Quantum computers have the potential to solve big scientific problems that are beyond the reach of today’s most powerful supercomputers, such as discovering new antibiotics or developing new materials.
But to achieve these breakthroughs, quantum computers will need to perform better than today’s best classical computers at solving real-world problems. And they’re not quite there yet. So what is still holding quantum computing back from becoming useful?
In this episode of The Conversation Weekly podcast, we speak to quantum computing expert Daniel Lidar at the University of Southern California in the US about what problems scientists are still wrestling with when it comes to scaling up quantum computing, and how close they are to overcoming them.
Quantum computers harness the power of quantum mechanics, the laws that govern subatomic particles. Instead of the classical bits of information used by microchips inside traditional computers, which are either a 0 or a 1, the chips in quantum computers use qubits, which can be both 0 and 1 at the same time or anywhere in between. Daniel Lidar explains:
“Put a lot of these qubits together and all of a sudden you have a computer that can simultaneously represent many, many different possibilities … and that is the starting point for the speed up that we can get from quantum computing.”
Faulty qubits
One of the biggest problems scientist face is how to scale up quantum computing power. Qubits are notoriously prone to errors – which means that they can quickly revert to being either a 0 or a 1, and so lose their advantage over classical computers.
Scientists have focused on trying to solve these errors through the concept of redundancy – linking strings of physical qubits together into what’s called a “logical qubit” to try and maximise the number of steps in a computation. And, little by little, they’re getting there.
In December 2024, Google announced that its new quantum chip, Willow, had demonstrated what’s called “beyond breakeven”, when its logical qubits worked better than the constituent parts and even kept on improving as it scaled up.
Lidar says right now the development of this technology is happening very fast:
“For quantum computing to scale and to take off is going to still take some real science breakthroughs, some real engineering breakthroughs, and probably overcoming some yet unforeseen surprises before we get to the point of true quantum utility. With that caution in mind, I think it’s still very fair to say that we are going to see truly functional, practical quantum computers kicking into gear, helping us solve real-life problems, within the next decade or so.”
Listen to Lidar explain more about how quantum computers and quantum error correction works on The Conversation Weekly podcast.


Elon Musk’s Empire: SpaceX, Tesla, and xAI Merger Talks Spark Investor Debate
SpaceX Pushes for Early Stock Index Inclusion Ahead of Potential Record-Breaking IPO
Elon Musk’s SpaceX Acquires xAI in Historic Deal Uniting Space and Artificial Intelligence
SoftBank Shares Slide After Arm Earnings Miss Fuels Tech Stock Sell-Off
BTC Flat at $89,300 Despite $1.02B ETF Exodus — Buy the Dip Toward $107K?
Global PC Makers Eye Chinese Memory Chip Suppliers Amid Ongoing Supply Crunch
Baidu Approves $5 Billion Share Buyback and Plans First-Ever Dividend in 2026
SoftBank and Intel Partner to Develop Next-Generation Memory Chips for AI Data Centers
Nasdaq Proposes Fast-Track Rule to Accelerate Index Inclusion for Major New Listings
TSMC Eyes 3nm Chip Production in Japan with $17 Billion Kumamoto Investment
Nintendo Shares Slide After Earnings Miss Raises Switch 2 Margin Concerns 



