from Emma Taubner, Daniela Balorezzo, and Will Hennessy.
I'm Elise Hugh. I'll be back tomorrow with a fresh idea for your feed.
Thanks for listening.
