Keynote by Vivek Mahajan CTO Fujitsu India AI Impact Summit
20 Feb 2026 16:00h - 17:00h
Keynote by Vivek Mahajan CTO Fujitsu India AI Impact Summit
Summary
The session centered on AI sovereignty and Fujitsu’s strategy to deliver sovereign AI capabilities for nations such as India [1][2][4-8]. Sovereignty is defined as owning, controlling, and flexibly managing data and models without excessive third-party dependence [4-10]. Fujitsu highlighted its 90-year history and breakthroughs, including upcoming 2 nm ARM servers and a 20-exaflop AI supercomputer powered by Monaca [15-22][36-41]. Monaca, a Japan-made 2 nm chip, will be succeeded by a 1.4 nm version with 256-core and 128-core CPUs and an NPU for inference [42-48][55-58]. Fujitsu’s software stack is fully open source, avoiding lock-in and tuned for AI, HPC, and data-center workloads [44-53]. Its quantum roadmap aims for 250 logical qubits by 2030 and a 10 000-qubit machine within three years, placing it among the top three players [62-71]. Network offerings include a 1.6-terabit low-power switch for long-range transmission and open-RAN integration to efficiently orchestrate AI workloads [76]. The Takane LLM platform and Kozuchi AI agent, built on a proprietary security layer, enable domain-specific, tunable, secure models for defense, healthcare, and finance [77-84]. Fujitsu markets an end-to-end solution that combines compute, network, and software, allowing selective adoption and leveraging partners such as AMD, Lockheed Martin, and Supermicro [85-99]. These components aim to create a physical AI platform that runs on edge devices such as robots, drones, and medical equipment [86-95]. The session concluded with an announcement of a fireside chat featuring CDAT and Intel executives, moderated by Aman Khanna [100-104]. Overall, Fujitsu positions itself as a Japanese alternative to U.S. vendors, offering open, secure AI infrastructure across compute, quantum, networking, and software [31-33].
Keypoints
Major discussion points
– Definition and importance of AI sovereignty – The speaker frames sovereignty as the ability to own, control, and flexibly manage data and AI models without heavy reliance on third-party providers, stressing its relevance for nations such as India that seek leadership in AI [1-9][10-11].
– Fujitsu’s sovereign-by-design hardware portfolio – Fujitsu highlights its home-grown, cutting-edge compute assets-including 2 nm ARM-based “Monaca” servers, a planned 20 exaflop AI supercomputer, NPUs for inference, and an open-source software stack – all built in Japan to ensure security and avoid vendor lock-in [20-23][36-43][44-48][55-58].
– Quantum and HPC integration as a strategic advantage – The company positions its quantum roadmap (250 logical qubits by 2030, 1 000-qubit machine launching soon) alongside high-performance computing to deliver mission-critical AI workloads, underscoring a unique combined capability [62-71][69-73].
– Network and photonics solutions for low-latency, power-efficient AI delivery – Fujitsu describes a 1.6 Tbps (future 3.2 Tbps) optical switch, long-reach low-power transmission, and open-RAN orchestration that together enable secure, high-speed movement of AI workloads across data-center and edge environments [76].
– End-to-end AI software platform and ecosystem partnerships – The “Takane” large-language-model platform and “Kozuchi” AI-agent stack provide domain-specific, fine-tunable, and secure models, while Fujitsu stresses a total-solution approach-partnering with firms such as AMD, Lockheed Martin, and Supermicro-to deliver compute, network, and application layers as a unified offering [78-86][92-99].
Overall purpose / goal
The discussion is a strategic presentation aimed at positioning Fujitsu as a provider of a complete, sovereign AI ecosystem-encompassing hardware, quantum/HPC, networking, and software-that enables governments and enterprises (especially in markets like India and Europe) to retain full control over their data and AI workloads while avoiding dependence on foreign cloud or AI vendors.
Tone of the discussion
The tone is consistently promotional and confident, using technical detail to convey credibility and optimism about Fujitsu’s capabilities. It remains upbeat throughout, with no noticeable shift to a more neutral or critical stance.
