
Artificial Intelligence (AI) - Thematic Intelligence
Description
Artificial Intelligence (AI) - Thematic Intelligence
Summary
For decades artificial intelligence (AI) has primarily been the territory of university and corporate R&D labs. Recent progress in machine learning (ML) on the back of improved algorithms (e.g., Google’s AlphaGo, OpenAI’s GPT-3, Tesla’s AutoPilot) and increasing computing power have made it possible for AI to solve real-life problems. GlobalData estimates the total AI market will be worth $383.3 billion in 2030, implying a 21% compound annual growth rate between 2022 and 2030. In the coming decade, the country that emerges on top in AI will lead the Fourth Industrial Revolution.
Despite the hype, artificial general intelligence (AGI), or the ability of machines to do anything that a human can and possess consciousness, is still decades away. However, ‘good enough’ AI is already here, capable of interacting with humans, motion, and making decisions. For example, OpenAI’s GPT-3 and ChatGPT models can write original prose and chat with human fluency, DeepMind's algorithms can beat the best human chess players, and Boston Dynamics' Atlas robots can somersault. If this evolution continues, it could upend the labor-based capitalist economic model.
Driven by ethical and political concerns, using AI for facial recognition will lead to conflict in standards and regulatory approaches. This will lead to the break-up of the global supply chain in the AI segment, as is already underway in semiconductors. Ultimately stricter ethical regulation will break the global AI market into geopolitical silos, in isolation from one another.
Scope
Summary
For decades artificial intelligence (AI) has primarily been the territory of university and corporate R&D labs. Recent progress in machine learning (ML) on the back of improved algorithms (e.g., Google’s AlphaGo, OpenAI’s GPT-3, Tesla’s AutoPilot) and increasing computing power have made it possible for AI to solve real-life problems. GlobalData estimates the total AI market will be worth $383.3 billion in 2030, implying a 21% compound annual growth rate between 2022 and 2030. In the coming decade, the country that emerges on top in AI will lead the Fourth Industrial Revolution.
Despite the hype, artificial general intelligence (AGI), or the ability of machines to do anything that a human can and possess consciousness, is still decades away. However, ‘good enough’ AI is already here, capable of interacting with humans, motion, and making decisions. For example, OpenAI’s GPT-3 and ChatGPT models can write original prose and chat with human fluency, DeepMind's algorithms can beat the best human chess players, and Boston Dynamics' Atlas robots can somersault. If this evolution continues, it could upend the labor-based capitalist economic model.
Driven by ethical and political concerns, using AI for facial recognition will lead to conflict in standards and regulatory approaches. This will lead to the break-up of the global supply chain in the AI segment, as is already underway in semiconductors. Ultimately stricter ethical regulation will break the global AI market into geopolitical silos, in isolation from one another.
Scope
- This report provides an overview of the artificial intelligence theme.
- It identifies the key trends impacting growth of the theme over the next 12 to 24 months.
- It includes a comprehensive industry analysis, including market size and growth forecasts for AI hardware, AI platforms, AI consulting and support services, and specialized AI applications.
- The detailed value chain breaks down artificial intelligence into five segments: hardware, data management, foundational AI, advanced AI capabilities, and delivery.
- From self-driving vehicles to fraud detection, AI plays a role in virtually every industry, putting pressure on incumbents to adapt and innovate or face stagnation and possible elimination. This report is an invaluable guide to this highly disruptive theme, including analysis of key AI technologies and assessment of the leading providers.
Table of Contents
98 Pages
- Executive Summary
- Players
- Technology Briefing
- What is AI?
- Branches of AI
- Weak AI
- Strong AI
- The AI roadmap
- Advanced AI capabilities
- Trends
- Technology trends
- Macroeconomic trends
- Regulatory trends
- Industry Analysis
- Market size and growth forecasts
- Mergers and acquisitions
- Venture financing
- Patent trends
- Company filings trends
- Hiring trends
- Social media trends
- Use cases
- Automotive
- Consumer electronics
- Cybersecurity
- Ecommerce and retail
- Financial services
- Healthcare
- Timeline
- Value Chain
- Hardware
- Semiconductors
- Cameras
- Sensors and lasers
- Servers
- Storage devices
- Networking equipment
- Edge equipment
- Data management
- Data governance and security
- Data storage
- Data processing
- Data aggregation
- Data integration
- Foundational AI
- Data science
- Machine learning
- 3D modeling
- Knowledge representation and reasoning
- Visualization engines
- Advanced AI capabilities
- Human-AI interaction
- Decision-making
- Motion
- Creation
- Sentience
- Delivery
- Hardware appliance
- Licensed software
- Artificial intelligence as a service
- Companies
- Public companies
- Private companies
- Sector Scorecards
- Application software sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Semiconductor sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Consumer electronics sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Glossary
- Further Reading
- GlobalData reports
- Our Thematic Research Methodology
- About GlobalData
- Contact Us
- List of Tables
- Table 1: Technology trends
- Table 2: Macroeconomic trends
- Table 3: Regulatory trends
- Table 4: Key M&A transactions associated with the AI theme since January 2021
- Table 5: Venture financing
- Table 6: Public companies
- Table 7: Private companies
- Table 8: Glossary
- Table 9: GlobalData reports
- List of Figures
- Figure 1: Who are the leading players in the AI theme, and where do they sit in the value chain?
