Automotive

AI-Defined Vehicle Era

10:00-10:30

The automotive industry is entering a new era—one where vehicles are no longer defined by mechanical capability but data, and intelligent decision-making: The AI-Defined Vehicle Era. AI is reshaping compute needs for driver assistance planning, perception and decision-making to personalized in-cabin experiences. Requirements for mixed critical, high-performance and efficient processing are driving new technology introductions, like Arm Zena Compute Subsystems. Join us to learn how to scale a new foundation for this new era and how that supports the latest Automotive trends in Japan.

Driven by Innovation

10:35-11:05

In the AI era, delivering advanced mobility solutions at scale and speed is a shared industry ambition. Achieving it requires a standardized, collaborative approach on, built on the right technical and strategic foundations. In this session, Arm is joined by Honda R&D to discuss how we're turning that vision into reality.

Accelerating Time to Market using Arm Virtual Platforms and Realizing Virtual System Development

11:10-11:55

As vehicle complexity grows, so does the need for early software development and validation before hardware availability. Virtual Platforms provide a range of high-fidelity simulation environments that enables developers to start building, testing, and optimizing automotive software well ahead of silicon availability. In this session, we will take you through how best to use these important tools to accelerate vehicle software development by up to 2 years as we enter the AI-Defined era. Arm and Siemens will provide insights into how to overcome challenges faced by the industry and how to utilize vehicle simulations. By applying Arm CSS for auto and PAVE360 together, Arm and Siemens offer a solution that makes virtual development for software-defined vehicles a reality.

Scalable Solutions

13:15-14:00

As vehicles become intelligent, connected platforms, the complexity of software and hardware continues to rise. Meeting these demands requires a new approach to automotive compute. This session explores how the industry achieves scalable, power-efficient solutions for next-gen mobility and supports continuous innovation.

Expectations and Challenges: Chiplets in the Next Generation of Mobility

14:05-14:50

The industry is increasingly turning to chiplet-based architectures as a path to greater scalability, flexibility, and diversity. Revolutionizing vehicle hardware in this way demands new thinking, new operating models, and broad collaboration across the ecosystem. However, mobility requires more real-time operation, functional safety and reliability than HPC. Who is driving this transformation, and how is the work progressing??

The Power of Many

15:10-15:55

Ensuring the entire software stack is optimised is important in the AI-Defined vehicle era.

In this session, we’ll talk to ecosystem partners who are collaborating to innovate and leverage new methodologies at scale. Join us to learn how early software availability is driving the future of automotive and enabling the industry to move at pace.

The Future of Automotive

16:00-16:30

The automotive industry is undergoing a fundamental transformation—from the mechanical era, to the software-defined era, and now into the AI-defined era. Cars are no longer just machines; they are continuously connected, enhanced by AI, and increasingly defined by software. This panel brings together leaders from across the industry to explore what vehicles will look like in 10 years and what it will take to make that vision a reality.

Discussion will include how AI can make road networks safer, the new security considerations that arise, and the convergence of advanced driver assistance systems (ADAS) and in-vehicle infotainment (IVI) into unified platforms. The panelists will also share perspectives on the evolving driver experience and the critical role of compute efficiency, scalable hardware, and AI enablement in shaping the future.

Infrastructure

The Future of AI Infrastructure: An Overview

13:10-13:40

The rapid growth of AI is accelerating a major shift in infrastructure technology. Arm Neoverse has emerged as the platform of choice for several key areas of this transformation including AI head nodes, on-CPU AI compute, hypserscale DPUs, AI focused DPUs, and AI accelerators bridged to Arm Neoverse cloud compute. Arm Neovers offers the best combination of total cost of ownership (TCO), performance, efficiency, and design flexibility. This roadmap session will look in detail at the capabilities of the latest Neoverse CSS offerings, the kind of innovation that has allowed Arm partners to pursue and accelerate thier innovative products to market for the AI era.

Software Driving Tomorrow's Datacenters

13:45-14:15

Uncover the critical role of software in scaling and optimizing next-gen AI workloads.

Computing Infrastructure in the AI Era: A Sustainable future AI platform envisioned by FUJITSU-MONAKA

14:20-14:50

Fujitsu, celebrating its 90th anniversary this year, is driving innovation in differentiated fields with AI at the core of its digital technology strategy. Processor technology, a domain in which Fujitsu has delivered value for over 50 years, is becoming increasingly vital for building sustainable, safe, and secure AI computing platforms. This presentation introduces the technical overview of FUJITSU-MONAKA, a next-generation processor for data centers featuring a 2nm process, arm-v9 architecture, and 3D many-core design. It also presents Fujitsu’s vision for an AI-HPC platform through future CPU-GPU collaboration.

Forefront of SoC design and development supporting next-generation infrastructure

15:15-15:45

To meet customer needs in the fast-changing market, Socionext acts as a "Solution SoC" company that delivers differentiated SoCs by being involved from the concept stage, then proposing the optimal choices and the best integration of components in the design ecosystem. Socionext is developping and utilizing a common development platform that can be applied to various fields based on computer architecture. This talk explains Socionext's Solution SoC / Computer Architecture-based platform and introduces recent Socionext's design experience in 3D IC.

