Quantum computers on silicon chips using AI.
TL;DR Quantum computing will not scale if every program is a hand-written circuit. The future is describing what you want a quantum computer to do and letting the system handle the rest.
Hi - We are Brandon and Joel from Conductor Quantum.
We’re announcing Coda - our natural language interface for quantum computing.
Quantum computers offer a new computing paradigm for simulating the world at the atomic level. This opens up new possibilities in chemistry, materials science, and drug discovery that push beyond what the largest classical supercomputers can handle.
Problem
Using quantum computers today requires deep domain expertise and low-level tooling.
Solution
Type your problem into a box, Coda builds the quantum circuit, verifies the code and runs it on current state-of-the-art quantum computers.
If you’re completely new to quantum, we’ve included a learn mode to get you started. One of the first quantum computers we’re offering on our platform is Rigetti’s (S14) 84-qubit quantum computer. We also support simulations up to 34 qubits supported by NVIDIA cu-Quantum.
Why?
We’re building Coda because we want everyone to be able to access a quantum computer from their desk, as soon as possible.
What we’ve achieved so far
- Built the first API for low-level silicon quantum chip control.
- Partnered with quantum chip maker SemiQon and ran our software across 64 of their quantum devices.
- Shipped quantum control software for companies including Quobly and EeroQ.
What’s next?
- End-to-end GPU + QPU orchestration, so classical and quantum computation work together in a single workflow.
- Connecting Coda to our lower-level quantum control and tune-up software, closing the loop from high-level intent to device-level execution.
- Pushing our control software to larger numbers of qubits as hardware scales.
Team
Brandon, CEO, Previously a postdoc at Oxford, with multiple Nature journal publications on silicon quantum computing. Developed early AI systems for automated qubit formation. PhD, Oxford.
Joel, CTO, Built machine-learning–based control software for superconducting qubits at QuantrolOx, with prior roles at Quantum Motion and C12. MSc Physics, UCL. Left machine learning and quantum computing PhD at Oxford to start Conductor.
Raymond, Founding Engineer, Former SpaceX guidance, navigation, and control software engineer whose code flew on 100+ Falcon 9 missions. Previously worked on robotics at NASA and quantum machine learning at Cornell. BS Physics and Computer Science, Harvard.
Asks
- Join our team. We’re looking for hardcore full-stack quantum engineers who want to work across the entire stack - from device fabrication, fridge wiring to qubit operation. As well as engineers focused on quantum algorithms and applications.
- Intros to companies based on hard science - think pharma, biotech, materials, chemistry, engineering who are interested in leveraging quantum computing in their workflows.
- Email us at founders@conductorquantum.com
- Try Coda here: https://coda.conductorquantum.com/
Conductor Quantum - Quantum computers on silicon chips using AI
What is your long-term vision? If you truly succeed, what will be different about the world?
Everyone will have access to a quantum computer from their desk.
