Podcast Summary
Streamline hiring with Indeed or manage finances with Rocket Money: Utilizing platforms like Indeed for hiring and Rocket Money for personal finance management can help save resources, improve processes, and deliver high-quality matches or savings of up to $720 a year respectively.
When it comes to hiring, instead of actively searching for candidates, utilizing platforms like Indeed can help streamline the process and deliver high-quality matches. Indeed, with over 350 million monthly visitors, functions as a matching and hiring platform, allowing employers to schedule, screen, and message candidates efficiently. Additionally, 93% of employers agree that Indeed delivers the highest quality matches compared to other job sites. On the other hand, managing personal finances can be a challenge with the numerous subscriptions we often forget about. Rocket Money, a personal finance app, can help identify and cancel unwanted subscriptions, monitor spending, and lower bills, saving users an average of $720 a year. In essence, whether it's hiring or managing finances, utilizing technology and platforms can significantly improve processes and save resources.
Our brains are active prediction machines: The mind is not limited to the brain but can include external tools, and our brains actively engage in processing information to minimize errors
Our brains don't just passively receive information but are active prediction machines. They construct expectations and compare them to actual experiences to minimize errors. This perspective, known as extended mind theory, suggests that the mind is not limited to the brain but can include external tools like notebooks or smartphones. The predictive processing model further supports this idea, as it shows that the brain treats internal and external information similarly. This active engagement of the brain in processing information has significant implications for understanding thinking, consciousness, and even philosophical questions about reality and free will. So, if you're interested in exploring these ideas further, check out Andy Clark's new book, "The Experience Machine: What Predictions Shape and Build Reality," and consider supporting Mindscape by pledging on Patreon or leaving a review.
The Mind Extends Beyond Biology: Extended Mind Concept: Our minds are not limited to our biology, but incorporate trusted and robust external resources, allowing for an emergent self and effective daily functioning.
Our minds extend beyond our biology, incorporating trusted and robust external resources that are constantly available to us. This concept, known as extended mind, is not just about having access to information, but also about the delicate temporal integration of our biological system with these external resources. This integration allows for an emergent self, where we function as the emergent property of our biological and external systems. The boundary of what counts as part of our mind isn't drawn by cognitive bloat, but by the robust availability and trustworthiness of these external resources. Our brains are location-neutral and can estimate where to get good information from, as long as it's accessible and trusted. The temporal dovetailing of our biological and external systems is an important aspect of this concept, allowing us to perform daily tasks effectively and feel a sense of our own capacities.
The Extended Mind: Functional Similarities and Moral Considerations: The extended mind theory, which includes external objects and environments as part of cognitive processes, raises functional similarities and moral considerations. Philosophers argue for it based on functional similarities, but it's a moral decision to acknowledge external aids in enhancing cognitive abilities.
The concept of the extended mind, which includes external objects and environments as part of cognitive processes, is a complex issue that involves both functional similarities and moral considerations. Philosophers like Dave Chalmers argue for this perspective based on functional similarities, but it doesn't always seem intuitively right. The decision to embrace the extended mind is, in part, a moral one, as failing to acknowledge the role of external aids, such as smartphones or home environments, in enhancing cognitive abilities can be seen as an injustice to individuals who rely on them. However, there is an intermediate stance that acknowledges the body as part of cognition but not external objects. This view is less stable and may require a clearer definition of what counts as part of the mind or cognition. The use of the body as a stepping stone to understand the extended mind is a useful approach, as continuous reciprocal interactions between the brain and body demonstrate that cognitive work can extend beyond the physical boundaries of the body. Despite the brain remaining largely unchanged over thousands of years, the mind has evolved through the use of intermediate technologies, such as writing, which have allowed us to offload cognitive tasks into the world. Ultimately, the decision to embrace the extended mind requires careful consideration of both functional and moral arguments.
