Podcast Summary
Security in AI and Machine Learning, Effective Communication, and Continuous Learning: Stay secure in AI and ML with Hidden Layer, bridge language barriers with Babel, and learn new skills with Masterclass
As technology advances, particularly in the realm of artificial intelligence and machine learning, it's essential to consider the security implications. Hidden Layer, a new sponsor of this podcast, provides a valuable service by helping secure machine learning models against potential threats. These threats can come in various forms, such as malicious models hidden in public repositories or delivering seemingly legitimate models that contain malware. As the use of machine learning continues to expand across industries, having experts to help incorporate these systems in a secure way becomes increasingly important. Another takeaway is the importance of communication and understanding between people from different cultures and backgrounds. Babel, another sponsor, offers a solution to this challenge by providing practical conversational language learning. This tool can help bridge the gap created by language barriers and facilitate more meaningful connections. Lastly, continuous learning and mastering new skills are crucial in today's world. Masterclass, a sponsor, offers access to classes from world-renowned experts in various fields, allowing individuals to learn and improve at their own pace. In summary, the conversation with Mark Reibert highlighted the importance of security in the age of AI and machine learning, the significance of effective communication, and the value of continuous learning.
Expert Passion and Communication: Passionate experts like Aaron Franklin in barbecue and Mark Reibert in robotics inspire us through their teachings and innovations. Effective communication and connection are crucial in various aspects of life, from learning through MasterClass to simplifying business operations with NetSuite and ensuring privacy with ExpressVPN.
The love and passion of experts in their craft, whether it's barbecue or robotics, shines through in their teachings and innovations. Aaron Franklin's dedication to barbecue and communication of its art is exemplified through his cookbooks and videos. Mark Reibert's fascination with robotics was sparked by observing the disassembled pieces of a robot arm in a lab during graduate school. Both individuals' enthusiasm for their respective fields has led to valuable resources and advancements for others. Furthermore, the importance of effective communication and connection in various aspects of life was emphasized. MasterClass offers unlimited access to learn from masters in various fields, and NetSuite simplifies business operations by connecting different components. ExpressVPN ensures privacy and access to geographically restricted content. In conclusion, the importance of passion, effective communication, and connection in various aspects of life, from cooking and robotics to business and technology, cannot be overstated. Embrace the wisdom and resources shared by experts and enjoy the benefits they bring.
The Tension Between AI and Robotics: Robotics and AI have a complex history marked by tension between cognitive science and robotics approaches. Interdisciplinary collaboration is crucial for their ongoing evolution.
The intersection of artificial intelligence (AI) and robotics has a long and complex history, marked by tension between two approaches: the cognitive science approach, which focuses on understanding intelligence through brain research, and the robotics approach, which emphasizes building functional machines. This tension has led to periods of connection and disconnection between the two fields. The speaker, a roboticist, shares his personal experiences with this history, including his time at MIT's AI lab in the 1970s, where he saw the first attempts to bridge the gap. He also reflects on his own work, which has focused on building aggressive, untethered robots that move quickly, inspired by his belief that function is not the only important aspect of robotics and that aesthetics and lifelike behavior can add value. Overall, the conversation highlights the importance of interdisciplinary collaboration and the ongoing evolution of robotics and AI research.
Moving beyond static grasping in robotics: Robotics pioneer Mark Weber advocates for dynamic, unconventional approaches to robot manipulation, inspired by human and animal behaviors, and encourages a long-term, aggressive approach to the problem.
In order to advance robot manipulation towards human-like abilities, we need to move beyond static grasping and consider more dynamic, unconventional approaches. Mark Weber, the founder of Boston Dynamics, suggests that being good at fumbling or juggling multiple objects might be more beneficial than striving for perfection in modeling and grasping. He draws inspiration from observations of humans and animals, and encourages a more aggressive, long-term approach to the problem. Weber's career in robotics spans over four decades, starting with the development of the first hopping robot at Carnegie Mellon in the late 1970s and 1980s. The creation of this robot was motivated by a conversation with Ivan Sutherland, who recognized the potential of the pogo stick robot project and provided initial funding. Despite the challenges and setbacks, Weber's persistence and innovative thinking have led to groundbreaking advancements in robotics.
Discovering the potential of hopping mechanics with DARPA: A young researcher's encounter with DARPA led to the development of a one-legged hopping robot, overcoming challenges in balancing and controlling movements through engineering innovations.
