In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
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In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
#26 - Heisenberg’s Uncertainty in Biology and Human Knowledge
Justin Riddle Podcast
32 minutes 33 seconds
3 years ago
#26 - Heisenberg’s Uncertainty in Biology and Human Knowledge
In episode 26 of the Quantum Consciousness series, Justin Riddle discusses Heisenberg’s uncertainty principle: the idea that every quantum bit comprises a bit of information and a bit of entropy such that knowledge of one dimension reduced knowledge of the other. We can think of each qubit has having two perpendicular axes: zero/one and plus/minus. The state of the qubit represents a point moving around on these axes. When you measure a qubit in the zero/one dimension, then it ends up getting reduced to a zero or one. From that state, the plus/minus dimension is now equal probability. By knowing about one dimension, we induce entropy in the other. You can only make one measurement at a time, so it is impossible to know whether the system is zero/one and plus/minus at the same time. In practice, physical systems, like an atom, will exhibit uncertainty between their position and momentum. This is more than just our knowledge of the system. When you know the momentum, the position is maximally smeared out across all possible options. This changes what the future of the system will look like. Biology might be leveraging measurement to change the future of physical systems like ions. In an ion channel, the center of the ion channel is so small that the ion gets spatially measured when passing through the channel. This has a dramatic effect on the momentum of the ion which could facilitate the transport of the ion to other receptor proteins. In addition, the uncertainty principle might be relevant to understanding human cognition, in that our knowledge of certain properties might coexist within an uncertainty relationship like that of position and momentum. By learning about one property, we reduce our knowledge of the other property. This is quite the divergence from classical models of human cognition. Finally, a speculation on how the uncertainty principle might be reflective of some deeper uncertainty in ascertaining existential truth. Carl Jung suggested that we can only ever reach a half truth, and that the core of reality is brimming with paradoxes. The more you get closer to some truth, the further you are from its complimentary opposite, which is also true. This form of cosmic censorship through paradox could be the ultimate expression of the uncertainty principle. Join me on this exciting delve into the mysteries of human consciousness through the lens of quantum mechanics.
Justin Riddle Podcast
In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
