[Volume 34. Figure AI: Leading Physical AI Company in Humanoid Robotics Commercialization]

1. Company Overview

Figure AI is a U.S. AI robotics startup specialized in developing general-purpose humanoid robots.

Basic Information

• Founded: 2022

• Headquarters: Sunnyvale, California

• Founder & CEO: Brett Adcock (former founder of Archer Aviation)

• Core Mission: Developing general-purpose humanoid robots to address labor shortage problems

• Main Products: Figure 01, Figure 02

Business Model

• Deploying humanoid robots in industrial sites requiring human labor such as manufacturing, logistics, and warehouse operations

• Providing robot solutions that can utilize existing infrastructure and tools designed for humans

• Robot sales and service contract model

2. Core Technology and Products

Figure 01 (First Generation)

Specifications:

• Height: Approximately 5 feet 6 inches (approximately 168 cm)

• Weight: Approximately 60 kg

• Operating Time: 5 hours

• Load Capacity: 20 kg

• Movement Speed: 1.2 m/s

• Key Features:

  • Fully electric drive

  • Human-like form factor for easy integration into existing work environments

  • Autonomous operation capability

Figure 02 (Second Generation) - Announced in 2024

Significantly Improved Performance:

• 3x increase in hand degrees of freedom (DoF) → Enables precise manipulation

• 50% increase in battery capacity

• Significantly improved movement speed

• Enhanced visual processing capability

Advanced Hand Design: Hands with 11 degrees of freedom enabling delicate object manipulation

Enhanced AI Integration: Integration of multimodal AI models enabling vision-language-action integration

AI Technology Stack

OpenAI Partnership: Integration of GPT-based language models into robots

• Natural language understanding and conversational ability

• Reasoning combining visual information and language

• Real-time task learning and adaptation

Multimodal AI:

• Environmental recognition through vision systems

• Understanding and execution of language commands

• Integration of action planning and execution

3. Strategic Partnerships and Investment

Major Funding Rounds

February 2024: $675M Series B Funding

• Post-Investment Valuation: $2.6 billion

• Major Investors:

  • Microsoft: AI technology integration cooperation

  • OpenAI Startup Fund: GPT model integration

  • Jeff Bezos: Personal investment

  • Nvidia: GPU and AI computing support

  • Intel: Hardware partnership

  • Amazon Industrial Innovation Fund

  • Parkway Venture Capital

  • Align Ventures

Strategic Partnerships

1) OpenAI Collaboration

• Integration of GPT multimodal models into Figure robots

• 2024 demonstration: Figure 01 performing tasks in real-time while conversing in natural language

• End-to-end learning system integrating vision-language-action

2) BMW Partnership (Announced January 2024)

• Deployment of Figure 01 at BMW's Spartanburg, South Carolina factory

• Automation of specific tasks in automotive manufacturing processes

• First large-scale case of commercial deployment

3) Microsoft Collaboration

• Utilizing Azure AI infrastructure

• Cloud-based AI model training and deployment

• Enterprise integration support

4. Competitive Environment

Major Competitor Comparison

Company	Main Product	Key Differentiator	Major Customers/Partners
Figure AI	Figure 01/02	OpenAI integration, emphasis on versatility	BMW, OpenAI, Microsoft
Tesla (Optimus)	Tesla Bot	Vertical integration, mass production capability	Tesla factories (internal use)
Boston Dynamics	Atlas	Advanced motor ability, mechanical sophistication	Hyundai-owned, research-focused
Agility Robotics	Digit	Logistics specialization, bipedal locomotion	Amazon, logistics centers
Apptronik	Apollo	Modular design, multipurpose	Mercedes-Benz, NASA
1X Technologies	NEO	Home robot oriented	OpenAI investment
Sanctuary AI	Phoenix	Emphasis on general intelligence, Canada-based	Retail pilots