The development of a one-legged hopping robot, which later became the Pogo stick robot, began with a chance encounter between a young researcher and Craig Fields of DARPA. Excited by the potential of understanding animal locomotion, the researcher received funding to explore the fundamentals of hopping mechanics. With the help of engineer Ben Brown, they overcame challenges in balancing the robot in 3D and controlling its movements. The actuation system involved measuring height and deciding where to place the foot, ensuring the body remained upright during each hop. The physics allowed for correction within certain limits, making the robot's ability to balance and correct itself a significant achievement.
Early Days of Robotics: Experimentation and Belief: The early days of robotics were marked by experimentation, belief in potential, and determination to make the seemingly impossible a reality, as shown by Boston Dynamics' Marc Raibert.
The early days of robotics research involved a lot of experimentation and belief in the potential of the field, even when others doubted its importance. Boston Dynamics, for instance, started as a physics-based simulation company but got back into robotics with projects like the IBO Runner for Sony. The founder, Marc Raibert, recalls the importance of finding like-minded collaborators and the unexpected appeal of robots like Spot, which drew crowds despite initial skepticism. Despite challenges, Raibert's determination and focus on functionality led to groundbreaking advancements in robotics, proving that the seemingly impossible could become a reality.
From surgical simulator to quadruped robots: Boston Dynamics started with a surgical simulator, pivoted to quadruped robots, and learned the importance of market understanding, pivoting, and effective design.
The founders of Boston Dynamics, a leading robotics company, started with creating a surgical training simulator using 3D computer graphics and force feedback devices. They aimed to teach surgeons through a scoring system, but discovered that surgeons wanted to teach them instead. They then attempted to sell it to hospitals but lacked resources. Pivoting, they built a quadruped robot named IBO, collaborating closely with Sony. Despite its impressive technology, they realized it didn't look exciting when moving fast. Their next milestone was creating Big Dog, a result of DARPA's bio-dinautics program, which put them on the map and led to scaling up the company. Through these experiences, they learned the importance of understanding their market, pivoting when necessary, and the challenges of creating robots that looked and functioned effectively.
Taking robots from lab to real world testing: Robot development involves crucial real-world testing to reveal challenges and lead to advancements in controls and systems integration.
Bringing robots from the lab into the real world for testing is a crucial step in their development. This was exemplified by the creation of Big Dog, a large quadruped robot that integrated power, computing, and controls onto its platform, enabling it to be taken out into challenging environments like hiking trails. The real-world testing revealed that while the woods presented challenges, the true test came when robots were introduced into homes and offices where damage was a concern. This led to advancements in controls and systems integration, eventually resulting in the creation of Spot, an electric and non-hydraulic robot designed for indoor use. A key figure in this process was Martin Bueller, a professor from McGill University, who played a vital role in getting Big Dog out of the lab and into the field.
Innovation in Robotics: From Hydraulics to Electric Technology: Boston Dynamics' robots use a dynamic approach to achieve natural movements, requiring both efficient hardware and innovative software. Calculating necessary rotations and momentum in real-time ensures successful landings.
The transition from hydraulic to electric technology in robotics involves significant innovation, particularly in the design of smaller, more efficient valves and power supplies. Boston Dynamics' robots are known for their natural movements, achieved through a dynamic approach that involves predicting future motion and adjusting in real-time. Making these robots look natural requires both good hardware and innovative software. The process of making a robot perform a natural-looking flip or landing involves calculating the necessary rotation and momentum, and adjusting in real-time to ensure a successful landing. The challenges of sticking a landing increase with the underactuated nature of a robot in mid-air, but with careful calculation and adjustment, it is possible to achieve consistent, successful landings.
Creating complex 3D movements for robots using physics and gymnastics background: MIT graduate student Roy Maraba combined gymnastics and robotics to create a 3D somersault for the first time. Understanding physics behind movements and animal inspiration can lead to efficient and natural human-like walking for robots.
Creating complex 3D movements for robots, such as a 3D somersault, involves understanding the physics behind the maneuver and finding ways to balance in additional degrees of freedom. This was achieved for the first time by MIT graduate student Roy Maraba, who brought his gymnastics background to robotics. However, humans may not fully understand the physics behind their own movements, and building robots can help us gain a deeper understanding. For instance, creating efficient and natural human-like walking for robots like Atlas is still a challenge. The number of actuators, joints, and compliances needed for efficient and functional design is a constant balance. Simplification, as seen in the pogo stick, can be a good starting point. Animals like kangaroos and ostriches, which were studied for inspiration, have unique morphologies and musculature that can inform robot design. The most beautiful animal movements, such as the graceful and fast running of cheetahs, continue to inspire and challenge robotics researchers.
