A complete breakdown of Physical AI sectors that JMoon Ventures aims to invest in because we are absolutely 100% incredibly thrilled about the potential of these sectors in the next decade as they represent the forefront of technological innovation using Large Models (LXMs) of AI.

AI Component of Physical AI

Large AI models enhancing current applications and paving the way for new innovations and efficiencies across physical AI sectors.

Large Language Model: Enhancing Natural Interaction with Devices

The incorporation of LLMs into physical devices revolutionises human-computer interaction by enabling communication with devices through speech, making robots, IoT, XR and Wearables more accessible and intuitive. In home automation, healthcare, and customer service, this creates more personalized and efficient user experiences, where devices can understand context, respond to complex queries, and anticipate needs based on conversational cues.

Large Action Model: Driving Robotic Autonomy and Ubiquitous Computing

Large action models are a key element for the realisation of Artificial General Intelligence (AGI) and the widespread adoption of ubiquitous computing. By enabling robots to adapt to real-time changes and make decisions autonomously, these models can drastically improve efficiency and flexibility of manufacturing processes, logistics, and service robots in public spaces. This adaptive capability allows for more sophisticated and varied applications, from autonomous vehicles navigating through unpredictable urban environments to robots performing complex tasks in dynamic settings of hospitals or disaster zones.

Large Vision Model: Revolutionizing Surveillance, AVs, and Robotics

These models enable precise object detection, recognition, and tracking, allowing for better navigation and obstacle avoidance makingautonomous vehicles (AVs) safer. In surveillance, it means more accurate threat detection and situational awareness. Enhanced vision capabilities facilitate more nuanced interactions with objects and environments, enabling tasks that were previously challenging due to visual complexity. Deployed on the edge, these models can also be used to improve IoT devices for creating personalized experiences for users.

Large Multimodal Model: Contextualizing Smart Environments and Wearables

Large multimodal models combine data from text, images, and sensor inputs, to create smart environments that adapt to the needs of their users. In smart homes and cities, these models can analyze a range of inputs to optimize energy use, enhance security, and improve residents’ quality of life. For wearables, multimodal models offer a deeper understanding of user behavior and health, providing personalized feedback and alerts that can contribute to better health outcomes and enhanced personal efficiency.

Large Generative Model: Creating Realistic Simulations for Training and Design

The application of large generative models in generating synthetic 3D data can create highly realistic and dynamic environments for simulation-based, safe and cost-effective skill development in surgery, piloting, and military operations using gaming, and virtual reality (VR). In design and architecture, generative models can produce intricate models and reduce waste in manufacturing by optimizing the design.

Large Graph Model: Enhancing Connectivity in Networked Systems

In the context of networked systems, such as fleets of vehicles or interconnected devices, large graph models understand and optimize social interaction graphs and connectivity. These models can analyze complex networks to improve routing, reduce congestion, and enhance coordination among units, leading to more efficient operations in logistics, transportation, and smart city management.

Large Reinforcement Learning Model: Optimizing Dynamic System Efficiency

By learning from interactions with the environment, these models can optimize operations in real-time, adjusting to changes and unforeseen circumstances. This capability is invaluable when applied to a network of agricultural robots and IoT sensors deployed across farmlands, to make it robust against unpredictable environmental changes, or dynamically balance supply and demand in fleets for optimizing logistics and delivery routes based on fluctuating factors.

Market: The integration of 5G is enhancing AR/VR experiences and robotics, particularly in automotive design and retail ¹. Digital twins and industrial metaverse are becoming key in simulating large-scale environments, improving manufacturing and planning processes. The collaboration between humans and intelligent machines is growing, driven by the need for efficiency in distribution and manufacturing. With IoT and Robotics hardware devices ready to be released on an large scale in this sector, it becomes incredibly important to have fleet management capability that effectively manages and monitors the swarm’s health. AI’s role in retail includes personalized marketing and risk management, leveraging NLP and machine learning ². AI’s application in safety and cybersecurity is crucial, with a focus on predicting safety events and protecting edge devices from cyber threats ³. Voice assistants and image recognition are becoming more sophisticated, offering improved user experiences and accurate identifications ⁴. Lastly, energy-efficient computing is making AI more cost-effective, emphasizing the importance of sustainable and efficient AI applications​​​​​​​​.

Hardware Component of Physical AI

Robotics

Startups that are developing innovative robotics solutions and business models for a wide range of industries, from manufacturing and logistics to healthcare, climate, or even consumer products because we believe robotics is one of the most exciting and transformative Physical AI fields in existence today that will transform all industries and leverage AI in a way that hasn’t been seen in this field yet.

