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Using AI in Robotics

November 2023
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To successfully make use of a technology, you need to understand the use cases for the industry. Context is everything, and AI and robotics go together like fish and chips. In this session, you'll learn about common uses of AI in the robotics field, best practices for making use of AI in robotics, and what skills you need to make use of AI for robotics.

Key Takeaways:

  • Learn how AI is used in the field of robotics.
  • Learn about the challenges of using AI in robotics - and how to overcome them.
  • Learn about careers for AI in robotics, and the skills you need to get a job in this area.

Additional Resources:

Slides

[COURSE] Robotics gets a mention in Understanding Artificial Intelligence

[WEBINAR] Computer Vision is useful for robots! AI for Visual Data: Computer Vision in Business

[PODCAST] Francesco's podcast, Data Science At Home

[PODCAST] Embedded Machine Learning on Edge Devices

Summary

Artificial Intelligence (AI) and robotics, though often mistaken as the same, are separate yet complementary fields. AI involves algorithmic processes for predictions and decisions, while robotics pertains to the physical implementation of these algorithms. The webinar explored the connection of AI and robotics, featuring experts Francesco Gadaleta and Eliseo Ferrante. They provided insights on the evolving field of AI, emphasizing that misunderstandings exist about AI's capabilities, especially around the elusive concept of Artificial General Intelligence (AGI). Robotics, they noted, is exceptionally interdisciplinary, requiring skills across various fields such as engineering, mathematics, and computer science. The discussion also emphasized various sectors where AI and robotics are increasingly used, from agriculture and healthcare to defense and space exploration. Challenges in these applications often involve integrating complex systems and ensuring safety and ethical considerations. The speakers highlighted the importance of realistic expectations, particularly concerning AI's current limitations and the necessity of continuing education in the rapidly changing field.

Key Takeaways:

  • AI and robotics are separate but complementary fields with significant potential when combined.
  • Misunderstandings about AI, particularly AGI, persist due to portrayals in media and popular culture.
  • Robotics is an interdisciplinary field, requiring a broad skill set across multiple disciplines.
  • AI and robotics are being used in diverse sectors, including agriculture, healthcare, defense, and space exploration.
  • Realistic expectations and continuous learning are important in understanding the evolving field of AI and robotics.

Deep Dives

Misunderstandings about AI and AGI

AI is often ...
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misunderstood, particularly in relation to AGI, which is frequently depicted in science fiction as machines with human-like intelligence. Francesco Gadaleta stressed that AGI is far from being realized with current technology. He emphasized that AI in its present form is primarily specialized intelligence, performing specific tasks rather than exhibiting general intelligence similar to humans. Eliseo Ferrante echoed this sentiment, attributing misunderstandings to media portrayals that often blur the lines between AI capabilities and science fiction narratives. The discussion highlighted the importance of setting realistic expectations and focusing on achievable advancements within the current technological framework.

Interdisciplinary Nature of Robotics

Robotics is identified as one of the most interdisciplinary fields, requiring expertise in various domains including engineering, computer science, and mathematics. Francesco Gadaleta described the complexity of robotics projects, which incorporate software and hardware components, electronics, and data science. This complexity requires a diverse skill set among practitioners, making it essential for those entering the field to possess or acquire knowledge across multiple disciplines. Eliseo Ferrante stressed the importance of adaptability and continuous learning due to the rapidly changing nature of robotics and its applications.

Sectoral Applications of AI and Robotics

The application of AI and robotics crosses several sectors, each presenting unique challenges and opportunities. In agriculture, robotics aids in tasks like precision farming and autonomous operations, enhancing efficiency and productivity. Francesco Gadaleta expressed a particular interest in agricultural technology, citing its potential for significant impact. Healthcare, though slower to adopt AI due to ethical and reliability concerns, is gradually integrating robotic systems for tasks such as surgery and patient care. Defense applications focus on surveillance and autonomous operations in complex environments, while space exploration presents challenges of operating in infrastructure-less settings, as noted by Eliseo Ferrante.

Challenges and Future Directions

Integrating AI with robotics presents numerous challenges, particularly in system integration and real-world application. Francesco Gadaleta pointed out the lack of standardization in robotics tools, which complicates integration efforts. Eliseo Ferrante noted the gap in hardware advancement between embedded systems used in robotics and traditional computing, although recent developments have started to close this gap. Looking forward, the speakers emphasized the need for realistic expectations about AI's capabilities, advocating for a focus on specialized intelligence and continuous adaptation to technological advancements. They also pointed out exciting future directions, such as the potential of large language models to enhance robotic systems, though this remains an area requiring further research and validation.


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