Unveiling Smartphone Trends Arising from the Rise of AI Phones
The world is gradually transitioning into the era of hybrid artificial intelligence (AI), fostering the emergence of edge computing and the development of end devices capable of directly running generative AI applications. Since the fourth quarter of 2023, global smartphone brands have introduced their AI phones, offering users diverse experiences with generative AI applications. The development of large language models (LLMs) has become a focal point for smartphone brands seeking AI dominance, alongside the enhancement of smartphone chip computing capabilities, expected to be a key trend in AI phones this year. This report offers an overview of AI phones from the perspectives of generative AI and edge computing, highlighting key players focusing on LLMs and diverse AI applications, including smartphone brands and software service providers; explores the opportunities and challenges in the era of AI phones
Table of Contents
1. BACKGROUND: AI PHONES ENABLE ON-DEVICE COMPUTING
1.1 Generative AI Transforms User Experiences via LLMs
1.1.1 Mainstream Generative AI Applications of: Image and Text Generation, Productivity Tools
1.1.2 LLMs: Utilizing Model Parameters, Tokens, and Penalty Mechanisms to Enhance Content Accuracy and User Relevance
1.2 Rise of Edge Computing Drives Mobile Chip Performance for Local AI
1.2.1 Emergence of Hybrid AI: Convergence of Cloud AI and Edge AI Models
1.2.2 Mobile Chips Redesigned for On-Device AI: Specification Upgrades and Configuration Changes
1.2.3 10 Billion Parameters: Mobile AI's Current Limit Due to Chip and Memory Constraints
3. BRANDS FOCUS ON DEVELOPING LLM AND DIVERSE AI APPLICATIONS
3.1 Smartphone Brands Shifting from Hardware Specifications to Proprietary LLM Development
3.1.1 Android Camp: Pioneering AI Phone Launches
3.1.2 iOS Camp: Building Competitiveness with Proprietary LLMs as Market Followers
3.2 Software Services: Focusing on End-user Applications and Upgrading Proprietary OS
4. OPPORTUNITIES AND CHALLENGES: MEMORY SPECS AS A BAREEIR TO AI DEVELOPMENT
4.1 Opportunities: AI Trends Boost Sales, Chip Supply Chain Benefits from Hardware Upgrades
4.1.1 Smartphone Brands: Generative AI Optimizes User Experience, Aligning with Social Interaction Needs of Users
4.1.2 Mobile Supply Chain: Suppliers Benefit from Specs Upgrades in Early AI Phone Development
4.2 Challenges: Memory Limits as Key Barrier for AI Phone Development
5. MIC PERSPECTIVE
5.1 Mobile Brands Enhance Generative AI with LLM
5.2 Generative AI Spurs Phone Hardware Upgrades, but Memory Limits Future Development
Appendix
LIST OF COMPANIES
1. BACKGROUND: AI PHONES ENABLE ON-DEVICE COMPUTING
1.1 Generative AI Transforms User Experiences via LLMs
1.1.1 Mainstream Generative AI Applications of: Image and Text Generation, Productivity Tools
1.1.2 LLMs: Utilizing Model Parameters, Tokens, and Penalty Mechanisms to Enhance Content Accuracy and User Relevance
1.2 Rise of Edge Computing Drives Mobile Chip Performance for Local AI
1.2.1 Emergence of Hybrid AI: Convergence of Cloud AI and Edge AI Models
1.2.2 Mobile Chips Redesigned for On-Device AI: Specification Upgrades and Configuration Changes
1.2.3 10 Billion Parameters: Mobile AI's Current Limit Due to Chip and Memory Constraints
3. BRANDS FOCUS ON DEVELOPING LLM AND DIVERSE AI APPLICATIONS
3.1 Smartphone Brands Shifting from Hardware Specifications to Proprietary LLM Development
3.1.1 Android Camp: Pioneering AI Phone Launches
3.1.2 iOS Camp: Building Competitiveness with Proprietary LLMs as Market Followers
3.2 Software Services: Focusing on End-user Applications and Upgrading Proprietary OS
4. OPPORTUNITIES AND CHALLENGES: MEMORY SPECS AS A BAREEIR TO AI DEVELOPMENT
4.1 Opportunities: AI Trends Boost Sales, Chip Supply Chain Benefits from Hardware Upgrades
4.1.1 Smartphone Brands: Generative AI Optimizes User Experience, Aligning with Social Interaction Needs of Users
4.1.2 Mobile Supply Chain: Suppliers Benefit from Specs Upgrades in Early AI Phone Development
4.2 Challenges: Memory Limits as Key Barrier for AI Phone Development
5. MIC PERSPECTIVE
5.1 Mobile Brands Enhance Generative AI with LLM
5.2 Generative AI Spurs Phone Hardware Upgrades, but Memory Limits Future Development
Appendix
LIST OF COMPANIES
LIST OF TABLES
Table 1: Comparison of Flagship Chip Specifications between Qualcomm and MediaTek (2022 vs. 2023)
Table 2: Comparison of LLMs in Android Smartphone Camp
Table 1: Comparison of Flagship Chip Specifications between Qualcomm and MediaTek (2022 vs. 2023)
Table 2: Comparison of LLMs in Android Smartphone Camp
LIST OF FIGURES
Figure 1: Qualcomm's Hybrid AI Concept
Figure 2: Distribution of Generative AI Applications and LLM Parameters
Figure 1: Qualcomm's Hybrid AI Concept
Figure 2: Distribution of Generative AI Applications and LLM Parameters