Exploring the unique forms of intelligence in animals and machines: Animals excel in athletic abilities while machines lag behind in cognitive capabilities. Boston Dynamics aims to bridge this gap by developing robots with both athletic and cognitive intelligence.
Both animals and machines exhibit unique forms of intelligence, with animals excelling in athletic abilities and machines lagging behind in cognitive capabilities. The pronghorn's misdirection tactics and a cheetah's agile movements showcase the power of athletic intelligence in the natural world. On the other hand, robots, such as Boston Dynamics' creations, have made significant strides in athletic intelligence through advanced mechanical design, real-time control, and energetics. However, they lack the cognitive intelligence that allows us to plan and adapt to new situations. The newly formed Boston Dynamics AI Institute aims to bridge this gap by focusing on designing robots with both athletic and cognitive intelligence, incorporating organic design principles and considering the machine's inherent capabilities to create more efficient and graceful robots.
Creating athletic intelligence in robots: The AI Institute aims to blend physical prowess with cognitive understanding in robots, starting with simple tasks like bicycle repair, to create athletic intelligence.
The AI Institute is focused on combining the physical abilities of robots with cognitive understanding to create athletic intelligence. This is a complex goal, but one that is essential for creating robots that can learn from humans and perform tasks effectively. The Institute recognizes the importance of both reliability and cost-effectiveness, as well as the need for incremental progress towards long-term goals. Boston Dynamics has shown what's possible with physically successful robots, but the lack of cognitive abilities is a major barrier. The Institute is using a "stepping stones to moonshots" approach, focusing on tangible progress and feedback along the way. One specific goal is to develop robots that can observe and understand human actions, break them down into skills, and then replicate those skills. This is a challenging problem, but progress is being made, starting with simple tasks like bicycle repair.
Navigating complex environments through sensing, mapping, and uncertainty: Robotics requires a combination of sensing the environment, building a mental map, and operating under uncertainty, with both machine learning and traditional control methods playing significant roles. Robots should be technically fearless, able to learn from humans, and diagnose and fix issues autonomously.
Navigating complex environments, whether it's a bicycle path or a physical workspace, can be achieved through a combination of sensing the environment, building a mental map, and operating under uncertainty. Machine learning plays a role in this process, but traditional control methods still hold significant value. Building a great team involves technical fearlessness, diligence, intrepidness, and a sense of fun. Technical fearlessness means tackling complex problems and finding solutions, even when the answer isn't clear-cut. In the context of robotics, this could mean having robots observe humans and learn from their actions to become effective actors in the world. Additionally, robots should be able to inspect, diagnose, and fix issues autonomously, combining AI and physical skills to perform these tasks. Overall, the future of robotics lies in the intersection of these various approaches.
The importance of diligence and intrepidness in robotics: Diligence creates robust solutions and adapts to conditions, intrepidness helps us persist in the face of challenges, and both are crucial for successful robot development
Diligence and intrepidness are crucial in the development of robotics. Robotics is not a simple process, and setbacks and failures are inevitable. The importance of diligence lies in creating robust solutions that can adapt to various conditions and perturbations. Intrepidness, on the other hand, is the courage to persist in the face of challenges and setbacks. The raw testing and demonstration of robots' limitations and resilience, as shown in the legendary videos, help us appreciate their successes. The simplicity of focusing on what's worth showing and avoiding unnecessary distractions is essential in effectively communicating the value of robotics. Ultimately, the journey towards creating functional robots requires a combination of diligence, intrepidness, and a willingness to embrace the learning opportunities that come with failure.
Engineering: A blend of science, art, and creation: Engineering is a rewarding profession that combines scientific knowledge, creativity, and financial compensation to bring inanimate objects to life and make a significant impact on the world.
Engineering, as demonstrated in the development of robots like Atlas at Boss Dynamics, involves a process of continuous learning from failures and iterations. It requires robust machines that can withstand testing and the willingness to repair and improve. Engineers get to combine scientific knowledge with creative design, resulting in the creation of new things and the possibility of art. The collaborative nature of engineering teams and the financial compensation add to the satisfaction of the profession. Engineering is a higher calling, blending the roles of scientist, artist, and creator, allowing us to bring inanimate objects to life and make a significant impact on the world.