Speakers
– Speaker 1
– Role/Title: Presenter (Fujitsu executive delivering a keynote on AI sovereignty)
– Area of Expertise: Artificial intelligence, sovereign AI platforms, high-performance computing, quantum computing, networking, Fujitsu hardware and software solutions
– Speaker 2
– Role/Title: Moderator / Session host (introducing the upcoming fireside chat)
– Area of Expertise: Event moderation / facilitation[S1][S2][S3]
Additional speakers:
– None identified beyond the two speakers listed above.
Speaker 1 opened the session by linking the theme of AI sovereignty – also raised in the previous plenary – to the strategic ambitions of nations such as India that wish to become leaders in artificial intelligence. He framed sovereignty not as a political slogan but as a technical requirement: organisations must own and control their data while retaining the flexibility to manage, tune and deploy AI models without excessive reliance on external providers [1-10][11].
He then highlighted Fujitsu’s 90-year heritage, from early DRAM and mainframe work alongside IBM to recent breakthroughs such as the world’s first two-nanometre ARM-based servers and a leading quantum-technology roadmap [14-23][20-22][21]. In 2021 Fujitsu launched a U.S. brand that aggregates all of its solutions for customers, reinforcing the company’s global reach [34-35].
The vision for a sovereign AI platform rests on three pillars – software, compute and networking [26-28].
Compute & Quantum – Fujitsu noted that it operated the fastest supercomputer in the world for five consecutive years, a record that stood until two years ago [36-38]. The upcoming hardware centrepiece is the Monaca two-nanometre ARM-based chip, which has confidential computing built at the hardware level to drive security [38-41]. Within two years the company plans to assemble a 20-exaflop AI supercomputer around Monaca, followed by a 1.4-nanometre processor family that will include a 256-core CPU, a 128-core CPU and an integrated NPU specialised for AI inference [42-48]. The stack is described as completely open with “nothing locked in,” allowing customers to fine-tune models without vendor lock-in [44-48][44-46].
On the quantum side, Fujitsu positions itself among the world’s top three quantum players. Its roadmap targets 250 logical qubits by 2030, with a 1 000-qubit machine scheduled to go live in Kawasaki next month and a 10 000-qubit system expected within three years. Integration of quantum processors with high-performance computing is intended to support mission-critical AI workloads that demand both speed and precision [62-66][67-71][62-71].
Networking – The company is developing a 1.6 TB photonic switch (expandable to 3.2 TB) that provides long-range, low-latency, power-efficient transmission for data-centre interconnects [70-71]. This hardware is paired with an open-RAN orchestration framework that can move AI workloads efficiently across optical and wireless links, extending sovereign AI capabilities to edge environments [72-73].
AI Software Stack – Fujitsu’s domain-specific platforms comprise the Takane large-language-model (LLM) platform and the Kozuchi AI-agent stack, both built on Fujitsu’s own security layer. They target verticals such as defence, nuclear energy, healthcare, finance, government and manufacturing [84-86]. Because the underlying software stack is fully open, customers can fine-tune models and use third-party tools without becoming dependent on Fujitsu-only solutions [44-48][44-46].
Fujitsu emphasises that it does not sell isolated components but an end-to-end solution that bundles compute, networking and application layers. It has already forged partnerships with major OEMs and system integrators-including AMD, Lockheed Martin, Supermicro and various robotics manufacturers-to deliver a cohesive physical-AI platform across a range of use-cases [85-99][96-98].
Looking ahead, Fujitsu envisions a “Kozuchi” physical operating system that embeds brain-inspired intelligence into robots and other edge devices. Research on memory-retention aims to let devices such as drones, medical equipment and smartphones retain state and operate autonomously, uniting compute, network and AI software stacks at the edge [86-89][90-94].
