The Evolution of Digital Twins: From Machines to Human Expertise

The Evolution of Digital Twins: From Machines to Human Expertise

Leadership in the Loop: Edition 18

Amir Hartman | Managing Director, Dasteel Consulting | Director AI Strategy Research Experience Alliance, Fidere.ai, Praxis AI

Venkataraman Lakshminarayanan | Chief Revenue Office & President Cron AI |

Digital twins have come a long way since their inception as virtual representations of physical objects, systems, or processes that are continuously updated with real-time data from their physical counterparts. Put in the context of AI, reflecting real-world conditions in a virtual environment brings new and exciting possibilities. A variety of fields such as manufacturing, healthcare, urban planning can benefit from the application of digital twins to simulate, predict, and improve outcomes. Indeed, digital twins are evolving into sophisticated, AI-powered replicas of human expertise.?

In this newsletter, let’s dive into how this fascinating journey started - and where it’s headed.

The Origins of Digital Twins

Back in the 1960s, NASA pioneered what we now know as digital twins. They created physical replicas on the ground to mirror conditions in space, helping them solve problems from afar. The Apollo 13 mission in 1970 was a perfect example of how this approach saved the day by simulating solutions for an oxygen tank explosion. Though the term “digital twin” wasn’t coined until 2010 by NASA’s John Vickers, the concept had already proven its worth.

Traditional Applications

Initially, digital twins were mainly used to replicate physical systems or processes. They relied on real-time data to help industries improve processes such as Predictive Maintenance, Performance Optimization and Scenario Testing & Design Improvements - all without touching the real thing. According to McKinsey, 75% of companies in advanced industries are adopting digital twins.

Rolls-Royce, for example, uses digital twins to monitor the health of its jet engines, optimizing efficiency and ensuring reliability. This has made servicing engines more proactive and data-driven.

As with all technology hype, it is worth asking demystifying questions.?

Are digital twins just digital simulations? Both digital twins and simulations create virtual models to predict outcomes or assess scenarios. Both use data and models to replicate the behavior of a physical system or process. However, digital twins use continuous, real-time connection to the physical counterpart, enabling ongoing feedback and adjustments. Simulations are typically one-off or scenario-specific representations that do not dynamically update based on real-time data.

The AI Revolution: Digital Twins Go Human

Today, digital twins aren’t just about machines anymore—they’re also about people. Enter Human Digital Twins, AI-powered replicas that capture a person’s expertise, personality, and decision-making style. Imagine having an expert available 24/7, offering insights or guidance whenever you need it. Here are a few examples from the companies we work or consult with.

Reid AI: A Glimpse into Human Digital Twins

One standout example is Reid AI, a digital twin created to emulate Reid Hoffman , co-founder of LinkedIn. It captures his entrepreneurial mindset, communication style, and expertise, allowing people to engage with an AI version of Reid for advice, insights, and even mentorship. It’s about scaling one person’s knowledge in a way that’s accessible and consistent.

Cron AI : Smart Cities and Intelligent Transportation

Digital twins, powered by 3D perception and edge AI, can transform industries by turning data from sensors such as LiDARs and cameras into real-time actionable insights. Traditionally, humans would manually analyze data from sensors or conduct physical inspections to monitor and maintain assets. This process is slow, prone to errors, and often reactive rather than proactive. In contrast, Cron AI’s edge AI-based 3D perception software senseEDGE automates this task by processing spatial data in real-time, detecting, classifying, and tracking objects with greater accuracy and speed. The software continuously updates to reflect current conditions, allowing for predictive maintenance and faster decision-making. Unlike manual methods, data from Cron AI’s software senseEDGE, in combination with analytics from Blue Band, can be analyzed to simulate potential outcomes, enabling optimization before issues arise, which results in better efficiency, cost savings, and enhanced operational performance across applications like smart cities and autonomous systems.