Externalizing thoughts for problem-solving: Writing things down helps us attend to our thoughts in new ways, breaking free from internal mental models and leading to novel ideas, especially in design and engineering
Writing things down and externalizing our thoughts is not just a way to record information, but an essential part of the problem-solving process. This was noted by physicist Richard Feynman, who saw it as an active working process rather than a passive recording. This ability to encode and manipulate symbols is a unique human capability, but other animals also exhibit similar behaviors to a lesser degree. By externalizing our thoughts, we can attend to them in new ways, breaking free from internal mental models and coming up with novel ideas. This is particularly useful in design and engineering, where physical models can lead to innovative solutions. This capacity for symbolic externalization sets humans apart from current AI systems, which lack this ability to engage with the physical world in the same way.
Exploring Embodied Learning for Advanced AI: Research suggests babies learn causal maps of the world through exploration, and embodied AI like robots could allow AI to learn from direct experience and interact with the environment, potentially leading to more advanced AI systems.
Current AI systems, particularly large language models, may lack true understanding due to their disembodied nature. They excel in perception-action loops but lack the ability to grasp causality and interact with the world like humans do. Embodied AI, such as robots, could potentially change this by allowing AI to learn from direct experience and interact with the environment. This idea is supported by research suggesting that babies learn causal maps of the world through exploration, and companies like Versus AI are exploring this concept. While large language models can be useful tools, they may not be the best starting point for creating artificial general intelligences. Instead, focusing on developmental trajectories and embodied learning could lead to more advanced AI systems. The speaker also emphasizes that they personally do not desire an artificial colleague but would find an artificial graduate student or postdoc helpful. The speaker's perspective on the location of consciousness and self is also discussed, with the suggestion that it may be linked to the perception-action loop. Overall, the discussion highlights the potential benefits of embodied learning and interaction for AI systems and the importance of considering alternative approaches to creating advanced AI.
The Perception-Action Loop: Our Actions Shape Our Perception: Our perception and actions are interconnected, with our actions influencing our perception and vice versa. The brain functions as a prediction machine, constantly making assumptions about the world and adjusting actions based on prediction errors.
Our perception of the world and our actions in response to it form a continuous loop, which is a fundamental aspect of how we learn and interact with our environment. This concept, known as the perception-action loop, challenges the common metaphor of the brain as a video camera with a computer, passively taking in sense data and processing it. Instead, our actions play an active role in shaping our perception of the world. For instance, when catching a ball, we don't calculate its trajectory and then move to intercept it. Instead, we adjust our movements to keep the ball's apparent position constant, allowing us to be in the right place at the right time. The brain, therefore, functions as a prediction machine, constantly making assumptions about the world and adjusting its actions based on the prediction errors. This perspective places prediction at the core of the brain's operations, shaping motor control, interoception, and exteroception.
Understanding the World through Predictions: Our brains minimize prediction errors in perception and action using a strategy called free energy minimization, which involves matching current sensory input with internal models and adjusting actions accordingly.
Our brains use a powerful strategy to make sense of the world around us by making predictions based on past experiences and current sensory evidence. This strategy, known as free energy minimization, is used both in perception and action. In perception, the brain tries to match the current sensory input with its internal model of the world to minimize prediction errors. In action, the brain uses the same strategy to predict the outcome of an action and then adjusts the action to fit the prediction. The neural operations used in perception and action are similar, with motor cortex being wired like ordinary sensory cortex. The key difference is that proprioception, or internal sensing of the body's position, plays a special role in motor control. This idea, which is related to Carl Friston's free energy principle and the Bayesian brain, provides a principled way of understanding the relationship between perception and action.
Brain makes proprioceptive predictions to guide actions: Our brains make assumptions based on patterns and focus on errors to efficiently navigate the world
Our brains make proprioceptive predictions, which act as motor commands, allowing us to adjust our movements and eliminate errors. These predictions are given significant weight, and by focusing our attention on the predicted outcome rather than the current state, we allow the prediction to guide our actions. This process can be thought of as targeted disattention, rather than lying to ourselves. It's similar to the concept of file compression, where our brains make assumptions based on patterns and focus on the differences or errors to improve efficiency. In perception, this process helps us quickly process and respond to our environment. By predicting sensory flows and focusing on the errors, we can efficiently and effectively navigate the world around us.
How our brains make predictions and refine them based on new information: As we age, our brains become more efficient at processing information by making predictions and refining them, but this can also lead to blind spots and a reluctance to learn new things that don't fit within our existing mental models.
