OktoberTech Silicon Valley 2025 underscored that Infineon no longer sees itself as a niche component supplier watching the AI wave from the sidelines.
The company used the event, held at the Computer History Museum in Mountain View, Calif., to frame a sharper, more assertive narrative: Infineon aims to be the foundational infrastructure provider for physical AI, edge intelligence, high-density AI data centers, and, increasingly, next-generation quantum systems.
The question for customers, partners, and investors is whether the company substantiated that ambition with enough technology, ecosystem proof, and strategic clarity to be credible. The evidence presented at the event points to yes.
Trust Platform for Advanced Systems
Infineon was careful to position OktoberTech Silicon Valley not as a product smorgasbord, but as what CMO and Management Board Member Andreas Urschitz described as a “trustful platform” that brings together innovators “who want to be part of the solution of tomorrow.”
That choice of framing matters because the environment is capital-intensive, with AI buildouts, robotics deployment, and electrification, and customers are looking for long-term partners with proven execution.
Infineon backed up its trust story with concrete proof points, most notably its fifth Bosch Global Supplier Award. The honor affirmed Infineon’s status as a top-tier supplier of next-generation automotive architectures. It showcased its strengths across microcontrollers, sensors, connectivity, and power, further reinforced by significant manufacturing investments such as 300 mm GaN wafer processing.
The company’s new long-term green power purchase agreements with PNE AG and Statkraft in Germany and Spain signaled that Infineon is aligning its operations with the decarbonization narrative it sells, committing to 100% green electricity and enabling additional renewable energy buildout.
Taken together, these moves framed OktoberTech Silicon Valley as more than a showcase. They underlined Infineon’s claim to be a strategically resilient, sustainability-aligned infrastructure partner for the AI era.
Infineon’s Role in Humanoid Systems
The robotics and physical AI content at OktoberTech Silicon Valley was central to that claim. Infineon’s leadership made a disciplined choice: rather than chase headlines about full-robot platforms, they mapped out how a humanoid or advanced autonomous system could be architected on Infineon technology.
In keynote and panel discussions, executives detailed how efficient drives using GaN and SiC can shrink joint sizes and extend runtime, how battery management and safety MCUs underpin reliability, how radar, environmental, and 3D sensing enable perception, and how secure connectivity and embedded security harden systems operating alongside people.
Infineon’s Division President of Power and Sensor Systems, Adam White, emphasized that customers increasingly expect not individual parts, but platform-level reference designs that reduce integration risk in complex robots and humanoids.
The message was clear and commercially pragmatic. Infineon is not trying to own the robot’s “brain.” It is positioning itself as the company that supplies and secures almost everything that allows the brain to sense, move, power up, and operate safely.
Given its depth in power, sensing, connectivity, and security, this is a credible and defensible lane, and OktoberTech Silicon Valley demonstrated that Infineon understands the requirements of industrial, logistics, and emerging humanoid deployments better than many would-be entrants.
Edge Intelligence Essential
Edge AI emerged as the second pillar of that strategy and one of the event’s strongest storylines. In conversations and demos, Infineon executives drew a clear distinction between monolithic cloud AI and distributed intelligence (“where the action is”) at the device level.
Infineon’s Division President of Connected Secure Systems, Thomas Rosteck, and others argued that many high-value use cases simply cannot tolerate cloud dependence: real-time control in vehicles and robots, privacy-critical health and home data, and systems deployed in regions with unreliable connectivity.
PSOC Edge and Deepcraft in Action
The launch positioning around PSOC Edge and the Deepcraft AI Suite translated that thesis into practice, demonstrating small language model and signal processing workloads running fully on-device with competitive responsiveness and significantly lower power consumption.
In an on-site discussion, Infineon’s EVP of IoT, Wireless, and Compute Business Sam Geha highlighted three advantages Infineon sees as decisive: deterministic latency for safety and autonomy, the ability to avoid wireless or cloud dependencies in cost-sensitive designs, and strong privacy by keeping biometric and behavioral data at the edge. That framing aligns tightly with regulatory and customer trends around security and data protection.
When combined with Infineon’s heritage in secure MCUs and connectivity, OktoberTech Silicon Valley made a persuasive case that the company is structurally well-positioned to power and enhance security for the next wave of edge AI endpoints, from health wearables and smart home devices to industrial controllers and automotive systems.
Building the 800 VDC Power Spine
The AI data center story at OktoberTech Silicon Valley elevated this positioning to infrastructure scale. Here, Infineon’s announcement supporting Nvidia’s move toward an 800 VDC architecture for AI racks was more than opportunistic alignment.
The technical sessions outlined a complete power path from the grid to the core using Infineon’s CoolSiC and CoolGaN. They advanced hot-swap and protection solutions to enable safe operation, high efficiency, and live serviceability at 800 VDC.
