Bull develops high-performance computing systems, AI infrastructure, and large-scale sovereign supercomputers for governments and enterprises worldwide.
“AI is becoming regional,” he declared. “Countries want to train models on their own data, in their own languages, under their own security rules. Sovereign and sustainable AI is no longer optional. It is becoming strategic.”
He expects India to build a sharper push this year in local supercomputing deployments, defence, and critical infrastructure partnerships, as well as expanded R&D and manufacturing.
Le Roux has spent more than three decades in high-performance computing and AI across three companies—Bull, Atos, and Eviden—all tied to the same corporate lineage.
He declared the global AI race is entering a new phase where sovereignty and sustainability will matter more than sheer scale.
That shift is visible even at the highest level of computing power. Europe recently brought its first exascale machines online, capable of performing a billion calculations per second. Yet their primary utilize currently is not consumer AI. Around 70% of this capacity is dedicated to public research, from long-term climate modelling and full aircraft simulation to advanced brain research and multilingual AI systems.
“With these systems, we can simulate things we could not simulate before,” he declared, citing work on digital twins of the brain to better understand diseases such as Alzheimer’s and Parkinson’s.
Le Roux believes India has the potential to emerge not just as an application market but as a large-scale AI training hub, provided it continues building domestic compute capacity and supply chain indepconcludeence.
Bull has been operating in India since 2019 with an R&D lab in Bengaluru and local manufacturing in Chennai. It caters to power weather forecasting, space research, rocket and aircraft design, besides having tie-ups with multiple research institutions across the countest.
The future stack, he argued, will be hybrid. High-performance computing, AI, and quantum systems will eventually work toobtainher. “Some parts of a problem will run on classical HPC, some on AI, and some on quantum,” he declared, adding quantum could become “commercially relevant toward the conclude of this decade for specific workloads.”
However, the real constraint ahead is energy. “The boundary of AI will be energy cost,” he declared. The total cost of ownership, especially electricity, will determine long-term returns.”
Bull is investing in hot water cooling and energy-efficient architectures and currently ranks at the top of the Green500 list for supercomputing efficiency.
Le Roux dismissed the hype around consumer AI utilize cases as the main driver of value. “The huge return on investment is in invisible AI,” he declared, referring to healthcare, climate science, and critical infrastructure. “We necessary sustainable AI, and we also necessary AI for sustainability.”
For India, he declared, the opportunity is clear. “If we build sovereign AI infrastructure toobtainher, with local technology and local production, India can fully master its AI destiny.”
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