Speaker 2 concluded the segment by announcing the next agenda item – a fireside chat featuring Mr Vivek Kaneja (Executive Director, CDAT), Mr Nitin Bajaj (Director, Sales and Marketing, Intel) and moderated by Mr Aman Khanna (Vice President, Asia Group) – and asked both speakers and the audience to clear the stage [100-104].
Overall, the presentation positioned Fujitsu as a Japanese alternative to U.S. AI vendors, offering a fully sovereign, open and integrated AI infrastructure that spans cutting-edge compute, quantum acceleration, high-capacity networking and domain-specific software, all designed to meet policy-driven demand for data ownership, security and flexibility [S7][S9][S21].
AI commerce. What I’m going to talk about is something that was discussed in the plenary session yesterday as well about sovereignty. And I believe something like sovereignty is very, very important for countries like India, which are trying to eke out a path in leading AI and being dominant in AI. Now, what is sovereignty, first of all? For us, it is being flexible. And being secure, right? So you want ownership of your data. You want to control that data. But you also want to have flexibility to manage that data, create models that meet your needs, that doesn’t have to be reliant on third party overwhelmingly. And you can modify and tune that data, right? Modify and tune those models.
So Fujitsu is on a path to – we’ve always been an innovative company, and we have a long history, and I’ll talk briefly. But how do we make that sovereign? And that’s what I’m going to talk about today. So Fujitsu, some of you might not know it. I mean, we have a 90 -year -old history, right? So we are a pretty old company. We have our roots all the way in technology. And if you look at some of the things that are demonstrated here, one megabit DRAM, for example, right? Of course, we were one of the pioneers of mainframe business along with IBM. In recent past, we’ve announced, which we will be shipping very shortly, the world’s first two nanometer servers, ARM -based servers.
We announced for quantum, if you are not aware, which I will be talking about shortly as well, we have the world’s leading quantum roadmap here that we are going to deliver. Same on networks. And our U .S. brand that we created in 2021, that effectively brings all of Fujitsu’s solutions. to be consumed by our customers. Now, how does this work in the context of AI? And why is this relevant in the context of AI? And that’s what I’m going to talk about. So, to effectively drive artificial intelligence, you need three key components, right? You obviously need software, you need compute, and you need three networks, right? If you don’t have those three, you can’t really build an AI platform that will suit your enterprise needs.
And our focus on sovereignty here is really being independent in all of these three areas and give customers a choice. We are a Japanese company. Our technology is made in Japan and that’s where we find ourselves at a very interesting point because we are a choice to a lot of American companies as an alternative. So if you’re looking for leading edge computing technology, leading edge quantum technology, leading edge network technology, leading edge AI software technology, agentic technology, and there’s an end user application on which you can build an AI platform in the area such as defense, government, healthcare, manufacturing, finance, where you do care about privacy, this becomes very, very important. Now how do we actually drive that?
Some of the speakers talked about commerce, which are big, but at the end of the day, if you don’t have a platform that helps you deliver that, you’re never going to be sovereign, you’re never going to control the AI business. Fujitsu has a couple of areas that we are focused on, as I mentioned, computing. If you think about CPUs, you think about AMD, you think about Intel, we were, until two years ago, we had the fastest supercomputer in the world for five years running. And we announced that we will be building a 20 AI exascale AI supercomputer in about two years from now, which will be driving pretty much AI application, AI workloads. This will be powered by our Fujitsu Monaca chip, which is a two nanometer chip.
It’s built in Japan, and it is completely ARM -based, highly power efficient, focused on data centers to reduce power efficiency. Okay, and it has confidential computing built at the hardware level to drive security. Now, this comes out, the servers come out in about two months from now, the test servers. It’s ARM -based. The follow -up of this is a 1 .4 nanometer, and that will also be the world’s first 1 .4 nanometer, which has two versions, 256 -core CPU plus 128 -core CPU plus an NPU to drive exactly what India needs, sovereign AI models focused on inferencing. And this is something that I believe we will drive a lot of value in countries like India as well as Europe. I’m not going to go into this in detail, but this stack is a completely open software stack.
