Classiq + UC Chile: What's actually launching

Classiq, the Israeli leader in quantum software, announced on June 4, 2026 the launch of joint research with Pontificia Universidad Católica de Chile (UC Chile), one of the most prestigious universities in Latin America. The goal is to use quantum artificial intelligence for biomedical image analysis — that is, X-rays, CT scans, MRI, and microscopic images.

The core of the technical solution is the integration of the Classiq platform with NVIDIA CUDA-Q, an open-source development platform for quantum computing that enables hybrid programming — combining classical GPU computations with quantum circuits (QPU) within a single program.

For an idea of the performance: in March 2026, Classiq demonstrated that their integration with CUDA-Q shortened the execution of a 31-qubit quantum circuit from 67 minutes to just 2.5 minutes on a single NVIDIA A100 GPU. That is a 27x speedup, which fundamentally changes the possibilities for iterative development of quantum algorithms.

Why biomedical images specifically?

Medical image analysis is one of the most complex tasks for artificial intelligence. Each image contains millions of pixels, while pathological changes (tumors, fractures, lesions) may be only a few pixels in size. Classical convolutional neural networks (CNNs) today achieve high accuracy, but they hit limits when processing huge datasets and when detecting rare, subtle anomalies.

Quantum machine learning (QML) theoretically offers several advantages:

• Quantum superposition enables parallel processing of multiple states at once, which can speed up feature extraction from image data.
• Quantum entanglement can capture complex correlations between pixels that classical networks overlook.
• The hybrid approach of Classiq + CUDA-Q combines the best of both worlds: classical GPUs for preprocessing and quantum circuits for specialized computational tasks.

Classiq is no newcomer to life sciences. Back in November 2023, they announced the creation of the Quantum Center for Life Sciences in collaboration with NVIDIA, and their platform is used by pharmaceutical companies to accelerate drug discovery.

What Classiq and its Quantum AI agents can do

Classiq differentiates itself from the competition by offering high-level modeling of quantum algorithms. Instead of manually programming individual gates, the developer describes the intent in the high-level programming language Qmod and the Classiq synthesis engine automatically generates an optimized quantum circuit for specific hardware.

In April 2026, Classiq also announced the certification of the first generation of expert Quantum AI agents — systems that generate structured, executable quantum programs from natural language. This means a researcher from UC Chile can describe a medical problem in plain English and the agent will propose a quantum algorithm.

The platform is hardware-agnostic — it supports over 75% of publicly available QPUs from manufacturers such as IonQ, Quantinuum, Rigetti, or QuEra. This is crucial because the university team does not have to be tied to a specific hardware manufacturer.

NVIDIA CUDA-Q as a bridge between worlds

CUDA-Q is NVIDIA's open-source platform for accelerated quantum supercomputing. Its main strength lies in the hybrid programming model: the developer writes in Python or C++ and CUDA-Q automatically distributes the computation between GPU, CPU, and QPU.

Key features of CUDA-Q:

• Up to 180× faster simulation of quantum algorithms compared to CPU
• Support for scaling to multiple GPUs (up to 300× speedup)
• Tools for quantum error correction (QEC)
• Integration with AI and HPC libraries

It is this platform that will power the computations for biomedical image analysis at UC Chile. Researchers will gain access to infrastructure that would otherwise be beyond the reach of an individual university.

Czech and European context

For the Czech reader, the topic is relevant for several reasons. The European Union is massively investing in quantum technologies — the Quantum Flagship program has a budget of over 1 billion euros, and the Czech Republic got involved in 2026 with the launch of Czech AI Factory in Ostrava, which will also serve as a node for quantum computing.

Czech universities — for example, CTU, Palacký University Olomouc, or Masaryk University — have active research groups in the field of quantum computing and medical image processing. The Classiq-UC Chile type of collaboration shows a model that could also serve as inspiration for Czech academic institutions: connecting commercial quantum software with academic research and hardware infrastructure from NVIDIA.

Moreover, Classiq collaborates with European institutions — for example, with CERN (smart energy grid project with Wolfram) or with the Fraunhofer Institute in Germany. Their platform is also available through the AWS Marketplace, meaning that European research teams have access to it as well.

What it means in practice

For now, it is not about a quantum computer diagnosing your CT scan tomorrow. Current quantum processors are still in the NISQ (Noisy Intermediate-Scale Quantum) era — they have tens to hundreds of qubits, but suffer from noise and errors. Nevertheless, the hybrid approach that combines classical GPUs with quantum circuits already allows testing algorithms on real data today and verifying where quantum computing brings an advantage.

According to analytics firm McKinsey, quantum computing could generate an annual value of 450–850 billion dollars by 2035, with healthcare and life sciences among the most promising sectors. Classiq, which in May 2025 closed a record investment round of 110 million dollars (the largest in quantum software history), is betting that the key to practical use is not waiting for perfect hardware, but building software that can extract the maximum from what is available today.