Our brains process information more efficiently by making predictions and refining them based on new sensory inputs. This predictive processing helps explain why certain experiences seem less novel and why learning new things becomes more challenging as we age. This process also leads to expert perception, where we quickly understand the meaning of sensory information. The efficiency of this model is a significant attraction, as it allows us to make the most of our finite resources. However, it can also lead to blind spots and a reluctance to put in the effort to learn new things that don't fit within our existing mental models. This discussion also touches on the idea that as we get older and become experts in certain areas, we may forget how hard it was to learn those things initially and therefore resist putting in the same level of effort to learn new things. Overall, the predictive processing model offers a fascinating perspective on how our brains process information and why we may get stuck in mental ruts as we age.
Understanding the World through Predictive Processing: Our brains use predictive processing to make sense of the world, updating internal models for efficient responses, but susceptibility to illusions is a trade-off.
Our brains use a predictive processing model to make sense of the world around us, which involves maintaining an internal world model at a metabolic cost. This constant updating allows for more efficient moment-by-moment responses, making anticipation beneficial for animals in various situations. However, this mechanism also makes us susceptible to illusions as our strong predictions can sometimes override real sensory evidence. Illusions like the phantom phone vibration, hollow mask, and McGurk effect demonstrate this phenomenon. The benefits and downsides of this predictive processing model are a subject of ongoing research, and it's unclear if there's an alternative way to proceed for understanding the world without bringing a world model to bear on current sensory evidence in a context-sensitive way. Despite the potential drawbacks, this predictive processing model is likely the most efficient way for our brains to function overall.
Our perception is shaped by expectations and filters: Be aware of biases and make a conscious effort to stay open-minded and consider different perspectives, as our perception can be influenced by internal filters and external expectations
Our perception of the world around us is shaped by our expectations and internal filters. This can lead us to see and believe things that may not be entirely accurate. For example, in the case of sensory information, our brains make predictions based on past experiences and crunch together internal and external data, which can sometimes result in optical or auditory illusions. Similarly, when reading news articles or abstract concepts, we may interpret information based on our biases and expectations, rather than the actual text. This can lead to misunderstandings and misperceptions. Additionally, our brains are tuned to detect patterns and are more likely to miss outliers or unusual events if we're not specifically attending to them. It's important to be aware of these biases and make a conscious effort to stay open-minded and consider different perspectives. In the realm of perception, expecting is believing, and sometimes feeling is seeing as well.
Understanding how our brains make predictions to minimize error: Our brains make predictions based on internal and external information to minimize error and drive curiosity and exploration
Our brains are constantly making predictions based on both external and internal information to minimize prediction error. The predictive brain theory explains how we attend to and process sensory information. However, it's important to note that the brain doesn't just focus on external stimuli but also makes interoceptive predictions about our internal states, such as thirst or hunger. These predictions trigger actions to maintain homeostasis and ensure survival. Additionally, our brains are naturally curious, and minimizing prediction error serves as a reward, driving us to explore and learn new things. Contrary to the "darkened room worry," staying in a room without any new stimuli would not be ideal for our predictive brains, as they would crave novelty and new information to minimize prediction error. Overall, the predictive brain theory offers a comprehensive understanding of how our brains process and respond to information, shaping our perception of the world around us.
Brains as Prediction-Driven Learners: Brains seek to minimize prediction errors, repeatedly exploring environments to learn and understand, leading to deeper problem solving but potentially longer solution times. Surprise adds value and enhances long-term predictions, making art and science valuable environments for learning.
Our brains are driven by a desire to minimize prediction errors, making them general-purpose structure learners. Prediction-driven learners, unlike reward-driven learners, repeatedly explore their environment to learn more, leading to a deeper understanding of the problem. However, they may take longer to find solutions. The constraint of survival adds value to surprise, leading the brain to temporarily increase uncertainty to improve long-term prediction. Art and science can be seen as environments curated to provide surprising experiences that enhance our understanding of the world. This concept can be applied to creating predictive models for various forms of media, such as games, stories, novels, movies, and music. Every novel, poem, or piece of music can be thought of as a probability design, building expectations, cashing them out, and providing surprise to engage and entertain. Roller coasters are another example of probability designs, providing repeated surprises. Understanding the predictive brain can offer new insights into the creation and consumption of various forms of media.