I just want you to remember, it’s a completely open software stack. There’s nothing locked in. There’s nothing. You don’t get locked into a Fujitsu stack. All the software that you see here, it’s completely open. It’s focused on AI. It’s focused on data centers, and it’s focused on HPC. This is what you need for AI, right? All the key areas are a lot of open source software that we have fine -tuned to work on this process. This can help you drive your AI workloads today on the Monaco servers. As I mentioned, what’s coming? There are two versions, the 256 -core CPU plus 128 -core CPU with the NPU on it. The NPU is focused on AI inferencing. You will see a lot of work going into inferencing moving forward.
And especially when you talk about sovereign, this will become extremely important, especially with small language models and medium language models. So you can contain that in a private or a semi -private environment that you can choose. Obviously, if you want large language models, you can choose what is going on on GPUs. And you can obviously choose the Monaco GPU hybrid architecture as well. Now, for those of you who might not be aware, we are extremely highly invested in quantum. We need quantum in Japan. I would say we are probably one of the top three players in quantum worldwide. We have announced a 250 logical qubit roadmap by the end of 2030, which is ahead of any other company in the world that I know of.
We make our own control systems. We are going to focus on driving the cooling systems as well. And this is going to become extremely important as you go ahead. Quantum plus HPC together driving mission -critical AI workloads. The 10 ,000 -qubit machine will go live in about three years from now. Next month, the 1 ,000 -qubit machine goes live in Kawasaki, Japan. As I mentioned, you would have HPC and Quantum working together to drive AI workloads. This is how computing will be consumed moving forward. And the software stack that we are working on, it will make transparent to you and users to use to consume compute and the workload can be optimized to whichever computer you want. Now, I’ll briefly talk about the networks because that’s the other part of the puzzle.
And finally, I’ll talk about the software for AI. photonics and wireless we’re one of the probably want two companies that does both no cares another one right and we are doing a 1 .6 terabyte switch that travels that is highly power efficient that drives about a thousand kilometer this distance distance on this long range transmission low latency low power consumption that’s the beauty of the switch right and and we are we will go on to 3 .2 tera this is very strong implicate implications and data centers that are being built in India as that would be highly highly power hungry and you would need to connect that through optical fibers and same with the wireless mobile systems okay now what we do is we also connect with open RAN and the network orchestration stack to bring the AI workloads move them in a highly efficient manner and we’re going to do that by using the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the This is the third part that really brings everything together, the AI software stack.
Fujitsu, as I mentioned at the very beginning, we are focused on sovereign. When we talk about sovereign, it’s got to be domain specific, something for defense. If you’re making nuclear plants or submarines or healthcare, this is not the data you want to put on public cloud. You want to define and build these domain specific models. Second, you need to have flexibility. You, as a company, should be able to fine tune these models to your own benefit, to your own needs. They need to be highly secure. These are the three key areas that we are focused on using what we call our Takane, the large language model platform, as well as our AI agent tech model from Kozuchi, powered by the security platform that we have built within our own research teams.
It’s a complete platform that you can use to build your own applications. Thank you. Again, I won’t go into details on this. but this is a platform that also uses third -party tools and you see on the extreme right where we have issue with their government manufacturing health care finance applications so Fujitsu has a fairly large business and services which brings all of this together so we are not just selling you pieces of technology we are selling your total solution or we are asking you to use a total solution here from compute all the way to networks and the application stack together and this is our vision that we want to continue to build on this continue to bring this to other to the end customers as well as users now where are we headed right we see all this converge in the physical AI platform space and what we are building is Kozuchi physical OS which will have the intelligence based on the brain intelligence for the robot and what that means is robots tend to forget And what we are working on, some intelligence work and research so that robots can continue to remember.
But then this technology, the compute networks, as well as the AI platform stack, comes together in edge devices. Robots are one example, but even drones or medical devices or your healthcare on your iPhones. That’s where it will all come together. And that’s the world we are aiming for. That will bring together the AI agentic platform together. That will bring the security platform together in the complete platform that could be consumed for our end users, our companies. And you can choose to play in a part that is comfortable for you. And we are obviously going to partner with a lot of different companies on this. So, as I mentioned, the software, compute, network, the three pillars.