Exploring Human-Robot Interaction through Dance: Robots are being developed to learn from humans through dance, with the ultimate goal of creating unique and fascinating performances. Boston Dynamics, a pioneer in advanced robotics engineering, started as a less sophisticated team but fostered an environment for interesting engineering work to thrive and reached the top tier.
The beauty of robotics lies in its ability to move with elegance, grace, and precision, even surpassing human capabilities in some areas. Researchers are exploring ways for robots to learn from humans, such as through dance, and are developing tools to make this interaction more intuitive. The ultimate goal is for robots to dance with humans, creating a unique and fascinating performance. To build a team of great engineers, it's important to foster an environment where interesting engineering work is taking place. Boston Dynamics, for instance, started as a less sophisticated engineering team but aspired to reach the same level as more hardware-focused companies. Over time, they achieved this goal, and the company is now known for its advanced engineering capabilities.
Passionate people, joy of building, and visual storytelling fueled Boston Dynamics' success: Boston Dynamics' success is rooted in hiring passionate individuals, the joy of building and overcoming failures, and effectively showcasing their work through platforms like YouTube.
The success of Boston Dynamics can be attributed to hiring passionate people, the joy of building and overcoming failures, and the power of visual storytelling through platforms like YouTube. The company's early days were filled with individuals who were passionate about robotics and engineering, often without formal degrees. This "maker" mindset brought endless energy and excitement to the team. The constant failure and eventual success in building functional robots also contributed to the team's happiness and motivation. YouTube played a significant role in showcasing Boston Dynamics' work to the world, inspiring both awe and fear, and attracting young people to the field of AI and robotics. The company's competitors, such as Tesla and SpaceX, also admired Boston Dynamics' work and were inspired by it. The founder hopes to host robot meetups and continues to be involved with the company through the board. The diversity of robots in the company's fleet, including Spot, animal robots, and arms from other companies, reflects the team's ambition to build and explore various robotics technologies.
Perspective on Competition in Robotics from Marc Raibert: Marc Raibert believes the focus is shifting from 'if' to 'which' robot for potential buyers, and creating profitable use cases is the key challenge in robotics, with social robotics being a promising area for growth.
While competition is heating up in the cognitive side of robotics, particularly in humanoid robots, the physical side, specifically in quadruped robots, still feels less competitive. Marc Raibert, the founder of Boston Dynamics, shares his perspective on competition, expressing that he doesn't focus much on it as he used to. He believes that the question for potential buyers is no longer if they want a robot but rather which robot they prefer. The key challenge in robotics is creating realistic use cases that make money, with social robotics being a promising area for growth. However, the road to success is not easy, as companies have faced failures in the past. Creating the right public perception and understanding of the technology's benefits and limitations is crucial for mass adoption. Despite the challenges, Raibert remains optimistic about the future of robotics and the potential for significant cost reduction.
Understanding the nuances of intelligence and AI: While computers excel in some areas like language processing, emotional intelligence and creativity remain a challenge. Fear of misalignment between human and AI is valid, but they're tools under our control, offering benefits and risks.
While there are ongoing debates about whether computers will surpass human-level or even superhuman intelligence, it's essential to remember that intelligence comes in various forms. Some areas, like language processing, computers already excel, while others, like emotional intelligence and creativity, remain a challenge. Fear of a potential misalignment between human and artificial intelligence, leading to unintended harm, is valid, but it's crucial to remember that computers are tools under our control. We've faced similar concerns with other technologies, like cars, which present risks but also offer significant benefits. For young people deciding on their careers, it's recommended to consider what they'd do if there were no constraints, then work towards making it a reality. The world of technology and robotics is vast, and opportunities are often more extensive than we think.
The journey of creating humanoid robot intelligence: Diligence, persistence, and showcasing a robot's learning process are key to creating advanced humanoid robot intelligence
Creating advanced humanoid robot intelligence is a challenging, yet rewarding pursuit. Mark Reiber, a leading figure in robotics, emphasizes the importance of diligence and persistence in this field. Special achievements often come after years of dedicated work. Reiber also highlights the value of showcasing a robot's learning process, even if it starts off clumsy or flawed. This mirrors the human experience and can be inspiring and charming. Ultimately, the journey of creating humanoid robot intelligence is a testament to human ingenuity and a reminder to enjoy the ride while we're here.