Our perception is an active construction shaped by expectations: Expectations shape our perception and experiences, highlighting the importance of staying connected to reality.
Our perception and experiences are not passive processes but active constructions shaped by our expectations. We are not just sensing reality, but also bringing it about through our own mental processes. This concept can be extended to our feelings and even our medical symptoms. The phrase "perception is controlled hallucination" is often used to describe this idea, but it's important to remember that control is a two-way street. Hallucination can be thought of as uncontrolled perception, which highlights the importance of staying in touch with the world and relying on both our expectations and sensory evidence. This idea has implications for various fields, including medicine and language models. In medicine, the power of placebos and the role of expectations in symptom relief demonstrate the importance of this concept. In the case of language models, their job is to predict what comes next, but they infamously hallucinate when their predictions are not grounded in reality. Understanding the active role of our expectations in shaping our perception and experiences can lead to new insights and potential applications. It also serves as a reminder of the importance of staying connected to the world and ensuring that our predictions are grounded in reality.
Understanding the Role of Perception-Action Loops and Reframing in AI and Mental Health: Perception-action loops anchor our brains in reality, preventing false or hallucinated outputs. Reframing negative thoughts or experiences can improve mental health and performance.
The way our brains process information and make predictions, especially when not anchored in reality through perception-action loops, can lead to false or hallucinated outputs. This phenomenon is not limited to individuals with mental health issues, but also applies to advanced language models like ChatGPT, which can generate false information with confidence. However, adjusting prompts or context can lead to more accurate and reality-anchored responses. This discussion also highlights potential applications for treating mental health issues, such as pain or anxiety, through reframing negative thoughts or experiences. For instance, pain reprocessing theory suggests treating pain as a misfiring signal rather than a reason to stop, allowing individuals to push through and potentially lessen the perceived pain. Similarly, self-affirmation can help individuals overcome perceived limitations and perform better in certain situations. Overall, understanding the role of perception-action loops and the power of reframing can lead to valuable insights for both improving AI models and addressing mental health challenges.
Our perception of pain and time are interconnected: Research shows that pain experiences and sense of time are influenced by expectations. Our brains make predictions and noticing discrepancies between predictions and reality can lead to feelings of happiness.
Our perception of pain and our sense of time are interconnected and influenced by our expectations. Pain research is revealing that people's experiences of pain can vary greatly, even when the standard physiological cause remains the same. This may be due to the activation of different expectations of pain or disability in various contexts. Similarly, our sense of time passage is rooted in our ability to predict future moments and remember the past, with updates happening in one direction. This predictive modeling view of the brain could also explain the hedonic treadmill hypothesis, which suggests that we derive happiness not from our overall welfare, but from changes in our welfare. Our brains are constantly making predictions, and noticing that our predictions were pessimistic and things are actually better than expected could lead to feelings of happiness. Despite some challenges to this view, it is an intriguing perspective on the nature of pain and our perception of time.
Brain's prediction-minimizing nature affects pleasure: Focusing attention and actively engaging with experiences can enhance pleasure, despite our brain's tendency to minimize predictions and errors, and seek familiarity and novelty.
Our brains are wired to minimize predictions and errors, which can affect our experience of pleasurable sensory inputs. Repeating experiences, even those that bring pleasure, can lead to diminished pleasure due to familiarity. However, by focusing our attention and actively engaging with the experience, we may be able to artificially surprise ourselves and enhance the pleasure. This concept applies to all types of pleasurable experiences, whether simple or complex, and even seemingly mundane ones. The brain's prediction-minimizing nature also means we tend to prefer predictable environments, but we also have a drive for novelty. By recognizing the multidimensional nature of our prediction engines, we can accommodate both the desire for novelty and the comfort of familiarity. For young intellectuals considering their future, there is still much to be discovered about the brain and body, and the questions that arise from current understanding will likely lead to new insights.