And we are going to be able to do that. We announced in October last year, our CEO Tokita and Jensen were on stage together announcing a huge partnership on physical AI, where we’re partnering with different robotics manufacturers. So it’s working with AMD, working in defense with Lockheed Martin, Supermicro. So this is something
Thank you. Thank you so much. For the next session, we have a fireside chat between Mr. Vivek Kaneja, Executive Director, CDAT, Mr. Nitin Bajaj, Director, Sales and Marketing, Intel, and the session will be moderated by Mr. Aman Khanna, Vice President of the Asia Group. May I request all the speakers to join us on the stage, please? I also request everybody to please clear the pathway. May I request the audience to please clear the pathway?
“Speaker 1 linked AI sovereignty to the strategic ambitions of nations such as India that wish to become leaders in artificial intelligence.”
Vivek Mahajan, CTO of Fujitsu India, explicitly highlighted the importance of AI sovereignty for India during the summit, confirming the report’s statement [S7].
“Fujitsu’s 90‑year heritage and recent breakthroughs such as the world’s first two‑nanometre ARM‑based servers and a leading quantum‑technology roadmap.”
The keynote notes that Fujitsu positions itself as a Japanese alternative with 90 years of innovation, including world-first 2-nm ARM-based processors and leading quantum computing capabilities, supporting the claim [S9].
“Fujitsu operated the fastest supercomputer in the world for five consecutive years, a record that stood until two years ago.”
The TOP500 history shows that Japan’s Fugaku was the world’s fastest for the two years prior to Frontier’s takeover, but it does not confirm a five-year streak; the record lasted until two years ago, not necessarily five years [S36].
“Sovereign AI requires organisations to own and control their data while retaining flexibility to manage, tune and deploy AI models without excessive reliance on external providers.”
Discussion sources describe AI sovereignty as encompassing data control, legal frameworks, encryption-key ownership and governance, providing broader context to the report’s definition [S28] and [S29] and [S30].
The transcript contains a substantive presentation by Speaker 1 on AI sovereignty, hardware, software, quantum and networking solutions, while Speaker 2 only performs a procedural hand‑over to the next session. There is no overlap in substantive arguments or viewpoints between the two speakers.
Very low substantive consensus; the only common ground is the procedural nature of the session transition, which has limited relevance to the thematic topics.
The two speakers addressed completely different aspects of the event. Speaker 1 delivered an extensive technical and strategic presentation on AI sovereignty, hardware, software, quantum and networking solutions ([1-99]), while Speaker 2 performed a brief logistical hand-over, announcing the next fireside chat and asking participants to clear the stage ([100-104]). No overlapping substantive claims were made, resulting in no observable disagreement or partial agreement between them.
Minimal – the speakers operated in separate domains (technical presentation vs. session moderation), so there is no conflict affecting the discussion of AI sovereignty or related topics.
The discussion was driven by a series of strategically placed, high‑impact statements from Speaker 1 that progressively broadened the concept of AI sovereignty. Starting with a clear definition of sovereignty (flexibility + security), the speaker introduced concrete hardware (2 nm ARM chips, exascale supercomputer), ambitious quantum roadmaps, advanced networking, and an open, domain‑specific software stack. Each comment acted as a turning point, shifting focus from abstract policy to tangible technology, then expanding the scope from compute to quantum, network, and finally edge devices. This layered approach not only reinforced Fujitsu’s positioning as a comprehensive, non‑US alternative for sovereign AI but also deepened the conversation by linking each technological pillar to real‑world use‑cases (defense, healthcare, finance, robotics). The cumulative effect was to transform a single‑speaker monologue into a compelling narrative that framed sovereignty as an achievable, end‑to‑end technical solution rather than a purely political aspiration.
Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.
Related event
