Infineon Technologies

Texas Instruments $Texas Instruments(TXN.US) doubled DC sales YoY and grew gross margins by 330 bps QoQ. FCF exploded with cut back in CapEx, but this is one of the few companies that was ahead of the curve with all their CapEx spend to get capacity ready.

They mentioned in the CC that power semis content will only grow as more DCs get built and come online.

They had a great report despite the AH reaction, and expect data center sales to be strong for the foreseeable future.

Power semis look good while many are ignoring them for other names.

$Infineon Technologies(IFNNY.US) $ON Semiconductor(ON.US) $STMicroelectronics NV(STM.US) $Analog Devices(ADI.US)

Morgan Stanley: AI Infrastructure Meets Humanoids

> Could have $305B semiconductor sales by 2045 related to humanoids, about 24% cost of components coming from semis by that time frame. Up from 5% by today.

> Potentially 1B units/year by 2045.

> Humanoids within semi ecosystem will be 15% of spend as early as 2040.

> Infineon & STMicroelectronics top picks from Europe. Both supplying microcontrollers.

> STMicro: AI vision. Time of flight sensors and experience with Mobileye for vision pro sensors.

> Infineon: inverters, on board charger, battery management system.

> The bill of materials for each of these companies is $500 for Infineon, over $700 when including the power semis. STMicro $300-$600, whether you have a consumer or high end industrial robot.

AI Infrastructure

> Going towards 800VDC, GaN and SiC will be ~35% of bill of materials for server racks.

> The best name based on power efficiency, delivery, roadmap, scale is Infineon.

> Infineon has a great array of products an manufacturing advantage such as 300 mil and thin wafer handling.

> Two things about servers comes down to as you enter the server and as you enter the GPU. Infineon has growth in both areas with GaN and vertical power delivery.

> Infineon is a strong player in 400V and 480V, the Oberon structure as it is called for Nvidia. They do well with TPUs, Trainium, and other ASICs. It is about $1.5B of sales (~10%). Expected to grow to $2.5B and then $3-4B in FY28.

$STMicroelectronics NV(STM.US) $Infineon Technologies(IFNNY.US)

Renesas Electronics: AI Infra & Compute

The Rise of AI Servers and Inference Compute

> Total general server shipments are expected to grow modestly (~1.3x) from 2024 to 2030. In contrast, AI Server volumes are projected to scale dramatically, growing ~2.4x, effectively doubling in volume over the period.

> While GPUs have driven the initial training wave, the market is seeing a major pivot toward AI ASICs and CPUs as the industry shifts heavily toward inference. AI ASIC shipments are projected to grow ~3.0x by 2030, vastly outstripping GPU growth (~1.5x) and standard CPU growth (~1.7x).

Revenue Drivers and Renesas’ TAM Expansion

> The primary structural tailwinds include the grid-to-rack transformation, an increase in system complexity requiring advanced MCU control, and a crucial architectural shift to 800V and vertical power architectures.

> Growth is driven heavily by Digital Power, followed by Memory Interfaces, and other supporting MCU components.

The Power Bottleneck: Grid-to-Core Architecture

> Grid Level: Managing power via Solid State Transformers (SST), Energy Storage Systems (ESS), and Uninterruptible Power Supplies (UPS) using Digital Controllers and high-voltage GaN (Gallium Nitride).

> Rack Level: Stepping down power using 800V DC/DC converters, hot-swap controllers, and Power Supply Units (PSUs).

> xPU Board Level: Delivering ultra-low voltage and high current directly to the processor via memory interfaces, high-speed optical module PMICs, and complex Vcore stages (utilizing integrated voltage regulators to optimize space and efficiency).

Exponential Power Demand Metrics

> Next-gen AI racks are projected to consume >1 megawatt (MW) of power, driving a >10x increase in power content per rack.

> The AI Infra & Compute Power TAM is scaling almost exponentially toward 2030, with Voltage Regulator Modules (VRM) making up the vast majority of this value, followed by Intermediate Bus Converters (IBC) and AC/DC stages.

> A single example leading next-gen AI board showcases the sheer complexity involved, requiring a GPU power solution with >10 Digital controllers and >100 Smart power stages, alongside a 48V IBC solution utilizing >30 MOSFETs. Dense packing drastically raises thermal constraints, making thermal performance and current density the ultimate competitive battlegrounds for silicon providers.

This is bullish for many power semi names. $STMicroelectronics NV(STM.US) $Infineon Technologies(IFNNY.US) $Texas Instruments(TXN.US) $ON Semiconductor(ON.US) $Wolfspeed(WOLF.US)