MSI Vision RS AI

• Background Problem: Individuals and small teams want to run LLM/Generative AI/video editing/3D/games, etc. locally.High-workload tasks in an "immediately usable form"• Limitations of existing methods: (1) Performance tuning, heat/power management of assembled/workstations depends on user capabilities (2) Typical gaming towers have noise, heat generation, and designs that clash with living room/office environments (3) Even if it claims to be an "AI PC", the actual management UX is separate, making the experience weak.

• Based on the CES description, the key is that AI software is built into the HMI (Human-Machine Interface), elevating the "operation/management experience" at the product level, rather than just a combination of high-performance components. • (Based on the official MSI product page) The 'living room/office-friendly' design positioning, such as the integrated curved tempered glass (270 degrees) chassis that shows the interior, differentiates it from general gaming PCs.

• Adopters: High-end gamers, creators (video/3D), power users for local inference (privacy/latency/cost reasons), small studios • B2C/B2B/B2G: B2C-focused + some B2B (small production/design organizations)

• Environmental/Regulatory Constraints: Regulatory issues are low, but the supply and price of high-end GPUs/components are a practical constraint on widespread adoption. • Industry/Market Scalability: It is easy to ride the "AI PC" trend, but it is essentially focused on the premium desktop segment (limited mass-market scalability).

• CES Award Context Evaluation: Suitable for the exhibition context as an "AI desktop showcase" that combines AI, high performance, and design. • Technical Completeness: The hardware itself is mature (the difference depends on how meaningful the built-in AI management/UX is in actual use). • Market Expectations: At CES 2026, MSI highlighted the Vision RS AI 2nd Gen as a major product, putting AI/business PCs at the forefront—it receives attention, but competition is also fierce. • Overrated/Underrated Factors: The "AI" label does not guarantee the reality of performance/automatic optimization (actual use benchmarks and operational convenience verification are needed).