- Figure 2: Artificial neural networks emulate the brain
- Figure 3: Symbolic AI is the main type of strong AI
- Figure 4: Google’s Gato aims for general AI
- Figure 5: Limited memory AI keeps track of the world
- Figure 6: We are at the early stages of the AI roadmap
- Figure 7: There are five categories of advanced AI capabilities
- Figure 8: The global market for specialized AI applications will be worth $146 billion by 2030
- Figure 9: The global specialized AI applications marke8t will grow at a CAGR of 21%
- Figure 10: North America and Asia Pacific are the leading AI markets
- Figure 11: Businesses all around the world view AI as a disruptive theme
- Figure 12: COVID-19 was a catalyst for increased AI adoption across all industries
- Figure 13: IBM, Microsoft, and Samsung Group lead the way in AI-related patents
- Figure 14: AI-related patent publications in the TMT sector have accelerated since 2018
- Figure 15: AI mentions in company filings in the TMT sector accelerated in 2020
- Figure 16: AI-related hiring in the TMT sector peaked in April 2022
- Figure 17: AI remains a consistent talking point
- Figure 18: Mobileye is a leading provider of automotive CV
- Figure 19: Virtual assistants are now part of everyday life, and they are getting more sophisticated
- Figure 20: AI can support advanced photo editing
- Figure 21: AI underpins Amazon recommendations
- Figure 22: CV can improve ATM security and usability
- Figure 23: CV and AI provide clinical decision support
- Figure 24: The AI story
- Figure 25: The artificial intelligence value chain
- Figure 26: The AI value chain - Hardware – semiconductors
- Figure 27: The AI value chain - Hardware – cameras
- Figure 28: The AI value chain - Hardware – sensors and lasers
- Figure 29: The AI value chain - Hardware – servers
- Figure 30: The AI value chain - Hardware – storage devices
- Figure 31: The AI value chain - Hardware – networking equipment
- Figure 32: The AI value chain - Hardware – edge equipment
- Figure 33: The AI value chain - Data management
- Figure 34: The AI value chain - Foundational AI – data science
- Figure 35: The AI value chain - Foundational AI – machine learning
- Figure 36: The AI value chain - Foundational AI – 3D modeling
- Figure 37: The AI value chain - Foundational AI – knowledge representation and reasoning
- Figure 38: The AI value chain - Foundational AI – visualization engines
- Figure 39: The AI value chain - Foundational AI – visualization engines
- Figure 40: The AI value chain - Advanced AI capabilities – decision-making
- Figure 41: The AI value chain - Advanced AI capabilities – motion
- Figure 42: The AI value chain - Advanced AI capabilities – creation
- Figure 43: The AI value chain - Advanced AI capabilities – sentience
- Figure 44: The AI value chain - Delivery
- Figure 45: Who does what in the application software space?
- Figure 46: Thematic screen - Application software sector scorecard
- Figure 47: Valuation screen - Application software sector scorecard
- Figure 48: Risk screen - Application software sector scorecard
- Figure 49: Who does what in the semiconductor space?
- Figure 50: Thematic screen - Semiconductor sector scorecard
- Figure 51: Valuation screen - Semiconductor sector scorecard
- Figure 52: Risk screen - Semiconductor sector scorecard
- Figure 53: Who does what in the consumer electronics space?
- Figure 54: Thematic screen - Consumer electronics sector scorecard
- Figure 55: Valuation screen - Consumer electronics sector scorecard
- Figure 56: Risk screen - Consumer electronics sector scorecard
- Figure 57: Our five-step approach for generating a sector scorecard
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