Market: The Robotics industry is experiencing remarkable growth, making it a prime investment target. The market size of the global robotics industry is expected to grow at a CAGR of 15.91% ⁵​​. This growth is driven by advancements in energy efficiency, reshoring manufacturing processes, ease of use, AI integration, and the potential for second-life applications of industrial robots ⁶​​. With the rise of Industry 4.0, there is an increased emphasis on safety and automation, particularly in oil and gas. Retail, Agriculture, and Social robots will play and incredible role in the growth of this sector. The consumer robotics market ⁷ is also set to grow to 5x its current size at a 26% CAGR by 2030 and 8x by 2032.

US robotics market is expected to grow at a CAGR of 18.5% till 2033​​; China by CAGR of 20.9% driven by government support and a focus on smart manufacturing​​; UK with a CAGR of 18.8% with Robotics-as-a-Service models​​; Japan at a CAGR of 19.1%​​; and South Korea at CAGR of 20.2% ⁸.

Internet of Things

We invest in startups that are developing cutting-edge IoT / IIoT solutions that are changing the way we live, work, and manufacture products for mass consumption with use cases spanning all industries.

Market: The IoT market is witnessing rapid innovation, including the introduction of cutting-edge IoT solutions for industrial applications by Qualcomm and the development of new Matter-enabled software for IoT applications by Texas Instruments ⁹. The IoT market’s growth is driven by increasing adoption of connected devices, advancements in data analytics, and the integration of AI and cloud computing​​​​ ¹⁰. There is a growing trend of investment in IoT, with an expected spending of $1.4 trillion by 2023, highlighting its impact and potential for innovative projects in hardware, software, and services ¹¹​​.

3D Printing

We invest in startups that are developing new 3D design and printing technologies and applications that potentially transform unexplored industries by revolutionizing the way products are designed and manufactured whether it is a software or hardware-focused solution. A growing cause of concern in additive manufacturing, and

Market: The 3D Printing market is showing robust growth, projected to grow by a CAGR of 24.9% till 2030 ¹². Key drivers include advancements in Direct Metal Laser Sintering (DMLS) and Selective Laser Sintering (SLS) technologies, predominant use in prototyping across automotive, aerospace, and defense industries, and increasing applications in automotive components and electronics. North America leads the market, particularly due to the adoption of additive manufacturing in the U.S. and Canada ¹³.

XR and Wearable Devices

We invest in Augmented, Virtual, or Mixed Reality devices and wearable consumer electronics with adoption across various industries such as education, productivity, entertainment, gaming, training, and business.

Market: The wearable XR devices market is rapidly expanding, with its value projected to 3x from 2021 to 2028 ¹⁴. This surge is driven by a growing demand for holistic health monitoring wearables in healthcare and wellness sectors where North America currently leads the market. The global wearable technology market, including wristwear and VR/AR headsets, is expected to grow at a CAGR of 33.9% till 2030 ¹⁵. China and India will account for the majority of the world’s manufacturing in this sector ¹⁶ soon so a deep network in either or both of these geographies will become increasingly important for startups in North America.

References

1. Nvidia Predictions: AI That Bends Reality, Unwinds the Golden Screw and Self-Replicates. Source. ↩︎
2. Lablab: Artificial Intelligence (AI) Industry Trends in 2023: Market Size, Share & Forecast. Source. ↩︎
3. Nvidia: AI Trends. Source 1. Source 2. ↩︎
4. What to Expect in Artificial Intelligence. Source. ↩︎
5. Mordor Intelligence: Robotics Industry Size & Share Analysis – Growth Trends & Forecasts (2023 – 2028). Source. ↩︎
6. International Federation of Robotics: Top 5 Robot Trends 2023. Source. ↩︎
7. Consumer Robotics Market by Level of Autonomy: Autonomous and Semi-autonomous Robots. Source. ↩︎
8. Future Market Insights: Robotics Market Outlook (2023 to 2033). Source. ↩︎
9. Mordor Intelligence: IoT Market Size & Share Analysis – Growth Trends & Forecasts (2023 – 2028). Source. ↩︎
10. IoT Analytics: Global IoT market size – IoT shows resilience despite economic downturn. Source. ↩︎
11. OpenMind BBVA: 9 Trends of IoT in 2023. Source. ↩︎
12. Fortune Business Insights: Global 3D printing market size. Source. ↩︎
13. Future Market Insights: 3D Printing Market Snapshot (2023 to 2033). Source. ↩︎
14. Clarkston Consulting: 2023 Wearable Device Trends. Source. ↩︎
15. Fortune Business Insights: Global wearable technology market size. Source. ↩︎
16. Future Market Insights: Smart Wearables Market Outlook (2023 to 2033). Source. ↩︎

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