Fireside Chat: From x86 to Arm – A Customer Success Story

15:50-16:10

Meta and Arm discuss how they achieved performance parity with x86 while cutting datacenter power use by up to 40%, showing why cloud and AI leaders are migrating workloads to Arm for lower cost, sustainability, and future-ready infrastructure.

The Future Enabled by AI-RAN and the AITRAS Orchestrator

16:15-16:35

SoftBank has proposed "AI-RAN", a technical concept that creates new value by integrating communication and AI technologies.
To realize this concept, SoftBank is advancing the development of its AI-RAN product "AITRAS". This session introduces vRAN running on Arm-based, high-efficiency and low-power architectures, AI use cases enabled by AI-RAN, and the AITRAS orchestrator, which dynamically manages these workloads.

IoT

Opportunities in Edge AI

10:00-10:30

AI is changing the way we think about everything and is transforming how we live, work and play. This trend will only accelerate as more and more intelligence moves to the Edge, in fact it has been predicted that over 70% of AI inference will run at the Edge by the end of the decade. Driven by the need for lower latency, increased privacy and a different economic models, AI is being used increasingly in everyday applications and devices and, as the most pervasive compute platform in the world, we believe the future of AI is on Arm

Please join us to hear how we will help you drive this amazing opportunity in Edge AI, as it becomes the dominant technology used across IoT projects over the next three years

Accelerating Smart Product SDLC with AI Agent

10:35-11:20

As IoT and AI/ML technologies become increasingly prevalent, embedded systems are growing more complex, presenting challenges in maintaining and managing edge devices, ensuring quality, and adapting to service-oriented business models. While generative AI is revolutionizing software development with its groundbreaking code generation capabilities, embedded systems face unique challenges, including hardware constraints and legacy codebase requirements. Furthermore, since the development lifecycle encompasses numerous activities beyond coding, a more comprehensive approach is essential for true optimization. In this session, we will explore practical applications of generative AI in embedded software development, demonstrating how to maximize its transformative potential while addressing embedded-specific constraints. Through concrete examples using AWS services for developing and managing machine learning models for edge devices, we will showcase how to effectively balance cutting-edge AI capabilities with embedded system requirements. This practical session is designed for practitioners seeking to optimize their development cycles, particularly those interested in leveraging the revolutionary possibilities of generative AI in embedded systems development. We will provide actionable insights into implementing these advanced technologies while navigating the unique challenges of the embedded development landscape.

The Future of High Performance Edge AI

11:25-11:55

Edge AI has emerged in recent years as a key component to successfully deploy new AI use cases, scaling from simple keyword spotting to large language models and applications.

The benefits of edge deployments, such as security, safety, privacy and low latency are driving millions of deployments. To enable this, Arm and its partners are delivering key new technologies, IP, software and tools that are game changers for Edge AI devices, offering scalability from real time deployments to rich operating systems.

During this talk, we will explore the latest technologies, ecosystem and tooling, and share what's coming next. We will also demonstrate concrete use cases enabled by Arm and its hardware and software partners. Join us in this journey to high-performance Edge AI.

ExecuTorch on Arm

13:15-14:00

ExecuTorch, Meta's first-party edge runtime for natively deploying PyTorch models, offers optimized inference for resource-constrained devices. From the project's inception, ExecuTorch has been developed in close collaboration with Arm, ensuring compatibility and optimal performance for Arm IP. This presentation will introduce ExecuTorch's core design principles and highlight key architectural decisions made to leverage the full potential of Arm IP. We'll discuss the substantial progress achieved thus far, demonstrating ExecuTorch's effectiveness within diverse Arm ecosystems. Additionally, we'll outline ongoing efforts and planned enhancements as we approach the full ExecuTorch release, offering attendees valuable insights into upcoming features.

The Growing Embedded Edge AI Market and Our Approach to Technical Challenges

14:05-14:50

With the rapid advancement of AI/ML technologies, the embedded edge AI market is expanding quickly, especially in environments requiring real-time processing and low power consumption. In this seminar, we will explore how Renesas Electronics’ AI/ML-enabled MCU/MPU products bring intelligence from cloud to edge. We’ll introduce specific product families and solutions, and discuss how they contribute to smarter decision-making and operational efficiency in business settings.

Standardizing and Optimizing the IoT Tooling Ecosystem

15:10-15:55

As part of a more efficient development landscape, the ecosystem increasingly benefits from Arm’s investment in efficient open-source tools reducing the efforts for maintaining dedicated toolchains. This presentation outlines how Arm enables the industry with standardised and optimised IoT tools—empowering partners to leverage LLVM compiler and a growing portfolio of VS Code extensions for debug and trace.

These tool components provide an easy-to-use, modern, integrated tool environment that may be extended with domain specific features. It delivers best-in-class developer experience and ensures compatibility and scalability across the ecosystem. With this robust tool and software foundation, Arm is shaping the future of an efficient, collaborative embedded development experience.

Simplifying Deployment on Arm: Ensuring Security and Compliance with Linaro ONELab

16:00-16:30

Navigating interoperability challenges while meeting new regulations such as the EU Cyber Resilience Act (CRA)/JC STAR is increasingly critical.

This session with Renesas demonstrates how improvements in Arm’s SystemReady Compliance Tooling streamlines interoperability testing and the transition to Arm by continuously identifying compatibility issues. Leading to simplified compliance with Arm SystemReady, accelerating your path to market.

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Further Information

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