Figure AI's Differentiation Factors

1) AI-First Approach

• Setting AI integration as core rather than simple robotics

• Leveraging latest foundation models through close collaboration with OpenAI

• Understanding and executing natural language commands with multimodal AI

2) Speed of Commercialization

• Rapid commercialization with BMW factory deployment in 2024 after 2022 founding

• Proven performance in actual industrial environments

3) Strong Investor Network

• Connected with core players in the technology ecosystem such as Microsoft, OpenAI, Nvidia, Intel

• Strengths in capital power and technology accessibility

4) Versatility Orientation

• Developing general-purpose robots capable of performing various tasks rather than specific tasks

• Form factor optimized for human work environments

5. Market Opportunity and Positioning

Target Markets

• Manufacturing: Assembly, inspection, material transport

• Logistics and Warehousing: Picking, packing, organization

• Retail: Inventory management, customer service

• Healthcare: Patient transport, medical equipment transport

• Construction: Material transport, repetitive tasks

Market Opportunity Scale

• Global Humanoid Robot Market: Approximately $1.8B in 2024 → Expected $17B+ by 2030 (CAGR 40%+)

• Labor Shortage: Over 2 million unfilled positions in U.S. manufacturing sector alone

• Automation Pressure: Increasing demand for productivity improvement and rising labor costs

Strategic Positioning

Figure AI pursues "practical versatility":

• Prioritizing practicality over Boston Dynamics' advanced mechanical capabilities

• Leveraging AI partnerships rather than Tesla's complete vertical integration

• Emphasizing general-purpose task capabilities rather than Agility's specialized approach

6. Technical Challenges and Risks

Current Limitations

1. Battery Life: 5-hour operating time is limited in 24-hour operating environments

2. Cost: High initial cost of humanoid robots (estimated $150K-$250K per unit)

3. Reliability: Need for verification of long-term failure-free operation

4. Versatility: Still limited in replacing all human tasks

Competitive Risks

• Tesla's Scale: Elon Musk announced plans to produce millions of Optimus robots

• Chinese Competitors: Emergence of low-cost alternatives such as Unitree, UBTECH

• Traditional Robotics: Entry of industrial robot companies such as ABB, FANUC into humanoid robots

Regulatory and Social Challenges

• Compliance with workplace safety regulations

• Social concerns about job displacement

• AI ethics and responsibility issues

7. Strategic Assessment

Core Strengths

1. AI Integration Capability: Access to cutting-edge AI technology through OpenAI partnership

2. Execution Speed: Achieved commercial deployment within 2 years of founding

3. Capital Power: Long-term R&D and scaling possible with $675M investment

4. Partner Network: Secured major customers and technology partners such as BMW, Microsoft

Strategic Implications

Another Case of "Orchestration over Foundation"

Figure AI shows a pattern similar to Manus AI:

• Utilizing OpenAI models instead of developing own foundation model

• Focusing on integrated orchestration of robot hardware and AI

• Prioritizing rapid market entry and learning through actual deployment

Difference: Figure secures some vertical integration by developing hardware platform in-house

Future Outlook

Near-Term (1-2 years)

• Expected expansion of partnerships with additional manufacturers beyond BMW

• Commercial deployment and performance verification of Figure 02

• Production scale expansion and cost reduction

Mid-Term (3-5 years)

• Entry into logistics and warehouse markets beyond manufacturing

• Building production capacity of thousands of units annually

• Robot capability improvement following OpenAI technology advancement

Long-Term Risks

• Tesla Optimus mass production and price competition

• Low-price offensive from Chinese companies

• Positioning choice in general-purpose vs. specialized robot market

Conclusion

Figure AI is one of the companies achieving commercialization fastest in the convergence of AI and robotics. The strategy of focusing on "AI-native" robot development through partnerships with core players in the AI ecosystem such as OpenAI and Microsoft shows a pattern similar to Manus AI's orchestration strategy.

However, there are challenges such as hardware manufacturing complexity, competition with Tesla, and high initial costs, and the commercial deployment performance over the next 2-3 years will be an important indicator for gauging long-term success.