With AI rack power projected to climb from roughly 120 kW to as high as a breathtaking 1 megawatt later this decade, the economics and sustainability of AI infrastructure hinge on squeezing losses out of every conversion stage and minimizing downtime.
Infineon executives leaned into the assertion that “there is no AI without power,” positioning the company as the de facto backbone provider for AI “gigafactories of compute” that must be both energy efficient and continuously serviceable.
By offering integrated hot-swap controllers, SiC-based protection, and high-frequency conversion reaching efficiency levels near 98% per stage, Infineon presented a differentiated, system-level solution rather than a parts catalog.
For hyperscalers and AI cloud operators, that combination of technology, safety, and manufacturability is highly relevant. OktoberTech effectively reinforced the message that Infineon intends to own the power spine from medium-voltage input through to accelerator boards in next-generation AI data centers.
Quantum Needs a Manufacturing Backbone
Quantum computing could have been the outlier topic, but instead, it pulled the narrative forward. The joint discussion with Quantinuum framed quantum not as a marketing experiment, but as a necessary complement to classical and AI compute in a world where power demand from data centers is scaling almost exponentially.
Infineon’s SVP and GM for the Power Switches Business Line, Richard Kuncic, noted that the company already “takes care of the complete power flow in the data center from grid to core” and argued that the current trajectory of power consumption is unsustainable without “smarter ways of computation,” with quantum emerging as one of the solutions for mathematically intractable problems.
Quantinuum Sr. Director of Product Technologies, Russell Stutz, was explicit about why the partnership matters technically: scaling trapped-ion systems to hundreds of thousands or millions of qubits requires advanced micro- and nanofabrication, industrial process control, and cost discipline, all areas where Infineon brings decades of expertise.
Infineon is positioning itself as the manufacturing and engineering bridge that turns fragile physics experiments into scalable quantum hardware. That role mirrors its broader position in power and automotive: not owning the full stack but enabling others to scale reliably.
From a strategic standpoint, OktoberTech Silicon Valley succeeded in tying quantum back to Infineon’s core competence in production and system quality, reinforcing the idea that the company will remain relevant as compute architectures evolve.
EVs as Intelligent Energy Assets
The closing “Hidden Revolutions from Mobility to the Grid” panel made explicit what was implicit throughout the event: Infineon’s vision is fundamentally system-level. Moderator Negar Soufi, Infineon’s SVP and GM for the high voltage automotive business, described EVs as “moving energy assets” that both draw from and feed into a more dynamic grid.
The panel accentuated that semiconductors and software power this transformation in the precise domains Infineon serves: efficient propulsion, secure connectivity, bidirectional charging, and AI-enhanced energy management.
The discussion around software-defined vehicles, automotive Ethernet, solid-state transformers, and grid infrastructure connected the dots between vehicle, data center, and grid demands.
It reinforced three themes in the Infineon DNA: efficiency as a financial and environmental currency, modular platforms that scale across applications, and intelligent, secured control that links endpoints back into the energy system.
This broader context strengthened the argument that Infineon is not only selling components into growth markets but helping shape how electrified mobility, AI compute, and infrastructure interact.
Credible System Strategy for the AI Era
Taken together, did OktoberTech Silicon Valley make the case that Infineon will remain a force in robotics, edge AI computing, AI data center infrastructure, and quantum computing?
On balance, yes, and in a way that aligns with how sophisticated buyers evaluate strategic partners.
Across robotics and physical AI, Infineon presented itself as a system enabler with credible breadth: efficient power stages, rich sensing, connectivity, and security, delivered as integrated, application-ready platforms.
In edge AI, it couples competitive silicon with the PSOC Edge and Deepcraft AI Hub software stack and a strong privacy and security argument, mirroring regulatory direction and real deployment needs.
Within AI data centers, it showed up not as a me-too supplier but as a co-architect of 800 VDC power systems with Nvidia, offering solutions that directly influence uptime, TCO, and sustainability. In quantum computing, Infineon’s role as a high-volume, precision manufacturing partner for leading platforms gave it a clear and defensible position in an emerging market without overreaching.
Execution Risks, but Strong Positioning
Naturally, execution questions remain. Infineon will need to continue investing in software, tools, and reference designs so that robotics and edge AI developers see it as the fastest path from prototype to product. It must sustain leadership in SiC and GaN and secure microcontrollers against intensifying competition.
Its quantum partnerships must evolve from promising pilots into meaningful, recurring business. But these are challenges of follow-through, not flaws in the strategic thesis.
What OktoberTech Silicon Valley 2025 demonstrated is that Infineon understands where value is migrating in the age of AI and electrification: to companies that can make intelligence physical, efficient, secure, and scalable.
By anchoring its message in tangible partnerships, manufacturing investments, sustainability commitments, and end-to-end solutions, Infineon used OktoberTech Silicon Valley to argue that it is one of those companies.
The argument, judged on the substance presented, was convincing.