Praxis AI : Revolutionizing Education with Expert Digital Twins

At Praxis AI, they’re taking Human Digital Twins to the next level—particularly in education. Our AI middleware is designed to enhance and empower an organization's most valuable asset: its people. Here's how we're making a difference:

  • Scale Expertise: Students get access to professors' knowledge beyond the classroom or office hours. Our digital twins show a 400% improvement in student engagement compared to generic chatbots, with 65% engagement for Praxis AI digital twins versus 14% for OpenAI ChatGPT.
  • Personalize Learning: Digital twins adapt explanations to fit each student's needs. This tailored approach has led to a significant correlation between the use of digital twins and student performance on assessments and courseware (Spearman: 0.55).
  • Continuously Improve: As more students interact with the AI, it learns and refines its teaching approach. We've seen a 10X growth in student and faculty usage over the past several months.
  • Bridge Disciplines: Combining digital twins from different fields, we're helping students make unique interdisciplinary connections, preparing them for future multidisciplinary challenges.
  • Empower Faculty: Our digital twins answer 70% of student questions in Praxis-powered courses, allowing faculty to focus their time on students who need additional support.
  • Meet Students Where They Are: With 86% of students already using AI tools in their studies, Praxis AI seamlessly integrates into existing workflows. However, less than 20% of universities currently offer a centralized AI solution.

Praxis AI works with major LLMs, including GPT-4, Amazon Bedrock, and @Anthropic to leverage Retrieval-Augmented Generation, providing a secure, private platform tailored to an organization's data and language. Documents are encrypted and deleted after analysis for full privacy.

By partnering with Praxis AI, higher education institutions are not just adopting a technology—they're championing innovation with a profound net positive effect on education. The digital twin middleware represents a significant leap forward, ensuring compatibility across a school's knowledge infrastructure, enhancing operational efficiency, ensuring security, and reducing costs.

The Future of Digital Twins

Looking ahead, Human Digital Twins have the potential to transform how we interact with expertise and knowledge. Here are a few possibilities:

  • Virtual Mentors: Personalized AI mentors combining insights from multiple experts.
  • Historical Figures: Imagine an interactive AI of your favorite historical figure for an immersive educational experience.
  • Healthcare: AI-powered medical experts that provide consultations and second opinions.
  • Customer Service: AI twins embodying a company’s values for a more personalized support experience.

Ethical Considerations

With great power comes great responsibility. As Human Digital Twins become more common, there are some ethical issues we must address:

  • Privacy & Consent: Ensuring that data used to create these twins is protected and used with permission.
  • Authenticity: Making sure it’s clear that these twins are AI and not the real person to avoid any deception.
  • Bias and Representation: Reducing biases in AI models to avoid skewed perspectives.

Reid AI, Cron AI and Praxis AI are just a few examples that show we’re entering an era where we break down traditional barriers. However, in discussing the potential of digital twins, it’s important to recognize their broad applicability across industries. From manufacturing and healthcare to urban planning and autonomous systems, digital twins have the power to revolutionize how we monitor, analyze, and optimize physical assets and processes. They offer a way to scale human potential by providing real-time, data-driven insights that far surpass manual methods in speed, accuracy, and predictive capability. However, as always with AI capabilities, ethical and governance aspects need a closer look. The widespread deployment of digital twins raises questions about data privacy, security, and decision-making biases and ownership rights. As digital twins become integrated into more industries, organizations must ensure that these tools are implemented responsibly, with strong oversight and clear ethical guidelines to govern their use.

Do you want a digital twin? Of yourself, specific expert, or other? How do you the digital twin of your choice being applied?

#DigitalTwins #Reid AI #Praxis AI #AI #3DPerception #EdgeAI #CronAI #SmartCities #AutonomousSystems #AIInnovation #PredictiveMaintenance #RealTimeData #AIethics #TechInnovation #Automation #DigitalTransformation

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Joy Katz

Global Business Strategy, Executive Alignment, and Ecosystem Development

5 个月

Very helpful!

回复
Qiong Wang

Ruby k. Powell Professor of Marketing & Associate Professor of Marketing and Supply Chain Management at the University of Oklahoma

5 个月

Well put, Amir! Digital twins handle the mundane tasks, freeing up us professors to focus on what really matters—building creative, meaningful connections with students to enrich their learning journey.

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